Observations from Dressing in Drag for Halloween

I published an article to Medium and on my Facebook page about the three times I dressed in drag for Halloween.

You can read it this link, free access to anyone who wants to read. 

tldr

• Women interact with you differently when you are in drag. 
• It was fun being someone I was not. 
• Women work hard at being beautiful. 
• Compliments are always welcome. 
• Nothing is too weird, especially on Halloween.
• No one is truly normal. 
• Everyone is different, and it is our differences that make us interesting and unique.

If there is something you want to do but worry about what other people would think or you think “No way I can do that,” do it any way. You might be surprised that doing something out of the ordinary for you is very ordinary and fun.

An Experiment

 I admire and respect wordsmiths – songwriters, authors, essayists, poets, columnists, playwrights, raconteurs, storytellers – anyone who uses words to express and share their experiences and emotions.

Writing anything longer than a quip or brief anecdote is difficult for me. For example, drafting this brief post took me over 10 hours.

One factor is my ADD. Whenever I try to write about something, my mind races in fifty directions. I can craft a well-structured draft in my head quickly. When it comes time to put it on paper or screen, all hell breaks loose. New ideas, some complimentary many unrelated, pop up. I start editing even before I write the thought. Somewhere there is a dam between my mind and my hands that blocks 90% of the words I want to write.

It was easier for me to write before laptop computers and the Internet. I would find a quiet room with a big table, spread out my notes, turn on some music, and write. Pretty straight forward. The books on the wall in the library didn’t distract me. If I really wanted to focus, I would go to a library where I didn’t know anyone. The Fondren Library at Rice University and the Architecture and Planning Library in Battle Hall at the University of Texas.

To write, I need a purpose and an audience. Once I reach a level of emotional charge that I must share with someone, words will flow freely from me onto the page. Often, the emotion I need to write is anger, disappointment, or frustration. I want to broaden that inspiration to write to include more positive emotions.

Though I enjoyed writing when I was younger, I never kept a journal. Difficult for me to share my inner thoughts, even with myself. Placing those feelings on paper made them more tangible. I have tried journaling, but without much luck. Whatever I write is an incoherent cluster of words. Typically, nothing longer than a three-word phrase. If you ever read my journal, you will question how I graduated high school.

I am not comfortable being vulnerable. I am a private person, raised in southern stoicism. Limited physical displays of affection, rare compliments, no tears, no loud laughter or anything that could draw attention to yourself. For those who follow astrology, I am a classic Cancer.

I am undertaking a radical experiment. One which terrifies me. Over the next few months, I will be posting more detailed thoughts on Facebook. Not because I am a narcissist (of course, that is what a narcissist would say) nor to be brave. But to find myself, free many of the thoughts trapped in my mind, and to exercise an efficient and effective writing style. Some topics will be personal, others will be about things that interest me. There may be a poem.

Let me know any topics or subjects you would like for me to write about. When I do post something, I will appreciate your comments and feedback. If there is anything you would rather share privately than in the comments, DM me.

Thanks, and hugs to you all.

Bullying

Bullying. The toxic culture that has developed over the past decade has caused me to think deeply about the subject recently.

I was bullied often while growing up. Most was verbal, some intimidation, very little physical violence. Over fifty years later, I remember my bullies’ names and have a visceral response of fear and hatred when I think of them.

I have also been a bully. Primarily teasing which crossed the line to cruelty. Looking back on when I have bullied people, I am disappointed in myself. I know I am a better person than that. As my wife often tells me she “didn’t marry an asshole.” There are times when she is wrong.

I hope those who were the subject of my bullying will forgive me. Ironic, since I cannot find it in my heart to forgive my bullies. Let me know how I hurt you and I will do all I can to make amends. Know that I am truly sorry for being mean to you.

I post this not to seek affirmation or absolution, but to ask for your help. When you see me write or say something mean-spirited, publicly call me out. Let me know you expect better of me. With your help, I hope to become a better person. Thank you.

Yes, the Best Seafood Restaurant in Texas is in Port Aransas

When I read the Redbook article claiming Ceviche Ceviche was the best seafood restaurant in Texas, I had two thoughts - no way (I was wrong) and we need to try it (we did).

The owners follow an important business precept - do one thing and do it well.

The restaurant I visited is located in a nondescript strip mall along Queen Isabella Boulevard. A second is located in South Padre Island. 

Menu is above the counter. You have two sets of options - protein (Mahi Mahi, shrimp, mix, poke tuna, or shrimp cocktail) and toppings (including veggies, savory, sweet, and spicy. The restaurant provides a list of 5 suggested mixes of toppings. We had the Classic - tomato, onion, cilantro, and avocado

After you place your order, you watch the staff assemble your ceviche. Chop up at least 8 ounces of toppings, chop 4 ounces of denatured fish and shrimp, mix the two piles together with gloved hands gently rolling the mixture, squeeze three limes on top, then transfer to a 8×8 clamshell takeout container for the customer to take home.

The amount of food is a feast for two adults. The ceviche was exquisite. The only thing I will change next time is replace the avocado with jalapeño for a little more kick and maybe add mango for some sweetness to counterbalance the spice and acid. For those who like their food really spicy, Ceviche Ceviche also offers Serrano and Habanero pepper as toppings.

Conclusion - this little hole-in-the-wall takeout ceviche only restaurant in the beach town of Port Aransas is one of the best seafood restaurants in Texas and the United States.

Ceviche Ceviche, 1004 Padre Blvd H1, South Padre Island, TX 78597, (956) 772-1555

The United States Could Have Saved over 150,000 Lives if it had Implemented more Stringent COVID- 19 Preventive Measures

Our World in Data recently released an article titled "Which Countries have Protected Both Health and the Economy in the Pandemic?" Some people have claimed that during the COVID‑19 pandemic countries face a trade-off between protecting people’s health and protecting the economy.  Joe Hasell, a Research Project Manager at the Oxford Martin School, considers the validity of the assumption in this article.

He does so by comparing countries' COVID-19 death rate with their latest GDP data. He finds there is no sign of a health-economy trade-off. Countries that have managed to protect their population’s health in the pandemic have generally also protected their economy.

He found that countries which suffered the most severe economic downturns were generally among the countries with the highest COVID-19 death rate. Conversely, countries where the economic impact has been modest managed to keep their death rate low. The United States is an outlier to these findings. It's rate of COVID-19 deaths per capita is between five to 10 times higher than countries with similar declines in GDP.

The dataset reviewed in the article included data for all countries which COVID-19 death rates and GDP. I believed a more relevant evaluation would how the United States performed compared to other countries with “advanced economies.”  

The World Economic Outlook (“WEO”), a report presented by the International Monetary Fund, classifies countries into two groups – advanced economies, and emerging and developing economies. The criteria the WEO to classify the world by economic development “are (1) per capita income level, (2) export diversification, … and (3) degree of integration into the global financial system.”[1] Currently, the WEO classifies 40 countries as having advanced economies, including the United States, Australia, the United Kingdom, and South Korea.[2]

The chart above compares the COVID-19 death rate for countries with advanced economies to their economic performance in Q2 2020. The dataset considered in the article included 23 advanced economies.[3] Belgium, Sweden, and the United States are outliers. These countries have significantly higher number of COVID-19 deaths per capita as compared to countries with similar economic decline.

The trend line is the relationship between economic decline and COVID-19 deaths for 20 advanced economies, thus excluding the three outliers. The trendline’s correlation coefficient is .656. As a result, the inverse relationship between economic decline and deaths per capita from COVID-19 is high. The trend line’s standard error of estimate is 131.56. 

The model estimates that the United States with a Q2 2020 GDP decline of 9.5% should have experienced about 116 deaths per million population as compared to an actual death rate of 552 per million population. The difference between the expected number of deaths and actual number of deaths in the United States is statistically significant. Based on data as of September 5, 2020, if the United States had implemented programs to contain the virus similar to countries like Japan, South Korea, Israel, and Germany, the United States would have experienced almost 152,000 fewer deaths from COVID-19 without any additional harm to the economy.[4]

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[1]   World Economic Outlook – Frequently Asked Questions

[2]   A full list can be found in the table “Advanced Economies” in the World Economic Outlook – Frequently Asked Questions referenced in footnote 1 above.

[3] Austria, Belgium, Canada, Czech Republic, Denmark, Finland, France, Germany, Israel, Italy, Japan, Latvia, Lithuania, Norway, Portugal, Singapore, Slovakia, South Korea, Spain, Sweden, Taiwan,United Kingdom, and the United States.

[4] Worldometers.info reports that as of 12:00 am GMT, September 6, 2020, the United States had 192,818 deaths from COVID-19. https://www.worldometers.info/coronavirus/country/us/, retrieved September 6, 2020.

Using k-Means Clustering to Identify Locations to Visit that are Similar to the Houston Heights

 

Introduction

My wife and I retired 5 years ago. We got rid of 99% of our stuff, sold our house, and bought a fifth wheel trailer to travel the United States and Canada with our two pugs, Pancho and Lefty. Over the past four years, we have visited over one hundred locations, generally spending between four to seven days at each stop. While it has been an amazing ride, we are starting to think about where we might want to settle down. By settle down, we mean to continue living in the 5th wheel but stay in a location from one to three months.

Earlier this year, I began taking classes on Coursera to qualify for the IBM Data Science Professional Certificate. The certification program consists of nine courses which cover a variety of data science topics including: open source tools and libraries, methodologies, Python, databases and SQL, data visualization, data analysis, and machine learning. The final course is a capstone project where the student applies the skills they developed in the previous eight courses. For my capstone project, I decided to identify locations Deb and I had not visited but that we might want to spend at least a month.

Before we retired, we lived in a neighborhood called the Houston Heights in Houston, Texas. We loved the area because of its convenient location (less than 5 miles from Downton), the friendly neighbors, and the neighborhood’s eclectic and quirky shops and restaurants.

For the project, I elected to find areas in the United States with RV parks that are like the Houston Heights neighborhood we lived in. The criteria we defined is areas with RV parks that are less than 60 miles from a Costco Warehouse and have similar venues as our old neighborhood within a 5‑mile radius. We keep all our prescriptions with Costco pharmacy and like to visit Costco at least once a month to buy bulk supplies. The 5‑mile radius allows for a short drive to local venues.

Data

I relied on three primary data sources to identify RV parks within 60 miles of a Costco Warehouse and located within the contiguous 48 United States in areas like the Houston Heights.

·         Costco_USA_Canada.csv, a list of Costco Warehouses located in the United States and Canada. I found this dataset on POI Factory

·        GoodSam.csv, a list of campgrounds in the United States and Canada that offer discounts to members of Good Sam Club. I found this dataset on POI Factory

·         Demographic data from the Census Bureau's American Community Survey 5-Year Data (2009-2018) (“ACS”).

The datasets for the location of RV Parks and Costco Warehouses included Zip Codes. However, the dataset for Census data used ZCTA as key. To insure all three datasets were based on the same key, I used the US Zip Codes Database provided by Simple Maps to cross reference the ZCTA selected in the demographic analysis to the related Zip Codes, and modify the Census Bureau dataset to present Zip Codes instead of ZCTAs.

To identify which locations are most common with the Houston Heights, I compared the 5 most popular venues within a five-mile location of the center of each zip code. Data for each zip code was provided by Foursquare, a social location service that allows users to explore the world around them.

Methodology

Good Sam RV Parks Dataset

My first step was to remove from the Good Sam RV Parks dataset any RV Parks outside of the 48 contiguous United States and any entries that did not have location data, such as latitude, longitude, city, and state. The GoodSam.csv dataset consisted of four columns – “Latitude”, “Longitude”, “Description”, and “Address”. To make the dataset usable for my analysis, I disaggregated the Description column and the Address column. I divided the Description column into two columns named ‘Park Name’ and ‘Location’, then eliminated the Location column as its data was partially redundant with data derived from the Address column. I divided the Address Column into five columns titled “Address", "City", "State, “Zip", and "Phone Number”. Upon completion of my data preparation, the Good Sam database included 2,216 unique RV Parks located in the 48 Contiguous United States.

Costco Warehouse Dataset

I removed from the Costco Warehouse Dataset all Costco Warehouses located outside of the 48 contiguous United States and any entries that did not have location data, such as latitude, longitude, city, and state. Similar to the GoodSam.csv dataset, the Costco_USA_Canada.csv dataset consisted of four columns – “Latitude”, “Longitude”, “Description”, and “Address”. To make the dataset usable for my analysis, I disaggregated the Description column and the Address column. I divided the Description column into two columns named ‘Park Name’ and ‘Location’, then eliminated the Location column as its data was partially redundant with data derived from the Address column. I divided the Address Column into five columns titled “Address", "City", "State, “Zip", and "Phone Number”. Upon completion of my data preparation, the Good Sam database included 543 Costco Stores located in the 48 Contiguous United States.

Find RV Parks within 60 miles of a Costco Warehouse

After cleaning and reformatting the Good Sam RV Park dataset and the Costco Warehouse dataset, I wanted to identify the distance from each RV Park to the closest Costco Warehouse. To do so, I designed an algorithm which calculated for each RV Park the geodesic distance between it and each Costco Warehouse, saving the lowest distance calculated. The analysis found 1,473 RV Parks in 984 cities and 1,146 unique zip codes that are within 60 miles of a Costco.

Demographic Data

My wife and I discussed factors that we considered most important to us to identify areas which we would like to spend more time. We reviewed the variables reported in the Census Bureau's American Community Survey to select the specific demographic characteristics we wanted to consider. The ACS is an ongoing annual survey covering a broad range of topics about social, economic, demographic, and housing characteristics of the U.S. population. We decided to analyze data provided in the ACS 5-Year Data “Data Profiles”. Data Profiles is the smallest dataset in the ACS and includes over 1,000 variables covering a broad range of social, economic, housing, and demographic information presented as population counts and percentages.

The list of locations in the United States to consider will be Zip Code Tabulation Areas (“ZCTA”). Per the Census Bureau, ZCTA "are generalized areal representations of United States Postal Service (USPS) ZIP Code service areas." ZCTA is the smallest geographical area for which the Census Bureau provides demographic data. As such, I believe ZCTA and Zip Codes best represent neighborhoods within given locations.

The four demographic variables we chose to consider were the estimated median age of the ZCTA population (DP05_0018E), estimated percentage of the ZCTA population over 25  with a Bachelor's degree or higher (DP02_0067PE), estimated median household income for each ZCTA (DP03_0062E), and the estimated median value of owner-occupied residences (DP04_0089E). We chose estimated median age because, although we are retired, we wanted to be in an area filled with a range of ages like the Houston Heights. We selected population with a Bachelor’s degree or higher because we both have graduate degrees and like being around people with whom we can discuss issues and new ideas. We chose estimated median household income and median home value to represent housing affordability.

Using the Census API, I retrieved the four variables for every ZCTA. For my next step, I cleaned the Census data by dropping all rows where one or more values were less than zero or blank. The table below presents a summary of basic statistical details of the Census data.

The chart below presents a box plot of the four demographic criteria considered.

The table below presents the demographic data for the ZCTA in which our Houston Heights neighborhood was located.

For three demographic criteria (Percentage of population with a bachelor’s degree or higher, Median Household Income, and Median Home Value), the Houston Heights is in an outlier while the estimated Median Age is in the bottom quartile.

As can be seen in the table below, Median Household Income, Median Home Value, and % Bachelor’s Degree or higher are highly correlated.

To filter the Census demographic data, I eliminated ZCTAs (a) which were outliers[1] of the Median Age, (b) where the percentage of the population over 25 with a Bachelor's degree or higher were not in the fourth quartile, (c) where Median Household Income was in the first quartile, and (d) where the Median Home Value was greater than the Median Home in ZCTA 77008 or in the  first quartile. The table below presents the summary statistics of the filtered Census demographic dataset.

As discussed above, the dataset of RV Parks within 60 miles of a Costco Warehouse uses Zip Codes as a reference, while the dataset for Census data uses ZCTAs as a reference. I used an inner merge of the filtered Census demographic dataset and the Simple Maps US Zip Codes dataset based on ZCTA, then dropped the ZCTA column of the merged dataset to yield a Census demographic dataset with Zip Codes instead of ZCTA, and the latitude and longitude of each Zip Code.

Combine Filtered Demographic Data and the Combined RV Parks and Costco Dataset

Next, I inner merged the filtered Census demographic data with Zip Codes dataset and the dataset of RV Parks within 60 miles of a Costco Warehouse, which yielded a dataset (the “Final Dataset”) of 198 unique zip codes in 186 cities. The map below presents those locations.

Download Venue Data for Selected Zip Codes from Foursquare

To identify the locations most common with the Houston Heights, I compared the most popular venues within a five mile location of the center of each zip code in the Final Dataset. I collected such data for each zip code using the Foursquare API. From Foursquare, I requested the 100 most popular venues in each Zip Code within a five-mile radius. I then removed any Zip Code which had less than 50 venues. For each remaining Zip Code, I determined the 5 most popular venues. The screening found 371 unique venues over 110 unique Zip Codes with 50 venues or more. The table below presents the information for Zip Code 77008, the zip code for the Houston Heights neighborhood in which we lived.

Identify Zip Codes Similar to the Houston Heights

To identify zip codes most similar to the Houston Heights, I used the k-means clustering method by using. The k-means clustering algorithm identifies k number of centroids, then allocates every data point to the nearest cluster, while keeping the centroids as small as possible. It is one of the simplest unsupervised machine learning algorithms and is highly suited for this project. For this analysis, I iterated the number of k-means to cluster the Zip Codes until 35 or fewer unique counties with Zip Codes with venues similar to the Houston Heights were identified. The search identified 34 unique locations.

Results

The map below shows the final 34 locations identified by my analysis.

The table below is list of the locations sorted by state presented in the final map. The ID number corresponds to the number on the map.

Discussion

Locations identified using the k-means clustering identified 34 unique locations in 18 states. Several locations we have visited and enjoyed like Tucson, Arizona, Tampa, Florida, Coeur D’Alene, Idaho, Swannanoa, North Carolina, Albuquerque New Mexico, Portland, Oregon, Bend, Oregon, Nashville, Tennessee, Austin, Texas, Fredericksburg, Texas, North Salt Lake, Utah, and the area around Seattle, Washington (La Conner, Poulsbo and Bellingham).

The clustering identified several areas that we had not visited and had not considered like Glenwood Springs, Colorado, the Denver, Colorado area (Colorado Springs, Estes Park, and Englewood), Ypsilanti, Michigan, Frankenmuth, Michigan, Reno, Nevada, Ulster County, New York, Dutchess County, New York, Ithaca, New York, Greenville, South Carolina, and Greenwood, Virginia. Since the clustering identified several places that we have enjoyed and have considered staying at for at least a month, we plan to include these places that are new to us in our travels to see how much we like them.

My sense is the final results would differ if the number of venues used to cluster areas was increased to 10, the maximum number of unique counties to end the k-clustering algorithm had been reduced or increased, the demographic data was included in clustering process. Results may have been different if I had been able to measure the drive time between the RV Parks and Costco Warehouses instead of the distance. It would be interesting to use a larger geographic area like congressional districts or Standard Metropolitan/Micropolitan Statistical Area to filter the demographic data and to identify the 100 most popular venues in order to find areas to visit.

I believe the analysis would have been faster if I had screened the demographic data first then merged that resulting data with the RV Park data. I expect that such a step would have reduced the number of RV Parks to find measure the distance to the closest Costco Warehouse.

We enjoy spending two to three months during the summer in Canada. I would like to prepare a similar analysis using Canadian demographic data, RV Parks, Costco Warehouses, and Foursquare data.

Conclusion

I used the k-means clustering technique to identify areas similar to the Houston Heights neighborhood where we lived before we retired. I used location data for RV Parks and Costco Warehouses in the United States along with demographic data for ZCTAs from the Census Bureau to identify 198 unique locations to consider. I then retrieved data for each locations 100 most popular venues. The k-means clustering method identified 34 unique areas with similar venues as the Houston Heights neighborhood. The clustering identified several locations that we have visited, have enjoyed, and have considered spending at least one month in the future. As a result, I believe it is highly likely that we would enjoy the areas identified which we have not visited identified by the k-means clustering method.

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[1] Outliers are points outside of the range from the 1^st quartile – 1.5*IQR to 3^rd quartile +1.5 IQR, where IQR is the difference between the 3^rd quartile and the 1^st quartile.

An Exercise in Data Visualization

I have been taking classes on data visualization. In this time of the COVID-19 pandemic, there is plenty of data about the disease. Yesterday, on Facebook, I shared a chart comparing the number of deaths in the United States reported weekly for the years 2015 through 2020. Below is that chart.

  

The chart is presented through April 11, 10 weeks before the last date reported in the dataset, because depending on the jurisdiction there is at least a one to eight week lag time for deaths being reported to and processed in the NCHS system. Thanks to Michelle Manos for that suggestion.

My friend Alison Jones asked if I could compare the excess deaths in 2020 to the number of reported COVID-19 deaths to see if it is possible there may be more deaths from COVID-19 than being reported. That chart is presented below.

Based on this analysis, through April 11, the estimated cumulative number of excess deaths in 2020 was about 117,000 compared to almost 58,000 deaths from COVID-19.

Former New Folk Spotify Playlist

Have created a Spotify playlist of music recently released by former finalists in the Kerrville Folk Festival New Folk Singer-Songwriter Competition.



Artists featured include:

Tom Meny
Mike P. Ryan
Wes Collins
Claudia Gibson
Austin MacRae
John Louis
Jaime Michaels
Karen Dahlstrom
K.C. Clifford
Amanda Pascali
Alice Howe
Michael Braunfeld
Andrew Delaney
Kelly Augustine
Clementine
Roy Schneider and Reckless Saints
Susan Cattaneo
Rebecca Loebe
Ellis Paul
Katy Vernon
Lynne Hanson
Lisa Bastoni
Sarah Jane Nelson
Martin Kerr

Ian Flanigan

Nels Andrews

David Berkeley
Lindsay May
Andrew and Zachari Smith
Ordinary Elephant
Raina Rose
John Batdorf
Letitia VanSant
Lindsay White
Storyhill
Nicolette Good
Korby Lenker
Rachael Sage
Scott Mulvahill
Mary Bragg
Anna Tivel
Michaela Anne
Robby Hecht
Nobody's Girl
Jimmy LaFave
Amy Speace
Kora Feder
Prateek
The Brother Brothers
Blue Water Highway Band
Sarah Morris
Ben de la Cour
Ezra Vancil

4th Anniversary of Being on the Road

While I am on the topic of new experiences and getting outside my comfort zone, today marks the 4^th anniversary of Deb, Pancho and Lefty, and I living full time on the road in our 5^th wheel trailer. Neither of us were quite sure whether we would enjoy living the vagabond life. Well the answer is – WE DO.

Traveling the U.S. and Canada has taken us to places we have always wanted to see and places we didn’t know we always wanted to see.

Not being an outdoorsy person, I did not expect to love Yellowstone National Park and Glacier National Park. The inner 5^th grade science geek in me got to see the tidal bore at the Bay of Fundy and rocket launches at Kennedy Space Center. Across the country, we have seen several exhibits of Dale Chihuly glassworks along with many buildings and homes designed by Frank Lloyd Wright. We have also visited quirky and offbeat museums, which may be my favorite part of this adventure. Who knew there was a museum dedicated to the homing pigeon, or to the banjo or to the umbrella cover? Along the way, I have had the chance to catch up with old friends from elementary school, high school and college. We have tasted wines from across the U.S. and Canada (Paso Robles is my favorite, and I am surprised how much I liked the New York Finger Lakes white wines). We have attended music festivals where our friends were performing and made many new music loving friends.

This year, we took the trailer by ferry to Newfoundland. For those of you who love hiking and rugged terrain, you must go. St. John is a lovely city – one which I could see staying for a while. I did not expect to enjoy the area as much as I did.

Another highlight of the year – seeing Cher the opening night of her residency in Las Vegas on our anniversary night. Great, great show. I was surprised there weren’t very many people in costume. Cher, Halloween, how could there not be costumes!?

For the next year, our itinerary consists of four parts. Returning to Texas for the Holidays, travel the Southeast U.S., return to the Kerrville Folk Festival to host New Folk, then head out the to Northwest. On the way to Texas, we will set up camp in Jersey City with a view of the Manhattan skyline, staying near Washington, D.C. planning to be super tourists, and spend Thanksgiving week in Nashville where we hope to catch up with any of our singer-songwriter friends.

For the Southeastern leg, we will stop in New Orleans to attend the Folk Alliance International conference where we hope to see many of our musician friend, then hang around another week to enjoy the city. After that we head down the Florida coast toward Key West, before beginning the trek back to Kerrville. After the Festival, we are off to the Pacific Northwest. If the RV park is still there, we want to attend the Canmore Folk Festival again. And we would like to spend more time on Vancouver Island, at least two weeks, if not a month. On the way back to Texas, we will stop in Portland, maybe Seattle, and Paso Robles.

One thing we will be doing is slowing down. We used to plan to spend no more than a week in one place, averaging about 4 days a stop. We didn’t want to miss anything. Our current plan is to spend a week to two weeks at each stop. Fewer stops, but more time to enjoy them.

In closing, I want to thank you for putting up with my over posting pictures of our stops. I appreciate you being allowing me to share our escapades with you.

To riff off the amazing Nick Lowe – I wish all of you “peace, love and understanding”.

Lindsey

Week 10 update

Not making much progress. Yesterday, started increasing my walking to over 10,000 steps a day. Hope that helps. Weight: 221.2 pounds Weekly Change: -0.2 pounds YTD Change: -5.0 pounds

Planned Stops for Next Three Months

September
Portland, ME
Burlington, NH
Boston, MA (while Deb is at SWRFA)

October
New York City
Washington, D.C. (2 weeks including our anniversary)

November
Asheville, NC
Nashville, TN (Thanksgiving)

Yakima - Haze is Lifting

Arrived in Yakima yesterday. During most of the drive, the haze was so thick you couldn't see the mountains. Visibility was less than a mile.

This morning, while the smell of smoke is in the air, the haze seems to be dissipating. I can see the face of the moon and clouds.

During the drive, a rock chipped the truck's front window. Was able to go online with my smartphone, schedule an appointment with Safelite, and have the claim approved by Farmers Insurance before we arrived at our campsite. Twenty years ago, this would have taken weeks. Actually, I probably wouldn't make the claim because of the hassle factor. Technology can make your life easier. Take that Ted Kaczynski..

Status Update - Boise

Since a few people have asked about the fires.

Currently, we are in Boise. It is pretty smoky here. Worse than it was in Canmore, AB. The haze has held the temperatures down below 90. The sun and moon are dim orange balls. There is a front with rain coming through the next couple of days which should help fight the fires.

When we left Utah, it was pretty clear. There were only two fires, both north of Salt Lake City.

Our plan is to go to Seattle, then turn south to follow the coast. We'll make a decision as to whether to change our route while in Yakima.

Hurricane Harvey Volunteer Opportunities

The following is a list of various organizations around the Houston area seeking volunteers to help with the Hurricane Harvey recovery.

• Volunteer Houston has a  Virtual Volunteer Reception Center that matches volunteers with agencies providing disaster relief.
• National Voluntary Organizations Active in Disasters has created a website to sign up to volunteer 
• Volunteer Louisiana has created a webpage for volunteer opportunities and for making cash donations. 
• The Houston Food Bank needs food, water and supplies.
• Help Houston has created a webpage of shelters that need volunteers (some shelters have reached capacity, so call ahead to check).
• A Hurricane Harvey 2017 Facebook page has been created to coordinate and correspond with other volunteers. There are over 125,000 members
• A group of volunteers has created the Hurricane Harvey Relief and Volunteer Opportunities Map to find volunteer opportunities, shelters, resource drop-off locations, medical aid and other relief efforts.
• Call 281-656-1533, a hotline for Volunteer Houston, to find volunteer opportunities

How to Help Hurricane Harvey Relief Efforts

Being from Houston, I am pained by the devastation from Hurricane Harvey. Looking to help, I began gathering a list of organizations focused on the Hurricane Harvey relief efforts. Because I have seen numerous posts from people seeking similar information, I decided to post this list and share with anyone interested.

I will be updating this list over time. Currently, it focuses on the Houston metropolitan area. I plan to expand it to include the Rockport area, Beaumont/Orange area, and western Louisiana. Click on the underlined name to go to the related site.

While organizations like the American Red Cross and The Salvation Army are dong great work helping the victims of Hurricane Harvey, I have tried to focus on organizations based in the area. If you know of any groups in the area I have not listed, message me. 

Cash

It is counter intuitive, but cash donations may provide the greatest leverage for helping people. The reason is relief organizations can purchase goods in bulk at a discount. In addition, a nonprofit does not have to pay sales tax on items it purchases. There are many fine organizations working to assist with the Hurricane Harvey relief efforts. The following is a brief list of some of these organizations. 

• Houston Food Bank
• Galveston County Food Bank
• Corpus Christi Food Bank
• Coastal Bend Recover Group - Regional nonprofit that addresses the unmet needs of Coastal Bend area residents affected by disaster
• Texas Diaper Bank - Federal relief does not include diapers
• Greater Houston Community Foundation - Established by Houston Mayor Sylvester Turner for Houston area victims affected by the floods
• United Way of Greater Houston - 100% of donations goes to help victims in the Greater Houston Area. You can designate the county in which the funds are spent.
• Coalition for the Homeless - Houston area organization helps homeless people get back into housing.

Amazon Wish Lists

If you're like me, you prefer giving goods to specific organizations to help the victims of Hurricane Harvey. These are some of the Amazon wish lists I have identified:

• Austin Pets Alive
• SPCA of Texas
• Animal Defense League of Texas
• Refugee Services of Texas
• Texas Diaper Bank
• Pughearts of Houston - Full Disclosure - Deb and I are active with this group, and fostered several pugs through the group before we went full time. The goods are being collected to help volunteers and the pugs they are fostering who are victims of Hurricane Harvey.
• Wolfe Elementary - School located in Katy, Texas providing shelter for displaced individuals
• Abundant Life Christian Center - LaMarque area church providing relief efforts to the area.
• George R Brown Convention Center - One of the largest shelters on the Houston area
• Port Aransas Hurricane Relief - A crowdfunding relief effort organized by Nathan Clark, a Port Aransaas resident and business owner

Disaster Averted. I WAS WRONG

Yesterday, while driving from Salt Lake City to Mountain View, Idaho to watch the eclipse, Deb noticed the 5^th wheel was leaning far to the driver side. I thought it wasn’t a big deal; she did. I was wrong. Let me repeat that – I WAS WRONG. One of the leaf springs had broken off the suspension.

We were only 2 miles away from the RV dealer/repair shop next to the RV park we had camped in, and we were able to get there before anything else happened. Further inspection found that a bracket on one of the leaf springs had broken and the leaf spring had twisted. That surprised me because we had replaced the leaf springs the week before. From talking to the person who replaced the springs and the head of the repair shop at the RV dealer, I realized our suspension was not strong enough for our trailer. The trailer weighs around 18,500 pounds, and the suspension was designed for a maximum of 14,000 pounds. That explained why we had had so much trouble with parts of the suspension breaking.

We have to replace the suspension. It will take about two weeks for the parts to get here. We are upgrading to 20,000 pound independent suspension. During that time we will remain in SLC. Have had to cancel our stops fpr the next couple of weeks. I t looks like we will not make it to British Columbia this trip.

We are fortunate on many fronts. (1) We could move the trailer to the RV park next door by replacing the leaf spring. (2) The RV park worked with us to find a space for our trailer for two week, so we can stay in our trailer while we waited for the part. (3) We didn’t break down in the middle of the nowhere, and are safe. (4) We can afford the cost to replace the suspension.

Trying to figure out if we can get up to Idaho to see the eclipse. It looks like hotel prices have started to come down. And we have a parking pass in Smiths Ferry to watch the eclipse. We may drive up to Boise on Sunday, then to Smiths Ferry the next day. Won’t decide until later today.

Island Falls, Idaho to Mossleigh, Alberta (7/3 – 7/9)

Driving from Yellowstone to Alberta, we would have preferred to stop once at Great Falls, MT before crossing the border. We had to leave the park near Yellowstone on July 3 because it was fully booked beginning that day. Unfortunately, none of the parks near Great Falls were available until July 4. I was able to find a spot in Bozeman, MT which is about halfway between Yellowstone and Great Falls. While staying in Bozeman was unintended, it worked out for the best as we were able to have dinner with and catch up Aaron Howard, a 2014 New Finalist who had camped with us, and his girlfriend Sarah.

We liked Bozeman. Although about the size of Kerrville (population of around 38,000), the city is thriving with many of the amenities you would expect in a much larger community. Specifically surprising to me – a Costco. According to Aaron and Sarah, the presence of major information companies like Google and Facebook is a major factor for Bozeman’s growth. Montana State University is there, which has several renowned science related programs

Since the drive from Island Falls to Bozeman was relatively short, less than 1.5 hours, I had time in Bozeman to take the Beast to the Ford dealership to have its 60,000 mile oil change. Incredible to think that during the less than two years we have owned the truck we have travelled that much.

The next day, July 4, we drove to Great Falls to stay for three days to stock up on goods and supplies which were less expensive in the States. While slightly larger than Bozeman, Great Falls felt very different. It is a mining and refinery town, as evidenced by the main street being named Smelter Avenue. Surprisingly, the town had very little 4^th of July activities going on.

Friday, July 7 we headed to Lethbridge, Alberta for the night. Crossing the border into Canada was less eventful than the first time. No questions about “Where are your guns? Where did you store them?” Instead just some perfunctory questions about the reasons for visiting, length of our stay, and how did Deb end up in the States.

Why Lethbridge you ask? To see John Wort Hannam perform. John was a New Folk contestant and winner in 2007. He claims he would not have won except for us. At the time, John was living in Fort Macleod, Alberta, smaller than the average attendance of the Festival. When he walked into the Mixmaster, the entrance to the Festival campgrounds, John was overwhelmed by the number of people and activity. He sat down on his luggage, called his wife, and told her he couldn’t do the contest and had to return home. She told him that was fine but he had to go down to our camp to tell us he would not be staying with us. Being a good husband, John did as he was told. When he appeared at our camp, I greeted him with a welcome hug and asked if he needed a beer. That apparently was enough to convince him to stay around for a while.

We were excited to be able to see John perform. We hadn’t seen him in over 6 years, just before the birth of his son, Charlie. We thought the show was to be a concert with John as the headliner – we were wrong. It was a musical theater revue with a salute to Canada’s 150^th anniversary as the theme with John as the musical guest. They asked for a show of hands as to who was not from Canada. Of the three, I was the only native born U.S. citizen. They were surprised we were from Texas, and more so when we said the reason we were there was to watch John perform, and for cooler weather which they had failed miserably at since it was a high of 101 that day. John performed two songs during each of the two acts, but only one was an original. The others, at the request of the revue, were covers of Canadian artists. As one of the songs was Four Strong Winds by Ian Tyson, Deb’s dad’s favorite song, they were forgiven. At intermission, we found someone to tell John we were in the audience. He came bounding out like a puppy for a snack. He told us he had heard some people from Texas were in the audience but never in his wildest imagination did he think it would be us. We talked to him during intermission and after the show, and set up breakfast the next morning to meet his wife and son.

Breakfast the next day was outstanding. Catching up with John and getting to know his wife and son was a great joy. For those of you who are John Wort Hannam fans, he is planning to record a new album later this year. Also, the Italian sausage breakfast sandwich I had was incredible, putting a Whataburger Breakfast on a Bun to shame. After breakfast, we returned to the trailer, packed up and drove to Mossleigh, Alberta. More about that in the next post.

Custer to Yellowstone (6/25 – 7/3)

The time to drive directly from Custer to Yellowstone is around 10 hours. As we prefer our drives to be between 3 to 5 hours with a maximum of 8 hours, we decided to break the drive into three parts.

The first stop was Devil’s Tower, WY. Devil’s Tower National Monument was the first declared National Monument. You may remember it as a key plot feature in Close Encounters of the Third Kind (For fans, in September, the movie will be re-released for its 40th anniversary http://io9.gizmodo.com/close-encounters-of-the-third-kind-is-flying-back-into-1796651191

Our campground (the KOA Devils' Tower) was next to the gate to the monument. After setting up the 5th wheel, we visited the monument and walked around it. Devil’s Tower is a sacred site to several Indian tribes. During our walk we saw numerous prayer bundles, which represent a person making an offering, a request, or simply in remembrance of a person or place. Climbing is a very popular activity at Devil’s Tower. As June is a culturally significant time to the tribes for which the butte is sacred, the National Park Service asks visitors to voluntarily refrain from climbing Devil’s Tower during the month.

We left Devil’s Tower the next day to stop in Billings and stock up before driving to Yellowstone. Billings is the fastest growing city in Montana, and the only city in the state with over 100,000 people. William Clark of the Lewis and Clark Expedition stopped in Billings in 1806. Since we were only there for a night, we didn’t get to see much of the city. However, I can see visiting in the future to see sites like Pompey Pillar and Pictograph Cave.

From Billings, we drove to Valley View RV Park in Island Park, ID, which is about 30 minutes west of Yellowstone National Park. It was the nearest place we could find that close to the 4^th of July holiday weekend. Because specific sites had been booked at different times halfway through our stay we had to move to a different site. That move led to a slight hiccup to our plans to be at Yellowstone by 9.

We were able to raise the stabilizers hook up to the truck, move 50 yards to the new spot, lower the stabilizers, and unhook. Then the challenge arrived. After Deb pressed the autostabilizer button, the front stabilizers lowered Beauty (the nickname of our 5^th wheel), stopped, then began making a loud clicking sound. As you can imagine, that is not supposed to happen. Checking the control panel, I saw a “low voltage” error message. I did a Google search for “LCI electronic leveling low voltage” and found that the culprit could possibly be a shorted out control panel or a loose wire in the system. Neither of those problems were ones I could repair. Talked to the park manager, who gave me the card of a mobile RV repair technician.

Called and left a message for Randy. His greeting noted that he often was in places with no cell coverage and it might be a while until he returned the call. While waiting for Randy to call back, we tried several different things to no avail. After 30 minutes, Randy called back to say he could fit us in but would have to charge a premium since it was a Saturday and he was trying to get home. Considering living in an unlevel 5^th wheel is no fun, I told him I understood and would happily pay. He told me he would probably be at our spot in two hours.

Relief that a possible solution was found apparently opened my mind to thinking. After ending the call, I went to the trailer’s battery storage area and inspected the cables. I found that one of the connections had become loose. I tightened the connection by hand, then tried the autostabilizer. It worked. Can I get a Hallelujah and an Amen. Relief swept over me. Deb was much happier. I immediately called Randy to tell him I found a solution. Again, reached his greeting. He called back ten minutes later and was very gracious. Before hanging up he asked me to thank the Valley View managers for him. I told him I had already done so, and that they loved him.

As for Yellowstone National Park, what an amazing place. After visiting I can easily understand why Theodore Roosevelt worked so hard make it the United States’ first National Park. The variety of topology and the vistas are majestic.

Yellowstone has the largest population (approximately 5,500) of free range Bison in the United States. It is the only place where Bison have lived continuously since prehistoric times. Bison are very quick and agile animals. The Park Service tells visitors to stay at least 25 yards away when viewing a Bison. However, many Yellowstone Bison don’t know this rule.

It appears that Bison have become so used to people in the park that they pretty much understand that they have the right of way.

During our visit, we saw all the required highlights:

Old Faithful

Waterfalls

Mud Volcanoes

Crossed the Continental Divide twice

That is a little bit of a taste of our trip. Next week, we will be on the road to Canada.