class: center, middle, inverse, title-slide # ETC1010: Data Modelling and Computing ## Week of Tidy Data ### Professor Di Cook & Dr. Nicholas Tierney ### EBS, Monash U. ### 2019-08-07 --- class: bg-blue .vvvhuge.white.center.middle[ What is this song? ] --- class: bg-black .gigantic.white.middle.center[ Recap ] --- class: bg-main1 .vhuge[ Hopefully a lot of you have done the Survey ] .large.pull-left[ - Traffic Light System: .green[Green = "good!"] ; .red[Red = "Help!"] - R + Rstudio - Tower of babel analogy for writing R code - We are using ___, not ___ for ETC1010? - Functions are ___ - columns in data frames are accessed with ___ ? ] .large.pull-right[ - packages are installed with ___ ? - packages are loaded with ___ ? - Why do we care about Reproducibility? - Output + input of rmarkdown - I have an assignment group - If I have an assignment group, have recorded my assignment group in the ED survey ] --- # Today: Outline .huge[ - An aside on learning - Tidy Data - Terminology of data - Different examples of data - Steps in making data tidy - Lots of examples ] --- # A note on difficulty .huge[ * This is not a programming course - it is a course about **data, modelling, and computing**. ] -- .huge[ * At the moment, you might be sitting there, feeling a bit confused about where we are, what are are doing, what R is, and how it even works. * That is OK! ] --- # A note on difficulty .huge[ * The theory of this class will only get you so far * The real learning happens from doing the data analysis - the **pressure of a deadline can also help.** ] --- # An aside on learning .huge[ * I want to take the first 15 minutes of class to discuss some ideas on learning, and how this ties into the course. * [new slides] ] --- class: bg-black .white.vvvhuge[Tidy Data]  --- .blockquote.huge[ You're ready to sit down with a newly-obtained dataset, excited about how it will open a world of insight and understanding, and then find you can't use it. You'll first have to spend a significant amount of time to restructure the data to even begin to produce a set of basic descriptive statistics or link it to other data you've been using. --John Spencer ] Source: [Measure Evaluation](https://www.measureevaluation.org/resources/newsroom/blogs/tidy-data-and-how-to-get-it) --- .blockquote.huge[ "Tidy data" is a term meant to provide a framework for producing data that conform to standards that make data easier to use. Tidy data may still require some cleaning for analysis, but the job will be much easier. --John Spencer ] Source: [Measure Evaluation](https://www.measureevaluation.org/resources/newsroom/blogs/tidy-data-and-how-to-get-it) --- # Example: US graduate programs .huge[ - Data from a study on US grad programs. - Originally came in an excel file containing rankings of many different programs. - Contains information on four programs: 1. Astronomy 1. Economics 1. Entomology, and 1. Psychology ] --- # Example: US graduate programs ```r library(tidyverse) grad <- read_csv("data/graduate-programs.csv") grad %>% top_n(10) # A tibble: 10 x 16 subject Inst AvNumPubs AvNumCits PctFacGrants PctCompletion <chr> <chr> <dbl> <dbl> <dbl> <dbl> 1 econom… BOST… 0.49 2.66 36.9 34.2 2 econom… UNIV… 0.79 2.68 71.4 42.6 3 econom… UNIV… 0.61 3.44 54.8 62.5 4 econom… UNIV… 0.61 1.81 50.4 37.9 5 psycho… NORT… 0.92 1.32 45.8 32.1 6 psycho… UNIV… 1.42 4.45 72 48.9 7 psycho… UNIV… 1.15 3.47 69.5 46.8 8 psycho… UNIV… 1.05 1.72 65.6 34.2 9 psycho… UNIV… 1.39 3.3 57.2 28.1 10 psycho… UNIV… 2.02 2.89 69.9 39 # … with 10 more variables: MedianTimetoDegree <dbl>, # PctMinorityFac <dbl>, PctFemaleFac <dbl>, PctFemaleStud <dbl>, # PctIntlStud <dbl>, AvNumPhDs <dbl>, AvGREs <dbl>, TotFac <dbl>, # PctAsstProf <dbl>, NumStud <dbl> ``` --- ## Example: US graduate programs .huge[ What's good about the format? ] -- .huge[ - **Rows** contain information about the institution - **Columns** contain types of information, like average number of publications, average number of citations, % completion, ] --- # Example: US graduate programs .huge[ Easy to make summaries: ```r grad %>% count(subject) # A tibble: 4 x 2 subject n <chr> <int> 1 astronomy 32 2 economics 117 3 entomology 27 4 psychology 236 ``` ] --- # Example: US graduate programs .huge[ Easy to make summaries: ```r grad %>% filter(subject == "economics") %>% summarise(mean = mean(NumStud), s = sd(NumStud)) # A tibble: 1 x 2 mean s <dbl> <dbl> 1 60.7 39.4 ``` ] --- # Example: US graduate programs .huge[ Easy to make plot ```r grad %>% filter(subject == "economics") %>% ggplot(aes(x = NumStud, y = MedianTimetoDegree)) + geom_point() + theme(aspect.ratio = 1) ```  ] --- class: bg-main1 # Your Turn: Go to the rstudio.cloud + open Lecture 2A. .huge[ - Notice the `data/` directory with many datasets! - flag a tutor with the traffic light system if you need a hand. - Open the `graduate-programs.Rmd` file - Can you answer these questions? - "What is the average number of graduate students per economics program?:" - "What is the best description of the relationship between number of students and median time to degree?" ] ```r countdown(minutes = 3) ```
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??? - "The average number of graduate students per economics program is:" - "about 61" (correct) - about 39 "What is the best description of the relationship between number of students and median time to degree?" - "as the number of students increases the median time to degree increases, weakly" (correct) - as the number of students increases the variability in median time to degree decreases --- ## Terminology of data: Variable .pull-left.huge[ - A quantity, quality, or property that you can measure. - For the grad programs, these would be all the column headers. ] .pull-right.huge[ ```r grad # A tibble: 412 x 16 subject Inst AvNumPubs AvNumCits PctFacGrants PctCompletion <chr> <chr> <dbl> <dbl> <dbl> <dbl> 1 econom… ARIZ… 0.9 1.57 31.3 31.7 2 econom… AUBU… 0.79 0.64 77.6 44.4 3 econom… BOST… 0.51 1.03 43.5 46.8 4 econom… BOST… 0.49 2.66 36.9 34.2 5 econom… BRAN… 0.3 3.03 36.8 48.7 6 econom… BROW… 0.84 2.31 27.1 54.6 7 econom… CALI… 0.99 2.31 56.4 83.3 8 econom… CARN… 0.43 1.67 35.2 45.6 9 econom… CITY… 0.35 1.06 38.1 27.9 10 econom… CLAR… 0.47 0.7 24.7 37.7 # … with 402 more rows, and 10 more variables: MedianTimetoDegree <dbl>, # PctMinorityFac <dbl>, PctFemaleFac <dbl>, PctFemaleStud <dbl>, # PctIntlStud <dbl>, AvNumPhDs <dbl>, AvGREs <dbl>, TotFac <dbl>, # PctAsstProf <dbl>, NumStud <dbl> ``` ] --- ## Terminology of data: Observation .pull-left.huge[ - A set of measurements made under similar conditions - Contains several values, each associated with a different variable. - For the grad programs, this is institution, and program, uniquley define the observation. ] .pull-right[ ```r grad # A tibble: 412 x 16 subject Inst AvNumPubs AvNumCits PctFacGrants PctCompletion <chr> <chr> <dbl> <dbl> <dbl> <dbl> 1 econom… ARIZ… 0.9 1.57 31.3 31.7 2 econom… AUBU… 0.79 0.64 77.6 44.4 3 econom… BOST… 0.51 1.03 43.5 46.8 4 econom… BOST… 0.49 2.66 36.9 34.2 5 econom… BRAN… 0.3 3.03 36.8 48.7 6 econom… BROW… 0.84 2.31 27.1 54.6 7 econom… CALI… 0.99 2.31 56.4 83.3 8 econom… CARN… 0.43 1.67 35.2 45.6 9 econom… CITY… 0.35 1.06 38.1 27.9 10 econom… CLAR… 0.47 0.7 24.7 37.7 # … with 402 more rows, and 10 more variables: MedianTimetoDegree <dbl>, # PctMinorityFac <dbl>, PctFemaleFac <dbl>, PctFemaleStud <dbl>, # PctIntlStud <dbl>, AvNumPhDs <dbl>, AvGREs <dbl>, TotFac <dbl>, # PctAsstProf <dbl>, NumStud <dbl> ``` ] --- ## Terminology of data: Value .pull-left.huge[ - Is the state of a variable when you measure it. - The value of a variable typically changes from observation to observation. - For the grad programs, this is the value in each cell ] .pull-right[ ```r grad # A tibble: 412 x 16 subject Inst AvNumPubs AvNumCits PctFacGrants PctCompletion <chr> <chr> <dbl> <dbl> <dbl> <dbl> 1 econom… ARIZ… 0.9 1.57 31.3 31.7 2 econom… AUBU… 0.79 0.64 77.6 44.4 3 econom… BOST… 0.51 1.03 43.5 46.8 4 econom… BOST… 0.49 2.66 36.9 34.2 5 econom… BRAN… 0.3 3.03 36.8 48.7 6 econom… BROW… 0.84 2.31 27.1 54.6 7 econom… CALI… 0.99 2.31 56.4 83.3 8 econom… CARN… 0.43 1.67 35.2 45.6 9 econom… CITY… 0.35 1.06 38.1 27.9 10 econom… CLAR… 0.47 0.7 24.7 37.7 # … with 402 more rows, and 10 more variables: MedianTimetoDegree <dbl>, # PctMinorityFac <dbl>, PctFemaleFac <dbl>, PctFemaleStud <dbl>, # PctIntlStud <dbl>, AvNumPhDs <dbl>, AvGREs <dbl>, TotFac <dbl>, # PctAsstProf <dbl>, NumStud <dbl> ``` ] --- ## Tidy tabular form .huge[ __Tabular data__ is a set of values, each associated with a variable and an observation. Tabular data is __tidy__ iff (if and only if): * Each variable in its own column, * Each observation in its own row, * Each value is placed in its own `cell`. ] --- background-image: url(https://njtierney.updog.co/img/tidy-data.png) background-size: contain background-position: 50% 50% class: center, bottom, black --- # The grad program .huge[ Is in **tidy** tabular form. ] ```r grad # A tibble: 412 x 16 subject Inst AvNumPubs AvNumCits PctFacGrants PctCompletion <chr> <chr> <dbl> <dbl> <dbl> <dbl> 1 econom… ARIZ… 0.9 1.57 31.3 31.7 2 econom… AUBU… 0.79 0.64 77.6 44.4 3 econom… BOST… 0.51 1.03 43.5 46.8 4 econom… BOST… 0.49 2.66 36.9 34.2 5 econom… BRAN… 0.3 3.03 36.8 48.7 6 econom… BROW… 0.84 2.31 27.1 54.6 7 econom… CALI… 0.99 2.31 56.4 83.3 8 econom… CARN… 0.43 1.67 35.2 45.6 9 econom… CITY… 0.35 1.06 38.1 27.9 10 econom… CLAR… 0.47 0.7 24.7 37.7 # … with 402 more rows, and 10 more variables: MedianTimetoDegree <dbl>, # PctMinorityFac <dbl>, PctFemaleFac <dbl>, PctFemaleStud <dbl>, # PctIntlStud <dbl>, AvNumPhDs <dbl>, AvGREs <dbl>, TotFac <dbl>, # PctAsstProf <dbl>, NumStud <dbl> ``` --- # Different examples of data .huge[ For each of these data examples, **let's try together to identify the variables and the observations** - some are HARD! ] --- # Your Turn: Genes experiment 🤔 ```r genes <- read_csv("data/genes.csv") genes # A tibble: 3 x 12 id `WI-6.R1` `WI-6.R2` `WI-6.R4` `WM-6.R1` `WM-6.R2` `WI-12.R1` <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> 1 Gene… 2.18 2.20 4.20 2.63 5.06 4.54 2 Gene… 1.46 0.585 1.86 0.515 2.88 1.36 3 Gene… 2.03 0.870 3.28 0.533 4.63 2.18 # … with 5 more variables: `WI-12.R2` <dbl>, `WI-12.R4` <dbl>, # `WM-12.R1` <dbl>, `WM-12.R2` <dbl>, `WM-12.R4` <dbl> ``` ```r countdown(minutes = 3, play_sound = TRUE) ```
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--- # Melbourne weather 😨 ```r melbtemp # A tibble: 1,593 x 12 X1 X2 X3 X4 X5 X9 X13 X17 X21 X25 X29 X33 <chr> <dbl> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> 1 ASN00… 1970 07 TMAX 141 124 113 123 148 149 139 153 2 ASN00… 1970 07 TMIN 80 63 36 57 69 47 84 78 3 ASN00… 1970 07 PRCP 3 30 0 0 36 3 0 0 4 ASN00… 1970 08 TMAX 145 128 150 122 109 112 116 142 5 ASN00… 1970 08 TMIN 50 61 75 67 41 51 48 -7 6 ASN00… 1970 08 PRCP 0 66 0 53 13 3 8 0 7 ASN00… 1970 09 TMAX 168 168 162 162 162 150 184 179 8 ASN00… 1970 09 TMIN 19 29 62 81 81 55 73 97 9 ASN00… 1970 09 PRCP 0 0 0 0 3 5 0 38 10 ASN00… 1970 10 TMAX 189 194 204 267 256 228 237 144 # … with 1,583 more rows ``` --- # Tuberculosis notifications data taken from [WHO](http://www.who.int/tb/country/data/download/en/) 🤧 ```r tb # A tibble: 3,202 x 22 country year new_sp_m04 new_sp_m514 new_sp_m014 new_sp_m1524 <chr> <dbl> <dbl> <dbl> <dbl> <dbl> 1 Afghan… 1997 NA NA 0 10 2 Afghan… 1998 NA NA 30 129 3 Afghan… 1999 NA NA 8 55 4 Afghan… 2000 NA NA 52 228 5 Afghan… 2001 NA NA 129 379 6 Afghan… 2002 NA NA 90 476 7 Afghan… 2003 NA NA 127 511 8 Afghan… 2004 NA NA 139 537 9 Afghan… 2005 NA NA 151 606 10 Afghan… 2006 NA NA 193 837 # … with 3,192 more rows, and 16 more variables: new_sp_m2534 <dbl>, # new_sp_m3544 <dbl>, new_sp_m4554 <dbl>, new_sp_m5564 <dbl>, # new_sp_m65 <dbl>, new_sp_mu <dbl>, new_sp_f04 <dbl>, # new_sp_f514 <dbl>, new_sp_f014 <dbl>, new_sp_f1524 <dbl>, # new_sp_f2534 <dbl>, new_sp_f3544 <dbl>, new_sp_f4554 <dbl>, # new_sp_f5564 <dbl>, new_sp_f65 <dbl>, new_sp_fu <dbl> ``` --- # French fries .pull-left.huge[ 10 week sensory experiment, 12 individuals assessed taste of french fries on several scales (how potato-y, buttery, grassy, rancid, paint-y do they taste?), fried in one of 3 different oils, replicated twice. ] .pull-right.huge[  ] --- # French fries: Variables? Observations? ```r french_fries <- read_csv("data/french_fries.csv") french_fries # A tibble: 696 x 9 time treatment subject rep potato buttery grassy rancid painty <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> 1 1 1 3 1 2.9 0 0 0 5.5 2 1 1 3 2 14 0 0 1.1 0 3 1 1 10 1 11 6.4 0 0 0 4 1 1 10 2 9.9 5.9 2.9 2.2 0 5 1 1 15 1 1.2 0.1 0 1.1 5.1 6 1 1 15 2 8.8 3 3.6 1.5 2.3 7 1 1 16 1 9 2.6 0.4 0.1 0.2 8 1 1 16 2 8.2 4.4 0.3 1.4 4 9 1 1 19 1 7 3.2 0 4.9 3.2 10 1 1 19 2 13 0 3.1 4.3 10.3 # … with 686 more rows ``` --- # Rude Recliners data This data is collated from this story: [41% Of Fliers Think You're Rude If You Recline Your Seat](http://fivethirtyeight.com/datalab/airplane-etiquette-recline-seat/) What are the variables? ```r recliners <- read_csv("data/recliners.csv") recliners # A tibble: 3 x 6 V1 `V2:Always` `V2:Usually` `V2:About half … `V2:Once in a w… <chr> <dbl> <dbl> <dbl> <dbl> 1 No, … 124 145 82 116 2 Yes,… 9 27 35 129 3 Yes,… 3 3 NA 11 # … with 1 more variable: `V2:Never` <dbl> ``` --- .center[ # Messy vs tidy ] .pull-left.huge[ Messy data is messy in its own way. You can make unique solutions, but then another data set comes along, and you have to again make a unique solution. ] .pull-right.huge[ Tidy data can be though of as legos. Once you have this form, you can put it together in so many different ways, to make different analyses.  ] --- ## Data Tidying verbs  Source: A drawing made by Alison Horst [@allison_horst](https://twitter.com/allison_horst?lang=en) --- # Data Tidying Verbs .huge[ - `gather`: Specify the **keys** (identifiers) and the **values** (measures) to make long form data. You can also think of this as longer form data. - `spread`: Variables in columns - `separate`: Split one column into many ] --- # one more time: `gather` ```r gather(<DATA>, <KEY>, <VALUE>, <COLUMNS TO SELECT>) ``` .huge[ * **Key** is the name of the variable whose values for the column names. * **Value** is the name of the variable whose values are spread over the cells. * **Columns** to select are those that represent values, not variables. ] --- # gather: example .pull-left[ ```r table4a # A tibble: 3 x 3 country `1999` `2000` * <chr> <int> <int> 1 Afghanistan 745 2666 2 Brazil 37737 80488 3 China<PHONE_NUMBER>66 ``` ] .pull-right[ ```r table4a %>% gather(`1999`, `2000`, key = "year", value = "cases") # A tibble: 6 x 3 country year cases <chr> <chr> <int> 1 Afghanistan 1999 745 2 Brazil 1999 37737 3 China 1999 212258 4 Afghanistan 2000 2666 5 Brazil 2000 80488 6 China 2000 213766 ``` ] --- ## Tidying genes data .large[ Tell me what to put in the following? * **Key** is the name of the variable whose values for the column names. * **Value** is the name of the variable whose values are spread over the cells. * **Columns** to select are those that represent values, not variables. ] ```r genes # A tibble: 3 x 12 id `WI-6.R1` `WI-6.R2` `WI-6.R4` `WM-6.R1` `WM-6.R2` `WI-12.R1` <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> 1 Gene… 2.18 2.20 4.20 2.63 5.06 4.54 2 Gene… 1.46 0.585 1.86 0.515 2.88 1.36 3 Gene… 2.03 0.870 3.28 0.533 4.63 2.18 # … with 5 more variables: `WI-12.R2` <dbl>, `WI-12.R4` <dbl>, # `WM-12.R1` <dbl>, `WM-12.R2` <dbl>, `WM-12.R4` <dbl> ``` --- ## Tidy genes data ```r genes_long <- genes %>% gather(key = variable, value = expr, -id) genes_long # A tibble: 33 x 3 id variable expr <chr> <chr> <dbl> 1 Gene 1 WI-6.R1 2.18 2 Gene 2 WI-6.R1 1.46 3 Gene 3 WI-6.R1 2.03 4 Gene 1 WI-6.R2 2.20 5 Gene 2 WI-6.R2 0.585 6 Gene 3 WI-6.R2 0.870 7 Gene 1 WI-6.R4 4.20 8 Gene 2 WI-6.R4 1.86 9 Gene 3 WI-6.R4 3.28 10 Gene 1 WM-6.R1 2.63 # … with 23 more rows ``` --- # Separate columns ```r genes_long %>% separate(col = variable, into = c("trt", "leftover"), "-") # A tibble: 33 x 4 id trt leftover expr <chr> <chr> <chr> <dbl> 1 Gene 1 WI 6.R1 2.18 2 Gene 2 WI 6.R1 1.46 3 Gene 3 WI 6.R1 2.03 4 Gene 1 WI 6.R2 2.20 5 Gene 2 WI 6.R2 0.585 6 Gene 3 WI 6.R2 0.870 7 Gene 1 WI 6.R4 4.20 8 Gene 2 WI 6.R4 1.86 9 Gene 3 WI 6.R4 3.28 10 Gene 1 WM 6.R1 2.63 # … with 23 more rows ``` --- ## Separate columns ```r genes_long_tidy <- genes_long %>% separate(variable, c("trt", "leftover"), "-") %>% separate(leftover, c("time", "rep"), "\\.") genes_long_tidy # A tibble: 33 x 5 id trt time rep expr <chr> <chr> <chr> <chr> <dbl> 1 Gene 1 WI 6 R1 2.18 2 Gene 2 WI 6 R1 1.46 3 Gene 3 WI 6 R1 2.03 4 Gene 1 WI 6 R2 2.20 5 Gene 2 WI 6 R2 0.585 6 Gene 3 WI 6 R2 0.870 7 Gene 1 WI 6 R4 4.20 8 Gene 2 WI 6 R4 1.86 9 Gene 3 WI 6 R4 3.28 10 Gene 1 WM 6 R1 2.63 # … with 23 more rows ``` --- # Now spread to examine different aspects ## Examine treatments against each other ```r genes_long_tidy %>% spread(trt, expr) %>% ggplot(aes(x=WI, y=WM, colour=id)) + geom_point() ```  Generally, some negative association within each gene, WM is low if WI is high. --- ##Examine replicates against each other ```r genes_long_tidy %>% spread(rep, expr) %>% ggplot(aes(x=R1, y=R4, colour=id)) + geom_point() + coord_equal() ```  Very roughly, replicate 4 is like replicate 1, eg if one is low, the other is low. That's a good thing, that the replicates are fairly similar. --- # Your turn: Demonstrate with koala bilby data (write this as live code) Here is a little data set to practice gather, spread and separate on. .pull-left[ ```r kb <- read_csv("data/koala_bilby.csv") kb # A tibble: 5 x 5 ID koala_NSW koala_VIC bilby_NSW bilby_VIC <chr> <dbl> <dbl> <dbl> <dbl> 1 grey 23 43 11 8 2 cream 56 89 22 17 3 white 35 72 13 6 4 black 28 44 19 16 5 taupe 25 37 21 12 ``` ] .pull-right.large[ - Read over `koala-bilby.Rmd` - Gather the data into long form, naming the two new variables, `label` and `count` - Separate the labels into two new variables, `animal`, `state` - Spread the long form data into wide form, where the columns are the states. - Spread the long form data into wide form, where the columns are the animals. ] --- # Exercise 1: Rude Recliners .huge[ - Open `rude-recliners.Rmd` - This contains data from the article [41% Of Fliers Think You're Rude If You Recline Your Seat](http://fivethirtyeight.com/datalab/airplane-etiquette-recline-seat/). - V1 is the response to question: "Is it rude to recline your seat on a plane?" - V2 is the response to question: "Do you ever recline your seat when you fly?". ```r recliners <- read_csv("data/recliners.csv") recliners # A tibble: 3 x 6 V1 `V2:Always` `V2:Usually` `V2:About half … `V2:Once in a w… <chr> <dbl> <dbl> <dbl> <dbl> 1 No, … 124 145 82 116 2 Yes,… 9 27 35 129 3 Yes,… 3 3 NA 11 # … with 1 more variable: `V2:Never` <dbl> ``` ] --- # Exercise 1: Rude Recliners (15 minutes) Answer the following questions in the rmarkdown document. ## Ex1 A) What are the variables and observations in this data? ## Ex 1B) Put the data in tidy long form (using the names `V2` as the key variable, and `count` as the value). ## Ex 1C) Use the `rename` function to make the variable names a little shorter. --- # Exercise 1: Answers --- # Exercise 2: Tuberculosis Incidence data (15 minutes) Open: `tb-incidence.Rmd` .large[ Tidy the TB incidence data, using rthe Rmd to orompt questions. ] --- ## Exercise 3: Currency rates (15 minutes) .large[ * open `currency-rates.Rmd` * read in `rates.csv` * Answer the following questions: 1. What are the variables and observations? 2. Gather the five currencies, AUD, GBP, JPY, CNY, CAD, make it into tidy long form. 3. Make line plots of the currencies, describe the similarities and differences between the currencies. ] --- # Exercise 4: Australian Airport Passengers (optional extension challenge!) .large[ * Open `oz-airport.Rmd` * This contains data from the web site [Department of Infrastructure, Regional Development and Cities](https://bitre.gov.au/publications/ongoing/airport_traffic_data.aspx), containing data on Airport Traffic Data 1985–86 to 2017–18. * Read the dataset, into R, naming it `passengers` * Tidy the data, to produce a data set with these columns - airport: all of the airports. - year - type_of_flight: DOMESTIC, INTERNATIONAL - bound: IN or OUT ] --- # Lab quiz .huge[ Time to take the lab quiz. ] --- ## Share and share alike
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. ??? --- # Learning is where you: 1. Receive information accurately 2. Remember the information (long term memory) 3. In such a way that you can reapply the information when appropriate --- # Your Turn: .huge[ Go to the data source at this link: [bit.ly/dmac-noaa-data](https://bit.ly/dmac-noaa-data) - "Which is the best description of the temperature units?" - "What is the best description of the precipitation units" - "What does -9999 mean?" ] ??? - "Which is the best description of the temperature units?" - degrees farehnheit F - degrees Kelvin K - "degrees C x10" "What is the best description of the precipitation units" - "mm x10" - inches "What does -9999 mean?" - it was really cold - the keyboard got stuck - "the value was missing"


Preparation time
overnight
Cooking time
10 to 30 mins
Serves
Serves 4-6
Dietary
The perfect combination of hot and cold. Prepare the ice cream balls in advance for an impressive dinner party dessert.
Place a small baking tray in the freezer for at least 20 minutes, until very cold. Remove from the freezer. Use an ice cream scoop to make balls of ice cream, each about the same size as a golf ball. Place on the baking tray and freeze for at least an hour, preferably longer.
In a food processor, blend the biscuits to the texture of fine breadcrumbs then mix with the desiccated coconut. Mix the eggs with the coconut cream.
Remove the ice cream from the freezer. Dip each ball into the biscuit and coconut mixture, patting it onto the ice cream. Then dip each ball into the egg and coconut cream mixture, then coat in the biscuit and coconut mixture again. Repeat this step again, to make sure you get a thick crust with no risk of leakages. Return to the freezer again, this time for several hours or preferably overnight.
Meanwhile, for the sauce, put the raisins and rum in a saucepan with the cinnamon. Bring to the boil, then immediately remove from the heat and add the lime zest. Leave to infuse while you make the caramel.
Put the sugar in a medium saucepan with 100ml/3½fl oz water. Stir until the sugar looks like very wet sand. Set over a medium heat and leave until the sugar starts to dissolve. Do not stir, but carefully shake the pan every so often if it looks as though it is cooking unevenly. When it has turned an amber colour, remove from the heat and pour in the cream – it will splutter and bubble, so be careful. If the caramel seizes up, set over a low heat and stir until it has dissolved back into a sauce. Add the infused rum and raisins. Taste, season with salt and add a more rum if needed.
When you are ready to fry the ice cream, heat the oil in a deep-fat fryer to 190C (CAUTION: hot oil can be dangerous. Do not leave unattended.) Remove the ice cream balls from the freezer right at the last minute, and carefully lower the balls into the oil and cook for around 15 seconds, until a rich golden-brown colour. Drain onto kitchen towel and serve immediately with the rum and raisin sauce.


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Position | The position of the clicked item in the recommendation list. The position of the first item is 1. |
|
LOGIN | GENERAL | The user logged in to the site. For this event the cookieId and also the userId must be specified. | |
ADD_TO_WISHLIST | ADDITIONAL | The user added the item to his wishlist. |
ListId | Use if the webshop supports multiple wishlists. |
|
REMOVE_FROM_WISHLIST | ADDITIONAL | The user removed an item from his wishlist. |
ListId | Use if the webshop supports multiple wishlists. |
|
HIDE_PRODUCT | ADDITIONAL | The user hides a product that should not be recommended to him. | |
UNHIDE_PRODUCT | ADDITIONAL | The user unhides a product that he marked as hidden previously. | |
PRODUCT_SEARCH | ADDITIONAL | A list of products was displayed to the user, for example by browsing a category or by free text search. |
SearchString | The search string, if the list is based on a free text search. |
Filter.* | If the listing is based on comparing an item namevalue to a filter value, you can provide the actual filter here.
For example, if the user was browsing a specific category, name='Filter.CategoryId' and value='CategoryA' can be specified. |
|
NEXT_RECOMMENDATION | ADDITIONAL | The user asked for more recommendation. | |
COMMENT | ADDITIONAL | The user wrote a comment for the item. | |
NOT_INTERESTED | ADDITIONAL | The user would not like this item and similar items to be recommended to him, but he also does not want to give a negative rating for this item. | |
LETTER_READ | ADDITIONAL | T The user read a letter which sent for him by the system (eg. a newsletter). | |
CLICK_OUT | PRICE COMPARISON | The user jumps to an external webshop to buy the product. Used by price comparison sites. | |
LANCE | AUCTION | The user place a bid on the item. | Value The value of the bid as a decimal number. |
LETTER_SEND | AUCTION, ADVERTISING | The user sent a message to the advertiser. | |
ADD_ITEM | AUCTION, ADVERTISING | The user added an item to the site. | |
FREE_VIEW | MEDIA | The user wached/listened an item for free. | Duration How long the user wached the item in seconds as a decimal number. |
PAID_VIEW | MEDIA | The user payed for waching/listening an item. |
Duration | How long the user wached the item in seconds. A decimal number. |
Value | How much the user payed for waching the item. A decimal number. |
|
SUBSCRIPTION_VIEW | MEDIA | The user watched an item that was available for him by a subscription. |
Duration | How long the user wached the item in seconds. A decimal number. |
|
FOLLOW_USER | SOCIAL | The user follows an other user. | OtherUserId The identifier of the followed user. |
SHARE | SOCIAL | The user share the item on a social site (eg. Facebook, Twitter,...). | |
REDEEM | COUPON | The user redeem the item (eg. a coupon). | |


00:00:00 00/00/0000
ID:
Battery:
0.0V
Start recording:
End recording:
Add recording period
Remove selected period
Clear all periods
Enable LED:
8
16
32
48
96
192
Sample rate (kHz):
Low
Mid
High
Gain:
Sleep duration (s):
Recording duration (s):
Configure AudioMoth


|
M480 BSP V3.05.005
The Board Support Package for M480 Series
|
Modules | |
| USCI_UART Exported Functions | |
Macros | |
| #define | UUART_WORD_LEN_6 |
| #define | UUART_WORD_LEN_7 |
| #define | UUART_WORD_LEN_8 |
| #define | UUART_WORD_LEN_9 |
| #define | UUART_PARITY_NONE |
| #define | UUART_PARITY_ODD |
| #define | UUART_PARITY_EVEN |
| #define | UUART_STOP_BIT_1 |
| #define | UUART_STOP_BIT_2 |
| #define | UUART_ABR_INT_MASK |
| #define | UUART_RLS_INT_MASK |
| #define | UUART_BUF_RXOV_INT_MASK |
| #define | UUART_TXST_INT_MASK |
| #define | UUART_TXEND_INT_MASK |
| #define | UUART_RXST_INT_MASK |
| #define | UUART_RXEND_INT_MASK |
| #define UUART_ABR_INT_MASK |
Auto-baud rate interrupt mask
Definition at line 52 of file usci_uart.h.
| #define UUART_BUF_RXOV_INT_MASK |
Buffer RX overrun interrupt mask
Definition at line 54 of file usci_uart.h.
| #define UUART_PARITY_EVEN |
UUART_PROTCTL setting to set UART as even parity
Definition at line 44 of file usci_uart.h.
| #define UUART_PARITY_NONE |
UUART_PROTCTL setting to set UART as no parity
Definition at line 42 of file usci_uart.h.
| #define UUART_PARITY_ODD |
UUART_PROTCTL setting to set UART as odd parity
Definition at line 43 of file usci_uart.h.
| #define UUART_RLS_INT_MASK |
Receive line status interrupt mask
Definition at line 53 of file usci_uart.h.
| #define UUART_RXEND_INT_MASK |
RX end interrupt mask
Definition at line 58 of file usci_uart.h.
| #define UUART_RXST_INT_MASK |
RX start interrupt mask
Definition at line 57 of file usci_uart.h.
| #define UUART_STOP_BIT_1 |
UUART_PROTCTL setting for one stop bit
Definition at line 46 of file usci_uart.h.
| #define UUART_STOP_BIT_2 |
UUART_PROTCTL setting for two stop bit
Definition at line 47 of file usci_uart.h.
| #define UUART_TXEND_INT_MASK |
Tx end interrupt mask
Definition at line 56 of file usci_uart.h.
| #define UUART_TXST_INT_MASK |
TX start interrupt mask
Definition at line 55 of file usci_uart.h.
| #define UUART_WORD_LEN_6 |
UUART_LINECTL setting to set UART word length to 6 bits
Definition at line 34 of file usci_uart.h.
| #define UUART_WORD_LEN_7 |
UUART_LINECTL setting to set UART word length to 7 bits
Definition at line 35 of file usci_uart.h.
| #define UUART_WORD_LEN_8 |
UUART_LINECTL setting to set UART word length to 8 bits
Definition at line 36 of file usci_uart.h.
| #define UUART_WORD_LEN_9 |
UUART_LINECTL setting to set UART word length to 9 bits
Definition at line 37 of file usci_uart.h.


If you use Windows 2000, you may have noticed a special tooltip that is used in some instances. At least one spot where it is displayed is after making a dial-up network connection.
CXInfoTip is a simple control that attempts to reproduce this tooltip. It supports multi-line text (seperated with a '\n') and an icon. The control can be used as a normal tooltip for controls or as an immediate popup data tip. It is not a direct replacement for CTooltipCtrl. The control itself is in the source files: CXInfoTip.h and CXInfoTip.cpp.
To use the control, create it and either call the immediate Show() method or add tools using AddTool(). If AddTool() is used then the RelayEvent() method must be called from the parent window's overridden PreTranslateMessage().
To use the control, add a CXInfoTip member variable to the class.
CXInfoTip m_Tip;
For dialogs, create it in OnInitDialog(). For other windows create it in OnCreate().
m_Tip.Create(this);
To show an immediate tooltip, call the Show() method.>
m_Tip.Show(_T("This is a toolip!"), CPoint(100, 100));
To show normal tooltips, use AddTool() for each control and call RelayEvent() from PreTranslateMessage().
m_Tip.AddTool(GetDlgItem(IDOK), _T("This is the OK button!"), m_TooltipIcon); .... BOOL CInfoTipTestDlg::PreTranslateMessage(MSG* pMsg) { m_Tip.RelayEvent(pMsg); ... }
BOOL Create (CWnd * pParentWnd)
pParentWnd
Pointer to the parent window.
void AddTool(CWnd *pWnd, LPCTSTR szTooltipText, HICON hIcon = NULL)
None
pWnd
Pointer to the tool window.
szTooltipText
Text to display in the tooltip for the window. Seperate mutiple lines with a '\n'.
hIcon
Icon to display in the tooltip or NULL for no icon.
void RemoveTool(CWnd *pWnd)
None
pWnd
Pointer to the tool window to remove.
void SetIcon(HICON hIcon)
None
hIcon
Handle to the icon to display.
void SetShowDelay(int nDelay)
None
nDelay
Delay in milliseconds.
void SetFont(CFont *pFont)
None
pFont
Pointer to the font.
void RelayEvent(LPMSG lpMsg)
None
lpMsg
Pointer to the message structure.


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Don't have an account? signup


Jeremie Frimpong earns Celtic plaudits as Neil Lennon provides Jonny Hayes injury update
The 18-year-old was the star man in today's 4-0 win over Livingston at Celtic Park.
by Gabriel McKayCeltic manager Neil Lennon raved about Jeremie Frimpong's performance after the young right-back ripped Livingston to shreds.
The 18-year-old started in Saturday's 4-0 win, which lifted the Hoops three points clear of Rangers at the top of the league.
Steven Gerrard's men will have the chance to close that gap on Sunday, but the Celtic manager sees his own side in formidable form.
Lennon told BBC Radio Scotland at the end of the match: "I'm thrilled, it was a lot better than I could have expected.
"We had good control of the game against a good side, we scored a great opening goal and we missed a couple of great chances to be even more ahead at half-time.
"The quality of the performance and the pace we played at was fantastic and second half we asked: 'you've got good control of the game, can you go and get a few more goals?'.
"They're answering all the challenges that are asked of them at the minute. A comprehensive in off the back of two week break: I can't ask for any more from the players.
"We look fit, we look powerful, and we're playing with real intent at the minute.
"For a player of that age and that inexperience he's come in here and hit the ground running really well. He was outstanding today.
"I've not seen many better performances in my time. As a right-back the chances he created, the goals he could have scored, the recovery runs - everything about his game today was of a really high quality.
"He's made the team better and that's a big compliment I can pay him."
Scott Brown also got his name on the score sheet, with a deflected strike from the edge of the box to make it 2-0.
Lennon said: "He's playing brilliantly.
"He was brilliant again today. Goals are always a bonus and he strikes the ball really well at times, and he got his just reward today.
"It was a great goal, we moved Livingston around from side to side and Browny took the opportunity beautifully, albeit it got a deflection.
"It was a fully deserved goal from player who's at the top of his game."

"That'll do him (Griffiths) the world of good. He almost scored and he's sniffing out chances, he's looking more and more like himself.
"(Hayes) landed on his shoulder really awkwardly very early and it looks like he's popped it a little bit. We'll have to scan it and see what the diagnosis is, hopefully he won't be out for too long.


data class RequestsOptionalParameters
Class that contains information about all the optional parameters the Request module requests can have. Every request of this module is a GET request and can have a query to get requests between dates. It also knows how to properly construct the url.
class Builder
Builder class to facilitate the insertion of the start and end dates. |
val mBuilder: RequestsOptionalParameters.Builder
The builder created by the user if he wants to get requests between dates. |
fun getQuery(): String
Constructs the query to parse between dates. |


#compress> <#noescape>
Redirecting...
If you are not redirected automatically, follow the
link
. #noescape> #compress>


Description:
This page will give you a randomized setup based on your player count. If you have incorporated all of the tiles from the 5 player expansion into the base game, then you will have to remove additional tiles. Select the option for the 5 player expansion below to account for the additional tiles.
Remove the following character tiles from the game:
Remove the following goods from the game:
0
0
0
0
0


Elder Filaur:
What!? Well, I'm not surprised. I always thought you looked like a quitter. I'll find someone better in no time!


--- home : true ---
$ npm install mediasoup
$ npm install mediasoup-client
Due to its versatility and flexibility, the SFU model (Selective Forwarding Unit) for multiparty conferencing and similar scenarios is taking over the more rigid and resource hungry MCU model.
Instead of creating yet another opinionated server, mediasoup is a Node.js module which can be integrated into a larger application or made standalone with just a few lines of JavaScript.
mediasoup comes with a extremely powerful JavaScript SDK (the mediasoup-client library) that makes it easy to build video conference applications that run in any browser by using an unified API.


/tles
Returns point geometries
Parameters
- f : Format (json, txt; unset or any other value returns txt
- names: Comma separated list of Satellite Names. You can end with * to get Satellites staring with prefix (e.g. GPS*).
- nums: Comma separated list of Satellite Nums. If Nums is specified Names are ignored.
Lines Returned for each Satellite
- TLE Header
- TLE Line 1
- TLE Line 2
For more information about the TLE format visit NORAD Two-Line Element Set Format
Examples


| Symbol | Metric | School numbers | National avg.* | |
|---|---|---|---|---|
| D | Debt (median $)Median original loan amount as students enter the repayment program | {% if sch.DEBT_MDN_PRESENT != 0 %}{{ sch.r_fin_DEBT_MDN }} | {% else %}- | {% endif %}{{ nat_mean.DEBT_MDN }} |
| E | Earning (6-yr.)Mean earning of students who are working and not enrolled 6 years after their entry to the school | {% if sch.MN_EARN_WNE_P6_PRESENT != 0 %}{{ sch.r_fin_MN_EARN_WNE_P6 }} | {% else %}- | {% endif %}{{ nat_mean.MN_EARN_WNE_P6 }} |
| C | Completion (%)% of full-time AND first-time students who complete within 150% of expected time to completion | {% if sch.C150_4_COMB_PRESENT != 0 %}{{ sch.r_fin_C150_4_COMB }} | {% else %}- | {% endif %}{{ nat_mean.C150_4_COMB }} |
| $ | Sticker price (avg. $): Net price + the average scholarship grants/aid | {% if sch.COSTT4_COMB != 0 %}{{ sch.r_fin_COSTT4_COMB }} | {% else %}- | {% endif %}{{ nat_mean.COSTT4_COMB }} |
| N | Net price (avg. $)Average net price for Title IV public, private for-profit and nonprofit institutions. | {% if sch.NPT4_COMB_PRESENT != 0 %}{{ sch.r_fin_NPT4_COMB }} | {% else %}- | {% endif %}{{ nat_mean.NPT4_COMB }} |
| W | Withdrawal (%)% of students withdrawn from original institution within 6 years | {% if sch.WDRAW_ORIG_YR6_RT_PRESENT != 0 %}{{ sch.r_fin_WDRAW_ORIG_YR6_RT }} | {% else %}- | {% endif %}{{ nat_mean.WDRAW_ORIG_YR6_RT }} |
| P | Pell recipient (%)% of undergraduates who receive a Pell Grant | {% if sch.PCTPELL_PRESENT != 0 %}{{ sch.r_fin_PCTPELL }} | {% else %}- | {% endif %}{{ nat_mean.PCTPELL }} |
| Ex | Expenses on students (avg, %)The amount schools spend on instructional expenditures per full-time equivalent student, adjusted for location | {% if sch.ADJ_INEXPFTE_PRESENT != 0 %}{{ sch.r_fin_ADJ_INEXPFTE }} | {% else %}- | {% endif %}{{ nat_mean.ADJ_INEXPFTE }} |
| R | Returing student (%)% of students who come back after first year of college | {% if (sch.RET_FT4_COMB_PRESENT)*(sch.RET_PT4_COMB_PRESENT)*(sch.PFTFTUG1_EF_PRESENT) != 0 %}{{ sch.r_fin_COMB_RET_RATE }} | {% else %}- | {% endif %}{{ nat_mean.COMB_RET_RATE }} |
| FT | Full-time faculty (%)% of full-time faculty | {% if sch.PFTFAC_PRESENT != 0 %}{{ sch.r_fin_PFTFAC }} | {% else %}- | {% endif %}{{ nat_mean.PFTFAC }} |
No entries found.
{% endif %}


Police arrest suspected killers of PDP women leader in Kogi
by Ifeanyi NgeremSix suspects has been arrested by the men of the Nigerian Police Force in connection with the murder of a Kogi State PDP women leader.
The 60-year-old Salome Abuh, who was the PDP women leader of Ochadamu Ward in Ofu Local Government Area of the state, had her house set on fire, while she was inside, by political thugs allegedly belonging to the ruling All Progressives Congress (APC) November 18.
The incident was believed to be a reprisal attack over the violence-ridden gubernatorial election in the state.
According to a report by Punch Metro, the Police Command in Kogi State arrested six suspects in connection with the killing of Mrs Salome Abuh.
The spokesman for the command, Deputy Superintendent of Police William Aya disclosed this while speaking with the News Agency of Nigeria, in Lokoja on Monday.
Aya said that the suspects were brought in on Friday.
Aya said the police had started interrogating the suspects to ascertain their level of culpability in the death of the woman.
He said that the outcome of the investigation would be made public as soon as it was completed.
President Muhammadu Buhari had on Sunday directed the police to arrest the killers of Abuh with a view to bringing them to justice.


Task App
Active Tasks
Active
Add a task...
{{level}}
{{ task.name }}
{{task.priority}}
delete
Expired Tasks
Expired Tasks
{{list.name}}
check
Completed Tasks
Completed Tasks
{{list.name}}
check


Preparation time
over 2 hours
Cooking time
10 to 30 mins
Serves
Serves 2
Combine all the marinade ingredients and marinate the duck breasts in the liquid for at least one hour.
Remove the duck breasts and place in a hot frying pan, skin side down, for 10 minutes. Turn the duck over and fry for a further five minutes.
Remove the pan from the heat, pour remaining marinade over the duck and allow to rest in the pan.
Heat the sesame oil in a pan, add the red peppers and cook for 2-3 minutes. Then add the chilli, ginger, and shallots and cook on a high heat for two more minutes.
Reduce the heat and add the sugar and lime juice. Once caramelised, add the pineapple and leave to cook for five minutes.
Add the pak choi and stir until cooked.
Put the vegetables on a serving plate and top with slices of the duck breasts. Pour over the juices and garnish with the coriander stalks.


The \hfill fill command produces a rubber length which can stretch or shrink horizontally. It will be filled with spaces. It is equivalent to \hspace\fill.
See Spaces and Boxes Back to the Table of Contents


| Package | Description |
|---|---|
| org.apache.beam.sdk.transforms |
Defines
PTransform s for transforming
data in a pipeline. |
| Modifier and Type | Method and Description |
|---|---|
static <K> Combine.PerKey<K,Double,Double> |
Min.doublesPerKey()
Returns a
PTransform that takes an input PCollection<KV<K, Double>> and returns
a PCollection<KV<K, Double>> that contains an output element mapping each distinct key
in the input PCollection to the minimum of the values associated with that key in the
input PCollection . |
static <K> Combine.PerKey<K,Double,Double> |
Max.doublesPerKey()
Returns a
PTransform that takes an input PCollection<KV<K, Double>> and returns
a PCollection<KV<K, Double>> that contains an output element mapping each distinct key
in the input PCollection to the maximum of the values associated with that key in the
input PCollection . |
static <K> Combine.PerKey<K,Double,Double> |
Sum.doublesPerKey()
Returns a
PTransform that takes an input
PCollection<KV<K, Double>> and returns a
PCollection<KV<K, Double>> that contains an output
element mapping each distinct key in the input
PCollection to the sum of the values associated with
that key in the input PCollection . |
static <K> Combine.PerKey<K,Integer,Integer> |
Min.integersPerKey()
Returns a
PTransform that takes an input PCollection<KV<K, Integer>> and
returns a PCollection<KV<K, Integer>> that contains an output element mapping each
distinct key in the input PCollection to the minimum of the values associated with that
key in the input PCollection . |
static <K> Combine.PerKey<K,Integer,Integer> |
Max.integersPerKey()
Returns a
PTransform that takes an input PCollection<KV<K, Integer>> and
returns a PCollection<KV<K, Integer>> that contains an output element mapping each
distinct key in the input PCollection to the maximum of the values associated with that
key in the input PCollection . |
static <K> Combine.PerKey<K,Integer,Integer> |
Sum.integersPerKey()
Returns a
PTransform that takes an input
PCollection<KV<K, Integer>> and returns a
PCollection<KV<K, Integer>> that contains an output
element mapping each distinct key in the input
PCollection to the sum of the values associated with
that key in the input PCollection . |
static <K,V extends Comparable<V>> |
Top.largestPerKey(int count)
Returns a
PTransform that takes an input
PCollection<KV<K, V>> and returns a
PCollection<KV<K, List<V>>> that contains an output
element mapping each distinct key in the input
PCollection to the largest count values
associated with that key in the input
PCollection<KV<K, V>> , in decreasing order, sorted
according to their natural order. |
static <K> Combine.PerKey<K,Long,Long> |
Min.longsPerKey()
Returns a
PTransform that takes an input PCollection<KV<K, Long>> and returns a
PCollection<KV<K, Long>> that contains an output element mapping each distinct key in
the input PCollection to the minimum of the values associated with that key in the
input PCollection . |
static <K> Combine.PerKey<K,Long,Long> |
Max.longsPerKey()
Returns a
PTransform that takes an input PCollection<KV<K, Long>> and returns a
PCollection<KV<K, Long>> that contains an output element mapping each distinct key in
the input PCollection to the maximum of the values associated with that key in the
input PCollection . |
static <K> Combine.PerKey<K,Long,Long> |
Sum.longsPerKey()
Returns a
PTransform that takes an input
PCollection<KV<K, Long>> and returns a
PCollection<KV<K, Long>> that contains an output
element mapping each distinct key in the input
PCollection to the sum of the values associated with
that key in the input PCollection . |
Combine.PerKey<K,InputT,OutputT> |
Combine.PerKey.named(String name)
Return a new
Globally transform that's like this transform but with the
specified name. |
static <K,NumT extends Number> |
Mean.perKey()
Returns a
PTransform that takes an input
PCollection<KV<K, N>> and returns a
PCollection<KV<K, Double>> that contains an output
element mapping each distinct key in the input
PCollection to the mean of the values associated with
that key in the input PCollection . |
static <K,T extends Comparable<? super T>> |
Min.perKey()
Returns a
PTransform that takes an input PCollection<KV<K, T>> and returns a
PCollection<KV<K, T>> that contains an output element mapping each distinct key in the
input PCollection to the minimum according to the natural ordering of T of the
values associated with that key in the input PCollection . |
static <K,T extends Comparable<? super T>> |
Max.perKey()
Returns a
PTransform that takes an input PCollection<KV<K, T>> and returns a
PCollection<KV<K, T>> that contains an output element mapping each distinct key in the
input PCollection to the maximum according to the natural ordering of T of the
values associated with that key in the input PCollection . |
static <K,V> Combine.PerKey<K,V,Long> |
Count.perKey()
Returns a
Combine.PerKey PTransform that counts the number of elements
associated with each key of its input PCollection . |
static <K,InputT,OutputT> |
Combine.perKey(CombineFnBase.GlobalCombineFn<? super InputT,?,OutputT> fn)
Returns a
Combine.PerKey PTransform that
first groups its input PCollection of KV s by keys and
windows, then invokes the given function on each of the values lists to
produce a combined value, and then returns a PCollection
of KV s mapping each distinct key to its combined value for each
window. |
static <K,InputT,OutputT> |
Combine.perKey(CombineFnBase.PerKeyCombineFn<? super K,? super InputT,?,OutputT> fn)
Returns a
Combine.PerKey PTransform that
first groups its input PCollection of KV s by keys and
windows, then invokes the given function on each of the key/values-lists
pairs to produce a combined value, and then returns a
PCollection of KV s mapping each distinct key to
its combined value for each window. |
static <K,T,ComparatorT extends Comparator<? super T> & Serializable> |
Min.perKey(ComparatorT comparator)
Returns a
PTransform that takes an input PCollection<KV<K, T>> and returns a
PCollection<KV<K, T>> that contains one output element per key mapping each
to the minimum of the values associated with that key in the input PCollection . |
static <K,T,ComparatorT extends Comparator<? super T> & Serializable> |
Max.perKey(ComparatorT comparator)
Returns a
PTransform that takes an input PCollection<KV<K, T>> and returns a
PCollection<KV<K, T>> that contains one output element per key mapping each
to the maximum of the values associated with that key in the input PCollection . |
static <K,V> Combine.PerKey<K,V,V> |
Combine.perKey(SerializableFunction<Iterable<V>,V> fn)
Returns a
Combine.PerKey PTransform that
first groups its input PCollection of KV s by keys and
windows, then invokes the given function on each of the values lists to
produce a combined value, and then returns a PCollection
of KV s mapping each distinct key to its combined value for each
window. |
Combine.PerKey<K,InputT,OutputT> |
Combine.PerKey.withSideInputs(Iterable<? extends PCollectionView<?>> sideInputs)
Returns a
PTransform identical to this, but with the specified side inputs to use
in CombineWithContext.KeyedCombineFnWithContext . |
Copyright © 2016 The Apache Software Foundation. All rights reserved.


def repeater(string, n):
return string * n
Write a function named repeater()
that takes two arguments (a string and a number), and returns a new string where the input string is repeated that many times.
Repeater.repeat("a", 5)
should return
"aaaaa"
def repeater(string, n):
return string * n


BAD
`Prev `__
B
`Next `__
--------------
**BAD**: /B·A·D/, adj.
[IBM: acronym, “Broken As Designed”] Said of a program that is
`*bogus* `__ because of bad design and misfeatures rather
than because of bugginess. See `*working as
designed* <../W/working-as-designed.html>`__.
--------------
+-------------------------------------------+----------------------------+----------------------------------+
| `Prev `__ | `Up <../B.html>`__ | `Next `__ |
+-------------------------------------------+----------------------------+----------------------------------+
| backward combatability | `Home <../index.html>`__ | Bad and Wrong |
+-------------------------------------------+----------------------------+----------------------------------+


StackFeed let's you find products, add them to your Shopify store and ship them directly to your customers


{% extends "base_generic.html" %} {% load crispy_forms_tags %} {% block pagetitle %}Point of Contact Form{% endblock %} {% block content %}
Fill-out this form with as much as information as possible about this contact at {{ client_name }}:
{% if form.errors %} {% for field in form %} {% for error in field.errors %}


Learn as much as you can.
Poaching is the killing of animals for their skins,horns and many more.
When people cut down trees,we are taking the animals home.
Pollution makes the enviroment dirty and wildlife deppends on the enviroment
Human conflict starts when wild animal kills domestic animals
We can conserve environment by planting trees
We can stop pollution by collecting rubbish...
Teaching people how to be game rangers.
We can stop human conflict with animals by putting a fence


if( staff_session ) {?> Error! You are still in a staff session. Please try refreshing the page or logging out again. } else {?> You have successfully logged out. Return to public Home. } ?>


Setup has been completed.
When you browse WallStreetBets, you should now see account age next to usernames.


Test for misc_validate API
Schema JSON
{ "$id": "https://example.com/person.schema.json", "$schema": "http://json-schema.org/draft-07/schema#", "title": "Person", "type": "object", "properties": { "firstName": { "type": "string", "description": "The person's first name." }, "lastName": { "type": "string", "description": "The person's last name." }, "age": { "description": "Age in years which must be equal to or greater than zero.", "type": "integer", "minimum": 0 } } }
Instance JSON
{ "firstName": "John", "lastName": "Doe", "age": 21 }
Post Data (both GET/POST supported)
Test property list API
Record type
glycan
protein
Test for misc_bcolist API
Query JSON
Post Data (both GET/POST supported)
Test xref links API
Record type
glycan
protein
ID list


Tag Admin
Found: .
Add New Tag
Enter tag value into the input field then click on the button to add new tag.
Update Tag
Select tag value from the drop down list, enter the new tag value into the input field then click on the
button to update tag.
Delete Tag
Select tag value from the drop down list then click on the button to delete tag.<


San Francisco Marathon
San Francisco CA/USA
Web Site: www.thesfmarathon.com
Race Winners
(40 runnings)
2:44:02 2:50:24 2:51:55 2:46:34 2:52:33 29 Jul
2007
2:25:57
2:43:41
30 Jul
2006
2:26:46
2:54:55
31 Jul
2005
2:31:57
2:56:55
01 Aug
2004
2:33:41
2:50:21
27 Jul
2003
2:35:11
3:02:00
28 Jul
2002
2:31:46
2:50:11
08 Jul
2001
2:30:53
3:12:10
09 Jul
2000
2:32:49
3:08:15
11 Jul
1999
2:24:36
3:09:44
12 Jul
1998
2:23:54
2:45:36
13 Jul
1997
2:26:49
3:02:33
14 Jul
1996
2:37:27
2:57:45
09 Jul 1995
2:23:38
2:51:12
31 Jul
1994
2:17:34
2:44:34
18 Jul
1993
2:20:02
2:40:32
30 Aug
1992
2:16:44
2:36:54
23 Jun
1991
2:15:31
2:35:33
01 Jul
1990
2:13:48
2:39:52
09 Jul
1989
2:15:01
3:09:08
1988
---
---
19 Jul
1987
2:14:07
2:39:02
20 Jul
1986
2:13:29
2:37:58
21 Jul
1985
2:15:07
2:38:04
19 Aug
1984
2:10:18
2:35:56
24 Jul
1983
2:14:45
2:35:44
11 Jul
1982
2:14:32
2:44:05
12 Jul
1981
2:15:17
2:38:04
13 Jul
1980
2:18:15
2:43:20
08 Jul
1979
2:18:54
2:49:46
09 Jul
1978
2:21:15
2:50:15
10 Jul
1977
2:24:59
2:53:20
Notes: Several different organizing groups have held marathons in and around San Francisco (see below). In addition,
the course used for the San Francisco Marathon has undergone almost annual changes and relocations. In the 2002
race. roughly 100 runners were led off course, including the designated women's winner, Magdalena Lewy whose time
was adjusted to 2:53:55 (still more than 12 minutes faster than the 2nd place woman).
23 Jul
2017
2:28:23
Jorge Maravilla (CA/USA)
2:52:49
Devon McMahon (CA/USA)
31 Jul
2016
2:30:42
Max Haines-Stiles (CA/USA)
2:49:51
Tori Tyler (CA/USA)
26 Jul
2015
2:26:22
Christopher Mocko (CA/USA)
2:49:42
Anna Bretan-3
27 Jul
2014
2:32:17
August Brautigam (NV/USA)
2:47:51
Anna Bretan-2
16
Jun 2013
2:25:15
Francois Lhuissier (NY/USA)
2:42:26
Anna Bretan (CA/USA)
29 Jul
2012
2:26:44
Nathan Krah (UT/USA)
Devon Crosby-Helms (CA/USA)
31 Jul
2011
2:27:06
Michael Wardian (VA/USA)
Emily Field (CA/USA)
25 Jul
2010
2:23:29
Keith Bechtol (CA/USA)
Emily Hardin (AL/USA)
26 Jul
2009
2:26:32
Andrew Cook-3
Yoko Shibui (JPN)
03 Aug
2008
2:31:52
Chad Worthen (CA/USA)
Lauren Gustafson (CA/USA)
Andrew Cook-2
Yolanda Flamino (MI/USA)
Andrew Cook (TX/USA)
Julia Stamps (NY/USA)
Tony Torres (CA/USA)
Sarah Hallas (CA/USA)
John Weru (KEN)
Susan Loken (AZ/USA)
Patrick Kamau (KEN)
Lucy Carr (CT/USA)
Nate Bowen (CA/USA)
Magdalena Lewy (CA/USA)
Vytautas Ezerskis (LTU)
Micha Lowe (CA/USA)
Michael Buchanan (CA/USA)
Lisa Murphy (CA/USA)
Brad Hawthorne (CA/USA)
Patti Smith (USA)
Hamid Oubadriss (FRA)
Salina Chirchir (KEN)
Habid Miloudi (ALG)
Kristen Orre (CA/USA)
Brad Lael (CA/USA)
Margee Brown (MN/USA)
Hector Lopez (MEX)
Lisa Kelp (PA/USA)
Patrick Muturi (KEN)
Karolina Szabo (HUN)
Driss Dacha (MAR)
Tatiana Titova (RUS)
Sergio Jimenez (MEX)
Irina Bogacheva (KGZ)
Daniel Martinez (CA/USA)
Lesley Ann Lehane (MA/USA)
Antonio Niemczak (POL)
Janis Klecker-2
Ernest Tjela (LES)
Stephanie Robertson (CA/USA)
not held
not held
Mehmet Terzi (TUR)
Eileen Claugus (CA/USA)
Peter Pfitzinger-2
Maria Trujillo (CA/USA)
Ric Sayre (USA)
Kersti Jakobsen (DEN)
Simon Kigen (KEN)
Katy Laetsch (CA/USA)
Peter Pfitzinger (MA/USA)
Janis Klecker (MN/USA)
Miguel Tibaduiza (COL)
Nancy Ditz (CA/USA)
Harold Schulz (CA/USA)
Laurie Binder (CA/USA)
Antonio Ramirez (CA/USA)
Joann Dahlkoetter (CA/USA)
John Moreno (CA/USA)
Carol Young (CA/USA)
Steven Palladino (CA/USA)
Sue Petersen (CA/USA)
Athol Barton (NZL)
Tena Harms (CA/USA)
Most Wins (1977-date)
Men
3
Andrew Cook (TX/USA)
2006-07,2009
Women
3
Anna Bretan (CA/USA)
2013-15
Prize Money (ADR
qualified runners)
Year Men Women Total 2004 $1,000 $2,000 $3,000 2003 1,000 1,000 2,000 2002 2,000 2,000 4,000 2001 none none none 2000 none none none 1999 17,000 17,000 34,000 .... 1994 14,000 14,000 28,000 1993 22,450 20,750 43,200 .... 1991 14,250 15,250 29,500 1990 14,250 14,750 29,000 .... 1987 11,500 11,750 23,250 .... 1985 11,500 11,750 23,250 1984 24,600 22,250 46,850 Sums $133,300 $132,000 $265,300
Race Time Bias (sec/km)
Year Men Women 1991 n/c +4.3 1990 n/c +5.3 .... 1987 +0.9 -1.8 1986 +1.7 n/c 1985 +4.2 +2.0 1984 -0.0 +0.3 1983 -1.5 -1.6 1982 -0.0 n/c Avgs +0.9 +1.4
Competitive Level (1990-date)
Year Men Women 1993 173 n/c 1992 n/c 457
Quality Performances
Men <2:11 1 <2:12 1 <2:13 2 <2:14 5 <2:15 13 <2:16 23 <2:17 31 <2:18 45 <2:19 60 <2:20 71 Women <2:36 3 <2:38 8 <2:40 22 <2:42 27 <2:44 42 <2:46 52 <2:48 67 <2:50 84
Golden Gate Marathon 28 Oct
1984
2:31:51
3:00:36
30 Oct
1983
2:32:41
3:17:25
31 Oct
1982
2:25:36
2:47:28
25 Oct
1981
2:28:30
3:06:11
26 Oct
1980
2:26:24
3:10:39
28 Oct
1979
2:29:16
3:05:59
12 Nov
1978
2:25:37
2:54:04
1973-1977
---
---
27 May
1972
2:33:35
3:27:03
29 May
1971
2:31:37
3:42:36
30 May
1970
2:34:00.4
4:06:34
Race Winners
(10 runnings)
Note: A race was scheduled for 25 May 1974 but was cancelled.
Paul Jacobs-2
Stephanie Gokbora (USA)
Paul Jacobs (USA)
Marilyn Petch (USA)
Francesjon Gailson (NV/USA)
Patricia English (CA/USA)
Virginio Deraujo (CA/USA)
Deborah Waldear (USA)
Skip Brown (CA/USA)
Hilary Naylor (CA/USA)
Bernd Heinrich (CA/USA)
Joan Ullyot (CA/USA)
Mike Porter (CA/USA)
Sue Krenn (CA/USA)
not held
not held
Martin Pabon (COL)
Fran Conley (USA)
Rich Delgado (CA/USA)
Nancy Laird (TX/USA)
Skip Houk (CA/USA)
Mary Cortez (CA/USA)
26 Aug
1979
2:27:21
2:54:30
29 Oct
1978
2:30:47
3:15:33
Mayor's Cup Marathon
Race Winners
(2 runnings)
Note: A race was tentatively scheduled for 24 Aug 1980 but probably was not held.
Ron Nabers-2
Sue Petersen (CA/USA)
Ron Nabers (CA/USA)
Ruth Anderson (CA/USA)
Last Updated on 24 Jul 2017
Contributors: Malcolm Heyworth, Mark Winitz (7), Jack Leydig (11)


EBD - Easton Bible DIctionary
Gittite
GITTITE
"GITTITE "a native of the Philistine city of Gath (
Joshua 13:3
). Obed-edom, in whose house the ark was placed, is so designated (
2 Samuel 6:10
). Six hundred Gittites came with David from Gath into Israel (
15:18, 19
).
"GITTITE "a native of the Philistine city of Gath (Joshua 13:3). Obed-edom, in whose house the ark was placed, is so designated (2 Samuel 6:10). Six hundred Gittites came with David from Gath into Israel (15:18, 19).


Please fill out all of the fields. Please feel free to contact me about questions or comments. All fields below are required so that I may properly respond back.
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© 2019 Chris Toplikar. All Rights Reserved


Welcome back, plant lover. Your plants will thank you.
Status: {{text}}
Last Update: {{time}}
These plants need daily attention.
These plants need to be watered only every few days.
Plants will be watered as soon as moisture sensor reports dry soil.
Here you can check when the plants were watered.
If you feel like something is going completely wrong.


Demystifying Modern
Web Development
whoami
Full Stack Web Developer
4 year experience
Full time freelancer
Procastinator
Gamer
What is our endgoal for today?
Shed some light on what modern web development is
Develop a modern web app together
Introduce you to the basics of React
Have fun
Web Development
The Traditional Way
The Modern/SPA Way
The modern way is:
Faster
More user engaging
capable to run offline
seprating front-end and back-end concerns
Modern tools and technologies for web development is limitless.
CSS
Bootstrap
Bulma
SASS
LESS
JavaScript
ES6
jQuery
TypeScript
Vanilla JS
Frameworks
React
Vue
Angular/AngularJS
Node
API
REST APIs
Firebase
GraphQL
Apollo
ReactJS
What is React JS
Developed by Facebook
React is a library, and not a full-fledged framework.
You can't use React to develop a full-stack web app.
Who Uses React?
The Good
Component-driven
Declarative
JSX
Uses full power of JavaScript
Not a complete framework
Easy to learn.
The bad
Not a complete framework
No events
No XHR
No data/models
Fundamentals
Most important things in React
Components
Props
State
JSX


Next Free Tech Course at Gilt (NYC: Chef
Just in time for the holidays, #gilttech offers a free gift for the NYC tech community: an opportunity to learn Chef! Chef is an automation platform that transforms infrastructure into code. On December 4, we host an all-day hands-on tutorial that will cover the basics that everyone needs to know about how to use Chef for system and infrastructure management. Your instructor, Nathen Harvey, will discuss the server API, the code primitives, and the tools required to successfully use Chef.
The essentials:
When: Thursday, December 4, 2014 from 9 AM-5 PM
Where: Gilt office in Manhattan
Cost: Nothing!
Who: Gilt technologists … and you?
Instructor Bio: As the Community Director at Chef, Nathen helps the community whip up an awesome ecosystem built around the Chef framework. Nathen also spends much of his time helping people learn about the practices, processes, and technologies that support DevOps, Continuous Delivery, and Web-scale IT. Prior to joining Chef, Nathen spent a number of years managing operations and infrastructure for a number of web applications. Nathen is a co-host of the Food Fight Show, a podcast about Chef and DevOps.
Fill out the form below to submit your contact info. (Note: You must be age 18 or older to attend.) Please keep in mind that submitting this form does not guarantee you a seat. However, it does mean that you’ll receive details about the other courses we’re developing as soon as they become available. We hope you can join us!
APPLICATIONS CLOSED.


--- layout: post title: The Manifesto of the Futurist Programmers date: 2006-11-30 20:48:52.000000000 +01:00 type: post published: true status: publish categories: - coding - 'understanding: IT' tags: [] meta: _publicize_job_id: '14401147420' original_post_id: '56' _wp_old_slug: '56' author: login: joesixpack email<EMAIL_ADDRESS>display_name: dirk lüsebrink first_name: '' last_name: '' ---
This manifesto shall not be forgotten. Provoked by the the gapingvoid request for manifesto submissions i was reminded of this importend piece of coder culture. The manifesto was part of making me believe in what i was doing at that time, damned maybe it was even (part of) the reason for not becoming an instant billionaire in the first new economy bubble.
have fun


--- layout: post status: publish published: true title: Podcast 2.17 - This week on the Carlos Zambrano Show.... author: display_name: Corey Fineran login: Corey email<EMAIL_ADDRESS>url: '' author_login: Corey author_email<EMAIL_ADDRESS>wordpress_id: 2925 wordpress_url: http://ivyenvy.com/?p=2925 date: '2010-06-28 00:15:09 +0000' date_gmt: '2010-06-28 05:15:09 +0000' categories: - Podcast tags: - Carlos Zambrano - Podcast - Derrek Lee comments: [] ---
Welcome to yet another podcast episode that is focused on Carlos Zambrano. Andy and Corey discuss the current Z situation over 2000 miles of distance. We also read your answers to the question of the week.


This is the lyrics of Durga Stotra in English and Devanagari script. You will also find the meaning of Durga Stotra in English. The Durga Stotra or Stotram is read to please Goddess Durga.

Et-davya Sanskritam Stotram
Yah Pate-niyatah Shuchi-hi
Grahe-va Shudh-bhaven
Prita Bhagwati Sada ||6||
This hymn is composed by Sage Vyasa,
Whoever recites this hymn regularly after becoming bodily and mentally
clean ,
in his home or anywhere with pure devotion to the goddess,
will please the Bhagavati Devi always.


Welcome to Mestizo restaurant!
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Christopher Biggins's panel show appearances
Christopher Biggins (born 1948-12-16[ref]) has appeared in 35 episodes between 2006-2015. Christopher Biggins on IMDB. Christopher Biggins on Wikipedia.
- 2015-07-14 / It's Not What You Know
- 2014-11-04 / Loose Women
- 2014-10-20 / Loose Women
- 2013-11-27 / Loose Women
- 2013-04-10 / Loose Women
- 2012-10-30 / Loose Women
- 2012-06-18 / Loose Women
- 2012-02-20 / Loose Women
- 2011-11-30 / Heresy
- 2011-10-25 / Loose Women
- 2011-07-08 / Loose Women
- 2011-04-06 / Loose Women
- 2010-12-23 / 8 Out of 10 Cats
- 2010-04-30 / Loose Women
- 2009-11-22 / The Christian O'Connell Solution
- 2009-10-30 / Loose Women
- 2009-10-01 / Loose Women
- 2009-09-30 / Loose Women
- 2009-09-29 / Loose Women
- 2009-09-28 / Loose Women
- 2009-07-21 / Loose Women
- 2009-04-15 / Loose Women
- 2009-04-15 / Celebrity Juice
- 2008-09-11 / 8 Out of 10 Cats
- 2008-09-09 / Loose Women
- 2008-08-05 / Loose Women
- 2008-06-04 / Loose Women
- 2008-01-17 / Never Mind The Buzzcocks
- 2007-12-14 / Loose Women
- 2007-08-10 / Loose Women
- 2006-12-22 / Loose Women
- 2006-12-20 / Loose Women
- 2006-12-19 / Loose Women
- 2006-11-23 / Loose Women
- 2006-10-13 / Loose Women


White to play 26
pips White=167 Black=160
(CorrectAnswer= 0/0, ErrorScore= 0)
1. 24/16* eq: +0.133 53.65% (G:13.70% B:0.68%) 46.35% (G:12.99% B:0.51%) 2. 13/7 6/4* eq: -0.162 (-0.295) 46.24% (G:12.22% B:0.54%) 53.76% (G:16.88% B:1.33%) 3. 24/18 6/4* eq: -0.167 (-0.300) 46.41% (G:10.90% B:0.52%) 53.59% (G:17.07% B:0.89%) 4. 24/18 13/11 eq: -0.189 (-0.322) 45.72% (G:10.26% B:0.44%) 54.28% (G:16.53% B:0.83%) 5. 24/22 24/18 eq: -0.244 (-0.378) 44.47% (G: 9.40% B:0.39%) 55.53% (G:17.83% B:0.65%)


Next: Restrictions on Wildcard Pathnames, Previous: ->UNSPECIFIC as a Component Value, Up: Interpreting Pathname Component Values
If a pathname is converted to a namestring, the symbols nil and :unspecific cause the field to be treated as if it were empty. That is, both nil and :unspecific cause the component not to appear in the namestring.
However, when merging a pathname with a set of defaults, only a nil value for a component will be replaced with the default for that component, while a value of :unspecific will be left alone as if the field were "filled"; see the function merge-pathnames and Merging Pathnames.


| ID |
Title |
Description |
Price |
Currency |
Image |
Thumbnail |
Dimensions |
Creation Date |
Credit Line |
Copyright Image |
Classification |
Availability |
Artist |
|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| {{artwork.id}} | {{artwork.title}} | {{artwork.description}} | {{artwork.price}} | {{artwork.currency}} | {{artwork.image}} | {{artwork.thumbnail}} | {{artwork.dimensions}} | {{artwork.creationDate | date:'mediumDate'}} | {{artwork.creditLine}} | {{artwork.copyrightImage}} | {{artwork.classification}} | {{artwork.availability}} |
|


{% include sidebar-links.html %} {% include upcoming-dates.html %} {% include useful-resources.html %} {% include side-bar-tags.html %}


The simple idea behind Arduimo programing is to create a closed electrial circuit with your positive and ground
both on the Arduino board. You then input code through the Arduino program on your computer to control the different things
on your circuit. Simply put, it's just computer coding and electrical circuits. So far all we've really covered are LED
features such as blink and fade.
Generally when making circuits you use a small box called a "Bread-board", which is just a small white box
with metal wires running thoughout.


This is an automatic report generated by the {{scraper.name}}
scraper. It contains information about each run of the scraper, and the
error messages and warnings emitted by the scraper.
The following configuration settings applied during the most recent run of this scraper.
| {{key}} | {{value}} |
|---|


To enter this website please confirm your age.
This content is age restricted. Please confirm your entry.


Loading data..
How to play
Use the arrow keys to control Cyan.
Get to the other side to earn bonus time and score.
Avoid the white walls
Try hit the yellow walls for bonus score and time.


There are three ways to add Height and Width: 1) Use both attributes with number like 100 because pixel is default 2) Use both attributes with percentage like 100% 3) Use CSS Style attributes with number as 100 px


Slidebars Mobile Only Example
The classes below will only show to operate on screens smaller than 480px. Try it now, resize your window.
Control Classes
- Toggle left Slidebar
- Toggle right Slidebar
- Open left Slidebar
- Open right Slidebar
- Close either Slidebar


class Input : Terminal
A terminal node that represents a feature value.
The features a referenced by their index into the feature set.
NOTE: Input nodes should not be directly evaluated, as evaluation results in an infinite value. Instead, the index should be used to find the appropriate feature from a feature set.
| <init> |
Input(index: Int)
A terminal node that represents a feature value. |
| index |
val index: Int
The index of the feature this node represents in a flat feature set. |
| arity |
val arity: Int
The number of arguments that this node expects. |


INGREDIENTS
- 1 onion, chopped
- 4 garlic cloves, crushed
- 1 pinch cayenne pepper
- 1 teaspoon paprika
- 1L vegetable stock
- 4 tbsp frik (crushed wheat)
- 1/2 tin chick peas, chopped
- handful of each parsely and coriander, chopped
- 4 mint leaves
- 1 lemon
METHOD
Prep time: 5 mins | Cooking time: up to 40 mins
- Gently fry the onion until soft
- Add the garlic and cook for another 2 minutes, then add cayenne and paprika and cook for another minute
- Add tomato puree and stock and bring to the boil
- Add the frik and simmer, until Frik is soft (approx:30min)
- Blend with a blender and add in the chickpeas and herbs, let it cook until the chickpeas are heated
- Add a squeeze of lemon and serve with borek (spring roll)


In this exercise nothing is going to change in your mail client's appearance, instead you are going to change your layout to use CSS 3 flexbox layout and make your site look exactly the same!


==== Forward/Reverse DNS ====
Reverse DNS can be used to obtain valid server names in use within an organizational. There is a caveat that it must have a PTR (reverse) DNS record for it to resolve a name from a provided IP address. If it does resolve then the results are returned. This is usually performed by testing the server with various IP addresses to see if it returns any results.


|
goog.dom.SavedCaretRange.CARET_REGEX()
A regex that will match all saved range carets in a string.
|
code » | |
|
Returns whether two strings of html are equal, ignoring any saved carets.
Thus two strings of html whose only difference is the id of their saved
carets will be considered equal, since they represent html with the
same selection.
|
code » |


The Wiring library includes components that relate primarily to wires and to basic electrical concepts.
Back to Library Reference


| DOSE: |
2 tablets |
oral |
Unknown |
(pill / tablet) |
Background Information: I am an 18 year old female. I do not take any medications, or vitamen supplements.
When visiting Scotland, I purchased one pack of legal highs called Doves from a head shop. Doves are made by a company called London Underground, and they are said to be safe alternatives to Ecstasy. They do not list the ingredients on the packaging.
7:00 PM - My boyfriend and I aren't really doing much tonight, so I decide to take the doves I've purchased. I decide this after I have eaten a full meal, so I know it'll probably take awhile to kick in. He decides to stay sober.
I'm in a very good mood when I take the two pills. I feel excited and happy to be trying something new. My boyfriend and I at the time had our own room to stay in at a friend's house. The friend was out of town, so we were by ourselves.
8:00 PM - Not feeling anything. I'm guessing it's due to the full stomach.
9:00 PM - Still not feeling anything. I'm starting think these are a scam.
10:00 PM - Nothing. Convinced this must be a scam.
11:00 PM - To my surprise, I start to feel more alert....Physical touch feels very similar to how MDMA feels, but other than that nothing.
12:00 AM - My boyfriend and I decide to go to sleep. I still feel alert, but not enough so that I don't think I could fall asleep. As soon as I close the laptop I'm on, I feel as if I'm slammed with a strong chemical force, very similar to when MDMA hits me all at once. I tell my boyfriend that I am suddenly VERY high.
The high is similar to MDMA in many ways. I feel very happy, open, and empathetic.  The main difference I can find is that this high isn't very speedy. Though I do have a lot of energy, I definitely don't feel the need to get up and dance. I can also say that I feel very much so in control of myself, unlike sometimes on large doses of MDMA where I become an 'e-tard.' Another interesting side effect is that it's pretty hard for me to motivate myself to do anything like go up and get a glass of water. I did drink water while I was high, but not nearly as much as I should have.
12:05 AM - Boyfriend and I have sex. After having sex (which, I will admit, was some of the best sex I've ever had, although I couldn't reach orgasm.) he passes out.
1:00 AM - With nothing else to do, I go online and see that a good amount of my friends are online. I talk with them for most of the night and have good conversations with many of them.
2:00 AM - Still very high.
3:00 AM - Still feeling just as high as when it hits me.
4:00 AM - This high lasts A LOT longer for me than with MDMA. I decide I like this more than actual MDMA due to it feeling more controllable but feeling just as good.
5:00 AM - Starting to come down. The come down feels very natural, very light. I feel a little bit disappointed upon coming down, but not nearly as disappointed as with regular MDMA. I feel less motivated to tell people how much I love them or talk to them and start looking at things online.
5:30 AM - Back to baseline, though feeling very awake. A little bit tired too.  My breathing is becoming more noticeable.
6:00 AM - Stomach is in IMMENSE amount of pain now.  My breathing is now considerably more noticeable, to the point where I feel like I'm hyperventilating.  He holds me to try and calm me down, and I begin crying from the physical pain. I have a pretty high tolerance for pain, so this is surprising even to me. Part of the crying could have also been due to fear because I didn't know what I had actually ingested.
7:00 AM - The pain is still very intense, and I'm still crying. My boyfriend has to keep reminding me to drink water. I feel very light headed and am still having trouble breathing.
7:45 AM - I can feel the pain starting to pass now.
8:00 AM - Pain is mostly gone. Boyfriend and I decide to try and sleep. He passes out, and I remain awake.
9:00 AM - Can't fall asleep. Boyfriend is out cold.
10:00 AM - 12:00 PM Still awake. Boyfriend wakes up and leaves to make money street performing so we can buy food. I obviously chose to stay home.
12:00 PM - 2:00 PM Go on the computer for awhile. Decide to try to sleep at about 2:00 PM.
2:00 PM - 5:00 PM - Sleep. I am woken up by my boyfriend coming back.
5:00 PM - 11:00 PM - Still feel decently tired, but am awake enough to go grocery shopping. We make food and spend time together till we go to sleep. I have no trouble falling asleep at this point.
I feel back to normal the next day. However, three days after I have taken the drug, I experienced a horrible depression. I had to head back to Dublin that day to catch my returning flight so I was alone. I can barely pull myself out of my bed at the hostel I'm staying at. I can't remember a time where I felt this upset. I have read about 'Tuesday blues', where MDMA users report that three days after they use MDMA they feel horrible. I acknowledge the possibility that I could have taken an MDMA analog when I took the doves, so it could cause a similar effect that MDMA would. I also took two hits of MDMA three weeks earlier, so that also could have contributed due to the fact my serotonin could still be in recovery mode. I return back to normal the next day.
In summary, I will not be doing these ever again.
Experience Reports are the writings and opinions of the individual authors who submit them.
Some of the activities described are dangerous and/or illegal and none are recommended by Erowid.


Implements interfaces:
This file is part of Terminalor.
For the full copyright and license information, please view the LICENSE file that was distributed with this source code.
Terminalor Container dependency injection container
Located in /Container.php (line 15)
Register new class in dependencies
Execute all registred dependencies
Get class instance by alias, make new instance if it doesn't exists
Get defined instances
Register and execute default dependencies
Documentation generated on Tue, 07 Feb 2012 14:40:54 +1100 by phpDocumentor 1.4.4


--- title: Distributed Issue Tracking layout: post tags: [git] uuid: 5c65dc10-582e-33a0-dc3c-d2b01a957a4c ---
In a previous post I discussed decentralized version control systems, Git in particular. Because decentralized version control is becoming so popular, we now have an exciting new area of development: distributed issue tracking.
Decentralized issue tracking seems to have popped into existance in the last year or so. A number of projects have appeared (cil, ticgit, ditz, to name some), but the one that really stands out for me is ditz. Keep an eye on that one. It's fairly active and mostly usable.
Decentralized trackers generally work by storing the issue tracking database within the repository itself. One possibility is to have it sit in its own branch, which I think is the Wrong Way. A second possibility is to have it sit right next to the code in its own directory. Yet another possibility is to put the issue tracker in its own repository. Git could even include this repository as a submodule (this is a lot like the Wrong Way, though).
First of all, everyone gets their own copy of the issue tracker database and its history. Second of all, it has history. It's tracked the same way the code is. And, in the second case usage, one of the coolest advantages is that issues follow the code very closely.
When a branch is created, it takes its own copy of the issue tracking database with it. If a bug is fixed in the main branch, the issue tracking database in the main branch is updated. The bug will remain in the side branch and the issue will still be open in the side branch reflecting this. If a merge occurs later, the issue tracking database also gets merged automatically. I think that's damn cool.
There are some issues that still need to be hammered out. How does a non-developer enter a ticker? They would need to work the version control system to do this, then be able to share that change. That's a pretty large barrier.
Perhaps a web interface could be set up for setting up issues. Developers could then cherry-pick/pull the issues from that repository and push ticket updates back out.
Then there is overhead incurred by moving tickets around with code. How bad is this overhead? How can this be dealt with in the most transparent way? This all needs to be tested still.
Could the issue database get too big? People like to attach screenshots to issues. Having many screenshots would make the repository very big. How do we deal with this?
It's an exciting, new realm to explore.


Hi. I am Andrew,
a Software Developer.
I've grown up loving video games
and doing lots of coding.
As a frontend developer,
I value simple content structure, clean design patterns, and thoughtful interactions.
I like to code things from scratch, and enjoy bringing ideas to life in the browser.
Check out my experience below :)
We learned geography, urban planning, geology, and GIS.
This project involve doing Web mapping for Social workers and their clients.
I used this project to finish my final Graduate research paper
This work exprience consist of providing software as a service to EMS and hospital staffs.
I was in charged of UI design and improving their accessibility to medical data and records.


Helping people get their money sorted can be good for business and the community. If you want to help the people you work with or your community to get sorted we have a range of resources you can use – all of which are free, independent and impartial. Here's a list of facilitators if you need one.
Seminar facilitators list
Enter your details to place your order for the resources selected above. Seminars will be delivered via digital download link, and you will receive booklets by mail within 2-3 weeks.


Overview
A platformer game, built using Java and the LibGDX framework. A personal project where you can play as a man trying to escape. Jump through dungeons and forests, killing skeletons and evil snails. The game consists of puzzles and boss battles at the end of each stage. Complete with custom music and art. Released on the Google Play Store, but no longer maintained.
Tools
Java, LibGDX, Pyxel Edit, IntelliJ


|
U.are.U SDK
3.2
DigitalPersona U.are.U SDK
|
Define image properties. More...
#include <dpfj.h>
Data Fields | |
| unsigned int | record_length |
| unsigned int | cbeff_id |
| unsigned int | capture_device_id |
| unsigned int | acquisition_level |
| unsigned int | finger_cnt |
| unsigned int | scale_units |
| unsigned int | scan_res |
| unsigned int | image_res |
| unsigned int | bpp |
| unsigned int | compression |
Define image properties.
Structure defines image properties for FIDs in ANSI 381-2004 and ISO 19794-4-2005 formats.
| unsigned int acquisition_level |
from Table 1 in "ANSI INSITS 381-2004"
| unsigned int bpp |
pixel depth, 1 - 16 bits
| unsigned int capture_device_id |
vendor specified
| unsigned int cbeff_id |
CBEFF product identifier
| unsigned int compression |
from Table 3 in "ANSI INSITS 381-2004"
| unsigned int finger_cnt |
total number of fingerprints in the record, must be greater or equal to 1
| unsigned int image_res |
image resolution
| unsigned int record_length |
total length of the image, including headers and all views
| unsigned int scale_units |
pixels/cm (2) or pixels/inch (1)
| unsigned int scan_res |
scan resolution


Graduated from Kharkov State University in 1970.
PhD Phys & Math, ILTPE, 1988.
Submitted thesis: Self-localized electron states in nonlinear medium.
Quantum theory of open systems and its applications to various soft sciences: biology, psychology and so on.
Considerable number of publications on the above topics have been published yet in Reseach Gate and Arxiv. The interested reader can refer to these sources for more detail information.


Poli
tico
LOGOUT
Settings
Personal account
Manage users
Reset password
Parties
Political parties
Offices
Political offices
Personal settings |
VOTE HERE
Account
Grace lungu
Birindwa
UPLOAD A PICTURE
DELETE
Candidates |
The list of the candidates you have voted for.
Prime minister's office :
Karen Castillo
Karie
12
Another office :
Dorothy Maldonado
Dorte
10
Another office :
Scarlet Mcmillan
Fowler
16
Personal details |
First name
*
Last name
*
Other name
*
Telephone
SAVE SETTINGS


1. Download the Clutch A/B Testing Framework for iOS
Download the Clutch iOS Library
zip file and extract it.
Now drag the Clutch.framework folder into your project:
Choose the option to "Copy items into destination group's folder":
Since Clutch relies on sqlite, add that to your linked frameworks as well:
2. Set up the A/B Testing Framework in Your App Delegate
In your #import <Clutch/ClutchAB.h>
In didFinishLaunchingWithOptions add the following lines:
// Set up Clutch A/B testing
[ClutchAB setupForKey:@"{{ app_key }}" rpcURL:@"http://<IP_ADDRESS>:41674/"];
3. Start A/B Testing!
Now you’re set up to run A/B tests, and you can start adding as many tests as you want to your app. Here’s an example:
[ClutchAB testWithName:@"loginButtonColor" A:^{ self.navigationItem.rightBarButtonItem.tintColor = [UIColor redColor]; } B:^{ self.navigationItem.rightBarButtonItem.tintColor = [UIColor greenColor]; }];For more information, visit our iOS A/B testing docs.


val samples: List<String>
The number of sample cards that this pack has to show users
samples - The number of sample cards that this pack has to show users
samples


WCTOB
Section: Linux Programmer's Manual (3)
Updated: 2011-09-22
Index
Return to Main Contents
NAME
wctob - try to represent a wide character as a single byte
SYNOPSIS
#include <wchar.h>
int wctob(wint_t c);
DESCRIPTION
The
wctob()
function tests whether
the multibyte representation of the
wide character
c,
starting in the initial state, consists of a single
byte.
If so, it is returned as an
unsigned char.
Never use this function.
It cannot help you in writing internationalized
programs.
Internationalized programs must never distinguish single-byte and
multibyte characters.
RETURN VALUE
The
wctob()
function returns the single-byte representation of
c,
if it exists, of
EOF
otherwise.
CONFORMING TO
C99.
NOTES
The behavior of
wctob()
depends on the
LC_CTYPE
category of the
current locale.
This function should never be used.
Internationalized programs must never
distinguish single-byte and multibyte characters.
Use either
wctomb(3)
or the thread-safe
wcrtomb(3)
instead.
SEE ALSO
btowc(3),
wcrtomb(3),
wctomb(3)
Index
- NAME
-
- SYNOPSIS
-
- DESCRIPTION
-
- RETURN VALUE
-
- CONFORMING TO
-
- NOTES
-
- SEE ALSO
-
This document was created by
man2html,
using the manual pages.
Time: 02:54:52 GMT, September 18, 2014


{% extends "base_generic.html" %} {% block content %} {{ form.errors }} {% load widget_tweaks %}
Type how many creatures you want to add.
No Creatures found.


WITNESS LIST
Agriculture, Water & Rural Affairs
May 8, 2017 2:00 PM - or upon adjournment
FOR:
Esparza, Connie Aldine isd trustee & resident (Self), Texas, TX
Rios, Alex Resident (Self), Houston texas, TX
Schnur, Carmen (Self), Tx, TX
Registering, but not testifying:
FOR:
Calderon, Bill (Self; East Aldine Management District), Houston, TX
Patterson, TJ Manager of Legislative Affairs (City of Fort Worth), Fort Worth, TX
ON:
Benter, Tammy Water Division Director (Public Utility Commission), Austin, TX
Davis, Amy (Attorney General), Austin, TX
Pritzlaff, Craig (Attorney General), Austin, TX
FOR:
Zent, Lara Executive Director & General Counsel (Texas Rural Water Association),
Austin, TX
Registering, but not testifying:
FOR:
Kramer, Ken Water Resources Chair (Sierra Club - Lone Star Chapter), Austin, TX
ON:
Zuba, Jessica Deputy Executive Adminisrator (Texas Water Development Board), Austin,
TX
Registering, but not testifying:
FOR:
Cook, Robby (Hemphill County Underground Water Conservation District), Austin, TX
Williams, C.E. General Manager (Self; Panhandle Groundwater Conservation District),
White Deer, TX
FOR:
Kramer, Ken Water Resources Chair (also providing written testimony) (Sierra Club -
Lone Star Chapter), Austin, TX
Mullarkey, Nora (Self), Austin, TX
Registering, but not testifying:
FOR:
Beving, Rita Consultant (Public Citizen), Farmers branch, TX
Cammack, Kerry (Southwest Water Company), Austin, TX
Hess, Myron (National Wildlife Federation), Austin, TX
McGeary, Judith (Self; Farm and Ranch Freedom Alliance), Cameron, TX
Peace, Annalisa (Self; Greater Edwards Aquifer Alliance), San Antonio, TX
Ponebshek, Philip (Self), Austin, TX
Townsend, Trent (The Nature Conservancy), Austin, TX
WITNESS LIST
Agriculture, Water & Rural Affairs
May 8, 2017 2:00 PM - or upon adjournment
Williams, C.E. General Manager (Self; Panhandle Groundwater Conservation District),
White Deer, TX
ON:
Kluge, Kevin Director, Conservation & Innovative Water Tech. (TWDB), Austin, TX
FOR:
Anderson, Andy (Self), Bowie, TX
Glasscock, JD (also providing written testimony) (Self; Baylor University), Columbus,
TX
Hansen, Eydin (also providing written testimony) (Self; Texas Hog Hunters Association),
Wichita Falls, TX
Herring, Charles (Self), Austin, TX
Herring, Will (Self), Austin, TX
Hunnicutt, Becky White Oak Outfitters Inc (also providing written testimony) (Self), Mt
Pleasant, TX
Hunnicutt, Bruce White Oak Outfitters Inc (Self), Mt Pleasant, TX
McDonald, Darryl Dr. (Self), Bryan, TX
Pieratt, John (Self), Giddings, TX
Smith, David P. (Self), Austin, TX
Yeates, David (Texas Wildlife Association), San Antonio, TX
AGAINST:
Bessent, Kody Vice President of Operations & Legislative Affairs (Plains Cotton Growers,
Inc.), Lubbock, TX
Dippel, Donnie (Self; Texas Ag Industries Association), La Grange, TX
Gwynn, Jon (Self), Corpus Christi, TX
Hodges, Kenneth (Corn Producers Association of Texas), Waco, TX
Huie, Matt (Self), Beeville, TX
Martinka, Aaron Farmer (Self; Corn Producers Association of Texas), Buckholts, TX
Nunley, Jeff Executive Director (Self; South Texas Cotton & Grain Association), Victoria,
TX
Ranly, Jared DVM (Self; Texas Farm Bureau), Lott, TX
Ring, Charles Farmer (Self; Corn producers association of texas), Sinton, TX
Robertson, Toby (Self), Corpus Christi, TX
Tomascik, Tracy Associate director (Texas Farm Bureau), Waco, TX
Wade, Patrick (Texas Grain Sorghum Association), Austin, TX
ON:
Bodenchuk, Michael State director (Texas A&M Agrilife Extension Service), San Antonio,
TX
Foster, Justin Research Biologist (Texas Parks and Wildlife Department), Hunt, TX
Kleinschmidt, Tim (also providing written testimony) (Texas Department of Agriculture),
Austin, TX
Powell, Ellis Asst Commander Law Enforcement (Texas parks and wildlife Law
Enforcement Division), Austin, TX
WITNESS LIST
Agriculture, Water & Rural Affairs
May 8, 2017 2:00 PM - or upon adjournment
Smith, Leslie Director of Consumer Protection Services (Texas Department of
Agriculture), Austin, TX
Wright, Philip Admin for ACO (Texas Department of Agriculture), Austin, TX
Registering, but not testifying:
FOR:
Barrett, John (Self), Austin, TX
Beving, Rita Consultant (Public Citizen), Farmers branch, TX
Choate, Elizabeth Director of Government Relations (Texas Veterinary Medical
Association), Austin, TX
Danley, Lisa Attorney (Self), Austin, TX
Houston, Joshua General Counsel (Texas Impact), Austin, TX
Jameson, Quentin (Self), Austin, TX
Johnson, Jonna (Self; Tx State Horse Council, wildlife rehabber and supporter), Magnolia,
TX
Kingston, Elvie (Self), Spring, TX
Kramer, Ken Water Resources Chair (Sierra Club - Lone Star Chapter), Austin, TX
McGeary, Judith (Self; Farm and Ranch Freedom Alliance), Cameron, TX
Mica, Tara (Self), Austin, TX
Propes, Jay (Self; Don't Poison Texas), Austin, TX
Roberts, Mark (Self), Boyd, TX
Shepperd, John Executive Director (Self; Texas Foundation for Conservation and Texas
Coalition for Conservation), Austin, TX
Sinclair, David Legislative Consultant (Game Warden Peace Officers Association),
Pflugerville, TX
Tarlton, Patrick (Texas Deer Association), Austin, TX
Townsend, Trent (The Nature Conservancy), Austin, TX
AGAINST:
Artho, Tara President Texas Grain and Feed Association (Texas Grain and Feed
Association), Fort Worth, TX
Gunn, Brandon Executive Vice President (Self; Texas Pork Producers Association), Kyle,
TX
Martin, Angie Corn Producers Association of Texas (Self; Corn producers association of
texas), Lubbock, TX
Thompson Jr, James E (Self), Austin, TX
Turner, Robert (Independent Cattlemens Assn of Texas), Voss, TX
ON:
Hunter, Dan Assistant Commissioner (TDA), Austin, TX
Registering, but not testifying:
FOR:
Hess, Myron (National Wildlife Federation), Austin, TX
Reaves, Jim State Legislative Director (Texas Farm Bureau), Austin, TX
Williams, C.E. General Manager (Self; Panhandle Groundwater Conservation District),
White Deer, TX
WITNESS LIST
Agriculture, Water & Rural Affairs
May 8, 2017 2:00 PM - or upon adjournment
Registering, but not testifying:
FOR:
Laney, J Pete (Texas Citrus Mutual), Austin, TX
McGeary, Judith (Self; Farm and Ranch Freedom Alliance), Cameron, TX
Wied, Lauren (Wonderful Citrus), Austin, TX
ON:
De Los Santos, Richard Director Produce Safety (Texas Department of Agriculture),
Austin, TX
Hunter, Dan Assistant Commissioner (TDA), Austin, TX
ON:
Hunter, Dan Assistant Commissioner (TDA), Austin, TX
FOR:
Berry, Marty Owner (Self), Corpus Christi, TX
Hellickson, Mickey (Self), Corpus Christi, TX
Ledbetter, Macy Wildlife biologist (Self), San Saba, TX
Price, Bob (Self; Texas Deer Assn), McKinney, TX
Tarlton, Patrick (Texas Deer Association), Austin, TX
Wood, Mike Treasurer (Self; Texas Deer Assn), Dallas, TX
AGAINST:
Campbell, Linda (also providing written testimony) (Self), Kyle, TX
Delaney, Dave Vp and gen mgr king ranch inc (Self; King ranch inc), Kingsville, TX
Shepperd, John Executive Director (also providing written testimony) (Self; Texas
Foundation for Conservation and Texas Coalition for Conservation), Austin, TX
Treadwell, Brian (Self), Christoval, TX
Yeates, David (also providing written testimony) (Texas Wildlife Association), San
Antonio, TX
ON:
Davis, Kevin Major (Texas Parks and Wildlife Department), Austin, TX
Wolf, Clayton Wildlife Division Director (Texas Parks and Wildlife Department), Austin,
TX
Registering, but not testifying:
FOR:
Clark, Chase (Self), Three Rivers, TX
Cunningham, Kip (Self), San Antonio, TX
Graf, Klint (Self), San Antonio, TX
Herndon, Charles (Self), Utopia texas, TX
Hubbard, Mark (Self), Boerne, TX
Martinez, Leo (Self), Freer, TX
Moore, Pete (Self), Dallas, TX
Schmidt, Robert (Self), Driftwood, TX
WITNESS LIST
Agriculture, Water & Rural Affairs
May 8, 2017 2:00 PM - or upon adjournment
Schmidt, Sue (Self), Niederwald, TX
Schmidt, Wenonah (Self), Driftwood, TX
Wood, Justin (Self), Combine, TX
AGAINST:
Barrett, Marko (Self), San Antonio, TX
Barrtee, John (Self), Austin, TX
Cox, Wally None (Self), San Antonio, TX
Hess, Myron (National Wildlife Federation), Austin, TX
Johnson, Tom (Self), Cleveland, TX
Klenzendorf, Whitney (Self), Austin, TX
McLaurin, Kaleb Director of Government Affairs (Texas and Southwestern Cattle Raisers
Association), Austin, TX
Simons, Greg (Self), San Angelo, TX
Steinbach, Don (Self; Texas Chapteer of The wildlife Society), Burton, TX
Thompson jr, James E (Self), Austin, TX
Vandivier, Tom (Self; Texas wildlife association), Austin, TX
Wagner, Matt Environmental Consultant (Self; Texas Chapter of The Wildlife Society),
Austin, TX
Providing written testimony:
AGAINST:
Leslie, Roy (Self), San Antonio, TX