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Trump and the History of Xenophobia in America
Dr. Dan-el Padilla Peralta, a former undocumented immigrant himself, argues that Trump's acolytes need to take a look into their own ancestral mirror before passing judgement on America's immigrants.
Born in Santo Domingo, Dominican Republic, Dan-el Padilla Peralta came to the United States with his family at the age of four and remained in the country when his visa expired, thus making him an undocumented immigrant.. He received his BA summa cum laude from Princeton University, where he was chosen salutatorian of the class of 2006. He received his MPhil from the University of Oxford and his PhD in classics from Stanford University. He is currently a Mellon Research Fellow at Columbia University. His memoir Undocumented: A Dominican Boy’s Odyssey from a Homeless Shelter to the Ivy League was published in July 2015.
Dan-el Padilla Peralta: It's common in public circles and in public discussions, notably those fueled by figures such as Donald Trump, to mischaracterize immigrants and say things like well they should have, especially the undocumented, they should have waited their turn in line or a language to that effect. But one of the ordeals immigrants, undocumented and documented face is that there is no one line. There is no one set path. There are multiplicities of the paths; each of them is complicated, in some cases dismally complicated. And sorting that out requires all this kind of prior knowledge that many immigrants don't have and resources that many of immigrants don't have. Those who are in support of Donald Trump or have lent their support to Donald Trump for now, I would say that the very first thing they need to do is to speak to some undocumented immigrants, to really have a conversation with them. I'd be happy to talk to more of them. And the reason why they should consider having this conversation is because it is always good to get the other side, even if one thinks that Trump happens to be completely right, it would be good of you to have a slightly different or markedly different perspective on things. And after you get that perspective you can see where you side.
But there are other reasons why it's important to push back against Trump and it's important for those who have been supporting him to rethink their commitment to Trump's immigration statements in particular. One has to do with the long, long history of xenophobia in the United States, a xenophobia that has touched many of the ancestors of those people who currently support Trump. It is easy when one settles into life in the United States and one has children and grandchildren who are pursuing the American dream to efface or begin blurring out the traumas of the immigration experience. Because everyone wants to be an American and that means well you sort of forget what your grandparents or great grandparents went through when they were immigrants. But I would encourage them to do some archival research in their own families; to begin asking around; to ask their grandparents, or, if they happen to be around, their great grandparents or great aunts and uncles to discuss what they experienced when they first arrived in this country. And they'll begin realizing that things were pretty grim in part because of nativist and xenophobic sentiment — especially those who happened to be descended from Irish immigrants or Italian immigrants might have some really bracing stories that they can share. And it's in this way by thinking both to our collected past as a nation and thinking about our past as an immigrant nation that we can begin to push back against some of Trump's more noxious statements.
Dr. Dan-el Padilla Peralta is a former undocumented immigrant and current postdoctoral fellow at Columbia University. His new memoir Undocumented recounts the events that allowed a young Dominican kid living past his visa in New York City to eventually graduate from Princeton as salutatorian.
In this video interview, Dr. Padilla argues that Donald Trump's acolytes need to take a good hard look into their own ancestral mirror before passing judgment on American immigrants. There's a long history of xenophobia in this country, he explains, and many of the people dishing it out today are the descendants of folks targeted by it in prior generations.
If machines develop consciousness, or if we manage to give it to them, the human-robot dynamic will forever be different.
- Does AI—and, more specifically, conscious AI—deserve moral rights? In this thought exploration, evolutionary biologist Richard Dawkins, ethics and tech professor Joanna Bryson, philosopher and cognitive scientist Susan Schneider, physicist Max Tegmark, philosopher Peter Singer, and bioethicist Glenn Cohen all weigh in on the question of AI rights.
- Given the grave tragedy of slavery throughout human history, philosophers and technologists must answer this question ahead of technological development to avoid humanity creating a slave class of conscious beings.
- One potential safeguard against that? Regulation. Once we define the context in which AI requires rights, the simplest solution may be to not build that thing.
Duke University researchers might have solved a half-century old problem.
- Duke University researchers created a hydrogel that appears to be as strong and flexible as human cartilage.
- The blend of three polymers provides enough flexibility and durability to mimic the knee.
- The next step is to test this hydrogel in sheep; human use can take at least three years.
Duke researchers have developed the first gel-based synthetic cartilage with the strength of the real thing. A quarter-sized disc of the material can withstand the weight of a 100-pound kettlebell without tearing or losing its shape.
Photo: Feichen Yang.<p>That's the word from a team in the Department of Chemistry and Department of Mechanical Engineering and Materials Science at Duke University. Their <a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/adfm.202003451" target="_blank">new paper</a>, published in the journal,<em> Advanced Functional Materials</em>, details this exciting evolution of this frustrating joint.<br></p><p>Researchers have sought materials strong and versatile enough to repair a knee since at least the seventies. This new hydrogel, comprised of three polymers, might be it. When two of the polymers are stretched, a third keeps the entire structure intact. When pulled 100,000 times, the cartilage held up as well as materials used in bone implants. The team also rubbed the hydrogel against natural cartilage a million times and found it to be as wear-resistant as the real thing. </p><p>The hydrogel has the appearance of Jell-O and is comprised of 60 percent water. Co-author, Feichen Yang, <a href="https://today.duke.edu/2020/06/lab-first-cartilage-mimicking-gel-strong-enough-knees" target="_blank">says</a> this network of polymers is particularly durable: "Only this combination of all three components is both flexible and stiff and therefore strong." </p><p> As with any new material, a lot of testing must be conducted. They don't foresee this hydrogel being implanted into human bodies for at least three years. The next step is to test it out in sheep. </p><p>Still, this is an exciting step forward in the rehabilitation of one of our trickiest joints. Given the potential reward, the wait is worth it. </p><p><span></span>--</p><p><em>Stay in touch with Derek on <a href="http://www.twitter.com/derekberes" target="_blank">Twitter</a>, <a href="https://www.facebook.com/DerekBeresdotcom" target="_blank">Facebook</a> and <a href="https://derekberes.substack.com/" target="_blank">Substack</a>. His next book is</em> "<em>Hero's Dose: The Case For Psychedelics in Ritual and Therapy."</em></p>
What would it be like to experience the 4th dimension?
Physicists have understood at least theoretically, that there may be higher dimensions, besides our normal three. The first clue came in 1905 when Einstein developed his theory of special relativity. Of course, by dimensions we’re talking about length, width, and height. Generally speaking, when we talk about a fourth dimension, it’s considered space-time. But here, physicists mean a spatial dimension beyond the normal three, not a parallel universe, as such dimensions are mistaken for in popular sci-fi shows.
An algorithm may allow doctors to assess PTSD candidates for early intervention after traumatic ER visits.
- 10-15% of people visiting emergency rooms eventually develop symptoms of long-lasting PTSD.
- Early treatment is available but there's been no way to tell who needs it.
- Using clinical data already being collected, machine learning can identify who's at risk.
The psychological scars a traumatic experience can leave behind may have a more profound effect on a person than the original traumatic experience. Long after an acute emergency is resolved, victims of post-traumatic stress disorder (PTSD) continue to suffer its consequences.
In the U.S. some 30 million patients are annually treated in emergency departments (EDs) for a range of traumatic injuries. Add to that urgent admissions to the ED with the onset of COVID-19 symptoms. Health experts predict that some 10 percent to 15 percent of these people will develop long-lasting PTSD within a year of the initial incident. While there are interventions that can help individuals avoid PTSD, there's been no reliable way to identify those most likely to need it.
That may now have changed. A multi-disciplinary team of researchers has developed a method for predicting who is most likely to develop PTSD after a traumatic emergency-room experience. Their study is published in the journal Nature Medicine.
70 data points and machine learning
Image source: Creators Collective/Unsplash
Study lead author Katharina Schultebraucks of Columbia University's Department Vagelos College of Physicians and Surgeons says:
"For many trauma patients, the ED visit is often their sole contact with the health care system. The time immediately after a traumatic injury is a critical window for identifying people at risk for PTSD and arranging appropriate follow-up treatment. The earlier we can treat those at risk, the better the likely outcomes."
The new PTSD test uses machine learning and 70 clinical data points plus a clinical stress-level assessment to develop a PTSD score for an individual that identifies their risk of acquiring the condition.
Among the 70 data points are stress hormone levels, inflammatory signals, high blood pressure, and an anxiety-level assessment. Says Schultebraucks, "We selected measures that are routinely collected in the ED and logged in the electronic medical record, plus answers to a few short questions about the psychological stress response. The idea was to create a tool that would be universally available and would add little burden to ED personnel."
Researchers used data from adult trauma survivors in Atlanta, Georgia (377 individuals) and New York City (221 individuals) to test their system.
Of this cohort, 90 percent of those predicted to be at high risk developed long-lasting PTSD symptoms within a year of the initial traumatic event — just 5 percent of people who never developed PTSD symptoms had been erroneously identified as being at risk.
On the other side of the coin, 29 percent of individuals were 'false negatives," tagged by the algorithm as not being at risk of PTSD, but then developing symptoms.
Image source: Külli Kittus/Unsplash
Schultebraucks looks forward to more testing as the researchers continue to refine their algorithm and to instill confidence in the approach among ED clinicians: "Because previous models for predicting PTSD risk have not been validated in independent samples like our model, they haven't been adopted in clinical practice." She expects that, "Testing and validation of our model in larger samples will be necessary for the algorithm to be ready-to-use in the general population."
"Currently only 7% of level-1 trauma centers routinely screen for PTSD," notes Schultebraucks. "We hope that the algorithm will provide ED clinicians with a rapid, automatic readout that they could use for discharge planning and the prevention of PTSD." She envisions the algorithm being implemented in the future as a feature of electronic medical records.
The researchers also plan to test their algorithm at predicting PTSD in people whose traumatic experiences come in the form of health events such as heart attacks and strokes, as opposed to visits to the emergency department.