Posts Tagged ‘excerptedquote’

Why American medicine still runs on fax machines

Wednesday, March 14th, 2018

Why American medicine still runs on fax machines Great article explains how the inability to kill the “cockroach of American medicine” illustrates the incentives or anti-incentives toward data sharing & interoperability HT @DShaywitz

“Competitive pressure between the companies that sell electronic record makers themselves only made things worse. The electronic record makers don’t have much incentive to connect well with other records, when they’d rather just convert that hospital on a different electronic platform into one of their own customers.

“When you want competing entities to share information, you have to realize that they’re sharing things that could help their competitors” “If [electronic record vendors] expended all that time and effort to make it so anyone could plug into any other system, it’s reducing the advantage of staying on your particular network,” Mostashari says.

This is especially true for larger electronic medical record companies, which want to sell the advantages of joining a record that is used in lots of doctor offices. “You want to make it easier for people to say, ‘Hey, if you’re on [our electronic record], look how awesome it is! You can talk to any user, anywhere in the country,” he argues.

In short, economics gave hospitals plenty of reasons not to connect their records with other hospitals — to stick with a clunky
technology, like fax, that makes it hard to transmit information. And the government didn’t give any incentives to connect — it stopped at digitizing medicine, falling short of the interoperability that patients actually want.

Thought experiments | The Economist

Sunday, February 25th, 2018

Thought experiments Amazing progress in Brain-computer interfaces (#BCIs): paralyzed patients manipulating silverware. Communicating w/ “locked-in” individuals. Will this scale?

Brain-computer interfaces sound like the stuff of science fiction. Andrew Palmer sorts the reality
from the hype

IN THE gleaming facilities of the Wyss Centre for Bio and
Neuroengineering in Geneva, a lab technician takes a well plate out of an incubator. Each well contains a tiny piece of brain tissue derived from human stem cells and sitting on top of an array of electrodes. …
To see these signals emanating from disembodied tissue is weird. The firing of a neuron is the basic building block of intelligence. ..

This symphony of signals is bewilderingly complex. There are as many as 85bn neurons in an adult human brain, and a typical neuron has 10,000 connections to other such cells. The job of mapping these connections is still in its early stages. But as the brain gives up its secrets, remarkable possibilities have opened up: of decoding neural activity and using that code to control external devices.


The iPhone, the Pixel, and the tragic anxiety of having to choose

Sunday, February 25th, 2018

The iPhone, the Pixel, & the tragic anxiety of having to choose, by
@vladSavov Mostly agreed with the comparison (better iOS interface v fantastic $GOOG camera) but feel gmail is definitely better on Android. My solution: carry both!

“Android’s way of consolidating notifications from the same person or app is vastly superior to iOS’s massive bubble for every single message, Twitter like, or email. When I wake in the morning with the Pixel, I get a complete account of what I’ve missed just from my lock screen: a dozen unread emails, three Telegram chats,

When I want to actively use my phone, though, my hand tends to sneak toward the iPhone. Twitter, Slack, Telegram, and Speedtest each have meaningfully superior apps for iOS than Android….BBC iPlayer Radio consistently streams live content 30 seconds earlier on iOS, and Gmail for iOS fetches emails faster than Gmail on Android. And it looks better, dammit!”

Imaging Without Lenses

Sunday, February 4th, 2018

Imaging Without Lenses Computational #photography w. compressive sensing (reconstruction from arbitrary image bases) & diffractive imaging (forming an image via scattering from gratings) via @AmSciMag


Computational Imaging

As its name suggests, the key advance in this new paradigm is the essential role played by computation in the formation of the final digital image. …
When the orbiting Hubble Space Telescope first sent its photos to Earth in the late 1980s, the images were far blurrier than expected; it quickly became apparent that something was wrong with the telescope optics. NASA scientists diagnosed the optical problems and, in the years before the unmanned telescope could be repaired, designed sophisticated digital processing algorithms to correct the images by compensating for many of the effects of flawed optics.

In the mid-1990s, W. Thomas Cathey and Edward R. Dowski, Jr., realized that one could go further still: One could intentionally design optics to produce blurry, “degraded” optical images, but degraded in such a way that special digital processing would produce a final digital image as good as, or even better than, those captured using
traditional optics

Diffraction for Imaging

One class of lensless devices for imaging macroscopic objects relies on miniature gratings consisting of steps in thickness in a
transparent material (glass or silicate) that delay one portion of the incident light wave with respect to another portion. The pattern of steps expresses special mathematical properties that uniquely ensure that the pattern of light in the material does not depend much on the wavelength of the light and thus upon the unintended variations in thickness arising during the manufacture of the glass. …The light from the scene
diffracts through the grating, yielding a pattern of light on the array that does not appear like a traditional image—it does not “look good” but instead more like a diffuse blob, unintelligible to the human eye. Nevertheless, the blob contains enough visual information (albeit in an unusual distribution) such that the desired image can be reconstructed through a computational process called image

Compressive Sensing

….An optical image on a sensor is just a
complicated signal that can be represented as a list of numbers and processed digitally. Just as a complicated sound can be built up from a large number of simpler sounds, each added in a proportion that depends on the sound in question, so too can an image be built up from lots of simpler images. …

Enter compressive sensing. Theoretical results from statisticians have shown that, as long as the information from the scene is redundant (and the image is thus compressible), one does not need to measure such mathematically elegant bases, but can use measurements from a suitably random one. If such “coded measurements” are available then one can still exploit the idea that the signal can be well represented in the elegant basis elements (such as cosines or wavelets) and recover the image through compressive sensing.

The Dark Bounty of Texas Oil

Sunday, January 28th, 2018

The Dark Bounty of Texas Oil The development of #fracking & horizontal drilling by Mitchell et al. is perhaps not appreciated as a major tech success of late 20th century (up there w/ the web & iPod!) but it did radically change the #energy economy

“In 1954, Mitchell obtained a contract to supply ten per cent of Chicago’s natural-gas needs. However, the producing wells operated by his company, Mitchell Energy & Development, were declining. He needed to discover new sources of petroleum, or else.

A safer and more precise method, developed in the seventies, was to use jets of fluid, under intense pressure, to create micro-cracks in the strata, typically in limestone or sandstone. Expensive gels or foams were generally used to thicken the fluid, and biocide was added to kill the bacteria that can clog the cracks. A granular substance called “proppant,” made of sand or ceramics, was pumped into the cracks, keeping pathways open so that the hydrocarbons could make it to the surface. The process, which came to be known as hydraulic fracturing, or fracking, jostled loose the captured oil or gas molecules, but the technology had a fatal flaw: it was too costly to turn a profit in shale.

In 1981, Mitchell drilled his first fracked well in the Barnett shale, the C. W. Slay No. 1. It lost money, as did many wells that followed it.

To cut costs, one of Mitchell’s engineers, Nick Steinsberger, began tinkering with the fracking-fluid formula. He reduced the quantity of gels and chemicals, making the liquid more watery, and added a cheap lubricant, polyacrylamide…

Mitchell combined his new fracking formula with horizontal-drilling techniques that had been developed offshore; once you bored deep enough to reach a deposit, you could direct the bit into the oil- or gas-bearing seam, a far more efficient means of recovery. In 1998, one of Mitchell’s wells in the Barnett, S. H. Griffin No. 4, made a profit. The shale revolution was under way. Soon the same fracking techniques that Mitchell had pioneered in gas were applied to oil.”

The world economy
was in danger of being held captive to oil states that were often intensely anti-American. Then, around the time that Barack Obama became President, U.S. production shot back up, approaching its all-time peak. On Fowler’s graph, it looked like a flagpole. “In the span of five years, we go from 5.5 million barrels a day to 9.5 million, almost doubling the U.S. output,”…The difference, Fowler said, was advanced fracking techniques and horizontal drilling. …
The town used to be called Clark, but a decade ago its mayor made a deal with a satellite network to provide ten years of free basic service to the two hundred residents, in return for renaming the town after the company. Satellite dishes still sit atop many houses there, and even though the agreement has expired the town’s name remains: dish.


Google Sells A.I. for Building A.I. (Novices Welcome) – The New York Times

Sunday, January 28th, 2018

$GOOG Sells AI for Building #AI QT: “Humans must label the data before the system can
learn…once images…labeled…[it] operates w/o human
involvement…It can build a model from scratch.” How can one preview this? Will it be integrated into gphotos?

Initially, Google will open this service only to a small group of businesses.

But sometimes, there is no substitute for good old human labor. With Google’s new service, humans must label the data before the system can learn from it. …

Google says that once images are labeled, its new service operates without human involvement….Given more time, it
can build a model from scratch, specifically for the problem at hand.

If you are a zoologist who wants an algorithm that identifies jaguars and giraffes, said Fei-Fei Li, chief scientist inside the Google cloud group, all you have to do is supply the right images. “You upload jaguars and giraffes,” she said. “And you are done.”

New York City’s Bold, Flawed Attempt to Make Algorithms Accountable

Sunday, January 21st, 2018

NYC’s Bold, Flawed Attempt to Make #Algorithms Accountable QT: “#NYC should commit to demanding openness in all future contracts with vendors of these algorithmic services…It’s a dereliction of duty to allow vital decisions to be made by a black box.”

“Frank Pasquale,… told me much the same. “While the terms of past contracts are hard to revisit, New York City should commit to demanding openness in all future contracts with venders of these algorithmic services,” he said. “They have the leverage here, not the firms. Secrecy may incentivize tiny gains in efficiency, but those are not worth the erosion of legitimacy and public confidence in government. It’s a dereliction of duty to allow vital decisions to be made by a black box.”

Cathy O’Neil, the author of “Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy,” told me. “What we’re finding is that the world of algorithms is one ugly wormhole.” In insulating algorithms and their creators from public scrutiny, rather than responding to civic concerns about bias and discrimination, the existing system “propagates the myth that those algorithms are objective and fair,” O’Neil said. “There’s no reason to believe either.””

Opinion | At the Solstice, in Praise of Darkness

Sunday, January 21st, 2018

At the Solstice, in Praise of Darkness QT: “Imagine a…movie…[capturing] the position of the setting sun…throughout the yr….[the sun] would migrate…betw its southernmost & northernmost positions on the horizon [&]…slow down toward the extremes.”

“When this cycle was first explained to me as a child, my teacher advised me to imagine the “leaning” Earth as it arcs through its annual orbit around the sun….But such
illustrations, however useful, make it easy to overlook the loveliest aspect of this Thursday: that a solstice is in fact a moment of rest.

What stops at the December solstice is the sun’s apparent southward and night-lengthening (or night-shortening, in the Southern
Hemisphere) march across the sky. The true meaning of “solstice” — indeed, the word’s Latin roots refer to the stilling of the sun — was made clear to me by George Greenstein…He asked me to imagine a continuous movie composed of photographs that capture the position of the setting sun (the rising sun would work equally well) throughout the year.

In this movie…the setting sun would migrate back and forth between its southernmost and northernmost positions on the horizon. The sun would accelerate toward the middle of its journey (around spring and autumn, when the lengths of the day and the night change most quickly) and slow down toward the extremes. Once the sun reached an endpoint, it would at last come to rest — as it will on Thursday — before its motion reversed.

How bike-sharing conquered the world

Sunday, January 14th, 2018

“Health benefits are harder to quantify, especially in smoggy cities like Beijing. Mobike has found that its bikes are used more or less as much when the air is really bad as when it is not, suggesting that the good done by exercise may be undone by heavy breathing in toxic air. But in less-polluted cities the gains from exercise are larger than the risks from road accidents or air pollution, according to a study of Barcelona in the British Medical Journal.

How #bikesharing conquered the world Using tech to overcome the problem of theft. Getting health benefits from exercise to counterbalancing breathing polluted air. Reducing congestion a bit.

Alignment-free sequence comparison: benefits, applications, and tools

Monday, November 13th, 2017

Might be useful for noncoding comparisons

Alignment-free seq. comparison: benefits, apps & tools Great tidbits, viz: Shannon asked von Neumann what to call his info measure – “Why don’t you call it entropy…no one understands entropy…so in any discussion, you’ll be in a position of advantage.”

“Reportedly, Claude Shannon, who was a mathematician working at Bell Labs, asked John von Neumann what he should call his newly developed measure of information content; “Why don’t you call it entropy,” said von Neumann, “[…] no one understands entropy very well so in any discussion you will be in a position of advantage […]” []. The concept of Shannon entropy came from the observation that some English words, such as “the” or “a”, are very frequent and thus unsurprising” ….
“The calculation of a distance between sequences using complexity (compression) is relatively straightforward (Fig. ). This procedure takes the sequences being compared (x = ATGTGTG and y = CATGTG) and concatenates them to create one longer sequence (xy = ATGTGTGCATGTG). If x and y are exactly the same, then the complexity (compressed length) of xy will be very close to the complexity of the individual x or y. However, if x and y are dissimilar, then the complexity of xy (length of compressed xy) will tend to the cumulative complexities of x and y.”

“Intriguingly, BLOSUM matrices, which are the most commonly used substitution matrix series for protein sequence alignments, were found to have been miscalculated years ago and yet produced significantly better alignments than their corrected modern version (RBLOSUM) []; this paradox remains a mystery.”