Lifeboat Foundation: Safeguarding Humanity
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Category: mobile phones – Page 86

Early detection and identification of pathogenic bacteria in food and water samples are essential to public health. Bacterial infections cause millions of deaths worldwide and bring a heavy economic burden, costing more than 4 billion dollars annually in the United States alone. Among pathogenic bacteria, Escherichia coli (E. coli) and other coliform bacteria are among the most common ones, and they indicate fecal contamination in food and water samples. The most conventional and frequently used method for detecting these bacteria involves culturing of the samples, which usually takes 24 hours for the final read-out and needs expert visual examination. Although some methods based on, for example, the amplification of nucleic acids, can reduce the detection time to a few hours, they cannot differentiate live and dead bacteria and present low sensitivity at low concentrations of bacteria. That is why the U.S. Environmental Protection Agency (EPA) approves no nucleic acid-based bacteria sensing method for screening water samples.

In an article recently published in ACS Photonics, a journal of the American Chemical Society (ACS), a team of scientists, led by Professor Aydogan Ozcan from the Electrical and Computer Engineering Department at the University of California, Los Angeles (UCLA), and co-workers have developed an AI-powered smart bacterial colony detection system using a thin-film transistor (TFT) array, which is a widely used technology in mobile phones and other displays.

The ultra-large imaging area of the TFT array (27 mm × 26 mm) manufactured by researchers at Japan Display Inc. enabled the system to rapidly capture the growth patterns of bacterial colonies without the need for scanning, which significantly simplified both the hardware and software design. This system achieved ~12-hour time savings compared to gold-standard culture-based methods approved by EPA. By analyzing the microscopic images captured by the TFT array as a function of time, the AI-based system could rapidly and automatically detect colony growth with a deep neural network. Following the detection of each colony, a second neural network is used to classify the species.

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By Subscription? – In California, You Can and it’s a Tesla Model 3 EV.

A Santa Monica, California-based company can put you into a Tesla Model 3 using its cellphone app which is now available for both Android and iPhones. The company offering the Car-as-a-service (CaaS) model is Autonomy. Although currently available only in California, the future plans include rolling it out to other U.S. states.

Until the outset of the global pandemic, owning a car was on a dramatic decline. Ride-sharing was exploding, and because cars were becoming pricier, young people entering the workforce were less inclined to join their parents’ generation of car owners.

Isolation and lockdowns temporarily took drivers off the road, as did sticker shock. The latter has been particularly true for electric vehicles (EV) which without government rebates and incentives can cost tens of thousands of dollars more than cars running on gasoline and diesel.

Continue reading “Want to Get Your Next Car” | >

At the heart of every resonator—be it a cello, a gravitational wave detector, or the antenna in your cell phone—there is a beautiful bit of mathematics that has been heretofore unacknowledged.

Yale physicists Jack Harris and Nicholas Read know this because they started finding knots in their data.

In a new study in the journal Nature, Harris, Read, and their co-authors describe a previously unknown characteristic of resonators. A is any object that vibrates only at a specific set of frequencies. They are ubiquitous in sensors, electronics, musical instruments, and other devices, where they are used to produce, amplify, or detect vibrations at specific frequencies.

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EPFL researchers have used swarms of drones to measure city traffic with unprecedented accuracy and precision. Algorithms are then used to identify sources of traffic jams and recommend solutions to alleviate traffic problems.

Given the wealth of modern technology available—roadside cameras, big-data algorithms, Bluetooth and RFID connections, and smartphones in every pocket—transportation engineers should be able to accurately measure and forecast . However, current tools advance towards the direction of showing the symptom but systematically fail to find the root cause, let alone fix it. Researchers at EPFL utilize a monitoring tool that overcomes many problems using drones.

“They provide excellent visibility, can cover large areas and are relatively affordable. What’s more, they offer greater precision than GPS technology and eliminate the behavioral biases that occur when people know they’re being watched. And we use drones in a way that protects people’s identities,” says Manos Barmpounakis, a post-doc researcher at EPFL’s Urban Transport Systems Laboratory (LUTS).

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As meetings shifted online during the COVID-19 lockdown, many people found that chattering roommates, garbage trucks and other loud sounds disrupted important conversations.

This experience inspired three University of Washington researchers, who were roommates during the pandemic, to develop better earbuds. To enhance the speaker’s voice and reduce , “ClearBuds” use a novel microphone system and one of the first machine-learning systems to operate in real time and run on a smartphone.

The researchers presented this project June 30 at the ACM International Conference on Mobile Systems, Applications, and Services.

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A cutting-edge AI development that could boost smartphone battery life by 30 percent and shave countless kilowatts from energy bills will be unveiled to technology giants. The ground-breaking University of Essex-developed work has been rolled into an app called EOptomizer—which will be demonstrated to expert researchers and designers as well as major manufacturing companies like Nokia and Huawei.

It is hoped the EOptomizer app will be adapted across the industry and help drive down , by making consumers’ goods last longer.

It will do this by using software to dramatically increasing efficiency and reliability in phones, tablets, cars, smart fridges and computers’ batteries—delaying when consumers need to buy carbon-footprint-producing replacements. The event—which takes place in Robinson College, in Cambridge, on 11July—will showcase the impact EOptomizer could have across the globe.

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According to the study, smart TV sets surpassed personal computers in 2021. After smartphones, TVs are the most used device to access the Internet — from 37% of users in 2019 to 50% last year. This increase was observed in almost all analyzed demographic strata, mainly among those aged 35 to 44 (59%), users from the North Region of Brazil (45%), and women (51%). In total, 74 million individuals accessed the Internet using their television sets, an increase of 25 million users during last year.

The survey also revealed the prevalence of exclusive smartphone use to access the Internet (64% of users). According to the research, smartphones have been the main Internet access device in Brazil since 2015, and between 2019 and 2021 there was an increase of 6 percentage points in the exclusive use of phones to go online.

The exclusive use of smartphones to access the web is higher among Brazilians living in rural areas (83%), in the Northeast Region of the country (75%), black individuals (65%), those aged 60 years and over (80%), and the poorest segments of the population (89%). Among lower middle class users, access to the Internet exclusively via smartphones increased from 61% in 2019 to 67% in 2021, reaching 51 million people.

View pictures in App save up to 80% data. An illustration of tiny wedge-shaped robots – collectively known as Sensing With Independent Micro-Swimmers (SWIM) – deployed into the ocean miles below a lander on the frozen surface of an ocean world data-image-width=982 data-image-height=726 An illustration of tiny wedge-shaped robots – collectively known as Sensing With Independent Micro-Swimmers (SWIM) – deployed into the ocean miles below a lander on the frozen surface of an ocean world NASA has unveiled a plan to unleash swarms of cellphone-sized robots to hunt for alien life on other planets.

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