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ScienceDaily

A wearable device so thin and soft you won’t even notice it

Wearable human-machine interfaces — devices that can collect and store important health information about the wearer, among other uses — have benefited from advances in electronics, materials and mechanical designs. But current models still can be bulky and uncomfortable, and they can’t always handle multiple functions at one time.

Researchers reported Friday, Aug. 2, the discovery of a multifunctional ultra-thin wearable electronic device that is imperceptible to the wearer.

The device allows the wearer to move naturally and is less noticeable than wearing a Band-Aid, said Cunjiang Yu, Bill D. Cook Associate Professor of Mechanical Engineering at the University of Houston and lead author for the paper, published as the cover story in Science Advances.

“Everything is very thin, just a few microns thick,” said Yu, who also is a principal investigator at the Texas Center for Superconductivity at UH. “You will not be able to feel it.”

It has the potential to work as a prosthetic skin for a robotic hand or other robotic devices, with a robust human-machine interface that allows it to automatically collect information and relay it back to the wearer.

That has applications for health care — “What if when you shook hands with a robotic hand, it was able to instantly deduce physical condition?” Yu asked — as well as for situations such as chemical spills, which are risky for humans but require human decision-making based on physical inspection.

While current devices are gaining in popularity, the researchers said they can be bulky to wear, offer slow response times and suffer a drop in performance over time. More flexible versions are unable to provide multiple functions at once — sensing, switching, stimulation and data storage, for example — and are generally expensive and complicated to manufacture.

The device described in the paper, a metal oxide semiconductor on a polymer base, offers manufacturing advantages and can be processed at temperatures lower than 300 C.

“We report an ultrathin, mechanically imperceptible, and stretchable (human-machine interface) HMI device, which is worn on human skin to capture multiple physical data and also on a robot to offer intelligent feedback, forming a closed-loop HMI,” the researchers wrote. “The multifunctional soft stretchy HMI device is based on a one-step formed, sol-gel-on-polymer-processed indium zinc oxide semiconductor nanomembrane electronics.”

Video: https://www.youtube.com/watch?time_continue=3&v=kC5gtHH33Lw

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Materials provided by University of Houston. Original written by Jeannie Kever. Note: Content may be edited for style and length.

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Hackster.io

Close Encounters of the MIDI LED Matrix Kind

As seen in the element14 Presents video below, Dave Darko was printing a volcano model, while eating a giant plate of something resembling scrambled eggs, when he noticed that his printer was making a distinct sound that “means something.” When hearing automated machinery like this, one’s brain does seem to try to pick out patterns or even messages, and in this case it apparently leading into him building a model of the famous sound/light device from Close Encounters of the Third Kind.

Input for Darko’s rig is via a miniature keyboard, which pipes signals to the setup’s Arduino Micro. This activates a series of programmable LED strips, arranged to light up a 3D-printed and laser-cut 12 x 6 matrix diffuser. In addition to its MIDI input, it features a microphone as well. The Arduino does a FFT (fast Fourier transform) with this info and lights the appropriate LEDs accordingly. Although playing the Close Encounters tune would get old after a while, the matrix looks like a really excellent way to visualize sound, and it could be a fun unit to mount next to your stereo.

In MIDI mode, signals are also passed along to Darko’s computer that functions to actually play the sounds, as his keyboard (and presumably many other instruments) does not make noise when in MIDI mode. If you’d like to make your own, design files and a parts list are found here.

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Author: Jeremy S. Cook

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Thingiverse

Collapsing Pirate Sword (Print in Place)

Collapsing Pirate Sword

This is a collapsing sword designed to be printed as one part. Its only 142mm high when printed but expands to over 860mm in total length! It also makes a really cool noise as it expands as a result of the layer lines rubbing together which really takes people off guard.

The sword is designed to be printed with a ,4mm nozzle, so the blade will be two shells thick. I had weird issues with blobs and zits at retraction which I normally don’t have until I turned on “wipe” and “coast”. I think this is a result of the thin walls with a narrow amount of clearance between the blade segments. Every printer is different but I had good luck with .15mm coast and 3mm wipe, on my MK3.

This is the second collapsing sword, you can find the first version here. This version is a little trickier then the first as the guard on the hilt can cause issues. It gets a little flimsy at the top so make sure you have z-hop turned on in case it curls.

I have included a blank template of the sword in a “STL” as well as a “STP” file so you can make you own designs! Please post a remix so I can make one too! 🙂

5/1/18 ~If it helps anyone out, I added a file named “test print”. If this works, you shouldn’t have a issue. If it fuses together, I would suggest adjusting your cost and wipe settings.

I also added a extended version. Its the same length, the blade comes out further. I thought that some peoples swords did not extend as far as mine. If you want to give this one a try go ahead and let me know the results.

Additional versions:
Broadsword
Katana
Dagger
Lightsaber (Print in Place)
Lightsaber (Removable Blade)
Sith Lightsaber (removeable blade)

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ScienceDaily

Quantum entanglement in chemical reactions? Now there’s a way to find out

Scientists have long suspected that a quantum phenomenon might play a role in photosynthesis and other chemical reactions of nature, but don’t know for sure because such a phenomenon is so difficult to identify.

Purdue University researchers have demonstrated a new way to measure the phenomenon of entanglement in chemical reactions — the ability of quantum particles to maintain a special correlation with each other over a large distance.

Uncovering exactly how chemical reactions work could bring ways to mimic or recreate them in new technologies, such as for designing better solar energy systems.

The study, published on Friday (Aug. 2) in Science Advances, generalizes a popular theorem called “Bell’s inequality” to identify entanglement in chemical reactions. In addition to theoretical arguments, the researchers also validated the generalized inequality through a quantum simulation.

“No one has experimentally shown entanglement in chemical reactions yet because we haven’t had a way to measure it. For the first time, we have a practical way to measure it,” said Sabre Kais, a professor of chemistry at Purdue. “The question now is, can we use entanglement to our advantage to predict and control the outcome of chemical reactions?”

Since 1964, Bell’s inequality has been widely validated and serves as a go-to test for identifying entanglement that can be described with discrete measurements, such as measuring the orientation of the spin of a quantum particle and then determining if that measurement is correlated with another particle’s spin. If a system violates the inequality, then entanglement exists.

But describing entanglement in chemical reactions requires continuous measurements, such as the various angles of beams that scatter the reactants and force them to contact and transform into products. How the inputs are prepared determines the outputs of a chemical reaction.

Kais’ team generalized Bell’s inequality to include continuous measurements in chemical reactions. Previously, the theorem had been generalized to continuous measurements in photonic systems.

The team tested the generalized Bell’s inequality in a quantum simulation of a chemical reaction yielding the molecule deuterium hydride, building off of an experiment by Stanford University researchers that aimed to study the quantum states of molecular interactions, published in 2018 in Nature Chemistry.

Because the simulations validated the Bells’s theorem and showed that entanglement can be classified in chemical reactions, Kais’ team proposes to further test the method on deuterium hydride in an experiment.

“We don’t yet know what outputs we can control by taking advantage of entanglement in a chemical reaction — just that these outputs will be different,” Kais said. “Making entanglement measurable in these systems is an important first step.”

The study is based on work supported by the U.S. Department of Energy, Office of Basic Energy Sciences, under award number DE-SC0019215.

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Materials provided by Purdue University. Original written by Kayla Wiles. Note: Content may be edited for style and length.

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Hackster.io

Maxim Integrated SIMO Webinar 中文

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3D Printing Industry

Carnegie Mellon advances FRESH 3D bioprinting to rebuild the heart

Scientists from Carnegie Mellon University (CMU), Pennsylvania, have used a novel 3D bioprinting method to build functional parts of the human heart.  According to a study published in Science, an advanced version of Freeform Reversible Embedding of Suspended Hydrogels (FRESH) technology was developed to 3D print collagen for small blood vessels, valves, and beating ventricles.  […]

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Author: Tia Vialva

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ScienceDaily

AI reveals new breast cancer types that respond differently to treatment

Scientists have used artificial intelligence to recognise patterns in breast cancer — and uncovered five new types of the disease each matched to different personalised treatments.

Their study applied AI and machine learning to gene sequences and molecular data from breast tumours, to reveal crucial differences among cancers that had previously been lumped into one type.

The new study, led by a team at The Institute of Cancer Research, London, found that two of the types were more likely to respond to immunotherapy than others, while one was more likely to relapse on tamoxifen.

The researchers are now developing tests for these types of breast cancer that will be used to select patients for different drugs in clinical trials, with the aim of making personalised therapy a standard part of treatment.

The researchers previously used AI in the same way to uncover five different types of bowel cancer and oncologists are now evaluating their application in clinical trials.

The aim is to apply the AI algorithm to many types of cancer — and to provide information for each about their sensitivity to treatment, likely paths of evolution and how to combat drug resistance.

The new research, published today (Friday) in the journal NPJ Breast Cancer, could not only help select treatments for women with breast cancer but also identify new drug targets.

The Institute of Cancer Research (ICR) — a charity and research institute — funded the study itself from its own charitable donations.

The majority of breast cancers develop in the inner cells that line the mammary ducts and are ‘fed’ by the hormones oestrogen or progesterone. These are classed as ‘luminal A’ tumours and often have the best cure rates.

However, patients within these groups respond very differently to standard-of-care treatments, such as tamoxifen, or new treatments — needed if patients relapse — such as immunotherapy.

The researchers applied the AI-trained computer software to a vast array of data available on the genetics, molecular and cellular make-up of primary luminal A breast tumours, along with data on patient survival.

Once trained, the AI was able to identify five different types of disease with particular patterns of response to treatment.

Women with a cancer type labelled ‘inflammatory’ had immune cells present in their tumours and high levels of a protein called PD-L1 — suggesting they were likely to respond to immunotherapies.

Another group of patients had ‘triple negative’ tumours — which don’t respond to standard hormone treatments — but various indicators suggesting they might also respond to immunotherapy.

Patients with tumours that contained a specific change in chromosome 8 had worse survival than other groups when treated with tamoxifen and tended to relapse much earlier — after an average of 42 months compared to 83 months in patients who had a different tumour type that contained lots of stem cells. These patients may benefit from an additional or new treatment to delay or prevent late relapse.

The markers identified in this new study do not challenge the overall classification of breast cancer — but they do find additional differences within the current sub-divisions of the disease, with important implications for treatment.

The use of AI to understand cancer’s complexity and evolution is one of the central strategies the ICR is pursuing as part of a pioneering research programme to combat the ability of cancers to adapt and become drug resistant. The ICR is raising the final £15 million of a £75 million investment in a new Centre for Cancer Drug Discovery to house a world-first programme of ‘anti-evolution’ therapies.

Study leader Dr Anguraj Sadanandam, Team Leader in Systems and Precision Cancer Medicine at The Institute of Cancer Research, London, said:

“We are at the cusp of a revolution in healthcare, as we really get to grips with the possibilities AI and machine learning can open up.

“Our new study has shown that AI is able to recognise patterns in breast cancer that are beyond the limit of the human eye, and to point us to new avenues of treatment among those who have stopped responding to standard hormone therapies. AI has the capacity to be used much more widely, and we think we will be able to apply this technique across all cancers, even opening up new possibilities for treatment in cancers that are currently without successful options.”

Dr Maggie Cheang, a pioneer in identifying different types of breast cancer and Team Leader of the Genomic Analysis Clinical Trials Team at The Institute of Cancer Research, London, said:

“Doctors have used the current classification of breast cancers as a guide for treatment for years, but it is quite crude and patients who seemingly have the same type of the disease often respond very differently to drugs.

“Our study has used AI algorithms to spot patterns within breast cancers that human analysis had up to now missed — and found additional types of the disease that respond in very particular ways to treatment.

“Among the exciting implications of this research is its ability to pick out women who might respond well to immunotherapy, even when the broad classification of their cancer would suggest that these treatments wouldn’t work for them.

“The AI used in our study could also be used to discover new drugs for those most at risk of late relapse, beyond 5 years, which is common in oestrogen-linked breast cancers and can cause considerable anxiety for patients.”

As well as ICR charity funding, the work was also supported by the NIHR Biomedical Research Centre at The Institute of Cancer Research, London, and The Royal Marsden NHS Foundation Trust.

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Hackster.io

SparkFun Artemis Unboxing // MCU Monday

Check it out – one powerful new module for AI on the edge, FOUR different ways to use it! This little powerhouse comes with 48 pins, Bluetooth 5, and tons of bells and whistles: Qwiic connector, MEMS mic, tons of power options… or mount it onto your own custom board! We’re pretty excited about this one.

// https://blog.hackster.io/say-hello-to-the-sparkfun-artemis-2af46ecfddec
// https://www.sparkfun.com/products/15376
// https://learn.sparkfun.com/tutorials/artemis-development-with-arduino
// https://github.com/sparkfun/Arduino_Apollo3
// https://learn.sparkfun.com/tutorials/designing-with-the-sparkfun-artemis
// https://github.com/uTensor/uTensor
// https://www.hackster.io/videos/164
// https://www.tensorflow.org/lite/microcontrollers/overview
// https://aiweirdness.com/post/174211306032/metal-band-or-my-little-pony

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Kennedy Christian

Wednesday 31st July 2019 Kennedy HS

Up on today’s agenda? #drones #smiles #soldering We made a raptor claw cookie cutter, golf ball prototype, broke a drone in under 4 minutes and Cole coached his mother in making a wiring harness. Another successful #makerspace at Kennedy Catholic High School.

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ScienceDaily

Clearing up the ‘dark side’ of artificial leaves

While artificial leaves hold promise as a way to take carbon dioxide — a potent greenhouse gas — out of the atmosphere, there is a “dark side to artificial leaves that has gone overlooked for more than a decade,” according to Meenesh Singh, assistant professor of chemical engineering in the University of Illinois at Chicago College of Engineering.

Artificial leaves work by converting carbon dioxide to fuel and water to oxygen using energy from the sun. The two processes take place separately and simultaneously on either side of a photovoltaic cell: the oxygen is produced on the “positive” side of the cell and fuel is produced on the “negative” side.

Singh, who is the corresponding author of a new paper in ACS Applied Energy Materials, says that current artificial leaves are wildly inefficient. They wind up converting only 15% of the carbon dioxide they take in into fuel and release 85% of it, along with oxygen gas, back to the atmosphere.

“The artificial leaves we have today aren’t really ready to fulfill their promise as carbon capture solutions because they don’t capture all that much carbon dioxide, and in fact, release the majority of the carbon dioxide gas they take in from the oxygen-evolving ‘positive’ side,” Singh said.

The reason artificial leaves release so much carbon dioxide back to the atmosphere has to do with where the carbon dioxide goes in the photoelectrochemical cell.

When carbon dioxide enters the cell, it travels through the cell’s electrolyte. In the electrolyte, the dissolved carbon dioxide turns into bicarbonate anions, which travel across the membrane to the “positive” side of the cell, where oxygen is produced. This side of the cell tends to be very acidic due to splitting of water into oxygen gas and protons. When the bicarbonate anions interact with the acidic electrolyte at the anodic side of the cell, carbon dioxide is produced and released with oxygen gas.

Singh noted that a similar phenomenon of carbon dioxide release occurring in the artificial leaf can be seen in the kitchen when baking soda (bicarbonate solution) is mixed with vinegar (acidic solution) to release a fizz of carbon dioxide bubbles.

To solve this problem, Singh, in collaboration with Caltech researchers Meng Lin, Lihao Han and Chengxiang Xiang, devised a system that uses a bipolar membrane that prevents the bicarbonate anions from reaching the “positive” side of the leaf while neutralizing the proton produced.

The membrane placed in between the two sides of the photoelectrochemical cell keeps the carbon dioxide away from the acidic side of the leaf, preventing its escape back into the atmosphere. Artificial leaves using this specialized membrane turned 60% to 70% of the carbon dioxide they took in into fuel.

“Our finding represents another step in making artificial leaves a reality by increasing utilization of carbon dioxide,” Singh said.

Earlier this year, Singh and colleagues published a paper in ACS Sustainable Chemistry & Engineering, where they proposed a solution to another problem with artificial leaves: current models use pressurized carbon dioxide from tanks, not the atmosphere.

He proposed another specialized membrane that would allow the leaves to capture carbon dioxide directly from the atmosphere. Singh explains that this idea, together with the findings reported in this current publication on using more of the carbon dioxide captures, should help make artificial leaf technology fully implementable.

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Materials provided by University of Illinois at Chicago. Note: Content may be edited for style and length.

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