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Welcome to the Champions Club Summer 2018!

Entries in thinking out loud (8)

Thinking Out Loud: Happiness in the Uphill Climb

by, VJ Tocco

It's been a minute since VJ did one of these, but hopefully this isa sign of things to come. If you are late to the game, here's his previous Thinking Out Loud installments. Now enough  of me, on to the good stuff.


ABC’s Shark Tank is one of my favorite shows. Besides the quirky inventions and new products, I love getting a glimpse of how wealthy people think during the negotiations. While the Sharks carefully ask questions, weigh their risk and calculate potential returns, I often wonder why they bother. After all, to a billionaire, buying $100,000 worth of a company is like the average person buying a soda.  Even a 100% return on an investment of this size, while substantial to the average person, is only like two sodas in few years to Mark Cuban.  Clearly, at a net worth of a few billion dollars, he has enough money for him to live the rest of his life, and to live well (and for many generations to live well beyond that). So why does he bother? Why put up with the stress and work of trying to build a company and mentoring young entrepreneurs?

“Perhaps happiness is always to be found in the journey uphill, and not in some fleeting sense of satisfaction awaiting at the next peak”

I obtained this quote from Dr. Jordan B. Peterson’s recent book “The 12 Rules for Life”. It stuck with me as a Ph.D. student, as someone who has felt like the journey of my last four years has been almost directly uphill. Previously, happiness to me was about having fun.  I was happy when I was playing a sport or spending a day at the beach. I would not characterize Ph.D. research as fun, and therefore it did not make me happy, and I initially dismissed this thought.

However, as I continued to read, Peterson explained more. How many days could you sit on the beach before you got bored?, he asked. While it may be fun for a vacation, or even a nice place to visit often, you need something else in your life. Ideally, that something else comes with the hope for a better future, and that hope is what makes people happy. In this context, his quote makes much more sense. My Ph.D. research came with the hope of better career prospects and better job security.  The work and energy that we expend lifting weights in a gym comes with the hope of living a longer, healthier lifestyle. We teach, coach, or mentor young people in the hope that they may one day pay it forward.

Now that I’m aware of it, this concept has been popping up a lot for me lately. It explains the thrill I feel when the pepper plant that I tend sprouts new growth, or when an investment in my portfolio appreciates, or when one of my students suddenly understands an engineering problem.

Mark Cuban must derive happiness from the uphill climb of building companies and seeing them prosper.  After all, he probably wouldn’t be a billionaire if he didn’t.

Thinking Out Loud: How Much Should Your Doctor Know?

by, VJ Tocco

During a recent eye exam, my optometrist administered eye drops to dilate my pupils. Being the curious type, I asked the doctor how the drops worked.

“Oh, um… They stimulate your sympathetic and parasympathetic nervous system.”

Granted, I’m no medical doctor, but I know that those nervous systems are two different things. Unsatisfied with this answer, I probed deeper, clarifying that I do research in the biomedical field, and my questions were out of genuine interest.

“Well, they, um, activate surface receptors that signal other receptors in the eye muscles”

My raised eyebrows must have betrayed my skepticism, because the doctor quickly clarified,

“You know, I’m not really sure much more past that.  It’s been a while since I’ve looked at that stuff.”

I accepted this answer, but it got me thinking: in general, when doctors prescribe a medicine or medication, do they actually know the biochemistry behind what the pharmacological agent does to your body? Should they? Or should that burden fall on the pharmaceutical company who manufactures the drugs? Is it enough for doctors to simply know the cause-and-(intended) effects?

TV ads for certain prescription medications usually include some kind of disclaimer about the side effects. Obviously, everyone is different, and some people should respond to treatment differently than others.  But, if doctors knew the mechanism of action, could they more accurately prescribe treatments?

For example, consider the drugs Zoloft and Prozac, both used to treat depression and anxiety, among other conditions.  A quick google search reveals that they have different chemical formulas, and slightly different intended effects and side effects, although they are both selective serotonin re-uptake inhibitors.  When your doctor prescribes one over the other, what is the basis of that decision?

I would hope that it is thorough knowledge of biochemistry and specific mechanism of action, with careful consideration for the unintended and unforeseen side effects.  But maybe I’m being unreasonable. 

I’m interested to hear other thoughts on this one.

Thinking out Loud: Published Paper Politics pt. III

by, VJ Tocco

Like many other kids who grew up in the 90s, I was very excited to learn about the new Bill Nye (the science guy) series on Netflix. I had cleared my entire schedule one Sunday evening, intending to binge the whole series.  Much to my dismay, I quickly realized the show was much different than the old Bill Nye show, and began to skim the content after two episodes and ultimately shut it off entirely in favor of The Office re-runs.

My biggest beef with the show was that Bill Nye was telling, not showing. Very little (if any) actual data or evidence was displayed. Rather "experts" and comedians joined the show to pontificate, promote their ideas and ridicule those with different viewpoints.  This ridicule reminded me of a news story from earlier this year, when NBA star Kyrie Irving made headlines for his beliefs that the earth is flat. Although I disagree, I admire and respect Kyrie's train of thought. He had never experienced direct evidence to the contrary, and refused to simply believe what others had taught him. The media who covered the story completely missed this point, and instead vilified him as a role model to young children.

Too many people blindly accept "conventional wisdom" as truth although they have no direct, indisputable evidence. Examples: breakfast is the most important meal of the day, 30 minutes of exercise per day avoids health problems, re-using the same plastic water bottle leaches chemicals that give you cancer, a diet full of omega-3 oils is good for heart health, etc.

I haven't regularly eaten breakfast in about seven years. I stopped sometime in college because I enjoyed sleeping more in the time that I would have spent preparing and eating the food. Truthfully, I don't even get hungry before noon anymore. Yet, when I share this fact about myself to my friends, most are shocked at the damage I'm doing to my metabolism. When I challenge them on these beliefs, not a single person can point me to a peer-reviewed article that indisputably shows evidence.

The only way to really know these things for sure is to evaluate the primary scientific literature that proposes these claims. However, primary scientific literature is mostly inaccessible to the public for three main reasons:

  1. Written in confusing and pretentious language:
  2. Many literature articles are written for other experts:
  3. Journal articles cost money to read: Unless the article is open access (free), scientific papers cost about $35! (Link:

So is all hope lost? Maybe not. Here is a blog I found for ways to access literature ( As for actually understanding what you read, I can personally ensure that it gets easier with practice. It's also easier if you can discuss with a friend who shares your interest.

Whatever you do, never ridicule those who think differently than you do without having done your research. Also do not be offended by being challenged on your beliefs. Healthy debate is good for your brain.

Thinking Out Loud: Published Paper Politics pt. 2

by, VJ Tocco


“In God we trust; all others bring data”

-W. Edwards Deming 

In 2006, my classmate Louis Eakins introduced me to Wikipedia during an assignment in Mr. Swanson's anatomy class. My world was transformed as we finished our lab in about 15 minutes by quickly finding our answers on the online encyclopedia. Wikipedia became my go-to website for looking up anything from chemistry to NBA trivia. Sadly, teachers began banning Wikipedia on assignments (especially essays) soon afterwards.

To this day, I still use Wikipedia judiciously to learn about unfamiliar topics. Wikipedia excels at educating the inexperienced to indisputable facts. However, for as informative as Wikipedia is, it suffers a critical flaw: its entries have not sustained peer-review.

Peer Review: What is it?

Peer review is the quality-control system to ensure the integrity and validity of scientific publications. After a scientist has finished writing a manuscript, he or she will submit it to a journal. The editor of the journal will quickly consider the suitability of the manuscript for the journal. If it passes, the editor sends the manuscript to several (usually three) experts in the particular area of science, who are instructed to objectively scrutinize the article. If the reviewers approve the work, the manuscript becomes published.

Very little journalism and media targeting the public is peer-reviewed.  For example, Dr. Oz advertises  miracle weight-loss solutions under the guise that scientific research has demonstrated their effectiveness. While the original research he references might have been peer review, his commentary has not. For this reason alone, I hope you will re-think your trust in anything that has not been peer-reviewed.  By the end of this post, I hope that you would also re-think your trust everything that has been peer-reviewed as well.

Who are the peer-reviewers?

Most fields of science are sufficiently specialized such that only a handful of people on the planet are recognized as "experts". Accordingly, the experts in any particular field are highly likely to know each other. Most peer-review is single-blind, meaning the reviewers are anonymous, although they know who authored a manuscript. Thus, peer review is problematic if any of the following relationships apply to the reviewer and author:

  1. Competitors: Funding in science is limited, and as I asserted in part I, those who publish the most high-quality work are usually first in line to receive said funding. Validating the work of a competitor can be harmful to one's own career.
  2. Enemies: The fragile egos of some scientists can possibly be attributed to the fact that most of them are males. Reviewers are less likely to validate the work of those they don't like.
  3. Allies: Perhaps the most dangerous of relationships between reviewer and author in terms of integrity during the review process. Reviewers who have a personal relationship with the author have a conflict of interest; although these types of relationships should be disclosed, it is not always the case.

Assuming that these relationships don't cause problems, the reviewers need to find the motivation to evaluate the manuscript. Being asked to review is a bit like jury duty; it can be a major inconvenience with no incentives except a fulfillment of your civil duties. Most academics are too busy to devote the appropriate amount of time and effort to give a proper review.

How in-depth does the review go? There are surprisingly little guidelines for reviewers, and they are able to use their discretion. No study is bulletproof, if questions for long enough, something questionable is bound to appear any research study. Surprisingly, most papers only speculate on the results, not the methods. That is, there is no rationale for how they chose their subjects (or how many), how they designed their experiment or survey, or why they chose their control experiments.

All of these nuances present valid reasons to be skeptical of peer-reviewed literature.  Although peer-reviewed papers are held to higher standards than non-peer reviewed papers, they should not be considered gospel.

In the third and final installment of this mini-series, I'll discuss some strategies that non-experts can make the literature more accessible.

Thinking Out Loud: Published Paper Politics pt. 1

by, VJ Tocco

“Believe nothing, no matter where you read it or who has said it, not even if I have said it, unless it agrees with your own reason and your own common sense.” - Buddha

I cringe when I hear or read the phrase "research has shown."  It is a pretentious way to make the statement or assertion that follows seem irrefutable, preying on the respect that the public has for science.  Although, I have to admit that even the most absurd statements appear at least plausible if a footnote referencing a scientific paper follows. For example, studies show that dairy cows produce more milk if you give them a name1. Other research has shown that rats that prefer to hear absolute silence instead of Miles Davis or Beethoven, unless they ingest cocaine2.  The trouble comes when an entire study is summarized into a single conclusive statement (as I've done above), by a person who hasn't read or fully understood the original research articles (full disclosure: I haven't).

In this three-part miniseries, I'll discuss the problems with accepting the results of science at face value. In reality, research is fraught with caveats and nuances that can sometimes devalue the conclusions. Interpreting research demands skepticism; as Buddha taught, you should believe only what you choose to believe after you've given it careful consideration, not everything that you've been told.

Part I is about the motivation of researchers to publish their work. When I started doing my own scientific research, I naively misconceived that all research was motivated solely by a desire to expand human knowledge.  To be fair, I've become more cynical in the last few years, and this is probably  the primary motivator in science. However, I've learned that there are alternative, less benevolent motivations as well.


All research requires money.  Lots and lots of money. In addition to researcher's salaries and bureaucratic overhead, reagents and laboratory materials cost a shocking amount of money. Earlier this year, I personally spent over 10k for a set of reagents that totaled less than ten micrograms of material. Most money that funds research comes from federal grants.  Consequently, researchers may feel the need to produce something (even if the work isn't up to par) to show that the spent taxpayer money went to good use. In fact, grant-awarding government agencies usually require a quota of output (in the form of papers) every few years in order to renew the grant.  

Sometimes, companies and corporations provide funding for research. As in politics, those who pick up the tab can becomes stakeholders in the results. For example, consider this article about research funded by Coca-Cola. Can you imagine any study funded by Coca-Cola concluding that drinking soda is harmful to your health? For this reason, knowledge of the funding source is critical to interpretation of any research paper – authors usually provide this information in the "acknowledgements" section.


“Publish or perish” is the most common mantra in academia. Perversely, the most important criteria in judging an academic’s work is quantity. Of course, the quality of the work is important too, but the metric of evaluating quality is seriously flawed (more on that in part II). Put another way, if rappers held to the same criteria as academics, Lil B might be considered the GOAT.

Because the number of publications is so critical to a scientist's reputation, scientists can sometimes resort to tactics that are frowned upon (albeit ethical) by the scientific community. For example, a not-uncommon practice is to withhold some data on a paper in the hopes of publishing a smaller, separate follow-up paper soon afterwards. For this reason, I usually check the publication record of the lead scientist when I read papers. An alarm bell rings in my brain if  the scientist is publishing more than ten papers per year, similar to Lil B's ten or so mixtapes per year.

Confirmation Bias

A sad reality in the sciences is that nobody gets excited about negative or neutral results. That is probably for a good reason; after all, who cares if it turns out that a new disease-treating drug doesn't improve patient health in clinical trials? But now imagine how disheartened a scientist might feel after arriving at a dead-end after a year or two of hard work. Neutral results, while still publishable, are not perceived as influential as positive results. This fact tempts scientists to enter the spin zone: downplaying negative results and inflating the impact of positive results.

The spin zone may even be an unconscious phenomenon. Humans are predisposed to seek out only evidence that supports their hypothesis, and to disregard any evidence that contradicts their beliefs (this is a psychological concept known as confirmation bias). It seems counter-intuitive, but science should be far more concerned with disproving hypotheses than supporting them. Notice my word choices there; hypotheses can never be proven; only supported.

Unfortunately, for all the reasons listed above, scientists have no motivation to tirelessly work to disprove their hypotheses. It is far easier to publish work that thoughtlessly support their hypotheses, thereby achieving the funding and accolades associated with publishing as much as possible.

Next week, I'll dive into the peer-review process, which is how the scientific community decides which papers get published.



  1. 1.      Catherine Bertenshaw & Peter Rowlinson (2009) Exploring Stock Managers' Perceptions of the Human—Animal Relationship on Dairy Farms and an Association with Milk Production, Anthrozoös, 22:1, 59-69
  2. 2.      JE Polston and SD Glick, (2011) Music-induced Context Preference Following Cocaine Conditioning in Rats, Behav Neurosci 125(4): 674-680

Thinking Out Loud: That Time I Met Flo (NTF)

by, VJ Tocco

In my introductory post, Chris mentioned a transcendent moment of my life last summer: the time I met Flo-Rida.  Flo's music has always held a special place in my heart. I can vividly recall cutting a rug to "Elevator" at senior prom. The energy on "Turn Around (5, 4, 3, 2, 1)" fueled most of my workouts in college. "Good Feeling" is still my favorite song to blast as loud as my car's speakers can play during my Friday afternoon drive home. Many other of his hits instantly take me back to fond memories. So you can imagine my surprise of that day, when I was out with my girlfriend, Terra, at an outdoor mall near Disney and I saw one of my favorite artists casually shopping amidst the public.

We were walking towards a candy store in the mall when I spotted distinctive, colorful tattoos on the man walking in front of me. My heart began to race when I saw a hundred-thousand dollar watch on his wrist with a pinky ring to match and realized I was only a few feet away from one of my idols. I noticed he was traveling with an entourage: four massive bodyguard-looking dudes and a woman with preposterously large buttocks (sadly, she was not clad in apple-bottom jeans, nor boots with the furs). We followed them at an awkward distance for about five minutes while I debated how to approach him.  In the end, I went with a cheery "Hey, Flo! Can I get a picture with you?"

In the aftermath of that event (after I had sent the picture to everyone I knew), I considered the trajectory of unlikely events that had led me to that exact moment. How was it that we both happened to be walking near each other at the same mall, at the same moment in time?

I'm not sure what happened in Flo's life that led him to that candy store at that precise time.  Maybe he just wanted him some sugar (da ba dee da ba daa).  As for Terra and me, we were out for dinner and shopping at the mall because of one of her friends in Orlando had recommended it. She had met that friend through work, at a job she sought out and accepted because of her desire to stay close to me until I graduated school at UF.

It occurred to me that had I never met and began dating Terra, I would have never met my idol. Terra and I had met on a chance encounter at UF, and she only kept talking to me because I was interested in her poodle.

Moving back further in the story, had I not been attending UF for grad school, I would have never met Terra. My decision to move to Florida was fraught with many other chance events that are too long and complicated to list here.

The entire saga reminds me of one of the more interesting topics that I learned during my education engineering: chaos theory. This concept is also known as the "butterfly effect", and if you've seen that goofy Ashton Kutcher movie, you already have some notion of how it works. The basic idea is that systems that seem random are actually deterministic (meaning able to be predicted), but depend heavily on the initial conditions. Also, miniscule differences in the initial conditions can yield completely different results.

Take for instance a coin flip, which many people consider a fair, random method to make a given decision. Theoretically, however, if you could know and measure all the input variables (the initial launch angle and velocity of the coin, the air currents in the surroundings, the elasticity of the landing surface...), you could calculate the outcome. Of course, this outcome is very sensitive to these initial conditions, so such a calculation would be futile. Even the smallest gust of wind or vibration in landing surface can cause an unpredictable outcome.

The broader lesson of chaos theory is that you can very rarely plan out your exact future.  For the younger member of the audience, you may soon have difficult decisions about where to attend school, what you will study, and who you befriend.  You may have long-term goals and stress out about how to achieve them. When you are confronted with two roads diverged in a yellow wood (Frost reference, thanks Mrs. Sienkewicz), you may have some idea where each road might lead, but you cannot predict what surprises, sub-plots, and other diverging paths await you along the way.

My advice is to not sweat it so much. Be decisive with your choices and have confidence that you chose correctly. You might not meet one of your favorite rappers as a result, but everything tends to work out in the end.

Thinking Out Loud: Engineer State of Mind

by, VJ Tocco

Too many people cringe when they hear the word engineering. This reaction is probably caused by painfully unfunny sitcoms like “The Big Bang Theory”, which conjures caricatures of dweeby engineers whose idea of fun is solving Rubik’s cubes for time. I used to resist becoming an engineer for fear that I would maybe one day find programming my calculator to tell a stupid joke enchanting or that one day I would understand all those complicated mathematical formulas with the Greek letters.

Against my preconceptions, I declared Chemical Engineering as my major when I was a sophomore at the University of Michigan about 8 years ago. During the first few weeks of classes, I was surprised and relieved that many of my classmates were “normal”. Most of them did not memorize pi to 50 digits or read Stephen Hawking’s books. Shockingly, I met a few students whose interests (sports, rap music, etc.) aligned with mine.

When people learn that I will soon have a Ph.D. in Chemical Engineering, they treat me similar to how I used to treat engineers. They say things like “you don’t look like an engineer”, or “wow, I could never understand what you do.”  I tend to disagree with both of these statements. If you think all engineers look the same, you’ve seen too many episodes of “Silicon Valley.” If you believe you could never think like an engineer, you’re selling yourself short.

At its core, engineering is nothing more than solving a problem in the most efficient way possible that satisfies all the constraints.  We solve problems as an engineer would more often than you realize.  You think like an engineer when you choose to buy a 4-pack of canned tuna for $3 instead of 4 individual cans for $1 apiece.  You may not calculate the exact cost-per-can difference ($1 vs 75 cents), but something in your brain tells you that the 4-pack is a better deal. In this example, you are solving a problem (you want some tuna), subject to the constraints (you must buy tuna at the grocery store), efficiently (you choose the tuna that gives you the best deal).

Sometimes, we don’t think like an engineer, even though we should.. How many times have you driven around the block in search of the cheapest gasoline? Consider the following two options: a nearby gas station is selling gas for $2.60 per gallon, while a station 2.5 miles away is offering a price of $2.50 per gallon.  Which would you choose? Would you even consider that during your fill-up you will only buy about 10 gallons of gas, and therefore only save $1? Not to mention the extra 5 miles you’ve put on your car (for the round trip), the time you’ve spent driving 5 miles, AND the gas you consume driving those 5 miles. Going to either gas station will solve your problem by filling up your tank, but the closer, more expensive station is clearly more efficient than the further, cheaper station.

Driving somewhere on the freeway is another example of a simple problem which you can solve like an engineer. Imagine you want to make a 100-mile journey as fast as possible. You intuitively know that the amount of time it takes to travel a certain distance depends on your average speed. The faster you drive, the sooner you arrive. Therefore, one option is to redline your vehicle the entire way, drive 150 miles per hour and arrive at your destination in 40 minutes. Obviously, this is not feasible because there are other considerations, such as the law, safety, and your fuel efficiency. Another option is to play it safe, avoid the highway and make the drive at 40 mph. This way, you get there in 2.5 hours; longer than you would like, but at least you are still alive with your driver’s license. The best solution exists somewhere in the middle of these extremes.

So how do you find the happy medium? Engineers specialize in graphing all possible solutions for visualization. To make such a graph, you need the relevant equation, which is distance traveled equals velocity multiplied by time. You need to rearrange the equation to isolate the dependent variable (time) as a function of the independent variable (speed); time = distance/speed.  Here’s what it looks like for a 100-mile journey:


Looking at this graph offers a few benefits. For one, it becomes easy to compare several solutions. If you drive 60 mph your trip takes 1 hour, 40 minutes. Going 70 mph saves you 15 minutes compared to going 60. You also learn gain valuable insight about the problem. Notice that the faster you drive, the less time you save. In other words, driving 50 mph vs 40 mph saves 30 minutes, while driving 80 mph vs 70 mph only saves 11 minutes. Therefore, you might conclude that the risk of speeding does not outweigh the small payoff.

Bringing it back to my thesis of this blog, anyone can think like an engineer. Engineering isn’t difficult. It seems difficult, because most engineers like to shroud what they do in fancy math-speak to seem important. Don’t let them fool you, their thought process is no more difficult than choosing a can of tuna fish from the grocery store.