According to a research paper published in Nature Communications, the concentration of micro-plastics in Antarctica is 10 times higher than assumed, which suggests that there is a presence of 12-21 million of it in the ocean. It is the first study which points towards the issue.

Any plastic which is less than 5 millimetres in diameter comes under micro-plastic and can enter the ocean through various methods in which the most famous are through cosmetic, clothing and industrial processes.

Only three common types of plastic wastes – polythene, polypropylene and polystyrene, used for packaging purposes were studied. As per the studies, across 65 years, 17 million of waste has polluted the ocean covering 10,000 kilometres and currently 80 % of the garbage constitutes micro-plastics.

The research was carried on by researchers of the National Oceanography Center from the UK who used spectroscopic imaging technique for pinpointing the plastic residuals and 200 metres deep water was filtered up for the process. They also raised concern over the issue by indicating towards it that every year 8 million tonnes of micro-plastic invade the ocean and if this keeps going on then the amount will become identical to the number of fishes in the ocean.

The rising popularity of JavaScript has carried with it many improvements and today’s landscape of web development is dramatically different. The stuff we can do on the web today with JavaScript running on the site, as well as in the application, were difficult to imagine just a few years ago, even encapsulated in sandboxed settings such as Flash or Java Applets.

In a single sentence: Node.js shines over websockets in real-time web applications utilizing push technology. What is it that is so revolutionary? Okay, after more than 20 years of stateless-web based on the stateless request-response model, we finally have web applications with real-time, two-way communications, where both client and server may initiate contact, enabling them to openly exchange data. This is in sharp contrast to the typical network response paradigm, where contact is always facilitated by the recipient. In fact, it’s all based on the open web stack (HTML , CSS and JS) running across the regular 80 channel.

Node.js’ main idea: use non-blocking, event-driven I / O to remain lightweight and efficient when confronted with data-intensive real-time applications running across distributed devices. How that also means say is that Node.js is not a silver-bullet modern technology that controls the field of web growth. It’s just a forum that meets a common need.

You certainly don’t want to use Node.js for CPU-intensive operations; using it for heavy computation would annul almost all of its obvious benefits. Where Node really shines is in building fast , scalable network applications, so that’s equipped to handle a huge number of concurrent connections with high throughput.

It is pretty interesting how this operates under-the-hood. Node.js acts as a single thread, using non-blocking I / O calls, helping it to accept tens of thousands of concurrent connections kept in the event loop compared to traditional web-serving approaches where each link creates a new thread, taking up machine RAM before ultimately maxing-out at the amount of RAM accessible.

Now a very popular question regarding node.js- is it used for front-end or backend? Node.js is effectively a runtime environment for Chrome built on the V8 Javascript engine, implying that Javascript can be omitted from a browser’s execution background. To draw a very vague analogy, Node.js is to Javascript, which is what JRE is to Java, (although not a very appropriate comparison). How you would like to leverage Node.js is dependent on you. Since it can operate Javascript outside a window background and also has the ability to run a non-blocking I / O-based HTTP server (with the aid of Http libraries) that it offers out of the box, it can be used in back-end/server-side scenarios.

Also you can use Node.js in the front end so as to simplify your daily tasks including construct, running unit tests of your front end code. Frameworks like Grunt, Gulp, Bower exploit features in Node.js so as to improve and enhance the software development.

Even actually Angular 2 uses Node.js to install packages and compile Typescript to Javascript. Therefore, Node.js can be used in both front-end and back-end scenarios in practice, but in essence it has been developed to serve the purpose where Javascript can be used on the server side to develop web applications, resulting in a single language for both front-end and back-end development.

Also you can use Node.js in the front end so as to simplify your daily tasks including construct, running unit tests of your front end code. Frameworks like Grunt, Gulp, Bower exploit features in Node.js so as to improve and enhance the software development.

Even actually Angular 2 uses Node.js to install packages and compile Typescript to Javascript. Therefore, Node.js can be used in both front-end and back-end scenarios in practice, but in essence it has been developed to serve the purpose where Javascript can be used on the server side to develop web applications, resulting in a single language for both front-end and back-end development.

Hope this helps.

A lot of pollution is caused due to the use of petrol and diesel in vehicles. This is the reason why the government is trying to use its alternate options like bio and green fuel. A step towards this is that a trial has been made to make green fuel from bamboo. National Green Tribunal (NGT) has given a go ahead to a bamboo based ethanol project. Through the Ministry of Environment, Forest and Climate Change, NGT has been given permission to make ethanol using bamboo in Golaghat, Assam. NGT chief A.K. Goyal has said that using bamboo fuel will help in reducing pollution. It will be an alternate option for petrol and diesel which will help in controlling the pollution level.

Powerful transformation serves as a tool for both patients and provider–and that trend will continue over the next decade. So if AI is unlikely to supplant trusted doctors and must accommodate patient data privacy, where will the big changes happen?

AI in Five Years: Smarter Machines and Virtual Assistant

Incremental jumps in technology will increase the ubiquity and strength of the examples above, but where will the real change happen?

Consider how much happens behind-the-scenes when working with a virtual assistant on your smartphone. From voice recognition that learns your voice to combing through live search results to leveraging past behaviours to sharing results across devices—this unfolds instantly and most of us never even consider the AI-powered how.

“Imagine you go to the hospital for a PET scan or MRI,” said Scott Tease, Lenovo’s executive director of High-Performance Computing and Artificial Intelligence.

“Before the doctor or technician reviews the images, an algorithm will interpret the data and flag every irregularity.

This accelerates the caregivers’ efforts, draws their attention to issues, and helps ensure nothing is overlooked. In fact, these processes are under review by regulatory bodies right now.”

Enhanced resolution and analysis will allow remote scanning and diagnosis — even of small and subtle symptoms. Doctors may be more apt to embrace this use of AI, but what about the deluge of tracking data?

The prospect of health-tracking devices automatically pinging clinics with potential concerns raises more than a few eyebrows.

We may also see the growing demand for “convenience”—everything available at your fingertips through a website or app—reshape low-risk patient care. Here, AI may lead to chatbot-style physician care, where a series of targeted questions combined with biometrics will help people find the right care. Telemedicine, of course, made consulting a doctor from the comfort of home possible years ago, but an electronic physician could radically reduce cost. Even if a real person steps in to review and approve, an AI-led interview and data assessment would certainly increase efficiency.

“Convenience, risk assessment, and accuracy all play a role.

We’re not likely to see the chatbot approach take over for anything with dangerous symptoms.”

AI in 10 Years: Personalized, Globally Accessible Medicine

Assume that the changes outlined so far march forward, driven by advances in technology and wider adoption. Misconceptions about AI will also continue to erode, and successful deployment of AI-assisted technology. Who can guess how fleets of autonomous vehicles smoothly navigating city streets and highways will change perception?

AI also notoriously employs a so-called “black box”—the essential genius of deep-learning unfolds behind a closed curtain. We know the input and output, of course, but seldom the step-by-step process of the AI reaching its conclusion. It can be difficult to trust an answer when the underlying work is hidden (and may contain accidental bias).

Trust will likely grow over the next decade, but even without that embrace, things may wildly transform—as much as possible in the regulated world of medicine. Mapping a genome opens a window into inherited conditions, susceptibility to disease, potential response to treatment, and countless other insights. But the process takes time and the considerable might of high-performance computers.

https://youtu.be/vLNhCaGDab4