A Recording Revolu(a)tion

Dream on little dreamers,

Recycling a half-remembered dream (pondering)

Eyes on a proud shape

Such is sight to beauty bring

lo, impermanence

Dream on little dreamers,

Dissected Dreams

Dream interpretation is as subjective as the dreams themselves. There is no one way to go about interpreting a dream, but there are a few good things to keep yourself reminded of in the process.

Carl Jung began a discussion on this topic in Man and His Symbols (1964) by emphasizing that there are two different things encountered in dreams. There are signs which are always less than the concept that they represent and symbols which always represent more than their obvious meaning.

Signs in dreams are typically things which contribute to an overall theme in the dream, whereas symbols give the dream a “point.” The tricky part is determining what is a sign and what is a symbol as relevance is not always linked to importance in the time of the dream. Arbitrary objects can be key symbols while main characters or scenarios can be just signs to continue the plot.

In Freud’s The Interpretation of Dreams (1900) he references the mystical feeling of dreams in our morning recollection of them. He continues to mention that the great majority of dreams will lead us back to our everyday life rather than release us from it. The content of dreams is determined by the personality, age, sex, education and habits of the person who dreams them. In that way it is essential to look not at the symbols as having some kind of set meaning but rather look for your own reaction to said symbols.

What I mean to get across through all of this is that when you’re attempting the process of dream interpretation it is not the dream you’re interpreting, but yourself. Stigmas of everyday life do not apply in dreams and you should avoid applying them. If you have sexual contact with a friend from years ago in a dream try not to immediately interpret it as a fantasy and consider your own meanings of sex and that person.

After all, in dreams and in reality not everything is what it seems.

Dream on little dreamers,

Memory on the fritz? Don’t give up!

I’ll say this as much to you all as I do to myself: When it seems like the dreams just wont come, keep trying! Even if you get one bizarre sentence into your dream journal every morning it’s better than nothing. Every little bit counts.

It’s hard to teach something like dream recording where the results do not always match the effort. It can be discouraging to even try when memorable dreams are rare.

Supplements like Fish-oil and multivitamins can be used to help improve memory recall. Also in Thomas Yuschak’s book “Advanced Lucid Dreaming The Power of Supplements,” Piracetam is said to increase the vividness of dreams if taken in low dosages immediately after experiencing a lucid dream. I’d say that seems like a tough moment to pinpoint to take a pill, but I figured I’d mention it for the sake of intrigue.

I’ve never been one to take any kind of supplements. I find it important to learn how to deal with the “lows” in your relationship with your dreams. When frustrated, I often begin to dismiss dreams as “meaningless” and slack on my recording routine.

It’s important to avoid letting this kind of burn-out thinking lessen your faith in dreams. Remember that no matter what every night you have a dream. It can be long or short, vivid or faded and even just wacky but they all mean something.

If you haven’t remembered last night’s dream, that’s ok. Try again tomorrow! Trust me that your unconscious mind won’t be silent any time soon.

Dream on little dreamers,

Angels and Dreamons

A Dream

I was standing outside on my balcony at night. As I looked out I found there was another apartment building across the road. The other building had a single balcony protruding from its shadowed bulk. I looked closer at the balcony. An ominous black mist emanated from the balcony . As I zoned in to the scene I felt my eyes lose focus.

An angelic figure appeared above me, glowing in white light. I pointed in the direction of the balcony across the way, hoping to bring his attention to the evil aura. I felt him fly away, but from my balcony could only see a glowing white light sinking into indistinct blackness. The white light came back soon after, but still my eyes were unfocused.

Dreams are a place of contrast. With a bit of thought archetypal themes can sometimes be found in dreams. These themes often revolve around simple things like what is large vs. small, what is bright vs. dim or even what is good vs. evil.

We can find these themes by focusing on what seemed important through a dream. Try asking yourself: What colors did you see? What textures did you feel? What sounds did you hear?

Oftentimes it’s not about what you actually saw or heard, but what you felt you saw or heard. If you asked me to describe the “angelic figure” of my dream I would be able to tell you that it was a figure in a bright white light. But I know it was angelic, not because I actually saw the perfect projection of an angel, but because I felt that I was looking at something that would be considered angelic.

I apologize if that seems redundant or arbitrary but I want to make a simple point. Don’t expect too much out of your dreams. You’re going to wake up with vague notions of the relationships that existed in your dreams, so take them at face value. Write what you know and interpret it later.

All that we see or seem

Is but a dream within a dream.

~Edgar Allan Poe

Dream on little dreamers,

Your Avatar and You.

A major appeal of lucid dreaming is the fact that you can be whoever you want to be. Many meditative practices revolve around the recognition of a distinction between the mind and the body. It can be very healthy to give yourself the perspective of a new shell, even if it’s only subjectively.

What’s great about dreams is that your avatar, the physical representation of yourself in your dreams, is only limited by your imagination. Manipulating the dimensions of your avatar is the usual way people experience this, whether they become as tall as a building or thin as a crack in a door. However, more abstract things are entirely possible through dreams such as taking the form of an animal or the wind.

In a dream that I had just last night I took the part of a strain of seaweed being pulled along by the crashing waves of a beach. With some effort I was able to direct the aim of my drifting in order to sting the main antagonist of the dream with the jellyfish eggs tangled within me.  Admittedly this was an extremely strange dream for me, but at the same time I was glad that I had trained myself to recognize this dream’s insight.

The forms you take can be extremely interesting to observe. Unfortunately, it can be difficult to recognize that you’re an active participant in your dreams and it can also be difficult to know what you look like. Thus, the two goals to avatar recognition are knowing that you are and knowing what you are.

Knowing that you are is the basis of all lucid dreaming and comes with practice but there are some checks you can do to make it easier. Looking at text such as watches, books or phones which tend to look garbled in dreams is usually a good way to assert consciousness. Another method is to focus your energy on any specific object or person in the dream. The “anchor” typically works well for this. Focusing on something allows you to control the flow of the dream and prove your presence to yourself. There are many more methods, but these are a couple that came to mind.

Knowing what you are is where the fun part comes in. Try to take note of the perspective from which you’re viewing the dream. Are you way down at the feet of the people around you? Are you looking them right in the eyes? Or are you soaring far above them like a bird?  Mirrors are usually a lucky find in dreams as they force your mind to either create a picture of your avatar or leave it blank and give you a blatant clue to the fact that you’re dreaming. If you’re able to catch a hint of what you are try to act the part. Ebb and flow like a wave, stretch your wings like a bird or simply just breathe.

Oftentimes it’s only in retrospect that you can recognize what your role was within the dream you just had. Even if you find that you were just yourself most of the time it’s a huge step forward to know even that. Keep on trying and see what you’ll become.

Dream on little dreamers,

Movies: The second showing is free!

If there’s one thing I’ve really come to notice about movies is how directly they influence dreams. TV shows and series can also have an influence, but movies are unique in the ability to affect your perspective in just 2-3 hours. I’d like to take a quick look at how and why movies imprint themselves in this way.

It’s late in the evening and you have a few hours to kill before bed. You curl up into your favorite recliner or just a theater seat that has no one in front so you can put your feet up. The next few hours it’ll be you and a screen, sometimes you’ll be so enraptured that you’ll  forget you’re even watching a movie. As though in a trance, you’ll dote on every quirk of the characters and twist of the plot.

Personally I’ve come to dislike watching too many movies as I feel their affect is too pronounced on my dreams. But that doesn’t mean that movies are a negative influence for lucid dreamers. In fact learning to manipulate the power of movies can give you a useful tool to have all sorts of dreams.

It’s common sense for most to think that a scary movie like The Exorcist or Insidious: Chapter 2 will cause you to have nightmares. In just the same strain of thought movies like Spirited Away or Memento can cause fanciful and thought provoking dreams. Similarly, its entirely possible to have dreams of movie universes like the Star Wars trilogy or The Avengers by having a movie marathon (bring a friend!).

I think a lot of the reason that movies become so imprinted on our subconscious is because our mind is processing the bulk of new information presented to us. The same affect happens when we read a new book, or go to a vacation somewhere exotic. The only difference being that while reading a new book or traveling may take half a day or more, movies pack all that newness into 3 hours. Superheros, demons and space stations are not things that we see on a daily basis, so our minds asses those images by reanalyzing them in our dreams. At least that’s my theory.

So why does it matter? Well it matters because fictional or not the characters in movies become symbols in our dreams long after we watch those movies. By contrasting what a movie character originally is versus our relationship with that character in our dreams we can make some interesting interpretations.

For example, I recently had a dream where Captain Jack Sparrow from Pirates of the Caribbean was sprinting around my apartment complex cutting into ship sails fastened to the side of the building with a scimitar. I wondered if I should stop him but he was running way too fast to catch. Soon he had ripped every sail attached to the apartment complex, leaving it woefully unable to go to sea again.

The unbelievably fast saboteur is quite different from the drunken free-spirited pirate from the movies. This might represent a feeling of being held back by those that once seemed fun to me. Or maybe something else entirely. What do you think?

What movie do you think has the best atmosphere?

Dream on little dreamers,


Nick Hatley
Jun 12 · 16 min read
(Illustration by Selena Qian/Pew Research Center)

Last year, I wrote an introductory blog post about how to access and analyze Pew Research Center survey data with R, a free, open-source software for statistical analysis. The post showed how to perform tasks using the survey package.

The survey package is ideal if you’re analyzing survey data and need variance estimates that account for complex sample designs, such as cluster samples or stratification. However, the first step of any data analysis is often exploring the data with simple but powerful summaries, such as crosstabs and plots. This usually requires significant re-coding of variables as well as data cleaning and other manipulation tasks that can be difficult and counterintuitive. Fortunately, something called the “tidyverse” is here to help.

In this post, I’ll show how to use tidyverse tools to do exploratory analyses of Pew Research Center survey data. (These tools, however, can be used with data from any source.)

What is the “tidyverse”?

R has a large community of users, many of whom make their own code freely available to other R users in the form of packages that implement specialized kinds of analyses or enable other programming tasks.

R packages are typically hosted on The Comprehensive R Archive Network (CRAN), but are also available on other primarily open-source code repositories like github, gitlab or bioconductor. One of the nice things about R is that anyone can build a package and contribute to the software’s development. But with so many packages (there were 14,366 on CRAN as of June 12, 2019), there are often many different ways to tackle the same challenge. This can lead to inconsistencies that are often confusing, making it harder on new users or those looking to develop their R skills.

Enter the tidyverse, a collection of R packages designed for data science that share a consistent design philosophy and produce code that can be more easily understood and shared. The tidyverse has a growing community of users, contributors and developers that aim to help R users access and learn these free, open-source tools. The book R for Data Science by Hadley Wickham and Garrett Grolemund walks through many key components of how to use these tools to do data science in R and can be accessed online for free.

For this post, we’ll need the tidyverse and haven packages. The haven package is the tidyverse’s solution for importing and exporting data from several different formats, including SPSS (the format in which most Center datasets are currently released), SAS and Stata.

The only functions from the haven package we'll use here are read_sav() and as_factor(). All other functions referenced in this post come from packages like dplyr, forcats or ggplot2, which are loaded automatically with the tidyverse package.

If you don’t already have these packages, you’ll need to install them in order to run the code in this post. Even if you have already installed them, you can update them by running the below code:

Next, load the packages in with the library() function:

#loads all "core" tidyverse packages like
#dplyr, tidyr, forcats, and ggplot2

One of the most appealing features of the tidyverse is its emphasis on making code easier to read and understand. A key tool for improving the readability of tidyverse code is the pipe, a set of three characters that looks like this: %>%. Placing a pipe to the right of an object (such as data %>%) tells R to take the object on its left and send it to its right. This allows you to chain multiple commands together without getting lost in a hailstorm of parentheses.

Let’s use a pop culture dataset to illustrate this point. The starwars dataset that comes with the tidyverse package contains information on the characters from the movies, made available through the Star Wars API. Suppose we want to filter the dataset to all characters for whom a height is known, arrange the dataset in order of decreasing height and then change the height variable from centimeters to inches.

Here is the code to do this without using pipes:

mutate(arrange(filter(starwars, !, desc(height)), height = 0.393701 * height)

And here’s the code with the pipe:

starwars %>%
filter(! %>%
arrange(desc(height)) %>%
mutate(height = 0.393701 * height)

As far as R is concerned, these two pieces of code do exactly the same thing. But using a series of pipes makes it much easier for humans to read and understand exactly what’s going on, and in what order. The code above can be easily read as a series of steps: take the starwars dataset, filter it to cases where height is not missing, arrange the remaining cases by height in descending order, and, finally, change the height variable to inches.

Readability makes it easier to share your code with other people. Even if you’ll never share your code with anyone else, this approach will make it easier for you to understand your own code if you ever need to revisit it weeks, months or even years later when the details are no longer fresh in your memory. (This can also help you or your team avoid technical debt.)

Beyond readability, pipes make your code easier to maintain. It’s easy to remove a step, insert a new step or change the order when all of the commands are in a sequential series of pipes, rather than nested.

Loading the data into R

Let’s shift gears and return our attention to using tidyverse tools to analyze Pew Research Center survey data. You can download the Center’s datasets via this link, and you can learn more here about the kind of data we release and how to access it.

For the purposes of this backgrounder, we’ll use data from our April 2017 Political survey. We’ll walk through how to use tidyverse tools to calculate weighted survey estimates (specifically, approval of President Donald Trump) broken out by other variables in our dataset (education, race/ethnicity and generation).

The first step is to load the dataset into your R environment. Almost all of the datasets available to download from the Center are stored as .sav (SPSS) files. The haven package can import datasets created by SPSS and a number other programs such as Stata and SAS.

There are a few features of SPSS datasets that require special handling when loading data into R. SPSS files often contain variables with both character labels and numeric codes that are not necessarily sequential (e.g. for party ID, 1 = Republican, 2 = Democrat, 9 = Refused). SPSS also allows variables to have multiple, user-defined missing values. This sort of variable metadata is helpful, but it doesn’t quite align with any of R’s standard data types.

The haven package handles these differences by importing variables in a custom format called "labelled" and leaving the user to decide which of the numeric codes or value labels he or she wants to work with in R.

We’ll import the data using haven’s read_sav() function. We'll set user_na = TRUE to ensure that responses such as "Don't know" or "Refused" aren’t automatically converted to missing values. In this case, we also want to convert any labelled variables into factors so that we can work with value labels instead of the numeric codes (e.g. "Republican" instead of "1"). We do this by piping (%>%) the entire dataset to haven's as_factor() function which converts any labelled variables in the dataset to factors.

Apr17 <- read_sav("Apr17 public.sav",
user_na = TRUE) %>%

Adding variables with mutate

The first question (q1) on the April 2017 survey asked whether or not respondents approved of Trump’s performance as president so far. The next question (q1a) asked respondents how strongly they approved or disapproved ("Very strongly," "Not so strongly," "Don't know/Refused (VOL.)"). We want to use these two variables to create a new variable that combines q1 and q1a. This sort of re-coding is extremely common when working with survey data, but it can be a surprisingly difficult task when using only base R functions. The dplyr package, which is loaded automatically as part of the tidyverse package, includes a number of tools that make these sorts of data processing tasks much easier.

The most general of these is the mutate() function, which either adds new variables to a data frame or modifies existing variables. We’ll use mutate() in the code below to create a variable called trump_approval. The actual re-coding is done with the case_when() function, which evaluates a series of conditions and returns the value associated with the first one that applies.

Apr17 <- Apr17 %>%
mutate(trump_approval = case_when(

q1 == "Approve" & q1a == "Very strongly" ~ "Strongly approve",
q1 == "Approve" & q1a != "Very strongly" ~ "Not strongly approve",
q1 == "Disapprove" & q1a == "Very strongly" ~ "Strongly disapprove",
q1 == "Disapprove" & q1a != "Very strongly" ~ "Not strongly disapprove",
q1 == "Don't know/Refused (VOL.)" |
q1a == "Don't know/Refused (VOL.)" ~ "Refused"
) #this parentheses closes call to
#case_when and sends it to
#fct_relevel with %>%
fct_relevel("Strongly approve",
"Not strongly approve",
"Not strongly disapprove",
"Strongly disapprove",
) #this parentheses closes our call to fct_relevel
) #this parentheses closes our call to mutate

We supply a series of formulas to the case_when() function. Each formula is an “if-then” statement, where the left side (everything to the left of ~) describes a logical condition and the right side provides the value to return if that condition is true. As a reminder, you can type ?case_when() to access the help page (this works for any function in R, not just case_when()).

The first line of the call to case_when() is: q1 == "Approve" & q1a == "Very strongly" ~ "Strongly approve". This can be read to mean that respondent said "Approve" to q1 and answered "Very strongly" to q1a, so we’ll code them as "Strongly approve" in our new trump_approval variable. We use five different clauses to make these new categories and add the trump_approval variable to our dataset.

Because case_when() returns character variables when used this way, the last step is to pipe the variable to fct_relevel() from the forcats package. This converts trump_approval to a factor and orders the categories from "Strongly approve" to "Refused."

We can run the table command on our new variable to verify that everything worked as intended.

table(Apr17$trump_approval, Apr17$q1)
## Approve Disapprove Don't know/
## Refused (VOL.)
##Strongly approve 476 0 0
##Not strongly approve 130 0 0
##Not strongly disapprove 0 143 0
##Strongly disapprove 0 676 0
##Refused 0 0 76

Having created our new trump_approval variable, we'd like to see how it breaks down according to a few different demographic characteristics: educational attainment (educ2 in the Apr17 dataset), race/ethnicty (racethn) and generation (gen5).

But educ2 has nine categories, some of which don’t have very many respondents. We thus want to collapse them into fewer categories with larger numbers of respondents. We can do this with the forcats function fct_collapse(). We use mutate() again to make new variables.

Let’s first check the answer options of educ2 to see the categories we need to collapse. Since we used as_factor() when we read the dataset in, educ2 is a factor variable. So, we can see the answer options by using the levels() function.

levels(Apr17$educ2)## [1] "Less than high school (Grades 1-8 or no formal schooling)"
## [2] "High school incomplete (Grades 9-11 or Grade 12 with NO diploma)"
## [3] "High school graduate (Grade 12 with diploma or GED certificate)"
## [4] "Some college, no degree (includes some community college)"
## [5] "Two year associate degree from a college or university"
## [6] "Four year college or university degree/Bachelor's degree (e.g., BS, BA, AB)"
## [7] "Some postgraduate or professional schooling, no postgraduate degree"
## [8] "Postgraduate or professional degree, including master's, doctorate, medical or law degree"
## [9] "Don't know/Refused (VOL.)"

Now that we know the levels, we can collapse them into fewer categories. The first argument to fct_collapse() is the variable whose categories you want to collapse, in our case educ2. We assign new categories on the left, like "High school grad or less", in the below example. We use the c() function to tell fct_collapse() these categories belong in our new "High school grad or less" category. Note that you need to use the exact names of these categories.

Apr17 <- Apr17 %>%
mutate(educ_cat = fct_collapse(educ2,
"High school grad or less" = c(
"Less than high school (Grades 1-8 or no formal schooling)",
"Some college" = c(
"Some college, no degree (includes some community college)",
"Two year associate degree from a college or university"
"College grad+" = c(
"Some postgraduate or professional schooling, no postgraduate degree",
) #this parentheses closes our call
#to fct_collapse
) #this parentheses closes our call to mutate

Getting weighted estimates with group_by and summarise

Now that we have created and re-coded the variables we want to estimate, we can use the dplyr functions group_by() and summarise() to produce some weighted summaries of the data. We can use group_by() to tell R to group the Apr17 dataset by these variables and then summarise() to create summary statistics among those groups.

To make sure our estimates are representative of the population, we need to use the survey weights (variable named weight) included in our dataset, as is the case in almost all of the Center's datasets. For the total sample, we can calculate weighted percentages by adding up the respondent weights for each category and dividing by the sum of the weights for the whole sample.

The first step is to group_by() trump_approval and then use summarise() to get the sum of the weights for each group. Then we use mutate() to convert these totals into percentages.

So the first step in code is this:

trump_approval <- Apr17 %>%
group_by(trump_approval) %>%
summarise(weighted_n = sum(weight))

We can see that group_by() and summarise() gives us a table with one row for each group and one column for the summary variables that we created. If we look at the trump_approval object that we just created, we can see we have a column for each of the categories in our trump_approval variable (that we passed to group_by()) and a column we created called weighted_n. The weighted_n column is the weighted sum of each category in trump_approval.

But since we want show proportions, we have another step to do. We’ll use mutate() to add a column called weighted_group_size that is the sum of weighted_n. Then we just divide weighted_n by weighted_group_size and store that in a column called weighted_estimate, which gives us our weighted proportions.

trump_approval <- Apr17 %>%
##group by trump_approval to calculate weighted totals
##by taking the sum of the weights
group_by(trump_approval) %>%
summarise(weighted_n = sum(weight)) %>%
##add the weighted_group_size to get the total weighted n and
##divide weighted_n by weighted_group_size to get the proportions
mutate(weighted_group_size = sum(weighted_n),
weighted_estimate = weighted_n / weighted_group_size

## # A tibble: 5 x 4
##trump_approval weighted_n weighted_group_size weighted_estimate
## 1 Strongly
## approve 1293. 4319. 0.299
## 2 Not strongly
## approve 408. 4319. 0.0945
## 3 Not strongly
## disapprove 458. 4319. 0.106
## 4 Strongly
##disapprove 1884. 4319. 0.436
## 5 Refused 275. 4319. 0.0636

To add a subgroup variable and get a weighted crosstab, we can use the same procedure with one slight addition. Instead of going straight from summarise() to mutate() and adding our group sizes and proportions, we have to tell mutate() to calculate the weighted_group_size of educ_cat. This gives the weighted number of respondents that are in each category of educ_cat ("High school grad or less," "Some college," "College grad+," "Don't know/Refused (VOL.)")

trump_estimates_educ <- Apr17 %>%
##group by educ and trump approval to get weighted n's per group
group_by(educ_cat, trump_approval) %>%
##calculate the total number of people in each answer and education category using survey weights (weight)
summarise(weighted_n = sum(weight)) %>%
##group by education to calculate education category size
group_by(educ_cat) %>%
##add columns for total group size and the proportion
mutate(weighted_group_size = sum(weighted_n),
weighted_estimate = weighted_n/weighted_group_size)

## # A tibble: 17 x 5
## # Groups: educ_cat [4]
## educ_cat trump_approval weighted_n weighted_group_… weighted_estima…
## <fct> <fct> <dbl> <dbl> <dbl>
## 1 High schoo… Strongly appro… 550. 1710. 0.322
## 2 High schoo… Not strongly a… 207. 1710. 0.121
## 3 High schoo… Not strongly d… 221. 1710. 0.129
## 4 High schoo… Strongly disap… 593. 1710. 0.347
## 5 High schoo… Refused 140. 1710. 0.0817
## 6 Some colle… Strongly appro… 404. 1337. 0.302
## 7 Some colle… Not strongly a… 111. 1337. 0.0833
## 8 Some colle… Not strongly d… 128. 1337. 0.0959
## 9 Some colle… Strongly disap… 605. 1337. 0.453
## 10 Some colle… Refused 88.1 1337. 0.0659
## 11 College gr… Strongly appro… 336. 1258. 0.267
## 12 College gr… Not strongly a… 89.9 1258. 0.0715
## 13 College gr… Not strongly d… 109. 1258. 0.0870
## 14 College gr… Strongly disap… 676. 1258. 0.537
## 15 College gr… Refused 47.0 1258. 0.0373
## 16 Don't know… Strongly appro… 2.97 13.3 0.224
## 17 Don't know… Strongly disap… 10.3 13.3 0.776

This may seem like a lot of work to create one weighted crosstab, and there are definitely easier ways to do this if that’s all you need. However, it gives us a great deal of flexibility to create any number of other summary statistics besides weighted percentages. Because the summaries are stored as a data.frame, it’s easy to convert them into graphs or use them in other analyses. (Technically the output is a tibble, tidyverse's approach to data frames.)

Perhaps most usefully, we can use this approach to create summaries for a large number of demographics or outcome variables simultaneously. In this example, we’re not only interested in breaking out trump_approval by educ_cat, but also the racethn and gen5 variables. With some reshaping of the data using the gather() function, we can use the procedure to get all of our subgroup summaries at once.

Rearranging data with gather()

The first step to making the process a bit simpler is to take the Apr17 dataset and select down to only the columns we need for our analysis using the select() function. The select() function is like a Swiss army knife of keeping, rearranging or dropping (using -) columns. There are also a number of helper functions like starts_with(), ends_with()and matches() that make it easy to select a number of columns with a certain naming pattern instead of naming each column explicitly. You can also rename variables with select() by supplying a new variable name before an = and the old variable name.

Apr17 <- Apr17 %>%
select(resp_id = psraid,
educ_cat, racethn, gen5)

This line of code uses the select() function to limit the Apr17 dataset to only the columns we need for our analysis. Just to illustrate how renaming works, we’ll change the name of the respondent identifier from psraid to resp_id. We’ll retain the survey weight (weight), the trump_approval variable and the subgroup variables we are interested in (educ_cat, racethn and gen5).

head(Apr17)## # A tibble: 6 x 6
## resp_id weight trump_approval educ_cat racethn gen5
## <dbl> <dbl> <fct> <fct> <fct> <fct>
## 1 100005 2.94 Strongly disappro… College grad+ Black, non… Silent (1…
## 2 100010 1.32 Not strongly appr… Some college Hispanic Boomer (1…
## 3 100021 1.24 Strongly disappro… College grad+ White, non… Silent (1…
## 4 100028 4.09 Strongly approve Some college White, non… Boomer (1…
## 5 100037 1.12 Refused College grad+ White, non… Boomer (1…
## 6 100039 6.68 Strongly disappro… High school gra… Black, non… Boomer (1…

The next step is to rearrange the data in a way that makes it easy to calculate the weighted summary statistics by each demographic group. We’ll do this with the gather() function, which reshapes data from “wide” format to “long” — an extremely useful function when working with data. (Recently, the team behind the tidyr package introduced functions called pivot_longer() and pivot_wider(). These functions will not replace gather() and spread(), but are designed to be more useful and intuitive.)

In wide format, there is one row per person and one column per variable. In long format, there are multiple rows per person: one for each of the demographic variables we want to analyze. The separate demographic columns are replaced by a pair of columns; a “key” column and a “value” column. Here, the “key” column is called subgroup_variable, and it identifies which demographic variable is associated with that row (one of educ_cat, racethn, or gen5). The "value" column is called subgroup and identifies the specific demographic category to which the person belongs.

Apr17_long <- Apr17 %>%
gather(key = subgroup_variable, value = subgroup,
educ_cat, racethn, gen5)

In this code, we’re telling gather() to name the key variable "subgroup_variable" and to name the value column "subgroup." The remaining arguments specify the names of the columns that we want to gather into rows. After the gather() step, we’ve gone from a wide dataset with 1,501 rows to a long dataset 4,503 rows (1,501 respondents x 3 demographic variables).

If you want to read more about gather(), I recommend starting with this tweet by Alison Hill from the WeAreRLadies twitter account. You can also go to the tidy data chapter in the previously mentioned R for Data Science book.

Now that we have our data arranged in this format, getting weighted summaries for all three subgroup variables is just a matter adding another grouping variable. Whereas before we grouped by educ_cat, we can now use our newly created subgroup_variable and subgroup columns instead.

trump_estimates <- Apr17_long %>%
#group by subgroup_variable, subgroup, and trump approval
group_by(subgroup_variable, subgroup, trump_approval) %>%
#calculate the total number of people in each answer and education #category using survey weights (weight)
summarise(weighted_n = sum(weight)) %>%
#group by subgroup only to calculate subgroup category size
group_by(subgroup) %>%
#add columns for total group size and the proportion
mutate(weighted_group_size = sum(weighted_n),
weighted_estimate = weighted_n/weighted_group_size)

Since we are only really interested in the proportions, we’ll remove the weighted_total and weighted_group_size columns using the select() function. Including the — before a column name tells select() to drop that column.

trump_estimates <- trump_estimates %>%
select(-weighted_n, -weighted_group_size)

Here’s what we end up with.

## # A tibble: 70 x 4
## # Groups: subgroup [14]
## subgroup_variable subgroup trump_approval weighted_estima…
## <chr> <chr> <fct> <dbl>
## 1 educ_cat College grad+ Strongly approve 0.267
## 2 educ_cat College grad+ Not strongly appr… 0.0715
## 3 educ_cat College grad+ Not strongly disa… 0.0870
## 4 educ_cat College grad+ Strongly disappro… 0.537
## 5 educ_cat College grad+ Refused 0.0373
## 6 educ_cat Don't know/Refuse… Strongly approve 0.0203
## 7 educ_cat Don't know/Refuse… Strongly disappro… 0.0704
## 8 educ_cat High school grad … Strongly approve 0.322
## 9 educ_cat High school grad … Not strongly appr… 0.121
## 10 educ_cat High school grad … Not strongly disa… 0.129
## # … with 60 more rows

Arranging the data this way makes it easy to create plots or tables of the variables of interest. Below is an example of a simple plot of the estimates we created in this post. We use the filter() function to remove the “Refused” category in the trump_approval variable and in any of our subgroup variables. Then, we pipe that data into the plotting code from ggplot2.

trump_estimates %>%
filter(trump_approval != "Refused") %>%
filter(!(subgroup %in%
c("Don't know/Refused (VOL.)", "DK/Ref"))) %>%
x = weighted_estimate,
y = subgroup
) +
geom_point() +
scale_x_continuous(limits = c(0, .8),
breaks = seq(0, .6, by = .2),
labels = scales::percent(
seq(0, .6, by = .2), accuracy = 1)
) +
facet_grid(cols = vars(trump_approval),
rows = vars(subgroup_variable),
scales = "free_y",
space = "free"
) +
theme_bw() +
theme(axis.title.y = element_blank())

Here is all the necessary code used in the post:

Pew Research Center: Decoded

The "how" behind the numbers, facts and trends shaping your world.

Nick Hatley

Written by

Research Analyst, Pew Research Center. Tweet about research methods, elections, R and the NBA. Views are my own.

Pew Research Center: Decoded


Problem of Explication the Social Intellect of the Person

  • Eduard Z. Ivashkevych Rivne State University of the Humanities
Keywords: social intellect, sensual components, semantic aspects, valuable substructure of social intellect, knowledge, desires, aspirations, attitudes

In this article is shown that as a semantic component of social intellect scientists consider the need for empathy to another person, understanding his/her inner world. It was noted that the higher the level of empathy was, the more a person was able to imagine how one and the same event was perceived by different people, and the better person was able to understand the right of existence of different points of view. Sensual components of social intellect are provided by the development of reflective abilities of individuals, their mastery of methods of self-improvement, determined attitude to human life values that a person as a result of mastering the world tries to understand and rethink.

It іs emphasized that speaking about the nature of the semantic aspects of social intellect was also very important, from the one hand, to understand that the knowledge and other meanings mostly clearly explicated in value of the object of this knowledge, through which desires, aspirations, attitudes are manifested towards other people.

It іs underlined that valuable substructure of social intellect of the person involved the idea that the individual evaluated himself / herself as a person who was able not only to know everything about surrounding world, but also to self-understanding of how he/she the entity examined himself/herself as so called “ethic individual”.

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Batarshev, A. V. (2006). Diagnostika sposobnosti k obshheniyu [Testing of the ability to communicate]. SPb.: Piter [in Russian].
Be'ron, R., Birn, D., Dzhonson, B. (2003). Socialnaya psixologiya: klyuchevye idei [Social psychology: the key ideas]. SPb.: Piter [in Russian].
Dodonov, B. I. (1978). Emociya kak cennost' [Emotion as value]. M.: Politizdat [in Russian].
Izmajlov, Ch. A., Chernorizov, A.M. (2004). Psixofiziologicheskie osnovy e'mocij [Psychophysiological bases of emotions]. M.: Moskovskij psixologo-social'nyj institut [in Russian].
Lopuxova, O. G. (2001). Vliyanie etnokulturnyx tradicij na stanovlenie psixologicheskogo pola lichnosti [The impact of ethnic and cultural traditions in the developing of psychological gender identity]. Voprosy psixologii. – Questions of psychology, 5, 73-79 [in Russian].
Majers, D. (2006). Social'naya psixologiya [Social Psychology]. SPb.: Piter [in Russian].
Mokshancev, R. I., Mokshanceva, A. V. (2001). Social'naya psixologiya [Social Psychology]. Novosibirsk: Sibirskoe soglashenie; M.: INFRA-M [in Russian].
Rubinshtejn, S. L. (1989). Obshhaya psixologiya [General Psychology]. M.: Pedagogika [in Russian].
Sobchik, L. N. (1998). Vvedenie v psixologiyu individual'nosti [Introduction to the psychology of personality]. M.: Institut prikladnoj psixologii [in Russian].
Shevandrin, N. I. (1995). Socialnaya psixologiya v obrazovanii [Social Psychology in Education]. M.: VLADOS [in Russian].
Chodorow, N. (1987). Feminism and difference: gender, relation and difference in psychoanalytic perspective. The psychology of woman: Ongoing debates, 2, 249-264 [in English].
Heckhausen, H. (1930). Motivationsanalyse der Anspruchsniveau. Setzung.: Psychologische Forschung [in English].

Abstract views: 18
PDF Downloads: 11
How to Cite
Ivashkevych, E. Z. (2016). Problem of Explication the Social Intellect of the Person. PSYCHOLINGUISTICS, (20(1), 77-87. Retrieved from


Information Technology

Nigerians without identity number can’t get loans — NIMC

Ozioma Ubabukoh

“The NIN enhances access to credit from financial institutions, protects citizens from identity theft, thereby being an antidote to identify theft driven frauds,” Aziz said.

He said, “It expands access to other financial services, including insurance. It enhances e-commerce by providing a means of payment. It is a tool for non-repudiation and security for financial transactions and it facilitates financial inclusion and hence cashless economy.”

 Other benefits of the NIN, the NIMC director-general said, included, “one person, one identity. It enhances participation in the political process. It is an important tool for the fight against corruption and terrorism.

 “It enables citizens to exercise their rights and facilitates management of subsidies and safety net payments such as the one that applies to Internally Displaced Persons.”

 Posing the question of ‘who you are ‘ which every human being is faced with globally, Aziz explained that the NIMC was established “to provide a single version of truth or unique identity for every citizen and foster the orderly development of an identity sector in Nigeria.”

 He stated that Nigerians should utilise the opportunity provided by the Federal Government through the NIMC, and obtain a NIN.

 “With the current campaign, the NIMC will continue to enlighten Nigerians on the importance of enrolling to obtain the National Identification Number, which fully confers on any citizen so enrolled Nigerian citizenship.

 “Without the NIN, anyone’s claims of being a Nigerian citizen are doubtful; that is what the NIMC Act stipulates,” he added.

The NIMC was established by the NIMC Act No. 23 of 2007, as an offshoot of the Department of National Civic Registration, to create, establish and maintain a unique National Identity Database, register persons covered by the Act, assign a unique National Identification Number, provide authentication platform for identity verification, issue general multi-purpose cards and harmonise and integrate existing identification databases in Nigeria.

   Copyright PUNCH.

Contact: [email protected]


Think of each day and each mile as an opportunity to add to your personal bank of fitness. Commit this month to getting in some great miles and really enjoying the process of moving and giving your body the gift of fitness.

Here are 10 May wishes straight from our hearts to yours:

  1. May you take the time each day to be thankful for each mile traveled.
  2. May you find balance in your busy life between work, play, family time, and YOU time.
  3. May you inspire others through your actions, dedication, and determination.
  4. May you take the time to celebrate others’ accomplishments and support those who need an extra boost.
  5. May you fuel your body with what it needs to stay strong and vibrant, allowing it to take you where you want to go.
  6. May you feel the support of your family, friends, and community as you work to achieve your goals.
  7. May you make habits out of what is important and let go of what is non-essential.
  8. May you awake each day with a purpose and a goal no matter how simple.
  9. May you empathize with those less fortunate and lend them a hand when possible.
  10. May you find beauty and grace in the simplicity of movement, heartbeat, and breath.

And one extra May wish from the classic Irish blessing:

“May the roads rise to meet you. May the wind be constantly at your back.”

Happy May,

The Run The Edge Team

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• Recent Posts

    Crystals, An Introduction in Sacred Spaces

    “Those who plants kindness gather love ”    St. Basil the Great

    Crystals are born of the earth and the stars and share their beneficial properties with us.  They are valuable, kind and insightful in healing the body, mind, and the earth itself.  In this post crystals, minerals and gems are used interchangeably to mean the same object.  They are used for many purposes such as in healing the human body or aid in easing a troubled mind, but my focus is sacred spaces.  When I visit clients, I like to partner with them and the space tuning into both with permission and always showing grace and respect when visiting.

    I am of the belief that everything is energy and is frequently in motion.  The plant kingdom and its many members are no different.  They partner with crystals to heal physical ailments within themselves, the earth, or your sacred space.  Each crystal has its own properties and in the next 2 to 3 posts, I will explore those that work in sacred spaces to make them more productive, healthy, and beautiful.

    My definition of sacred space is broad.  It is always small spaces, containers, urban balconies, cottage gardens in the country or flower beds in urban areas.  It can be the one tree you absolutely love, a sitting area or a large space.  Your statue, art work or water feature are all part of a sacred space.  Crystals can partner with all of them in short spurts or for several years.  One of my standard practices is to place quartz crystals in the four corners of one’s property offering protection, a healthy space and vivacious plants.

    This post includes ideas and why partnering with gems would be of help.  Like plants and sacred spaces, I believe crystals speak to the individual.  If you are wandering in a shop, ask what crystals help with my space today and where would I place it?  Sparkling gems are always magical for humans, birds and plants.  Remember crows love sparkling things–if your crystals have gone traveling–crows are gifting them.

    Sacred spaces flourish when using the energy of the Earth.  Copper is a great example of this.  As a mineral, color and gem it speaks to the earth, and anything near it.  It is one of the 8 micronutrients required for plant life.  It directs energy from the earth to the plant.  This is one role of crystals, the ability to send specific energies that support growth and vibrancy.  They enhance nurturing to plants helping them to grow.

    Crystals in a sacred space channel the energy of its properties or attributes and where they can be the most beneficial.  In partnering with our plants and crystals we are respecting the gifts of the Earth’s Cycle of Giving.  An example is several years ago, a crystal called Earthkeepers appeared on the surface of the planet.  Rumored to exist but never found, Earthkeepers with their advance vibration are here to help the earth and bring future protection and peace to humans and the earth.  They believe their properties can now be respected and worked with successfully.  These crystals are still hard to find.  I was lucky enough to be in a class to seen them and buy one.  It is a constant stay in my sacred spaces.

    Giving Sacred Spaces a helping hand

    All crystal work begins with cleared and charged gems. They can be ‘programmed’ though meditation and intention or in conversation with the spiritual entities of your sacred space and plants.  You can program a crystal to supplement the vital energies of plant growth.  When sowing seeds in the spring.    Ask them what crystals will work for the current situation.  Choose crystals that speak to you.  Place in a grid formation or as a border around plants, shrubs or trees.  Blend sand, high in quartz composition with potting soil.  Evoke the elements (air, fire, water, earth, spirit) by coordinating your space with crystals associated with each season and direction.  Crystals can be used in plant food, but you will want to place them in the mixture 24 hours before use.  Include gems in flower bouquets and potted plants when you give them as a gift.

    To give the roots and the rest of the plant a helping hand, stick part of the crystal into the soil about 2 inches away from the main stalk or trunk.  When a tree limb or branch needs more healing, wrap the gem directly to the branch with soft copper wire.  Leave in place until health is restored, two weeks or longer depending on the condition.  Another technique is to soak a gem in warm water charging the liquid, making it an effective irrigator for sick plants.

    For potted plants, place crystals into the soil or when re-potting place, a gem in the bottom of a pot.

    Look for gems that reflect the colors of water, earth, and sun or the stars.  You can store the collection in a pretty bowl placing them next to a fountain, aligning them in a windowsill, or place them in the ground.

    Use the right size gem for the task at hand.  Example small container, small gem, small plant; a small moss agate for an orchid is perfect.  If a plant is struggling health wise, a larger stone may bring more vitality and strength to the plant.  Larger stones are important if your sacred space is near power lines or electrical equipment with EMF (Electric Magnetic Fields ).

    The field of Geobotany explores the natural relationship between plants and crystals.  Lychinis alpina, found under these common names (Arctic Campion, Alpine Campion, Alpine Catchfly) is a small plant with pink flowers, indicating copper deposits.  A shrub named Haumaniastrum katagense is found nearby depending on its location.  Diamonds and Pandanus candelabrum, Chandelier Tree are another example.  This screw palm with spiny thorns grows just above sites where diamonds are located.

    Another example is quartz, jasper and agate that are excellent choices and are hardy enough to endure the watering without damaging the crystal.  Clear Quartz raises vibrational energy and working with amethyst become super healers.  Apatite when partner with citrine and peridot works well on quince production.

    Amethyst is a great partnering gem working with sage, blueberries, lavender and basil to increase food production levels and often bumper crops.  Or with lepidolite enriching purple plants (lavender, purple sage, plums, eggplant, etc.) in their health and color.  And yet another example is partnering with green calcite for stressed and anxious plants.  Place them in the soil around the roots and bless them with healing energy.

    Set up a bowl of tumble crystals of amethyst, tourmaline, quartz, and moonstone as a gift to earth elements.  Dig a shallow hole and place your crystals within the dirt where they make direct contact with the plant’s roots.

    To add sparkle, scatter quartz chips on the ground. The sparkling may confuse predatory insects.

    Many stewards wear or carry their favorite gem on their person while performing the tasks related to sustaining their sacred space.  Jet when wore partners with plants to make them flourish.  More direct ways to use crystals and gem in harmonious partnership with plants can be through bury a crystal in the middle of your sacred space.  Place crystals at the four corners of a specific area to ward off pests, disease or bring calm to the plants.

    From Feng Shui practices the crystals quartz, rose quartz, amethyst, and tiger eyes all help in protecting and stopping weeds.  Some of these crystals are said to protect your sacred space from large scale disasters.

    Thank them for their service.


Edinburgh to Stirling distance by car and plane

What is the Edinburgh to Stirling distance? To answer the question and find out how far is Edinburgh from Stirling you need to check out the map below and look up the table. Driving distance from Edinburgh to Stirling is 0 miles or 0 km by car. Check out straight line distance if you are taking the flight. How long does it take to get from Edinburgh to Stirling? Approximate time of driving is .

Drive distance
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See the return route - Distance from Stirling to Edinburgh

How far is Edinburgh from Stirling?

To get to your destination, please, use the map with marked route for your trip. To see more distances you can use mileage calculator box at the top of the page. Go to weather in Stirling today and tomorrow to find out about conditions for your upcoming trip.

Book a Hotel for your trip to Stirling

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Code of Conduct

Amazon Nook Kobo
Apple Books

1999 Philip K. Dick Award Nominee

 Original Mass Market Cover by Jean-Pierre Targete

code of conduct cover

Reissue cover by Dave Smeds

Publisher’s Weekly, Nov. 8, 1999

“I’ve seldom come across a novel more complex, with so much depth and so much to offer. CODE OF CONDUCT is a must-read.”
– Barnes and Noble’s EXPLORATIONS newsletter

“Remarkable! This extraordinarily solid first novel succeeds on many levels. Like Le Carré at his best, Smith creates a complex and deftly shaded background populated with vivid, memorable characters–a universe of power politics, commercial and political espionage, and personal and impersonal relationships. The hard-edged story of nested loyalties and treacheries between humans and aliens kept me enthralled to the very end. CODE OF CONDUCT is a novel for adults who have lost their illusions but not their love of story.”
-Elizabeth Moon, Hugo-nominated author of Remnant Population and Once a Hero

“Finally! CODE OF CONDUCT gives SF fans who demand strong characterization something wonderful to read when there’s no new Bujold or Moon novel. In Jani Kilian, we have a heroine both ruthless and curiously compassionate, a woman who has survived tragedy and may yet redeem humankind. And there’s a bonus–the most fascinating alien culture since C. J. Cherryh’s Foreigner. More Jani! More Tsecha! More Kristine Smith!”
-Katharine Eliska Kimbriel, author of Night Calls

“Kristine Smith tells a fascinating story that weaves intrigue, politics, and personal honor into a sophisticated tapestry. With well-realized characters, both human and alien, and a plot full of gratifying twists and turns, CODE OF CONDUCT showcases a fine new voice in the field of science fiction.”
-Catherine Asaro, double Nebula Award nominee for her novel The Last Hawk and her novella Aurora in Four Voices, author of The Veiled Web

 About the book:

Pharmaceutical R&D is an interesting field. While I don’t work in it, the field of pharmacogenomics, or the tailoring of drug design and therapy to the genetic makeup of the patient, interests me greatly.

The ruminations snowball…what happens if someone’s body chemistry alters to the point that formerly benign substances become poisonous? How does that person react? How do the physicians who have to attempt to treat this person deal with their lack of ability to do so, in an age where the knowledge base is so deep and broad that the question of “how to treat” has not been considered an issue for quite some time?

To take it one step farther…what if that person’s condition does not remain static, but changes constantly? What if, just when you think you have their treatment under control, they develop some other idiosyncratic condition? How do you hit the constantly moving target?

* * *

Jani Kilian has, in one form or another, been stewing in my backbrain for 8 or 9 years. I initially planned to portray her in a series of short stories. She was much less sympathetic back then, a drug-addicted sociopath whose never-ending quest to sate her various hungers led her into the paths of unsuspecting innocents. Sometimes, she helped them, as long as there was something in it for her.

As the ideas grew to novel-length, I realized someone might be able to turn a completely unsympathetic individual into a series centerpiece, but that someone wasn’t me. Slowly, Jani evolved into a conflicting combination of survivor guilt, hair-trigger survival instinct, and protectiveness toward those she considered ‘under her wing.’ She’s capable of heroic acts, but she’s not a heroine.

* * *

Because of CODE’s mystery aspects, I originally tried to set the story in London, England. Blame the influence of Sayers and Christie. But after failing to create a sound sense of place, I realized I lived quite close to a fine location, and one, since the story is set in the future, which I could rework at will.

Some parts of Chicago will seem familiar. I enjoyed preserving place names: O’Hare, Boul Mich. Substituted “The Parkway” for North State Parkway, and consolidated most of the North Shore into “the Wilmette Bluffs.” Reopened Fort Sheridan. It’s fun when it’s your ball.

Read the first chapter of CODE OF CONDUCT.


Speculator Sam
RE: some training question
That'll work for a while and boost your aerobic capacity and 5k-10km times for about a month or too. Eventually, you'd have to improve your lactate threshold and your mitochondria count in order to continue to make progress. This classic formula will never cease to improve long term when done 2-4 months at a time with some form of deloads and off-seasons throughout the year.

Long run of 1/4-1/3 weekly mileage
some form of intervals at roughly 800m-1mile pace at least once every two weeks
some form of longer intervals at 5km pace at least once every two weeks
some form tempo running at least once every two week

The balance of these will change depending on the time of the year and what race you're training for but even marathoners will run 3km/2mile pace and 1mile pace in a workout, even if the mile pace running is limited to 3 x 10sec. strides during an easy run. Also depends on your goals, what kinda improvement are you looking for, stamina or speed for a particular race distance?


National Volunteer Week 2018 – Lynda Johnson

Branch: Quarry Park

Name: Lynda Johnson

Position: Reception/Front Assistant

Number of Years Volunteered: 2

Number of Volunteer Hours in 2018: 28

How has the nominee been a YMCA Calgary Ambassador?

Lynda has always been a true ambassador for the YMCA. She knows what the YMCA’s values are and she demonstrates these values, not only when she is here, but in her life daily.

How does the volunteer engage in the YMCA Calgary Community?

Lynda always has a smile and greets everyone. Everyone expects to see her when they arrive on Tuesdays. She is a part of our family.

How has the nominee built positive relationships?

Lynda always has a smile for everyone. She interacts with staff and families alike. She makes people feel welcome and at home. Lynda takes on any task that needs to be done.

Lynda is always willing to help with anything, and with very short notice, if necessary. She has offered to come in and put in extra time if we need her. We rely on Lynda and we know she will be there for us.


What could cause a tsunami along the Grand Strand?

MYRTLE BEACH, SC (WMBF) – Devastating tsunamis have struck around the world, leaving those along the Grand Strand to wonder if the area is at risk, too.

The Grand Strand knows its vulnerability from tropical storms and hurricanes, but buried deep in the area’s past is evidence tsunamis have also impacted the region.

There are records from the not-too-distant past to show that tsunamis have impacted the East Coast.

“Yeah, you might not think that having a tsunami on the East Coast is something that could happen, but there have been records of past tsunamis along the Carolinas,” said Steven Pfaff, with the National Weather Service. “As recently as 1929, there was a tsunami that impacted Nova Scotia and Newfoundland.”

Research shows a few likely areas where a tsunami could be generated that could reach the Grand Strand.

An underwater landslide off the North African coast, or an earthquake or landslide in the northern Atlantic could both send tsunamis toward the Grand Strand, but the greater and most likely threats lie a bit closer to home.

“Yeah, the deepest part in the Atlantic basin is the Puerto Rico Trench and that has a history of tsunamis in the past causing submarine landslides and causing a tsunami like Indonesia, where there’s plate tectonics involved,” Pfaff said.

The Puerto Rico Trench is 1,200 miles away and an area where two of earth’s plates are pushing against each other. It’s a hotbed of earthquake activity.

Most of those earthquakes are weak, but scientists believe that a magnitude 9 quake in that area would be large enough to send a tsunami toward the Grand Strand.

An earthquake that large would displace tremendous amounts of ocean water and send large waves quickly out into the Atlantic. Like a ripple on a pond, those waves would travel outward until eventually reaching the Carolina coast in a fairly short amount of time.

Something coming from the Puerto Rico Trench would take us a few, maybe six hours, before it reaches parts of the Southeast United States,” Pfaff said.

The waves generated by an earthquake in the Puerto Rico Trench could be as small as 2 feet, or as large as 10, but tsunami waves don’t act like regular waves that crash on local beaches every day. They move fast and carry a tremendous amount of energy.

Even if it’s just a small tsunami, a 2- or 3-foot run up from that, with it moving so fast, anyone that was caught on the beach, they’d be knocked down, potentially carried out into the ocean or slammed into piers and other things,” Pfaff said. “It’s a hazard that is real.”

However, there’s another threat area that is just offshore.

“The one that concerns me the most is something that would be a submarine landslide off the continental shelf and slope just off our coast,” Pfaff said.

A submarine landslide, or a landslide that occurs under water, has happened many times before and right offshore. Once past the shallow waters of local beaches, the ocean bottom drops off very fast.

It’s along that slope and into the depths of the open ocean where these landslides can occur.

“All it’s going to take is a little earthquake in the continental slope offshore and that might trigger the next submarine landslide and now we’re going to be dealing with a tsunami warning as a result,” Pfaff said.

Recent studies from the U.S. Geological Survey modeled a large underwater landslide off the Outer Banks of North Carolina.

The simulations revealed waves as high as 18 feet on much of the North Carolina coast, and over 10 feet on the South Carolina coast. A tsunami generated that close to home would arrive in a short amount of time.

“If it’s a submarine landslide just offshore, it would be about one to two hours before it moves in, so we have time to issue the warnings,” Pfaff said.

One of these landslides would most likely be triggered by an earthquake nearby or just offshore.

“I think any earthquake we have in the coastal areas, especially just off the coast, that’s one we’re going to have to pause and make sure and listen for watches and warnings in case we need to take action,” Pfaff said.

The Charleston Earthquake of 1886, a magnitude 7.3, likely generated a landslide just off the Florida coast that resulted in a small tsunami there. As recently as 2002, magnitude 4.3 and 3.8 earthquakes occurred just 15 miles offshore of Charleston.

While the threat of a tsunami off the Grand Strand’s coast is low, it is one that does not go unnoticed.

“If we prepare for a terrorist attack in Myrtle Beach, we need to be preparing for a tsunami event in Myrtle Beach,” Pfaff said. “They’re both very low-probability scenarios, but when it does happen, it could be high impact. “So, we can’t disregard tsunamis.”

The threat is real enough that local and state governments have a plan in place.

“We had a tsunami drill last year and the year before, where we tested communications from the state level down through the counties and the coastal communities that was very successful,” Pfaff said. “So having that plan in place that has everybody going in the same direction when that event does occur, and the main intent of that is to keep everyone safe and off the beaches when a tsunami does threaten.”

All the cities along the Grand Strand are certified tsunami ready, meaning they have a comprehensive plan in place for when a tsunami may strike.

“We just don’t know. Is it going to be two days, two hours from now or 2,000 years from now? Pfaff said.

Copyright 2017 WMBF News. All rights reserved.


Hungry Earth

School transmutation; Level druid 5, sorcerer/wizard 5, witch 5

Casting Time 1 standard action
Components V, S

Area 20-foot-radius spread
Duration 1 round/level
Saving Throw none; Spell Resistance no

The ground attempts to pull creatures beneath its surface as if hungry for the flesh of mortals.

Immediately, and at the beginning of each of your turns, every creature touching the ground within the area of the spell is the target of a grapple combat maneuver. Creatures that enter the area of effect are also automatically attacked. The ground does not provoke attacks of opportunity. The earth’s CMB is equal to 5 + your caster level for the purpose of this combat maneuver check.

Attempt the combat maneuver check only once each round and apply the result to all creatures in the area of effect.

Each time the ground succeeds at a combat maneuver check to grapple a foe, it drags the creature farther down, eventually forcing the creature below its surface. With the first successful check, the target gains the grappled condition. Grappled opponents can’t move without first breaking the grapple (doing so requires a successful DC 20 combat maneuver or Escape Artist check). The ground receives a +5 bonus on combat maneuver checks to grapple opponents it is already grappling. After the second successful grapple combat maneuver check, the grappled creature is pulled to the ground and becomes prone. On the third successful grapple combat maneuver check, the creature is fully buried and must hold its breath or begin suffocating.

A buried creature can’t attempt to escape unless the effect ends or it breaks the grapple. The DC to escape the grapple increases to 25 for a creature that has been pulled beneath the earth.

Section 15: Copyright Notice


Preachers and their Esoteric Language

Preaching PulpitThousands of people who do not know Jesus Christ attend church each week. Most of these people never received the christianese Sunday school training that began with large felt boards. As preachers deliver their messages and the members back-slap each other with approval, many of these visitors walk away without any clearer understanding of Jesus Christ. Further, many preachers deliver sermons where once Christians concepts have morphed into meaninglessness.
How do I know this? Each week I visit a new church for a column I write, Sheep & Goats, for the San Diego Reader. So I hear a variety of preachers exercising their gifts of gab. Certainly my experience is not an exhaustive research, but it is through these sermons that IÄôve heard the preaching of christianese without Christ.
Let me give you two examples. Last month, I listened to a preacher at an emerging church speak about ‘rebuilding our faith’. This preacher spoke for 45-minutes, sharing stories, speaking about TV shows and discussing his life. Through the sermon faith was never defined. The preacher spoke about rebuilding faith in relationships, in hope and love. There was never a mention of ‘faith in Jesus Christ’. There was never a mention of the gospel. The sermon ended up preaching a faith in whatever the listener intended with or without Jesus Christ.
The very next week a mainline denomination preacher spoke about hope. This sermon hinged on many Christian ideas. Comments, such as “Jesus provided a way for all people out of darkness, cold and misery” were the extent of communicating Jesus work on Earth. The preacher never connected Jesus providing hope with his salvific work conquering sin and death. Christianity became a philosophy of self-help to have hope in this life, regardless of a saving relationship with Jesus Christ.
In all fairness, as an occasional preacher, I confess I also do this. We all can easily fall into our linguistic auto-pilot and drop words like ‘faith’, ‘hope’, ‘salvation’, ‘cross’ and ‘Jesus’ without explanation. A sermon would end up being really long if we had to define every word and concept we brought in. This is not my biggest concern. What concerns me more than defining every term is that we use these terms out of context. If we are preaching messages on hope in a better world, faith in our friendships, being saved from foolish decisions we are no longer preaching Christ. Certainly a saving relationship with Christ and an obedience to follow the path he walked before us will make this world better (not in a materialistic way), our friendships more important (not necessarily easier) and correct bad decisions, but is this why Jesus came? My encouragement is that we return to the joy of our salvation. If you are a preacher, preach a Jesus Christ that conquered sin and death, and now sits on a throne in heaven from where he will return to earth and establish an eternal kingdom. Preach a Christ that allowed us to have a relationship with the creator and sustainer of the universe, God. This should give us hope and build a faith in us that we can be passionate about!
Note: I would clarify that the primary purpose of preaching in service is to equip Christians (Eph 4:11) for the work of the ministry not to evangelize the lost. Yet, how will sinners hear the message unless a preacher is sent…


Draft - send us your comments and additions

Roads and road transport

In the 17th and 18th c. all over Europe new roads and bridges began to be built, often based on Roman designs, without much useful innovation in road building. Many however were not laid out for industrial and commercial, but rather for military purposes.

In the last half of the 18th century the fathers of modern road building and road maintenance appeared in France, with Pierre-Marie-Jérôme Trésaguet (1716-1796 ) and in Britain Thomas Telford (1757-1834) and John Loudon McAdam (1756 - 1836).
The actual process of road building has changed dramatically over the past century, going from large gangs of workers with picks and shovels to enormous specialized machines.

Beginning in the 1840s, the rapid development of railroads brought the construction roads to a virtual halt. For the next 60 years, road improvements were essentially confined to city streets or to feeder roads to railheads. Many rural roads became impassable in wet weather.

The situation changed again when motor cars and bicycles appeared.
Predecessors of the bicycle, the 'draisines' and 'velocipedes' appeared between 1817 and 1820, the high-wheel bicycles in the 1870s, and the first 'safety bicycles' in the 1880s and 1890s. In 1870 Siegfried Marcus built the first gasoline powered combustion engine, which he placed on a pushcart, and in 1885, Karl Benz developed a petrol or gasoline powered automobile.
The owners of the first 'cars and bicycles were rather wealthy citizens from the higher classes of society wanted to drive on safe and comfortable surfaces - which influenced road building. Later the new forms of moving around changed the lifes of all classes.

Canal du Midi

harbourboat lift.

Canals and harbours

While travelling and transporting voluminous goods on muddy and rough roads, for a long time in coaches and carriages withouth suspension, was neither comfortable neither efficient, barges on rivers offered the best solution till the mid 19th c. Water transport of goods and raw materials was also several times cheaper and faster than transport overland.

The first artificial canal in Western Europe was the Fossa Carolina built at the end of the 8th century under personal supervision of Charlemagne. Canal building was revived in this age because of commercial expansion from the 12th century especially in the flat, highly populated and industrious County of Flanders and adjacent regions - where before the  the first canal networks connected towns and economic centres. The Lieve-canal, connecting Ghent with the Scheldt and the North Sea was dug between 1251 and 1269.

The heydays of the European canals started in the 17th and 18th centuries when various countries were developing their internal trade. Most famous were the Briare Canal connecting the Loire and Seine (1642), and the Canal du Midi (1683) connecting the Atlantic to the Mediterranean, which included a flight of 8 locks at Béziers, a 157 metres (515 ft) tunnel and three major aqueducts. Canal building speeded up during the first decades of the Industrial Revolution Impressive lock systems, canal tunnels and aqueducts, boat lifts and waterway infrastructures were built. Canal building slowed down when railways became their main competitors.- but on the continent canal development never ended. A proof is the plan which is now being carried out to connect Seine and Scheldt via an inland waterway.

From the second half and especially since the last quarter of the 19th c. one saw an impressive growth of sea harbours and transport by sea between the continents

Canals and harbours have an important heritage to put into the focus - not only ships and boats in museums or safeguarded by associations and individuals, but also all the civil engineering connected to them, bridges, canal tunnels, boat lifts, locks and lock keeper's houses, quays, warehouses, harbour cranes, shipyards,...

Stephensonsteam locomotivetram

Wagonways (or tramways), with wooden rails and horse-drawn traffic, are known to have been used in the 1550s to facilitate transportation in mines. In 1784 James Watt patented a design for a steam locomotive, and in the same year his employee William Murdoch produced a working model of a self-propelled steam carriage.
Twenty years later Richard Trevithick built the first full-scale working railway steam locomotive and on 21 February 1804, his locomotive hauled a train in the Penydarren ironworks, near Merthyr Tydfil in South Wales. He also showed his  engine, the Catch Me Who Can, on a piece of circular rail track in London, but because of it weight it never got a practical use.
From 1814 onwards George Stephenson, experimented with steam locomotion on rails. In 1825 he built the ‘Locomotion’ for the Stockton and Darlington Railway , and in 1829 the Rocket
Six years later, on May 5th 1835, the first passenger railway on the continent was opened between the Belgian towns of Brussels and Mechelen.
In 1850 most of the European countries had established railway connections.
The first railway in Germany opened on December 7 1834 between Nuremberg and Fürth, the Bavarian Ludwigsbahn. The first passenger steam railway in France, the Paris-Saint Germain Line dates from 1837. The Netherlands (between Amsterdam and Haarlem) and the Kingdom of the Two Sicilies (between Naples and Portici) got their railway in 1839, Poland in 1844v (Warsaw - Pruszków), Hungary 1846 (Pest - Vác), Spain 1848 (Barcelona-Mataró),...
On November 6th 1842, a first train crossed a border by rail between Mouscron (Belgium) and Tourcoing (France), which was a part of connection between Lille, Ghent and Antwerp. In
1846 the first international railway connection between two capitals, Paris and Brussels, was established.

Transport on rails, trains, trams in towns, underground lines,... marked the transport revolution of the 19th century and left us an impressive heritage of railway stations, old and derelict lines (now sometimes 'green corridors'), bridges and tunnels, and the engines, wagons and tools in museums and kept alive by hundreds of volunteers on heritage and tourist railways

Blériot 1909

Concorde 1989

In the air and in space

On November 21, 1783 Pilâtre de Rozier and the marquis d'Arlandes were the first people to take off in a hot-air balloon. The balloon stayed in the air for 25 minutes, glided over Paris and made a smooth landing 8 kilometers further.
This had the same importance as the first gliding flight of Otto Lilienthal (1891), the first flight with a motor-powered aircraft by Orville Wright (1903) and the first human in space (Yuri Alexeyevich Gagarin, 12 April). 1961).

In Europe, many aeronautic  experiments were also conducted at the beginning of the last century to take off with aircraft heavier than the air, including Robert Esnault-Pelterie and Léon Levavasseur in France, and by S.F. Cody in Britain. In 1905, the Voisin brothers built the first aircraft factory in Billancourt, France. On September 25, 1909, a first international aviation exhibition took place at the Grand Palais in Paris, organized by the new 'Chambre Syndicale des Industries Aéronautiques'.

It was the beginning of an aviation industry.
Today aeronautics is one of the EU's key high-tech sectors on the global market, providing more than 500,000 jobs and generates a turnover of close to EUR 140 billion (in 2013). The EU is a world leader in the production of civil aircraft, including helicopters, aircraft engines, parts and components.

But in those early years flying was a privilege for the rich upperclass - the same people who before could afford a bike and a car. The first associations of aviation pioneers arose in the salons of the Automobile Clubs ... But flying was not a ‘sport’ for long.
Aircraft and airships, the Zeppelins, acquired a strategic role during the First World War. On the night of 2 to 3 September 1916, London suffered a major air strike. Sixteen German zeppelins,  one of which was shot down by a British plane, aimed military and industrial targets around the British capital.

After the First World War, aeronautical technology developed rapidly, and the aircraft gradually evolved into an all-in workhorse for long-distance connections, for mail, goods, and passengers.

On April 3, 1925, a three-engine biplane Handley-Page, nicknamed "Princesse Marie-Josée" landed in Kinshasa (then 'Leopoldville') and completed the first fligth between Brussels and Congo. The aircraft left Brussels in mid-February and completed its journey under the command of Lt. Thieffry in 75 hours or flying time (over 50 days). Today it takes 8 hours...
Charles Lindberg flew on May 20 and 21, 1927 with his 'Spirit of St. Louis' as the first pilot solo and non-stop from New York to Paris - today this takes about 7 hours.

Antoine de Saint-Exupéry's ‘Vol the Nuit’, about the heroic air mail pilots in South Amzerica was published in 1930.
During the Spanish Civil War, German and Italian aircraft that supported Franco were often decisive. On April 26, 1937, Guernica was bombed. The battle in the air was decisive for during The Battle of Britain (July-October 1940). Civilians suffered bombings during the German Baedeker Blitz (April-May 1942) who wanted to destroy British historical monuments - as a revenge on the Royal Air Force's (RAF) bombing offensive and the bombing of Lübeck in March 1942. Dresden was devastated by the Allied air raid of 13 and 14 February 1945...

In Casablanca the cult film of 1942 with Humphrey Bogart and Ingrid Bergman, airplane connections play an important role - even in war time.

During the Second War, the V1 and V2, ,the first rockets, were developed in Peenemunde  a technology that Werner Von Braun took with him to the United States. The Atlas rocket, which launched the first Mercury capsules in space, was designed in 1950 for the American Air Force by the Flemish emigrant Karel Jan Bossart.
In 1973, after long-term discussions between France, Germany and the UK, 11 European countries decided to jointly to establish the European Space Agency (ESA). Ariane's maiden flight took place December 24, 1979 from the Guiana Space Center at Kourou, French Guiana.


Materials used to slow the transfer of heat or cold through walls, reducing energy costs and maintaining a consistent temperature.

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Mentioned in these terms

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The Nature of Things implies the dualities of the physical, elemental state of nature, and the spiritual, metaphoric, and contemplative nature. I am intrigued by the mysterious and sometimes humorous similarity of structures, from the microscopic to the macroscopic, found in biology, botany, geology, and anthropology. My work is symbolic of the cycles of life, of the elements, and of the forces of growth, change, and evolution. It alludes to the passage of time, petrified in stone or concrete. Lines become blurred and distinctions ambiguous between fossil and artifact, natural history and cultural history, and the present, past and future.

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Salamandastron, under the guardianship of old Lord Stonepaw, is under threat from an enemy of immense and terrifying power. Ungatt Trunn, the wildcat who can make the stars fall from the sky, has attacked with his Blue Hordes and is determined that the fortress should be his. The mountain's defences are weak and it seems that nothing can stand in his way. Nothing, that is, but the badger Lord Brocktree, who is drawn to Salamandastron by an undeniable sense of destiny. But if he is to rescue the mountain from Trunn and his verminous hordes, he must gather about him an army capable of defeating them in battle. Together with the irrepressible haremaid, Dotti, and a host of brave creatures, Brocktree journeys to Salamandastron to fulfil his destiny. A captivating blend of heroism and adventure set against a backdrop of the legendary mountain fortress of Salamandastron.
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