Random number and random data generators.
Commons-math provides a few pseudo random number generators. The top level interface is RandomGenerator. It is implemented by three classes:
The JDK provided generator is a simple one that can be used only for very simple needs. The Mersenne Twister is a fast generator with very good properties well suited for Monte-Carlo simulation. It is equidistributed for generating vectors up to dimension 623 and has a huge period: 219937 - 1 (which is a Mersenne prime). This generator is described in a paper by Makoto Matsumoto and Takuji Nishimura in 1998: Mersenne Twister: A 623-Dimensionally Equidistributed Uniform Pseudo-Random Number Generator, ACM Transactions on Modeling and Computer Simulation, Vol. 8, No. 1, January 1998, pp 3--30. The WELL generators are a family of generators with period ranging from 2512 - 1 to 244497 - 1 (this last one is also a Mersenne prime) with even better properties than Mersenne Twister. These generators are described in a paper by François Panneton, Pierre L'Ecuyer and Makoto Matsumoto Improved Long-Period Generators Based on Linear Recurrences Modulo 2 ACM Transactions on Mathematical Software, 32, 1 (2006). The errata for the paper are in wellrng-errata.txt.
For simple sampling, any of these generators is sufficient. For Monte-Carlo simulations the JDK generator does not have any of the good mathematical properties of the other generators, so it should be avoided. The Mersenne twister and WELL generators have equidistribution properties proven according to their bits pool size which is directly linked to their period (all of them have maximal period, i.e. a generator with size n pool has a period 2n-1). They also have equidistribution properties for 32 bits blocks up to s/32 dimension where s is their pool size. So WELL19937c for exemple is equidistributed up to dimension 623 (19937/32). This means a Monte-Carlo simulation generating a vector of n variables at each iteration has some guarantees on the properties of the vector as long as its dimension does not exceed the limit. However, since we use bits from two successive 32 bits generated integers to create one double, this limit is smaller when the variables are of type double. so for Monte-Carlo simulation where less the 16 doubles are generated at each round, WELL1024 may be sufficient. If a larger number of doubles are needed a generator with a larger pool would be useful.
The WELL generators are more modern then MersenneTwister (the paper describing than has been published in 2006 instead of 1998) and fix some of its (few) drawbacks. If initialization array contains many zero bits, MersenneTwister may take a very long time (several hundreds of thousands of iterations to reach a steady state with a balanced number of zero and one in its bits pool). So the WELL generators are better to escape zeroland as explained by the WELL generators creators. The Well19937a and Well44497a generator are not maximally equidistributed (i.e. there are some dimensions or bits blocks size for which they are not equidistributed). The Well512a, Well1024a, Well19937c and Well44497b are maximally equidistributed for blocks size up to 32 bits (they should behave correctly also for double based on more than 32 bits blocks, but equidistribution is not proven at these blocks sizes).
The MersenneTwister generator uses a 624 elements integer array, so it consumes less than 2.5 kilobytes. The WELL generators use 6 integer arrays with a size equal to the pool size, so for example the WELL44497b generator uses about 33 kilobytes. This may be important if a very large number of generator instances were used at the same time.
All generators are quite fast. As an example, here are some comparisons, obtained on a 64 bits JVM on a linux computer with a 2008 processor (AMD phenom Quad 9550 at 2.2 GHz). The generation rate for MersenneTwister was about 27 millions doubles per second (remember we generate two 32 bits integers for each double). Generation rates for other PRNG, relative to MersenneTwister:
| Example of performances | |
| Name | generation rate (relative to MersenneTwister) |
| {@link org.apache.commons.math.random.MersenneTwister MersenneTwister} | 1 |
| {@link org.apache.commons.math.random.JDKRandomGenerator JDKRandomGenerator} | between 0.96 and 1.16 |
| {@link org.apache.commons.math.random.Well512a Well512a} | between 0.85 and 0.88 |
| {@link org.apache.commons.math.random.Well1024a Well1024a} | between 0.63 and 0.73 |
| {@link org.apache.commons.math.random.Well19937a Well19937a} | between 0.70 and 0.71 |
| {@link org.apache.commons.math.random.Well19937c Well19937c} | between 0.57 and 0.71 |
| {@link org.apache.commons.math.random.Well44497a Well44497a} | between 0.69 and 0.71 |
| {@link org.apache.commons.math.random.Well44497b Well44497b} | between 0.65 and 0.71 |
So for most simulation problems, the better generators like {@link org.apache.commons.math.random.Well19937c Well19937c} and {@link org.apache.commons.math.random.Well44497b Well44497b} are probably very good choices.
Note that none of these generators are suitable for cryptography. They are devoted to simulation, and to generate very long series with strong properties on the series as a whole (equidistribution, no correlation ...). They do not attempt to create small series but with very strong properties of unpredictability as needed in cryptography.


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The visionary behind Dive Beneath the Surface, Crow White a professor at Cal Poly, was inspired by his love of marine biology to create an interactive experience for elementary school students. His hope is that students would be given the opportunity to develop a greater understanding of the ocean which is such a vast ecosystem that provides the foundation for an abundance of learning.
Phasellus eget enim eu lectus faucibus vestibulum. Suspendisse sodales pellentesque elementum.
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Al Zimmermann's Alphabet City Contest — Technical Report
This report currently assumes quite a familiarity with the contest. Also, it is just converted from a post in the discussion group, so a bit of context goes from there.
Here's a brief overview of what my program was able to do.
I had no GADDAG implemented, just a trie, see below. I was curious of DAWG or GADDAG, and it would have helped with the speed, and thus allow better search parameters, but I had unimplemented problem-level ideas all the way, and these usually turn out to outperform optimization-level ideas. There's no point in a 100x speedup when your program can't choose the right words to put, right?
Also, I had no visualizer since Al's online visualizer was enough for me to see whether everything went as planned, and look for potential improvements. When it was not enough, I switched to debugging with textual views of the board.
The basic technique for the entire contest is Beam Search. In simple terms, for every number N in [0..100] of letters on the board, we store W best boards with N letters on the board (best in terms of score). Another view is that it is a breadth-first search keeping W best results on each level. Here, W is the width of the search. For my program, it was on the order of 50 to 40,000, most runs were made with widths 250 to 1000. A single successful width-50 search with no other constraints takes a few seconds on my Core i7. I believe that's slow, and other contestants perhaps have programs which would be orders of magnitude faster (or consequently, of much higher width within the same time). The result of such a run has a score of 900-1200.
To generate all moves from a certain position, I used my trusted (see my report for the 2007 Words Search contest) compressed trie which turns out to be about 8 MB in size for the given dictionary. We store the nodes of the trie in an array. The twist is that we build the trie by breadth-first search over all the words in the dictionary. This allows us to put each node's children together in the array. So, instead of 26 pointers to different parts of the array, we are good to go with one pointer to the start of the children block and one 26-bit mask specifying which children are present. A transition involves a bitwise AND with that mask and a POPCNT of what's left, all O(1) operations on modern hardware. I believe this implementation is a reasonable compromise between size (cache misses => slow) and speed (too much instructions per transition => slow). Here is the code.
The basic search suggested that most score points result from putting two tiles on Triple-Word cells simultaneously. Naturally, it looked like covering three such cells simultaneously would be a big win. So, I introduced goals. In the middle of implementing that, people started reporting that it is possible on the list, so I was motivated to continue.
A goal is a 15-letter word along with the position where I want it to be placed, and a mask specifying which of the letters are restricted, that is, must be placed simultaneously after all other letters are present. The other letters must either be single or form dictionary words. It is mandatory that letters 1, 8 and 15 are restricted. It is good when letters 4 and 11 are restricted, since there are Double-Letter bonuses beneath them. There turned out to be a bit more than 3000 words and a bit more than 100,000 valid (word, mask) pairs. Each such pair has a guaranteed score associated with it.
This list of goals looks like:
-----
OxYPHenButaZonE 1508 7
OxYPhEnButaZonE 1508 7
OxYPheNButaZonE 1508 7
...
TrinITrOtoluEnE 405 6
TrinItROtoluEnE 405 6
-----
Here, the uppercase letters are the restricted letters. The numbers are the score (all bonuses and +50 for a bingo included) and the number of restricted letters.
After discovering that OXYPHENBUTAZONE is both an easy and a high-scoring word (X|Y, HEN, UTA, ON are usually the non-restricted parts), I got something like 2000-2400 for each bag.
The beam search picks W "best" boards on each level. The "value" function to determine what's "best" was just the score of the board initially. Later, this function was separated from the score. Of course the base value is the score, but we could now do some tweaks to help the distant purposes of our search.
After each successful move, my search now checked whether the goal is still possible to achieve (value = -1 if not). It also added to the value all the score I would get if I somehow placed the goal word immediately. This allows to build words "hanging" on the future goal word in advance. One downside to this is that it is always required that both the hanging word with the restricted goal letter and the hanging word without it are valid dictionary words. This limitation remained in my program until the end of the contest.
To help approach the goal, I introduced a bias: every cell close to the goal word adds some points to the value. The final scheme for the bias was the following. Suppose the goal is at line 1. Now, for each column, find the uppermost covered cell in it. If it is at row 7, add 1 * C points to the value. If it is at row 6, add 2 * C points, and so on to 7 * C points if the covered cell is at row 1. Also, a few more points were given for each non-restricted letter of the goal which was put successfully. A similar scheme applied if the goal is at row 15.
When we successfully put an OXYPHENBUTAZONE, we will most likely make some unnecessary moves: the moves which can be removed and played elsewhere. After all, the upper part of the board is 105 cells, and we have 100 tiles. Surely they don't all go there.
So, we make a carcass of the necessary moves, and then replay the remaining letters freely. Now, we don't have to add bias and goal tweaks to the value, since the required moves are already fixed. Of course, after each new move, we check that all the remaining required moves are still possible. As a result, this usually allows to get a few more points.
After it became easy for my program to put an OXYPHENBUTAZONE in place, leaving quite a few tiles for refinement, I wondered whether two goal words were possible. Again, when I was toying with the idea, people on the list reported it's already done for some of the bags, so I went on with the implementation.
First, we pick two goal words: one from the start of the problem's 100 letters and another from the end, so that they don't intersect. After that, we try to put the first word, just like we put OXYPHENBUTAZONE before. If we succeed, we fix the necessary moves for that word and run another search with an opposite bias to place the second word. If we succeed once more, we may refine the whole solution, fixing the moves required for both goal words.
This approach allowed me to get to the top near the first month's end, giving an average score of 2990. Still, it didn't look like the best approach one is able to come up with. I expected my result at that time to finish 5th. Looks like in fact it would be 4th, between Gil Dogon and Stuart Martin Klimek. Anyway, I motivated myself by thinking my current result will be soon beaten.
The main improvement I dreamed of was to be able to construct the two goal words simultaneously: bring a letter to row 1, then two letters to row 15, then a few more to row 1, and so on. Obviously, the technique I used so far (adding bias to one of the sides of the board) won't help here. Also, when the letters of the two goals intersected (last letter of the first goal not earlier than first letter of the second goal), I had no way to check whether that was even possible.
At this point, my program became hard to maintain. I wanted to introduce the third goal word at the center for a 9x bonus. I wanted to try finding words of moderate length which can lie next to goal words (at rows 2 and 14), so that it would be easier to approach the goals (didn't get to it until the end of the contest). I had a few more ideas to try. And I implemented them with a bit of thought, but not too much of it. As a result, all the ideas and tweaks turned into a twisted 1000+ lines monster, and it took hours to introduce a new one.
I decided to start from scratch and implement most parts of the engine once more. The upside was that now I knew what are the parts of my program which proved useful, and could separate them better. For example, I separated beam search from move generation and the general flow of the game. The new implementation took a few weeks, and was a bit slower initially, but it turned out to be a lot more open to improvements. The old implementation remained runnable side-by-side with the new one, and the part refining existing solutions was useful until the end of the contest.
In the meantime, Wes Sampson took the first place again, proving that I was right to worry about my current score.
My new approach which was working until the end of the contest is a multi-step process.
First, we select two goal words. They are used to build a Sketch: which 30 of the 100 tiles will go to cover the letters of our two goal words. At this point, we pretend there is nothing on the board except the two goal rows, and we can put the letters in these rows immediately. Many positions are tried in a recursive fashion by starting from the latest possible tiles and then substituting them by earlier ones. Each configuration which does not look surely impossible is given a score, and the best-scoring one becomes the Sketch.
Here is a Sketch for problem A:
-----
*97U *95N 93e *90X 52c 67e 73p *99T 88i 70o 92n *89A 42b *91L *96Y
*84D 64e 77m *66Y 71t 34h 69o *78L *83O 56g *87I *37Z 79i 85n *63G
-----
The uppercase letters (with asterisks) are restricted, the lowercase letters (without asterisks) have to arrive before the final goal move. The construction procedure recursively tries a few mappings of restricted goal 1 letters, for each of them a few mappings of restricted goal 2 letters, and for each of these puts the free ones for goals 1 and 2 almost greedily.
Next, we construct a Plan. The Plan contains the 30 tiles information from the winning Sketch, but also tries to give a hint on how we will approach the non-restricted letters. In each run of consecutive free letters, the earliest tile is called a CheckPoint. A CheckPoint has the tile number (time), coordinates, and is also given a value based on the letter, neighboring free letters and their relative times.
Here is a complete Plan for problem A:
-----
Plan: goals=2 check_points=8 goals_score=2503 sketch_value=1274
GameMoves: [ 1A UNEXCEPTIONABLY, 15A DEMYTHOLOGIZING]
CheckPoints: [34(14,5)525, 42(0,12)513, 52(0,4)531, 56(14,9)539, 64(14,1)565,
70(0,9)526, 79(14,12)628, 93(0,2)545] legend: time(row,col)value
Sketch:
*97U *95N 93e *90X 52c 67e 73p *99T 88i 70o 92n *89A 42b *91L *96Y
*84D 64e 77m *66Y 71t 34h 69o *78L *83O 56g *87I *37Z 79i 85n *63G
Problem Constraints: A (30/100)
AIOIETPRTIRDDGNEOEDERUCERAAOIOEEFAhASzENKBbSTLRIUR
MSc[SFgLQETAIgeOyeAoot[pVNUmliJVWodnAiiaxlneWnyuHt
-----
An important tweak here is that we are allowed to use earlier tiles when the letter is the same. So, for example, instead of 88i 70o 92n, we can use 88i 70o 74n and so have "o" -> "on" -> "ion" where "on" is a valid dictionary word (while "io" is not). I was willing to actually check whether all the words are in the dictionary if we follow the order of the tiles, and do something if they are not, but didn't figure out how to do that without another combinatorial explosion, and this tweak was enough most of the time.
Now, we play a game with that Plan. For each CheckPoint, much value is given for getting closer to it. Also, the order of CheckPoints is taken into account, giving less value to all CheckPoints after a non-visited CheckPoint in that order. As a result, the program tries to visit the first CheckPoint, then the second one, and so on.
Two results of such games would be (successful and unsuccessful):
-----
beam search: width 320, depth 0
A: 3089 (314329) [100]
...
beam search: width 320, depth 0
A: 423 (272637) [77]
-----
These are score, value and the number of tiles in the best solution. As you can see, the value components related to CheckPoints turn out to be much more important than the score.
For unsuccessful games, there may also be a few plan refinement steps. The first unvisited CheckPoint is given a bit more value and moved one place closer to the start of the CheckPoints array. Then, another game takes place.
Finally, to find good results for a bag, we construct plenty of Plans (up to 125,000) using pairs of high-scoring goals, pick a few (30-300) Plans which are the best by some combination of goals_score and sketch_value, and then run a game, or a sequence of refining games, for each such Plan. As you may remember, each game is essentially a beam search. When a game is moderately successful (within 150 score of the current best score), we run the beam search a few more times, doubling the width each time.
This approach allowed me to get scores of 2989-3254 for each of the 26 bags, and return to the first place.
Sometimes, using a wildcard allows a much better pair of goal words to be picked. I had to balance between allowing such wildcards and spending too much time building sketches. I implemented some limited ways of using wildcards, and even had a few running records with them, but there are no wildcards in the goals in my final submissions. Other people had more success with them (see submissions for letters H and Y in the final report).
When rewriting my program, I made sure that the number of goal words scales without problems for Sketch, Plan and the following game. This allowed me to try introducing center goals: 15-letter words on the center row. They give only a 9x bonus which is not as much as the 27x bonus for border goals (on rows 1 and 15). Still, I believed they can give one or two hundred points more than just aimlessly wandering around after putting the two border goals.
The biggest problem for me was how to select the third long word. I already spent a minute searching for the list of the best two goals for each problem, and so decided to just pick the first few possible third goals greedily. I had limited success with the idea, as my program produced records for letters P (3288), R (3400) and U (3342). I also got some non-record games with three long words for letters A (3067), G (2987), L (3027) and M (3118).
You can see the three three-word record games in the final report, though they got "canonicalized" and thus turned in a not very readable way. Well, at least one can write a simple tool to swap the row and column for every move, and then use the visualizer.
My guess in the mini-contest (3360 * 26 versus the actual average of ~3178) was based on the assumption that the people will be able to put three long words and add like 200 points to the score. I believe the idea has more potential than I was able to unravel.
My main programming language was D. I must say it is a convenient language which (1) allows to express higher level stuff in a short way when you just want to get things done, and (2) allows to express lower level optimizations when you need the program to be fast. While learning the language, I've had quite a few insights, both related to the language and of broader applicability, thanks to the helpful community around it.
The code statistics are ~230K code, ~10K lines, 195 commits to a local Subversion repository, all that now exported to GitHub.
I've also used a few tiny Python, awk and bash scripts where appropriate.
That's it for this technical report.
Ivan Kazmenko.


| copyDependencyToDir {htmltools} | R Documentation |
Copies an HTML dependency to a subdirectory of the given directory. The
subdirectory name will be name-version (for example,
"outputDir/jquery-1.11.0"). You may set options(htmltools.dir.version =
FALSE)
to suppress the version number in the subdirectory name.
copyDependencyToDir(dependency, outputDir, mustWork = TRUE)
dependency |
A single HTML dependency object. |
outputDir |
The directory in which a subdirectory should be created for this dependency. |
mustWork |
If |
In order for disk-based dependencies to work with static HTML files, it's generally necessary to copy them to either the directory of the referencing HTML file, or to a subdirectory of that directory. This function makes it easier to perform that copy.
The dependency with its src
value updated to the new
location's absolute path.
makeDependencyRelative
can be used with the returned
value to make the path relative to a specific directory.


{# Copyright 2020 Google LLC Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at https://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. #} {% extends "base.html" %} {% block styles %} {{ super() }} {% endblock %} {% block page_title %}About Mentor Matcher{% endblock %} {% block main_content %}
Individuals that are seeking mentorship often find it difficult to find someone that can relate to them on a personal level beyond the goals of the mentee/mentor relationship. There are nonprofit programs in place to help these individuals by matching them with registered volunteer mentors, however this selection often feels like a black box process to the mentee, which is not as conducive of a fruitful relationship compared to simply choosing their own mentor.
Mentor Matcher aims to create a way for students/individuals to find and connect with mentors of their own choosing, so that they may build better relationships with those helping them. Not only will a user be able to choose who they would like to work with, our algorithm will provide them a selection of individuals who share similar interests and goals. This will ensure that the user can find someone they truly want to initiate a connection with.


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Create your ride
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Departure time flexible
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WHAT IF THERE WAS A BETTER WAY TO MAKE DECISIONS.  THE HIGHER THE PERCENTAGE, THE BETTER YOUR LIKELIHOOD OF PERFORMING THAT CHOICE.


CSS Border
The CSS border is a shorthand property used to set the border on an element. The CSS border properties are use to specify the style, color and size of the border of an element. The CSS border properties are given below
- border style
- border width
CSS border-style
The Border style property is used to specify the border type which you want to display on the web page. There are some border style values which are used with border-style property to define a border.
Output:
No border.
A dotted border.
A dashed border.
A solid border.
A double border.
A groove border.
A ridge border.
An inset border.
An outset border.
A hidden border.
CSS border-width
The border-width property is used to set the border's width. It is set in pixels. You can also use the one of the three pre-defined values, thin, medium or thick to set the width of the border.
Output:
Write your text here.
Write your text here.
Write your text here.


TABLE OF INTERACTIONS WITH
DAPTOMYCIN
From the French ANSM drug interactions document of September 2016, p. 70
DAPTOMYCIN RxNorm: 22299 ATC: J01XX09 |
HMG-COA REDUCTASE INHIBITORS (STATINS) CLASS CODE: C10AA |
Risk of addition of undesirable effects (dose dependent) of the rhabdomyolysis type. |
Not recommended If administering these substances together cannot be avoided, reinforce biological monitoring (CPK levels more than once a week) and strict clinical monitoring. |


| Contents | Previous | Next |
This guide describes the features provided by the Java 2D™ API and illustrates how you can use the Java 2D API classes to enhance your applications. For additional information about the Java 2D APIs, see the 2D Graphics trail in the Java Tutorials.
This information in this guide is organized into seven chapters:
Overview —introduces the packages and key classes in the Java 2D API.
Rendering with
Graphics2D—describes the Java 2D API classes in the
java.awt
package and how to set up the
Graphics2D
rendering context.
Geometries—describes the Java 2D API classes in
the java.awt.geom
package and how to
define and manipulate 2D shapes and areas.
Fonts and Text
Layout—describes the Java 2D API classes in the
java.awt.font
package, how to specify
and retrieve font information, and how to display and manipulate
international text using the Java 2D text layout APIs directly.
Imaging—describes
the Java 2D API classes in the java.awt.image
, java.awt.image.codec
, and java.awt.image.renderable
packages and how to
display and manipulate images and offscreen buffers.
Color—describes
the Java 2D API classes in the java.awt.color
package and color management.
Printing—describes
the Java 2D API classes in the java.awt.print
package and the Java 2D API printing
model.
| Contents | Previous | Next |


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An R list
object of POWER parameters and metadata available
for querying from the POWER database.
parameters
A list with 146 weather and climate parameters contained within the POWER database.
Downward Thermal Infrared (Longwave) Radiative Flux
All Sky Insolation Incident on a Horizontal Surface
All Sky Insolation Incident On A Horizontal Surface at 00 GMT
All Sky Insolation Incident On A Horizontal Surface at 03 GMT
All Sky Insolation Incident On A Horizontal Surface at 06 GMT
All Sky Insolation Incident On A Horizontal Surface at 09 GMT
All Sky Insolation Incident On A Horizontal Surface at 12 GMT
All Sky Insolation Incident On A Horizontal Surface at 15 GMT
All Sky Insolation Incident On A Horizontal Surface at 18 GMT
All Sky Insolation Incident On A Horizontal Surface at 21 GMT
Maximum Monthly Difference From Monthly Averaged All Sky Insolation
Minimum Monthly Difference From Monthly Averaged All Sky Insolation
Top-of-atmosphere Insolation
Cooling Degree Days Above 0 C
Cooling Degree Days Above 10 C
Cooling Degree Days Above 18.3 C
Daylight Cloud Amount
Cloud Amount at 00 GMT
Cloud Amount at 03 GMT
Cloud Amount at 06 GMT
Cloud Amount at 09 GMT
Cloud Amount at 12 GMT
Cloud Amount at 15 GMT
Cloud Amount at 18 GMT
Cloud Amount at 21 GMT
Clear Sky Diffuse Radiation On A Horizontal Surface
Normalized Clear Sky Insolation Clearness Index
Clear Sky Insolation Incident on a Horizontal Surface
Diffuse Radiation On A Horizontal Surface
Maximum Diffuse Radiation On A Horizontal Surface
Minimum Diffuse Radiation On A Horizontal Surface
Direct Normal Radiation
Maximum Direct Normal Radiation
Maximum Difference From Monthly Averaged Direct Normal Radiation
Minimum Direct Normal Radiation
Minimum Difference From Monthly Averaged Direct Normal Radiation
Equivalent Number Of NO-SUN Or BLACK Days Over A Consecutive 1-day Period
Equivalent Number Of NO-SUN Or BLACK Days Over A Consecutive 14-day Period
Equivalent Number Of NO-SUN Or BLACK Days Over A Consecutive 21-day Period
Equivalent Number Of NO-SUN Or BLACK Days Over A Consecutive 3-day Period
Equivalent Number Of NO-SUN Or BLACK Days Over A Consecutive 7-day Period
Equivalent Number Of NO-SUN Or BLACK Days Over A Consecutive Month Period
Frost Days
Frequency Of Broken-cloud Skies 10 - 70 percent At 00 GMT
Frequency Of Broken-cloud Skies 10 - 70 percent At 03 GMT
Frequency Of Broken-cloud Skies 10 - 70 percent At 06 GMT
Frequency Of Broken-cloud Skies 10 - 70 percent At 09 GMT
Frequency Of Broken-cloud Skies 10 - 70 percent At 12 GMT
Frequency Of Broken-cloud Skies 10 - 70 percent At 15 GMT
Frequency Of Broken-cloud Skies 10 - 70 percent At 18 GMT
Frequency Of Broken-cloud Skies 10 - 70 percent At 21 GMT
Frequency Of Clear Skies < 10 percent At 00 GMT
Frequency Of Clear Skies < 10 percent At 03 GMT
Frequency Of Clear Skies < 10 percent At 06 GMT
Frequency Of Clear Skies < 10 percent At 09 GMT
Frequency Of Clear Skies < 10 percent At 12 GMT
Frequency Of Clear Skies < 10 percent At 15 GMT
Frequency Of Clear Skies < 10 percent At 18 GMT
Frequency Of Clear Skies < 10 percent At 21 GMT
Frequency Of Near-overcast Skies >= 70 percent At 00 GMT
Frequency Of Near-overcast Skies >= 70 percent At 03 GMT
Frequency Of Near-overcast Skies >= 70 percent At 06 GMT
Frequency Of Near-overcast Skies >= 70 percent At 09 GMT
Frequency Of Near-overcast Skies >= 70 percent At 12 GMT
Frequency Of Near-overcast Skies >= 70 percent At 15 GMT
Frequency Of Near-overcast Skies >= 70 percent At 18 GMT
Frequency Of Near-overcast Skies >= 70 percent At 21 GMT
Heating Degree Days Below 0 C
Heating Degree Days Below 10 C
Heating Degree Days Below 18.3 C
Minimum Available Insolation Over A Consecutive 1-day Period
Minimum Available Insolation Over A Consecutive 14-day Period
Minimum Available Insolation Over A Consecutive 21-day Period
Minimum Available Insolation Over A Consecutive 3-day Period
Minimum Available Insolation Over A Consecutive 7-day Period
Minimum Available Insolation Over A Consecutive Month Period
Insolation Clearness Index
Clear Sky Insolation Clearness Index
Midday Insolation Incident On A Horizontal Surface
Normalized Insolation Clearness Index
Maximum NO-SUN Or BLACK Days
Surface Geopotential
Precipitation
Surface Pressure
Corrected Atmospheric Pressure (Adjusted For Site Elevation)
Specific Humidity at 2 Meters
Relative Humidity at 2 Meters
Daylight Average Of Hourly Cosine Solar Zenith Angles
Daylight Hours
Declination
Hourly Solar Azimuth Angles
Hourly Solar Angles Relative To The Horizon
Sunset Hour Angle
Maximum Solar Angle Relative To The Horizon
Cosine Solar Zenith Angle At Mid-Time Between Sunrise And Solar Noon
Solar Noon
Maximum Solar Irradiance Optimal
Maximum Solar Irradiance Optimal Angle
Maximum Solar Irradiance Tilted Surface Orientation
Maximum Solar Irradiance for Equator Facing Tilted Surfaces (Set of Surfaces)
Minimum Solar Irradiance Optimal
Minimum Solar Irradiance Optimal Angle
MinimumSolar Irradiance Tilted Surface Orientation
Minimum Solar Irradiance for Equator Facing Tilted Surfaces (Set of Surfaces)
Solar Irradiance Optimal
Solar Irradiance Optimal Angle
Solar Irradiance Tilted Surface Orientation
Solar Irradiance for Equator Facing Tilted Surfaces (Set of Surfaces)
Surface Roughness
Surface Albedo
Temperature at 10 Meters
Maximum Temperature at 10 Meters
Minimum Temperature at 10 Meters
Temperature Range at 10 Meters
Temperature at 2 Meters
Dew/Frost Point at 2 Meters
Wet Bulb Temperature at 2 Meters
Maximum Temperature at 2 Meters
Minimum Temperature at 2 Meters
Temperature Range at 2 Meters
Climate Thermal and Moisture Zones
Total Column Precipitable Water
Earth Skin Temperature
Earth Skin Temperature Amplitude
Maximum Earth Skin Temperature
Minimum Earth Skin Temperature
Earth Skin Temperature Range
Climate Thermal Zones
Eastward Wind at 10 Meters
Northward Wind at 10 Meters
Wind Direction at 10 Meters (Meteorological Convention)
Wind Direction at 2 Meters (Meteorological Convention)
Wind Direction at 50 Meters (Meteorological Convention)
Wind Speed at 10 Meters
Maximum Wind Speed at 10 Meters
Minimum Wind Speed at 10 Meters
Wind Speed Range at 10 Meters
Wind Speed at 2 Meters
Maximum Wind Speed at 2 Meters
Minimum Wind Speed at 2 Meters
Wind Speed Range at 2 Meters
Wind Speed at 50 Meters
Maximum Wind Speed at 50 Meters
Minimum Wind Speed at 50 Meters
Wind Speed Range at 50 Meters
Corrected Wind Speed (Adjusted For Elevation)
https://power.larc.nasa.gov/RADAPP/GEODATA/powerWeb/POWER_Parameters_v109.json


142,765 Computer Engineers follow this
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A documentary about wounded veterans that Roger championed gets a screening at the Rehabilitation Institute of Chicago and screenings in New York and Los Angeles…
Loose is the third studio album by Canadian singer-songwriter Nelly Furtado It was Other standout singles include the UK number-one single "Maneater" and the (featuring Timbaland) was released for. digital download in North America
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The Choose A Connection Card dialog box allows you to select an existing connection card or create a new connection card for use with your new terminal connection.
To select an existing connection card, choose one from the Connect With list. To create a new connection card click the Create a new connection card button.
Click the Finish button to save your new terminal connection. You will be able to add a button to the toolbar to run your connection by selecting the Toolbar command from the Settings menu.


Updates current video tile’s state with the provided arguments. If the tile state is updated, the new tile state is sent to the meeting session's AudioVideoObserver's videoTileDidUpdate callback.
Captures a snapshot image from the tile, or null if the tile is not active right now.
Cleans up resources associated with the tile. The tile may not be used after destroy is called.
Called when the device pixel ratio monitor detects a change in the HTML window's device pixel ratio. This can happen if the window is dragged to a monitor with a different hi-dpi characteristics.
Returns the tile id for this tile.
Marks the tile as having poor connection returning whether it was previously unmarked. The updated video tile state is sent to the meeting session’s AudioVideoObserver's videoTileDidUpdate callback.
Pauses the tile if it is not paused. When paused, the tile moves to an inactive state. The updated video tile state is sent to the meeting session’s AudioVideoObserver's videoTileDidUpdate callback. This API is intended to be called on the remote videos. If called on a local video tile, then the tile will no longer be updated, but the local video source will continue to be sent into the meeting.
Override the internal stream ID. Needed as some logic around pause state has been
coupled to the stream ID in the VideoTileState
struct.
Returns a VideoTileState representing a copy of the state of the tile.
Returns a VideoTileState] representing a mutable reference to the state of the tile.
Unmarks the tile as having a poor connection returning whether it was previously marked. The updated video tile state is sent to the meeting session’s AudioVideoObserver's videoTileDidUpdate callback.
Unpauses the tile if it was paused. When unpaused, the tile moves to the active state. The updated video tile state is sent to the meeting session’s AudioVideoObserver's videoTileDidUpdate callback. This API is intended to be called on the remote videos and has no effect on the local video. When called on a remote video, the remote video source will start getting the updates if paused earlier.
Connect a video stream to a video element by setting the srcObject of the video element to the video stream.
The video stream input.
The video element input.
Flag to indicate whether this is a local video.
Disconnect a video stream from a video element by setting HTMLVideoElement.srcObject
to null
.
The video element input.
A flag to indicate whether this function is called due to pausing video tile.
Based on keepLastFrameWhenPaused
, it sets HTMLVideoElement.srcObject
to null
.
If true
and dueToPause
is also true
, then we will not set HTMLVideoElement.srcObject
of the
video element to null
when it is paused and therefore, the last frame of the stream will be shown.
Generated using TypeDoc
Binds the video element to the tile and sends out updates. This must also be called anytime the display of the video element changes, for example, when changing its dimensions or hiding it. To unbind the video element from the tile pass null.


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This module installs the following actions in Edit:Rectangle Menu and Rectangle toolbar.
|
Action |
Icon |
Description |
Rectangular Cut ( Ctrl+Alt+X ) |
Cuts the contents of rectangle defined by the selection | |
Rectangular Copy ( Ctrl+Alt+C ) |
Copies the contents of rectangle defined by the selection | |
Rectangular Paste ( Ctrl+Alt+V ) |
Pastes the contents of rectangle defined by the selection | |
Rectangular Delete ( Ctrl+Alt+Minus ) |
Deletes the contents of rectangle defined by the selection | |
Rectangular Clear ( Ctrl+Alt+Space ) |
Replace the contents of rectangle defined by the selection with spaces. Retains selection. | |
Rectangular Replace ( Ctrl+Alt+R ) |
Replace the contents of rectangle defined by the selection with user specified string | |
| Rectangular Uppercase | Replace the contents of rectangle defined by the selection with uppercase form. Retains selection. | |
| Rectangular Lowercase | Replace the contents of rectangle defined by the selection with lowercase form. Retains selection. |
Note: The leading column of the rectangle defined by the selection has to be less than the trailing column.
| Text and Selection |
Action | Text in editor | Clipboard |
0123456789 |
Rectangular Cut |
0123456789 |
2345 |
0123456789 |
Rectangular Copy |
0123456789 |
2345 |
0123456789 |
Rectangular Paste with text in clipboard-- |
0123456789 |
-- |
0123456789 |
Rectangular Delete |
0123456789 |
No change |
0123456789 |
Rectangular Clear |
0123456789 |
No change |
0123456789 |
Rectangular Replace with user specified text--- |
0123456789 |
No change |
aBcDeFgHiJ |
Uppercase selected rectangular text |
aBcDeFgHiJ |
No change |
aBcDeFgHiJ |
Lowercase selected rectangular text |
aBcDeFgHiJ |
No change |
Sources: http://www.netbeans.org/source/browse/contrib/RectangularEditTools
TODO
DISCLAIMER: This module is experimental. So no guarantees. Use the module at your own risk.


Referals this Month
Avg 1214 per Day
Conversions this Month
Avg 256 per Day
Returns this Month
Avg 2175 per Day
Sales
Comments
Views
Likes
Earnings
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{% extends "template.html" %} {% block title %}Home{% endblock %} {% block content %}
And AI will try to predict you have covid disease from your CT scan.
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Course files for the Microsoft Data Science Essentials Course
View the Project on GitHub MicrosoftLearning/Data-Science-Essentials
Demand for data science talent is exploding. Develop your career as a data scientist, as you explore essential skills and principles with experts from MIT and Microsoft.
In this data science course, you will learn key concepts in data acquisition, preparation, exploration, and visualization. Plus, look at examples of how to build a cloud data science solution using Azure Machine Learning, R, and Python.
This GitHub repository contains the lab files for the course. If you'd like to attend the course, sign up for free on edX.


Welcome to my component library!
I've created this library while learning HTML and CSS. The library includes components for:
I plan to use this for reference in my web development journey.


I am an Enthusiastic, dynamic and ambitious professional who is result orientated and committed to research and engineering. I have the same passion and drive for every available project. I am a well - organized individual with an effective use of time management and an ability to prioritize effectively and be flexible where necessary. A fast learner with talent of developing complex solutions and algorithms for difficult problems. Ability to provide solutions for wide range of industries .


Study: Copper Beds Are Key to Staving Off Hospital Infections
by MADELINE REYES(CN) – The key to reducing bacterial infections in hospitals and preventing almost 100,000 deaths each year may be to replace standard hospital beds with copper beds, according to new research released Friday.
In a new study published in the journal Applied and Environmental Microbiology, copper hospital beds in the Intensive Care Unit were found to harbor an average of 95% less bacteria than standard hospital beds, maintaining these levels throughout patients’ stays.
“Hospital-acquired infections sicken approximately 2 million Americans annually, and kill nearly 100,000, numbers roughly equivalent to the number of deaths if a wide-bodied jet crashed every day,” said co-author Michael G. Schmidt, professor of microbiology and immunology at the Medical University of South Carolina, Charleston.
Hospital beds are among the most contaminated surfaces in the world of patient care, and the subsequent infections are the eighth leading cause of death in the U.S. In their study, researchers compared samples from ICU beds outfitted with copper rails, footboards, and bed controls to traditional hospital beds with plastic surfaces. The results showed that 90% of the bacteria taken from the plastic outfitted beds had bacterial concentrations that surpassed what is deemed safe.
“The findings indicate that antimicrobial copper beds can assist infection control practitioners in their quest to keep healthcare surfaces hygienic between regular cleanings, thereby reducing the potential risk of transmitting bacteria associated with healthcare associated infections,” Schmidt said.
Copper surfaces, including hospital beds, have been known to repel and kill bacteria. The use of copper for its antibacterial properties dates back to ancient Ayurveda, one of the oldest systems of medicine, during which drinking water was stored in copper vessels to prevent illness. More recently, numerous medical studies have shown the antimicrobial benefits of copper.
Despite the evidence, copper hospital beds have yet to be commercialized.
“Based on the positive results of previous trials, we worked to get a fully encapsulated copper bed produced,” Schmidt said. “We needed to convince manufacturers that the risk to undertake this effort was worthwhile.” He adds that these beds will pay for themselves in patients’ lives and healthcare dollars saved.
Copyright © 2019 courthousenews.com


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Sweden’s prosecution authority said Tuesday it had dropped its investigation into WikiLeaks founder Julian Assange over a 2010 rape allegation, even though prosecutors found the plaintiff’s claim “credible”.
“My assessment is that all investigative measures that can be taken have been taken. But… the evidence is not strong enough to file an indictment,” deputy director of public prosecutions Eva-Marie Persson told reporters.


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Post/Zip Code
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<EMAIL_ADDRESS>Website：
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The section below contains the console output from running the program.
What's most interesting is the generated code, so switch to that tab and compare with the original program.
Version 1.1 March 2018


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pg_controldata - display control information of a PostgreSQL database cluster
pg_controldata [option] [datadir]
pg_controldata prints information initialized during initdb, such as the catalog version. It also shows information about write-ahead logging and checkpoint processing. This information is cluster-wide, and not specific to any one database.
This utility can only be run by the user who initialized the cluster because it requires read access to the data directory. You can specify the data directory on the command line, or use the environment variable PGDATA. This utility supports the options -V and --version, which print the pg_controldata version and exit. It also supports options -? and --help, which output the supported arguments.
PGDATA
Default data directory location


Ibrahimovic open to Bologna move
by BeSoccerBologna have been in touch with Zlatan Ibrahimovic and are closely monitoring his situation as he looks for a new club.
Zlatan Ibrahimovic has informed Bologna of his willingness to consider joining them in January, according to the Serie A side's sporting director Riccardo Bigon.
Ibrahimovic this week confirmed his departure from LA Galaxy after two seasons in MLS.
The 38-year-old intends to see out his career in Italy, Galaxy head coach Guillermo Barros Schelotto claimed, and will not be short on options given his free agent status.
AC Milan, Fiorentina and Napoli are among those to have been linked but Bologna could have the inside running thanks to Ibrahimovic's rapport with Rossoblu boss Sinisa Mihajlovic, who crossed paths with the Swede at Inter.
"There is a month and a half to go until to the transfer window opens," Bigon told Sky Sport Italia.
"As has been said, Ibrahimovic and the coach have a strong personal relationship. He expressed an openness to the idea of coming to Bologna but now he will take time, after announcing the farewell to MLS, to evaluate all the possibilities for his future. We are very fascinated by this situation but it is clear that we do not control it 100 per cent. The choice is exclusively down to the player. We will wait in case [Ibrahimovic confirms his interest], then we will be ready and more than positive."
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Issue #1575
This test-case is intended for Issue #1575
- New watch expression can't be created when breakpoint is active.
Jan Odvarko<EMAIL_ADDRESS>- Enable Script panel.
- Put a breakpoint into the issue1575GlobalFunction method (within issue1575.js).
- Press runTest button. The execution should stop at the breakpoint.
- Select Watch side panel and try to insert a New watch expression...
- The edit box for new watch expression should be displayed - BUG.


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Please Note: Images can take a few seconds to load if internet connection is slow
SPLITZ
Imported
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FunAqua
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Made in EU
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Drag
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Imported
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Made in SA
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Cobra Googles
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‘Sithalapakkam needs a bus stop and a shelter’
by T.S. ATUL SWAMINATHANCommuters boarding buses from Sithalapakkam halting point have urged the Metropolitan Transport Corporation (MTC) to designate a proper halting point near the intersection and build a bus shelter.
Without a designated halting point, commuters are running across the road at the intersection of Sithalapakkam Koot Road and Otttiyambakkam Main Road, putting their safety at risk.
Bus numbers 51B (Saidapet - Karanai), 105 (East Tambaram - Siruseri IT Park) and M51V (Kolathur - T. Nagar) ply on this stretch.
Route numbers 51B and 105 plies through Ottiyambakkam Main Road and M51V through Sithalapakkam Koot Road.
“We have been asking for a bus stop and a bus shelter to be built here for many months but MTC has not taken any action so far. Senior citizens and differently-abled are the most affected,” says S. Karthik, a commuter.


2/15/14
- Worked out today! (Day 1)
- Finished 131 group work; updated group mates.
- Sent out VGDC email updates to my Mentee. Coaching underway!
- Arranged schedule for Project Blood meet-up times.
- Checked officer apps. Worried about future of VGDC.
- [decision] Dropping down to staff for TAO next year, may/may not take president role for VGDC.
- Made this uh. Handy app.
- Fixed my main website bugs, added more images.
- More incoming! I also plan to add a pomodoro timer + client side adding functionality.


ETERNITY AND A DAY (Mia Eoniotita Ke Mia Mera) (director/writer: Theo Angelopoulos; screenwriters: Giorgio Silvagni/Tonino Guerra/Petros Markaris; cinematographer: Georges Arvanitis/Andreas Sinanos; editor: Yannis Tsitsopoulos; cast: Bruno Ganz (Alexander), Isabelle Renauld (Anna), Achileas Skevis (Albanian Boy), Despina Bebedeli (Mother), Fabrizio Bentivoglio (The Poet), Iris Chatziantoniou (Daughter), Eleni Gerasimidou (Urania), Vassilis Seimenis (Son-In-Law); Runtime: 134; 1998-Greece/France/Italy)
Reviewed by Dennis Schwartz
Theo Angelopoulos (The Travelling Players) directed this 1998 Cannes Film Festival Palme d'Or winner about a renown poet who is dying.
The film is stunningly beautiful, as visually, it is a masterpiece. The film's Thessaloniki landscapes are monumental, but at times, the story was pretentious and much too tedious. The poet is still searching in this 24-hour period, trying to find his roots and resolve his moral dilemma, trying to be no longer scared of dying, which is the same theme Tarkovsky used for "Nostalgia." The other evident influences on the Greek filmmaker are Bergman's somber look at family life and Antonioni's picturesque and quirky photography.
The film's title comes from when his attractive wife Anna (Renauld), who is deceased, but is seen in flashback as she was when she was his young wife. She answers her husband's question of how long tomorrow lasts, by saying it last for eternity and a day! This comes back to him when he is alone by the sea at his journey's end, and he jumps for joy thinking that he will meet his eternally youthful wife on the other side.
The poet's search starts mundanely when he visits the modern but cold apartment of his daughter to say goodbye he is going on a trip, and he has her read a letter he just found that her mother wrote to him at the time she was born. This is used as an excuse for Alexander to think back to the happy times in that house and the birth of his daughter. Her cold fish of a husband then comes out of the bath and gruffly tells the poet they sold the old house by the sea, where the poet had so many lovely memories, and the poet can only look disappointed, and doesn't even ask his son-in-law, who hates dogs, to watch his dog while he goes on his trip. Instead he will interrupt the wedding of his servant Urania's son, to get her to take the dog. There wasn't much point to that, except to watch the bride and groom stylishly dance through the streets of this small northern Greek town.
The film raises two nagging but specious philosophical questions, that will haunt him on his last journey, one he says aloud to himself after buying words for his poetry: "Why am I always a stranger in exile?" The other he asks of his ghostlike mother he visits in a hospital-like setting: " Why didn't we know how to love?"
The poet is on a bum trip, as he acts as if he were in a dazed dreamworld, thinking glumly about his death. At a red light he feels sorry for one of the traffic kids cleaning his window with a squeegee, who is suddenly being chased by the police. He decides to give the kid a ride, and finds out he is Albanian (Skevis), and is used by a ring that does scam adoptions to wealthy Greeks who can't adopt legally.
The difference in their journey's is: the boy's exile is political, while the poet's is spiritual.
The poet has rekindled hope when riding with the young orphan, he decides that he wants to help take the tight-lipped kid back to Albania. But the kid lied to him about having a grandmother there, and they trudge for nothing through the snowy border road along the misty mountain passes, amid the barrenness in which Angelopoulos shoots best, evoking a sense of being lost and alienated from the world, as they come to the border and end up running away from the border guard.
Out of his compassion for the child, he takes a deep interest in his problems, but that relationship is strangely unmoving, as the kid has no personality. The relationship is fueled only because of what they both have in common: they are afraid to be on their perilous journeys, inspite of their smiling faces they put on for show. But their bonding never seemed real, it was like a dance where they kept stepping on the other's foot, and they were never seen dancing gracefully together.
Ganz spoke in German when performing, which was later dubbed into Greek. But the little dialogue there was seems too supercilious anyway to really matter, as the weight of this film is captured only in its photography. As the film's spiritual guide, Ganz brings some authority to this desperate man searching for meaning to his incomplete life, who has worked, since his wife's death, on a 19th century unfinished poem. But the story seems too symbolic and arty to make a direct impact, every thought, no matter how banal, has to be philosophically scrutinized, which becomes unnerving.
We get to hear all of the poet's thoughts, his regrets, to see his visions of the past, and how his life is shaped by his thoughts and the words he has paid dearly to put into his work. The film is a slow meditation on his life memories, where every stop he makes, gives him a chance to recapture his life again. This film is a conspicuous art film (get a load of that overworked bus scene, on its spiritual route, where every passenger is used as a symbol--a poet in 19th century dress gets aboard, symbolizing that we still have not learned our lesson of virtue from the past).
To its credit, the film has certain scenes that stay with you the way a meditation exercise does, that may even alleviate some of the dullness the film generated, but it falls far short of a film that is great. The 66-year-old director has made an accessible film despite its ambiguity, but it was lacking fluidity in its overstated symbolism and its idiosyncratic statement was not that deep for all its huffing and puffing, and pouring out of philosophical thoughts. The film could have ended forty minutes sooner and still would have said what it ended up saying.
REVIEWED ON 8/31/2000 GRADE: B-
Dennis Schwartz: "Ozus' World Movie Reviews"
http://www.sover.net/~ozus
<EMAIL_ADDRESS>© ALL RIGHTS RESERVED DENNIS SCHWARTZ
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
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Related links: index of all rec.arts.movies.reviews reviews


| Name: | Theo Van der Burgt |
|---|---|
| Student No: | 300019142 |
| Email: |<EMAIL_ADDRESS>|
| Calix | Doing work on the sales aspects of their GigaSpire Series of routers with some sftwear development for aplication for the routers |
|---|---|
| Active Camps | Head of coding and gaming camps. Taught kids aged 7-13 wiht no coding experience how to make a basic game over the course of a week |
| Youth of Manotick Association | Facilitator running events for local youth on Firday nights |
| Youth of Manotick Association | One of the founding members in the creating of the local youth group. Over 150 hours of volenteering |
|---|


forces-assemble backend
This backend supports custom clients that wish to implement the following basic behavior.
- Users subscribe to various "channels".
- A user wishing to notify other users pushes an event on a channel.
- All subscribers to that channel receive a push notification with that event.
Test web clients
Test client with password sign-in
Google sign-in example
Description of how to integrate with the backend endpoints.
In order to authenticate with the backend, you need to follow the instructions to integrate your client with Firebase.


|
BL3 SDK
0.0.1
Borderlands 3 Class Documentation
|
#include <BL3_NavigationSystem_structs.hpp>
Public Attributes | |
| unsigned char | bNavFlag0: 1 |
| unsigned char | bNavFlag1: 1 |
| unsigned char | bNavFlag2: 1 |
| unsigned char | bNavFlag3: 1 |
| unsigned char | bNavFlag4: 1 |
| unsigned char | bNavFlag5: 1 |
| unsigned char | bNavFlag6: 1 |
| unsigned char | bNavFlag7: 1 |
| unsigned char | bNavFlag8: 1 |
| unsigned char | bNavFlag9: 1 |
| unsigned char | bNavFlag10: 1 |
| unsigned char | bNavFlag11: 1 |
| unsigned char | bNavFlag12: 1 |
| unsigned char | bNavFlag13: 1 |
| unsigned char | bNavFlag14: 1 |
| unsigned char | bNavFlag15: 1 |
| unsigned char | UnknownData00 [0x2] |
| unsigned char bNavFlag0 |
| unsigned char bNavFlag1 |
| unsigned char bNavFlag10 |
| unsigned char bNavFlag11 |
| unsigned char bNavFlag12 |
| unsigned char bNavFlag13 |
| unsigned char bNavFlag14 |
| unsigned char bNavFlag15 |
| unsigned char bNavFlag2 |
| unsigned char bNavFlag3 |
| unsigned char bNavFlag4 |
| unsigned char bNavFlag5 |
| unsigned char bNavFlag6 |
| unsigned char bNavFlag7 |
| unsigned char bNavFlag8 |
| unsigned char bNavFlag9 |
| unsigned char UnknownData00[0x2] |


1 On this lake they enact by night the story of the god's sufferings, a rite which the Egyptians call the Mysteries. I could say more about this, for I know the truth, but let me preserve a discreet silence.
2 Let me preserve a discreet silence, too, concerning that rite of Demeter which the Greeks call Thesmophoria , except as much of it as I am not forbidden to mention.
3 The daughters of Danaus were those who brought this rite out of Egypt and taught it to the Pelasgian women; afterwards, when the people of the Peloponnese were driven out by the Dorians, it was lost, except in so far as it was preserved by the Arcadians, the Peloponnesian people which was not driven out but left in its home.


{% load static %}
There are errors on this form!
You are not logged in yet
Username: {{ form.username }}
Password: {{ form.password }}
Forgot password? Click here to reset.


int getpagesize(void);
Feature Test Macro Requirements for glibc (see feature_test_macros(7)):
getpagesize():
_BSD_SOURCE || !(_POSIX_C_SOURCE >= 200112L || _XOPEN_SOURCE >= 600)
#include <unistd.h> long sz = sysconf(_SC_PAGESIZE);
(Most systems allow the synonym _SC_PAGE_SIZE for _SC_PAGESIZE.)
Whether getpagesize() is present as a Linux system call depends on the architecture. If it is, it returns the kernel symbol PAGE_SIZE, whose value depends on the architecture and machine model. Generally, one uses binaries that are dependent on the architecture but not on the machine model, in order to have a single binary distribution per architecture. This means that a user program should not find PAGE_SIZE at compile time from a header file, but use an actual system call, at least for those architectures (like sun4) where this dependency exists. Here glibc 2.0 fails because its getpagesize() returns a statically derived value, and does not use a system call. Things are OK in glibc 2.1.


Clean. Responsive. Mobile-first. Simple. This is the montra of the modern developer, and words I live by when developing my own projects. Developing clean, elagant sites by day, and studying computer science by night. I'm a developer with a drive to create the best.
Hire Me


At R&B Company, we are a vital part providing one of the most important resources to our communites: Water. The case studies you find below are a selection of jobs that the resources and expertise of R&B Company were used to get the job done. Wether it is a simple as installing a new fire line or a new well and water treatment center.
Central Valley Drought Relief
Bakersfield, CA.
Farmers and Irrigation districts trough out the Central Valley are turning to enclosed pipelines to transport water instead of canals in order to minimize water loss.
Read MoreIrrigation Bypass
Dixon, CA.
During the contruction of new weir's in Salona County, HDPE pipe was used to create a temporary bypass to keep water flowing to the adjacent farmlands.
Read MoreArmona Well & Water Treatment
Fresno, CA.
A new water treatment facility gets installed in the Central Valley Community of Armona. This facility will help the community remove Arsenic, Iron and Aluminum from the water.
Read MoreHeartland Gardens
Gilroy, CA.
Development of the new community in Gilroy's Heartland Gardens used HDPE pipe to install a new reclaimed water line. Both the existing line and the new line will provide reclaimed water to the Gilroy Gold course.
Read MoreMoss Landing Power Plant
Moss Landing, CA.
The Moss Landing Power plant has thousands of feet of HDPE pipe running below it. Due to the being fused under pressure when it was first out in, many leaks have begun to appear. R&B Fusion has been helping to repair those leaks.
Read MoreLandels Elementary School
Mountain View, CA.
When Landels Elementary School added a new sports building to the campus, they choose to use HDPE pipe for the new fire line that had to be installed. By using HDPE, they were able to use HDD to install the new pipe and this resulted in less damage to the campus.
Read More


{% extends "pathways/snippets/question.html" %} {% load i18n %} {% load static %} {% block question %}
{% blocktrans %} Because you indicated someone in your household is enrolled in an assistance program like SNAP or HEAP, your household is automatically eligible to receive a discount on your water bill. {% endblocktrans %}
{% else %}{% blocktrans with household_size=request.session.household_size %} The pre-tax annual income limit for a household size of {{ household_size }} is {{ max_income }}. {% endblocktrans %} {% if is_eligible %} {% trans "Based on your answers, you look to be under the pre-tax income limit." %} {% else %} {% trans "Based on your answers, you look to be over the pre-tax income limit." %} {% endif %}
{% if not is_eligible %}{% blocktrans %} If you are interested in any of these additional Pathways to Affordable Water, please contact Buffalo Water directly at buffalowater.org/contactus/ {% endblocktrans %}


This example demonstrates switching between different intervals of aggregation over time.
You can supply your own data source with query string parameters:
average
total


Yoga Sleep is made by Nick Cole, a yoga instructor, cognitive behavioural hypnotherapist and life coach based in Vancouver, British Columbia. For more information visit www.digitalspirituallife.com. For feedback, requests or questions related to Yoga Sleep, please select the link below or visit the contact page on the website. The app will continually be improved and updated with new recordings and more advanced features so we would love to hear what you like, don't like and would like to see.


|
Connected Home over IP
672cf7684
|
Classes | |
| class | bdist_wheel_override |
| class | InstalledScriptInfo |
Variables | |
| parser = argparse.ArgumentParser(description='build the pip package for chip using chip components generated during the build and python source code') | |
| default | |
| help | |
| args = parser.parse_args() | |
| string | chipDLLName = '_ChipDeviceCtrl.so' |
| packageName = args.package_name | |
| chipPackageVer = args.build_number | |
| list | installScripts |
| curDir = os.curdir | |
| manifestFile = os.path.abspath(args.manifest) | |
| buildDir = os.path.abspath(args.build_dir) | |
| distDir = os.path.abspath(args.dist_dir) | |
| tmpDir = os.path.join(buildDir, 'chip-wheel-components') | |
| manifest = json.load(open(manifestFile, 'r')) | |
| exist_ok | |
| manifestBase = os.path.dirname(manifestFile) | |
| srcDir = os.path.join(manifestBase, entry['src_dir']) | |
| srcFile = os.path.join(srcDir, path) | |
| dstFile = os.path.join(tmpDir, path) | |
| requiredPackages | |
| list | packages |
| name | |
| version | |
| description | |
| url | |
| license | |
| classifiers | |
| python_requires | |
| package_dir | |
| package_data | |
| scripts | |
| install_requires | |
| options | |
| cmdclass | |
| script_args | |
| build-chip-wheel.args = parser.parse_args() |
| build-chip-wheel.buildDir = os.path.abspath(args.build_dir) |
| string build-chip-wheel.chipDLLName = '_ChipDeviceCtrl.so' |
| build-chip-wheel.chipPackageVer = args.build_number |
| build-chip-wheel.classifiers |
| build-chip-wheel.cmdclass |
| build-chip-wheel.curDir = os.curdir |
| build-chip-wheel.default |
| build-chip-wheel.description |
| build-chip-wheel.distDir = os.path.abspath(args.dist_dir) |
| build-chip-wheel.dstFile = os.path.join(tmpDir, path) |
| build-chip-wheel.exist_ok |
| build-chip-wheel.help |
| build-chip-wheel.install_requires |
| list build-chip-wheel.installScripts |
| build-chip-wheel.license |
| build-chip-wheel.manifest = json.load(open(manifestFile, 'r')) |
| build-chip-wheel.manifestBase = os.path.dirname(manifestFile) |
| build-chip-wheel.manifestFile = os.path.abspath(args.manifest) |
| build-chip-wheel.name |
| build-chip-wheel.options |
| build-chip-wheel.package_data |
| build-chip-wheel.package_dir |
| build-chip-wheel.packageName = args.package_name |
| build-chip-wheel.packages |
| build-chip-wheel.parser = argparse.ArgumentParser(description='build the pip package for chip using chip components generated during the build and python source code') |
| build-chip-wheel.python_requires |
| build-chip-wheel.requiredPackages |
| build-chip-wheel.script_args |
| build-chip-wheel.scripts |
| build-chip-wheel.srcDir = os.path.join(manifestBase, entry['src_dir']) |
| build-chip-wheel.srcFile = os.path.join(srcDir, path) |
| build-chip-wheel.tmpDir = os.path.join(buildDir, 'chip-wheel-components') |
| build-chip-wheel.url |
| build-chip-wheel.version |


Luke Folger Gallery
About the Artist
Working Title 1
Optional description.
Working Title 2
Optional description.
Working Title 3
Optional description.
Working Title 4
Optional description.


Flexbox is a layout model for CSS3, it allows the browser to arrange elements on the screen in a predictive way.
Flexbox is fluid, responsive, adaptive
Short answer is: YES>
(except if you have to support IE8/9)
There are still some quirks and bugs and support is not complete across the board (caniuse.com) but most of it is working fine on most platforms/browsers
Main issue: wrapping elements
There are 2 main elements in a flexbox layout:
A container is used to wrap your flex items
It defines the flow, distribution and alignment of the items
An item is an element in the flexbox flow
It can alter its size, relative size, order and alignment
.mycontainer {
display: flex;
}
Let see a basic example
Important: only the direct children elements are affected
for better compatibility:
.mycontainer {
display: -ms-flex;
display: -webkit-flex;
display: flex;
}
The -webkit-
and -ms-
prefixes are ensuring the extra.
Behold the almighty absolute centering
html,
body {
height: 100%;
}
.container {
display: flex;
height: 100%;
}
.item {
margin: auto;
}
.container {
display: flex;
flex-direction: column;
}
Options are: row
(default), column
, row-reverse
, column-reverse
.container {
align-items: flex-start;
display: flex;
}
Options are: stretch
(default), flex-start
, flex-end
, center
, baseline
.container {
display: flex;
justify-content: flex-end;
}
Options are: flex-start
(default), flex-end
, center
, space-between
, space-around
.item {
flex: 1;
}
.item-1 {
order: 2;
}
.item-2 {
order: 3;
}
.item-3 {
order: 1;
}
.item-1 {
flex: 3;
}
.item-2,
.item-3 {
flex: 1;
}
This presentation and the examples are availabe at https://github.com/hrbonz/flexbox-presentation/


Chapter 1 Analysing Texts
Learning Objectives
- to come
We’ll use several libraries today. sotu
will provide the metadata and text of State of the Union speeches ranging from George Washington to Barack Obama. tidyverse
provides many of the standard “verbs” for working with our data. tidytext
provides specific functions for a “tidy” approach to working with textual data. readtext
provides a function well suited to reading textual data from a large number of formats into R.
library(sotu)
library(tidyverse)
library(tidytext)
library(readtext)
1.1 Reading text into R
First, let’s look at the data in the sotu
package. The metadata and texts come separately. We’ll use the supplied metadata object, but we’re going to use a utility function (sotu_dir
) in the package to write the texts to disk so that we can practice reading text files from disk.
# Let's take a quick look at the state of the union metadata
summary(sotu_meta)
# sotu_dir writes the text files to a temporary dir, but you could specific where you want them.
fp <- sotu_dir()
head(fp)
Now that we have the files on disk, and a list of filepaths stored in the fp
variable, we can use readtext
to read the texts into a new variable.
# let's then read in the files with readtext
texts <- readtext(fp)
head(texts)
So that we can work with a single tabular dataset with a tidy approach, we’ll convert the metadata and text tables to tibbles, and combine them into a single tibble. You can see that our texts are organized by alphabetical order, so first we’ll need to sort our metadata to match.
sotu_meta_tib <- as_tibble(sotu_meta) %>%
arrange(president)
head(sotu_meta_tib)
# We can now combine the sotu metadata with the texts
# first, we'll turn both pieces of data into tibbles, then combine
sotu_texts <- as_tibble(texts)
sotu_whole <- bind_cols(sotu_meta_tib, sotu_texts)
glimpse(sotu_whole)
Now that we have our data, we need to think about cleaning it. Depending on the quality of your data, you might need to explicitly replace certain characters or words, remove urls or types of numbers, such as phone numbers, or otherwise clean up misspellings or errors. There are several ways to handle this sort of cleaning, but we’ll look at some straightforward string manipulation and replacement.
1.2 String operations
R has many functions available to manipulate strings including functions like grep
and paste
, which come with the R base install.
Perhaps one of the most comprehensive packages is stringi
. However, we will here take a look at the stringr
package, which is part of the tidyverse
, wraps a lot of the stringi functions, and is easier to begin with.
Below are a examples for a few functions that might be useful.
- How many words in each speech?
str_count(sotu_whole$text, boundary("word"))
- Measured by the average number of words per sentence for each speech - what is the length of the speech with the shortest/longest sentences?
range(str_count(sotu_whole$text, boundary("word"))/str_count(sotu_whole$text, boundary("sentence")))
How man times does the word “citizen” appear in the speeches?
str_count(sotu_whole$text, "[C|c]itizen")
What are the names of the documents in of the speeches where the word “citizen” does not occur?
sotu_whole$doc_id[!str_detect(sotu_whole$text, "[C|c]itizen")]
- Get me the first 5 words for each speech
word(sotu_whole$text, end = 5) %>%
unique()
- Now remove newline character (
\n
) and get rid of the leading white space:
word(sotu_whole$text, end = 5) %>%
unique() %>%
str_replace_all("\\n", " ") %>%
str_trim()
(For spell checks take a look at https://CRAN.R-project.org/package=spelling or https://CRAN.R-project.org/package=hunspell)
1.3 Tokenize, lowercase
A very common part of data cleaning involves tokenization. While our data is already “tidy” insofar as each row is a single observation, a single text with metdata, the tidytext approach goes a step further to make each word it’s own observation with metadata. We could write our own function to do this using a tokenizer, but tidytext
provides a handy utility function just for this purpose.
tidy_sotu <- sotu_whole %>%
unnest_tokens(word, text)
tidy_sotu
Before we move on, we should note that the unnest_tokens
function didn’t just tokenize our texts at the word level. It also lowercased each word, and it could do quite a bit more. For instance, we could tokenize the text at the level of ngrams or sentences, if those are the best units of analysis for our work. We could also leave punctuation, which has been removed by default. Depending on what you need to do for analysis, you use do these operations during this step, or write custom functions and do it before you unnest tokens.
# Word tokenization with punctuation
tidy_sotu_w_punct <- sotu_whole %>%
unnest_tokens(word, text, strip_punct = FALSE)
tidy_sotu_w_punct
# Sentence tokenization
tidy_sotu_sentences <- sotu_whole %>%
unnest_tokens(sentence, text, token = "sentences", to_lower = FALSE)
tidy_sotu_sentences
# N-gram tokenization
tidy_sotu_trigram <- sotu_whole %>%
unnest_tokens(trigram, text, token = "ngrams", n = 3)
tidy_sotu_trigram
1.4 Stopwords
Another common type of cleaning in text analysis is to remove stopwords, or common words that theoretically provide less information about the content of a text. Depending on the type of analysis you’re doing, you might leave these words in or use a highly curated list of stopwords. For now, as we move toward looking at words in documents based on frequency, we will remove some standard stopwords using a tidytext approach.
First, let’s look at the stopwords that tidytext gives us to get a sense of what they are.
data(stop_words)
head(stop_words, n = 60)
You can see that we now have one word per row with associated metadata. We can now remove stopwords using an anti-join
.
tidy_sotu_words <- tidy_sotu %>%
anti_join(stop_words)
tidy_sotu_words
We went from 1965212 to 778161 rows, which means we had a lot of stopwords in our corpus. This is a huge removal, so for serious analysis, we might want to take a closer look at the stopwords and determine if we should use a different stopword list or otherwise create our own.
1.5 Word Stemming
Another thing you may want to do is to stem your words, that is, to reduce them to their word stem or root form, like reducing fishing, fished, and fisher to the stem fish.
tidytext
does not implement its own word stemmer. Instead it relies on separate packages like hunspell
or SnowballC
.
We will give an example here for the SnowballC
package. (hunspell
appears to run much slower, and it also returns a list instead of a vector, so in this context SnowballC
seems to be more convenient.)
library(SnowballC)
tidy_sotu_words %>%
mutate(word_stem = wordStem(word)) %>% head()
For lemmatization, you may want to take a look a the koRpus
package, another comprehensive R package for text analysis. It allows to use TreeTagger, a widely used part-of-speech tagger. For full functionality of the R package a local installation of TreeTagger is recommended.
Now that we’ve read in our text and metadata, reshaped it a bit into the tidytext format, and cleaned it a bit while doing so, let’s move on to some basic analysis.
TODO?: Tag text with cleanNLP maybe?


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JS Pride
Invitation webgl demo to
demojs
, 28-30 June, Paris
Download :
js-pride.rar
View in your navigator
Made by
wsmind : code
titeiko : 3D
modraw : music


Matahi MOARII
Mail: moariim at mskcc dot org
Address: Memorial Sloan Kettering Cancer Center - Papaemmanuil Lab - Department of Epidemiology and Biostatistics
Zuckerman Research Center, 417 East 68th Street, Room 545-B, New York, NY 10065
I am a postdoctoral research fellow at the Memorial Sloan Kettering Cancer Center in the Department of Epidemiology and Biostatistics under the supervision of Elli Papaemmanuil. I am trying to delineate the heterogeneity of the hematopoietic and lymphoid tissues such as Acute Myeloid Leukemia from genetic and transcriptomic sequencing data using machine learning in order to develop personalized predictive models for diagnosis and targeted therapy.
I obtained my PhD at the Center for Computational Biology from the Ecole Mines Paristech under the supervision of Jean-Philippe Vert and Fabien Reyal. I was a fellow from the Ligue Nationale contre le Cancer, a French non-profit organization which funds research against cancer in France. During my thesis, I was working on the role of Epigenetics in particular the role of DNA Methylation in gene expression variation using Machine Learning.
I'm mostly interested in:


| NEWS | R Documentation |
The transmission models now contain an intercept term iota
.
lambda.out
is now present as a parameter in all models.
The recovery rate gamma
is assumed constant everywhere (in and out of hospital) for all models.
The filter functions now return the patient ID.
The simulated data in fake_data
now use a character variable as the unique identifier for the patients.
Export new functions indep_homog_filter
, indep_unit_spec_filter
, trans_homog_filter
, and trans_unit_spec_filter
, which perform appropriate versions of the filtering computations.
Fixed bug in the parameterization of the unit-specific transmission model (trans_unit_spec_objfun
).
The a
parameter is now global.
Fixed bug in the parameterization of the homogeneous transmission model (trans_homog_objfun
).
It is possible to set maxit
and tol
at the top level.
Efficiency is much greater now that patients out of hospital are jumped immediately to the next admission.
Transmission model is reparameterized in terms of a and b.
Refactor the independent model objective functions.
The fake data in fake_data
no longer have contact isolation when patients are out of the hospital.
The codes have been refactored to reduce unnecessary data manipulation.


Functions are re-usable collections of statements.
First declare the function:
function sayMyName() {
console.log('Hi Claire!');
}
//Then call it (as many times as you want):
sayMyName();
Functions can accept any number of named arguments:
function sayMyName(name) {
console.log('Hi, ' + name);
}
sayMyName('Claire');
sayMyName('Testy McTesterFace');
function addNumbers(num1, num2) {
var result = num1 + num2;
console.log(result);
}
addNumbers(7, 21);
addNumbers(3, 10);
Parameters: noun. Information. Stuff.
1. the information the function needs to perform its task
2. parameter values are called arguments
3. arguments can be values (i.e. specific numbers) or variables
Making decisions with code is called control flow.
Control flow statements enable JavaScript to make decisions by executing different code based on a condition.
For example, is the weather cold today?
var safeToProceed = true;
if (safeToProceed) {
alert("You shall pass!");
} else {
alert("You shall not pass!");
}
var safeToProceed = false;
if (safeToProceed) {
alert("You shall pass!");
} else {
alert("You shall not pass!");
}
If...else statements allow you to execute certain pieces of code based on a condition, or set of conditions, being met.
if (/* this expression is true */) {
// run this code
} else {
// run this code
}
var number = 16;
if (number % 2 === 0) {
console.log("even");
} else {
console.log("odd");
}


If You Ever Come to Western Nebraska
Come in late summer, early fall. Come when the cornfields stand up straight and tall — holding ears full of two seasons of hard farm work. Find someone who can get you a dozen of the sweet kind. You’ll be hard-pressed to find better.
Seek out a good place to watch the sky. Sit with a cold glass of whatever you choose as the thunderheads roll east from the mountains. In the afternoon, they might sweep overhead, spitting a little


data class ConstraintInfo
Constraint information associated with a net.corda.v5.ledger.contracts.ContractState. See CPKConstraint
Type |
enum class Type |
<init> |
Constraint information associated with a net.corda.v5.ledger.contracts.ContractState. See CPKConstraint ConstraintInfo(constraint: CPKConstraint) |
constraint |
val constraint: CPKConstraint |
data |
fun data(): ByteArray? |
type |
fun type(): Type |


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class: center, middle, inverse, title-slide # STA 235 - Review Session ## Spring 2021 ### McCombs School of Business, UT Austin --- <style type="text/css"> .small .remark-code { /*Change made here*/ font-size: 80% !important; } .tiny .remark-code { /*Change made here*/ font-size: 90% !important; } </style> # Some Updates .box-2LA[Homework 2 will be posted today (due March 8th)] -- - Shorter assignment, but you **.darkorange[need to review the material and videos]**. -- - Get your questions in **.darkorange[early]** (OH or Piazza). **.darkorange[No answers during the weekend]**. -- - Run the **.darkorange[R scripts]** posted for each class, and replicate other exercises. -- - Slides and videos for matching class will be posted **.darkorange[tomorrow]**. --- # Some Updates (cont.) .box-4LA[Midterm is now on 03/29] -- - It will be **.darkorange[very similar to homework assignments]**. -- - You will need a **.darkorange[web cam or camera]**. -- - Make sure you have a **.darkorange[stable internet connection]**. -- - Absences to the midterm need to be **.darkorange[properly justified]** and your midterm grade will be **.darkorange[the grade on your final exam]**. --- # Other notes -- .box-2[It's ok to struggle with the homework] -- .box-4[It's ok to struggle with R code] -- .box-5[Ask questions, reach out!] -- .box-7[Do it in a timely manner!] --- # Professional Courtesy: The Hidden Curriculum -- .box-1[Plan ahead!] -- .box-3[Weekends/non-regular working hours are important] -- .box-6[For meetings, propose a number of dates and time slots] -- .box-7[Follow instructions] --- .center2[ .box-5LA[Let's review Homework 1]]


This issue of Emerging Infectious Diseases highlights the role of arthropod vectors in the origin and dissemination of emerging pathogens. As Woolhouse and Gaunt have pointed out ( 1 ), a substantial proportion of human pathogens are zoonotic and vector-borne, and they infect a substantial proportion of the world’s population. Vector-borne pathogens also are prominent contributors to emerging disease. There are 3 principal reasons for this influence.
First, most major classes of pathogens have evolved agents that are capable of being transmitted by blood-feeding arthropods: viruses (e.g., yellow fever virus, Rift Valley fever virus), rickettsiae ( Rickettsia rickettsii, R. typhi), bacteria ( Borrelia burgdorferi, Francisella tularensis), protozoa (genera Plasmodium and Leishmania), and helminths ( Onchocerca volvulus, Wuchereria bancrofti). Fungi seem to be the only category not represented.
Second, vectors bridge barriers that would prevent transmission by direct contact among humans and especially between animals and humans. These barriers are not only spatial but behavioral and ecological. Transmission of yellow fever virus between arboreal monkeys and humans by mosquitoes is the classic example, but there are many others; transmission of B. burgdorferi, the agent of Lyme disease, between evasive forest rodents and humans by ticks is just as exemplary. In such cases, direct contact between feral host and human would rarely take place. A corollary of this ability to bridge environments occurs when animals or humans move the pathogen from one vector-capable region to another. The introduction of West Nile virus into the United States in 1999 was a dramatic example, as was the recent introduction of Usutu virus to Europe from Africa in migrating birds ( 2 ). The potential for vector-borne zoonotic transmission to adapt to vector-borne human-to-human transmission is exemplified historically by dengue virus and Plasmodium spp., and more recently by Zika virus ( 3 ) and probably P. knowlesi ( 4 ).
Third, the complexity of vector transmission offers the pathogen increased opportunities to evolve. In almost no instances is the arthropod simply a vessel for transmission. Usually, the pathogen must move from the gut to the feeding apparatus to be transmitted. Mechanisms range from the relatively simple, as with the plague bacillus, Yersinia pestis, to the elaborately intricate, as with parasites in the genera Plasmodium and Leishmania. In these examples, the pathogen replicates in some fashion, which makes it dependent on an invertebrate host physiology much different from what it will encounter in its various vertebrate hosts. As a consequence, epidemic emergence can result from enhanced transmission independent of increased pathogenicity to humans. This is especially true of the arthropod-borne viruses (arboviruses) that infect humans, all of which are RNA viruses and have high potential mutability. A notable recent example is the chikungunya virus epidemic that swept through the Indian Ocean region beginning in 2006 and which is believed to have infected >2 million persons. A single-nucleotide polymorphism (SNP) in the virus genome accelerated its replication in the relatively common mosquito Aedes albopictus, usually a poorer host than Ae. aegypti mosquitoes ( 5 ). There is also evidence that an SNP enabled Venezuelan equine encephalitis virus to jump vectors, sparking the 1993 epidemic in Mexico ( 6 ), and it might have been an SNP in West Nile virus that increased its virulence to birds and influenced the shape of the epidemic in the United States ( 7 ). In none of these examples was increased pathogenicity to humans an apparent seminal factor in the epidemics.
Complexity of epidemiology and adaptive plasticity of pathogen and arthropod make the vector-borne diseases especially difficult to control, much less to eradicate. Vaccines are unavailable for all but a few diseases; and even when they are available, as for yellow fever, prevention can be difficult to achieve. The yellow fever epidemic that began in Uganda at the end of 2010 was the first in that country in 20 years. Tools for treatment are nearly as scarce. Falling behind in the race to keep up with developing resistance of P. falciparum to artemisinins is a specter that haunts malariologists, and treatment for visceral leishmaniasis remains too expensive and complicated to be widely practiced where it is most needed.
The constant development of pesticide resistance is even more worrisome than drug resistance because a pesticide can often be used to suppress vectors of many different pathogens. Even when pesticides are efficacious, their effectiveness is often compromised by human behavior and vector biology, as is often seen in campaigns against dengue. Changes in climate, land use, and transport will affect rates of pathogen emergence in ways we poorly understand. Fortunately, there is a growing appreciation by scientists and by funding agencies ( 8 ) that characterizing factors that influence pathogen and disease emergence are worthy goals for investigation, especially in those tropical environments where rapid change is most likely to incubate new pathogens.
Suggested citation for this article: Rosenberg R, Beard CB. Vector-borne infections. Emerg Infect Dis [serial on the Internet]. 2011 May [ date cited]. http://dx.doi.org/10.3201/eid1705.110310
Dr Rosenberg is associate director for science in the Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, Fort Collins, Colorado.
Dr Beard is chief of the Bacterial Diseases Branch, Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, Fort Collins, Colorado. His research interests are Lyme disease, plague, tularemia, and the influence of climate on disease ecology.