Visualizing the Origin of Elements
Most of us are familiar with the periodic table of elements from high school chemistry. We learned about atoms, and how elements combine to form chemical compounds. But perhaps a lesser-known aspect is where these elements actually come from.
Today’s periodic table showing the origin of elements comes to us from Reddit user u/only_home, inspired by an earlier version created by astronomer Jennifer Johnson. It should be noted that elements with multiple sources are shaded proportionally to reflect the amount of said element produced from each source.
Let’s dive into the eight origin stories in more detail.
The Big Bang
The universe began as a hot, dense region of radiant energy about 14 billion years ago. It cooled and expanded immediately after formation, creating the lightest and most plentiful elements: hydrogen and helium. This process also created trace amounts of lithium.
Low Mass Stars
At the beginning of their lives, all stars create energy by fusing hydrogen atoms to form helium. Once the hydrogen is depleted, stars fuse helium into carbon and expand to become red giants.
From this point on, the journey of a low and a high mass star differs. Low mass stars reach a temperature of roughly one million kelvin and continue to heat up. Outer layers of helium and hydrogen expand around the carbon core until they can no longer be contained by gravity. These gas layers, known as a planetary nebula, are ejected into space. It is thought that a low mass star’s death creates many heavy elements such as lead.
Exploding White Dwarfs
In the wake of this planetary nebula expulsion, a carbon core known as a “white dwarf” remains with a temperature of about 100,000 kelvin. In many cases, a white dwarf will simply fade away.
Sometimes, however, white dwarfs gain enough mass from a nearby companion star to become unstable and explode in a Type 1a supernova. This explosion likely creates heavier elements such as iron, nickel, and manganese.
Exploding Massive Stars
Massive stars evolve faster and generate much more heat. In addition to forming carbon, they also create layers of oxygen, nitrogen, and iron. When the core contains only iron, which is stable and compact, fusion ceases and gravitational collapse occurs. The star reaches a temperature of over several billion kelvin—resulting in a supernova explosion. Astronomers speculate that a variety of elements, including arsenic and rubidium, are formed during such explosions.
Exploding Neutron Stars
When a supernova occurs, the star’s core collapses, crushing protons and neutrons together into neutrons. If the mass of a collapsing star is low enough—about four to eight times that of the sun—a neutron star is formed. In 2017, it was discovered that when these dense neutron stars collide, they create heavier elements such as gold and platinum.
Cosmic Ray Spallation
The shockwaves from supernova explosions send cosmic rays, or high energy atoms/subatomic particles, flying through space. When these cosmic rays hit another atom at nearly the speed of light, they break apart and form a new element. The elements of lithium, beryllium, and boron are products of this process.
Supernova explosions also create very heavy elements with unstable nuclei. Over time, these nuclei eject a neutron or proton, or a neutron decays into a proton and electron. This process is known as radioactive decay and often creates lighter, more stable elements such as radium and francium.
Not Naturally Occurring
There are currently 26 elements on the periodic table that are not naturally occurring; instead, these are all created synthetically in a laboratory using nuclear reactors and particle accelerators. For example, plutonium can be created when fast-moving neutrons collide with a common uranium isotope in a nuclear reactor.
Discoveries Yet to be Made
There is still some uncertainty as to where elements with a middle-range atomic number—neither heavy nor light—come from. As scientific breakthroughs emerge, we will continue to learn more about the elements that make up the mass of our solar system.
How Many People Die Each Day?
COVID-19 deaths can be hard to interpret without context. This graphic shows how many people die each day globally, by cause.
How Many People Die Each Day?
As the COVID-19 pandemic rages on, the media continues to rattle off statistics at full force.
However, without a frame of reference, numbers such as the death toll can be difficult to interpret. Mortalities attributed to the virus, for example, are often measured in the thousands of people per day globally—but is this number a little or a lot, relative to typical causes of death?
Today’s graphic uses data from Our World in Data to provide context with the total number of worldwide daily deaths. It also outlines how many people who die each day from specific causes.
Worldwide Deaths by Cause
Nearly 150,000 people die per day worldwide, based on the latest comprehensive research published in 2017. Which diseases are the most deadly, and how many lives do they take per day?
Here’s how many people die each day on average, sorted by cause:
|#4||Lower respiratory infections||7,010|
|#24||Alcohol use disorders||507|
|#25||Drug use disorders||456|
|#30||Heat (hot and cold exposure)||146|
|Total Daily Deaths||147,118|
Cardiovascular diseases, or diseases of the heart and blood vessels, are the leading cause of death. However, their prominence is not reflected in our perceptions of death nor in the media.
While the death toll for HIV/AIDS peaked in 2004, it still affects many people today. The disease causes over 2,600 daily deaths on average.
Interestingly, terrorism and natural disasters cause very few deaths in relation to other causes. That said, these numbers can vary from day to day—and year to year—depending on the severity of each individual instance.
Total Daily Deaths by Country
On a national level, these statistics vary further. Below are the total deaths from all causes for selected countries, based on 2017 data.
China and India both see more than 25,000 total deaths per day, due to their large populations.
However, with 34.7 daily deaths per million people each day, Russia has the highest deaths proportional to population out of any of these countries.
While these numbers help provide some context for the global scale of COVID-19 deaths, they do not offer a direct comparison.
The fact is that many of the aforementioned death rates are based on much larger and consistent sample sizes of data. On the flipside, since WHO declared COVID-19 a pandemic on March 11, 2020, daily confirmed deaths have fallen in a wide range between 272 and 10,520 per day—and there is no telling what could happen in the future.
On top of this variance, data on confirmed COVID-19 deaths has other quirks. For example, testing rates for the virus may vary between jurisdictions, and there have also been disagreements between authorities on how deaths should even be tallied in the first place. This makes getting an accurate picture surprisingly complicated.
While it’s impossible to know the true death toll of COVID-19, it is clear that in some countries daily deaths have reached rates 50% or higher than the historical average for periods of time:
Time, and further analysis, will be required to determine a more accurate COVID-19 death count.
11 Cognitive Biases That Influence Political Outcomes
Humans are hardwired to make mental mistakes called cognitive biases. Here are common biases that can shape political opinion, and even elections.
Cognitive Biases in the Political Arena
With the 2020 U.S. presidential election fast approaching, many people will be glued to the 24-hour news cycle to stay up to date on political developments. Yet, when searching for facts, our own cognitive biases often get in the way.
If this isn’t problematic enough, third parties can also take advantage of these biases to influence our thinking. The media, for example, can exploit our tendency to assign stereotypes to others by only providing catchy, surface-level information. Once established in our minds, these generalizations can be tough to shake off.
Such tactics can have a powerful influence on public opinion if applied consistently to a broad audience. To help us avoid these mental pitfalls, today’s infographic from PredictIt lists common cognitive biases that influence the realm of politics, beginning with the “Big Cs”.
The First C: Confirmation Bias
People exhibit confirmation bias when they seek information that only affirms their pre-existing beliefs. This can cause them to become overly rigid in their political opinions, even when presented with conflicting ideas or evidence.
When too many people fall victim to this bias, progress towards solving complex sociopolitical issues is thwarted. That’s because solving these issues in a bipartisan system requires cooperation from both sides of the spectrum.
A reluctance towards establishing a common ground is already widespread in America. According to a 2019 survey, 70% of Democrats believed their party’s leaders should “stand up” to President Trump, even if less gets done in Washington. Conversely, 51% of Republicans believed that Trump should “stand up” to Democrats.
In light of these developments, researchers have conducted studies to determine if the issue of confirmation bias is as prevalent as it seems. In one experiment, participants chose to either support or oppose a given sociopolitical issue. They were then presented with evidence that was conflicting, affirming, or a combination of both.
In all scenarios, participants were most likely to stick with their initial decisions. Of those presented with conflicting evidence, just one in five changed their stance. Furthermore, participants who maintained their initial positions became even more confident in the superiority of their decision—a testament to how influential confirmation bias can be.
The Second C: Coverage Bias
Coverage bias, in the context of politics, is a form of media bias where certain politicians or topics are disproportionately covered. In some cases, media outlets can even twist stories to fit a certain narrative.
For example, research from the University of South Florida analyzed media coverage on President Trump’s 2017 travel ban. It was discovered that primetime media hosts covered the ban through completely different perspectives.
Each host varied drastically in tone, phrasing, and facts of emphasis, […] presenting each issue in a manner that aligns with a specific partisan agenda.
—Josepher, Bryce (2017)
Charting the ideological placement of each source’s audience can help us gain a better understanding of the coverage bias at work. In other words, where do people on the left, middle, and right get their news?
The horizontal axis in this graphic corresponds to the Ideological Consistency Scale, which is composed of 10 questions. For each question, respondents are assigned a “-1” for a liberal response, “+1” for a conservative response, or a “0” for other responses. A summation of these scores places a respondent into one of five categories:
|Consistently conservative||+7 to +10|
|Mostly conservative||+3 to +6|
|Mixed||-2 to +2|
|Mostly liberal||-6 to -3|
|Consistently liberal||-10 to -7|
Overcoming coverage bias—which dovetails into other biases like confirmation bias—may require us to follow a wider variety of sources, even those we may not initially agree with.
The Third C: Concision Bias
Concision bias is a type of bias where politicians or the media selectively focus on aspects of information that are easy to get across. In the process, more nuanced and delicate views get omitted from popular discourse.
A common application of concision bias is the use of sound bites, which are short clips that can be taken out of a politician’s speech. When played in isolation, these clips may leave out important context for the audience.
Without the proper context, multi-faceted issues can become extremely polarizing, and may be a reason for the growing partisan divide in America. In fact, there is less overlap in the political values of Republicans and Democrats than ever previously measured.
In 1994, just 64% of Republicans were more conservative than the median Democrat. By 2017, that margin had grown considerably, to 95% of Republicans. The same trend can be found on the other end of the spectrum. Whereas 70% of Democrats were more liberal than the median Republican in 1994, this proportion increased to 97% by 2017.
Overcoming Our Biases
Achieving full self-awareness can be difficult, especially when new biases emerge in our constantly evolving world. So where do we begin?
Simply remembering these mental pitfalls exist can be a great start—after all, we can’t fix what we don’t know. Individuals concerned about the upcoming presidential election may find it useful to focus their attention on the Big Cs, as these biases can play a significant role in shaping political beliefs. Maintaining an open mindset and diversifying the media sources we follow are two tactics that may act as a hedge.
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