Artificial Embryos

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Artificial mouse embryo

Artificial mouse embryo after 48 hours (right) and 96 hours, with embryonic tissue in red and extra-embryonic tissue in blue

Sarah Harrison and Gaelle Recher, Zernicka-Goetz Lab, University of Cambridge

Artificial mouse embryos grown from stem cells in a dish could help unlock secrets of early development and infertility that have until now evaded us.

Magdalena Zernicka-Goetz at the University of Cambridge and her team made the embryos using embryonic stem cells, the type of cells found in embryos that can mature into any type of tissue in the body.

The trick was to grow these alongside trophoblast stem cells, which normally produce the placenta. By growing these two types of cell separately and then combining them in a special gel matrix, the two mixed and started to develop together.

After around four-and-a-half days, the embryos resembled normal mouse embryos that were about to start differentiating into different body tissues and organs.

“They are very similar to natural mouse embryos,” says Zernicka-Goetz. “We put the two types of stem cells together – which has never been done before – to allow them to speak to each other. We saw that the cells could self-organise themselves without our help.”

This is the first time something resembling an embryo has been made from stem cells, without using an egg in some way. Techniques such as cloning, as done for Dolly the sheep and other animals, bypass the need for sperm, but still require an egg cell.

Body plan

The artificial embryos are providing new insights into how embryos organise themselves and grow, says Zernicka-Goetz. The team engineered the artificial embryos so the cell types fluoresced in different colours, to reveal their movements and behaviour as the embryos go through crucial changes.

Mammal embryos were already known to start as a symmetrical ball, then elongate, form a central cavity and start developing a type of cell layer called mesoderm, which ultimately goes on to form bone and muscle.

“We didn’t know before how embryos form this cavity, but we’ve now found the mechanism for it and the sequential steps by which it forms,” says Zernicka-Goetz. “It’s building up the foundations for the whole body plan.”

“The work is a great addition to the stem cell field and could be extended to human stem cell populations,” says Leonard Zon at Boston Children’s Hospital, Massachusetts. “Using the system, the factors that participate in embryo development could be better studied and this could help us understand early events of embryogenesis.”

But Robin Lovell-Badge at the Francis Crick Institute in London says that the embryos lack two other types of cell layer required to develop the bodies’ organs: ectoderm, which forms skin and the central nervous system, and endoderm, which makes our internal organs.

Zernicka-Goetz hopes to see these types of cell layers develop in future experiments by adding stem cells that normally form the yolk sac, a third structure involved in embryonic development, to the mix.

Hidden steps

If a similar feat can be achieved using human stem cells, this could tell us much about the earliest stages of our development. Current research is limited by the number of excess embryos that are donated from IVF procedures. But the new technique could produce a limitless supply, making it easier to conduct in-depth research. These artificial embryos may also be easier to tinker with, to see what effect different factors have in early embryogenesis.

Disrupting development in this way may provide new insights into the causes of abnormal embryo development and miscarriage. “You would be able to understand the principles that govern each stage of development. These are not normally accessible, because they happen inside the mother,” says Zernicka-Goetz.

But it is doubtful that this work could ever lead to fully grown babies in the lab. Lovell-Badge says the artificial embryos are unlikely to develop in vitro much further than shown in the study, as they would soon need the supply of nutrients and oxygen that a placenta normally channels from the mother.

“We’re not planning to make a mouse in the lab using stem cells,” says Zernicka-Goetz. But she is hopeful that adding yolk sac stem cells will allow these artificial embryos to survive long enough to study the beginnings of organs like the heart.

Read more: Artificial Human Embryos Are Coming, and No One Knows How to Handle Them

 

Read more: Artificial Human Embryos Are Coming, and No One Knows How to Handle Them

Read more: It’s time to relax the rules on growing human embryos in the lab

Journal reference: Science, DOI: 10.1126/science.aal1810

This entry was posted in SCI & TECH, Science, Videos.

RBI bans Bitcoin and other virtual currencies

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A day after the Reserve Bank of India (RBI) barred banks from dealing in cryptocurrencies, investors rushed to square off positions and sought advice on how much tax they should pay on returns made in FY18 and if they can do so before the July-end deadline.

The worry is that they may be left holding the virtual currency if they don’t sell it now and transfer the money into their bank accounts. They also fear a crackdown by tax authorities and other government agencies, experts said.

Bitcoin exchanges such as Zebpay and CoinSecure saw a spike in transaction volumes of about 40%, with about 90% of that being on the sell side, sources said.

The Reserve Bank of India (RBI) has effectively banned any dealings in  cryptocurrency via banks or e-wallets in the country stating “dealing with or providing services to any individuals or business entities dealing with or settling virtual currencies.”

Nischal Shetty, CEO of  WazirX , a Bitcoin and crytocurrency exchange said: “Blockchain technology and cryptocurrencies are going to define the future of financial technology and the way money operates. While the security features intact in the blockchain technology have been acknowledged by the Finance Minister himself, the latest mandate by the Reserve Bank of India, discouraging Indians from dealing in cryptocurrencies, is quite disheartening. More so, since in the recent past, the RBI had seemed to be favourably predisposed towards supporting new, innovative and tech-driven processes.
“While India continues to debate and hold back the mainstreaming of cryptocurrencies, our global counterparts in the USA, Japan, South Korea etc are moving forward and regulating cryptos. By supporting blockchain and cryptocurrency, RBI could have given Indians an opportunity to be at the forefront of a global phenomenon, act ahead of time and be future-secured with our own set of digital assets.”
The central bank said in its statement that virtual currencies (VCs), also variously referred to as cryptocurrencies and crypto assets, raise concerns of consumer protection, market integrity, and money laundering, among others.
“The RBI statement will negatively impact startups, because no matter how great an idea they have, investors will be wary of putting money into a crypto-venture given their uncertain future in uncertain regulatory environments,” said Nehaa Chaudhari, Public Policy Lead, TRA, a technology policy and law firm.
After these RBI guidelines, Shetty added that this will exclude India from global crypto revolution. There will be massive wealth erosion of all the tax paying people who have invested in cryptocurrencies.
“Gullible investors will now try to buy cryptos through cash and other OTC means where they would have no buyer protection and end up falling for scams. This will also make illegal trades almost impossible to track,” said Shetty.
Atulya Bhatt, Co-founder of BuyUcoin, a multi cryptocurrency wallet and exchange, said: “There will be a parallel economy and in few months people will find unregulated ways of cashing out. Some investors are in utter shock because the government has given only three months to handle the transactions. ”
As for startups, he said, “It disturbed the whole structure of crypto exchanges. We have plans and we are discussing it. But banning it is an unfair step.”
“The alternate way for the cryptocurrency exchange will be to do crypto to crypto trading,” said Bhatt.
Ravi Kikan, COO, Panaesha Capital, said: “If you look at the complete circular it first talks about RBI exploring the desirability and feasibility of introducing its own crypto currency (a fiat-digital one). In fact, it has set up a panel to review the proposal and come up with suggestions by June.

“The RBI is more concerned about the other side of negatives like speculative trading, Consumer protection, Ponzi Schemes, Money laundering and terror financing that can pop up through this un regulated market, which I think is a very fair stand to safeguard the public at large. In the long run keeping the above in light the digital currencies which have a certain usefulness towards their utility/usage will be the ones that will have a shot at the silverline and more prone to acceptability.”
In its budget speech, Finance Minister Arun Jaitley clarified in his budget speech that it is not a legal tender and the government will discourage its use. However, he had mentioned that the government will look at the utilisation of blockchain.

This entry was posted in Market.

Trade Setup for Wednesday: Top 15 things to know before Opening Bell

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The index formed a Doji type of pattern after a strong bullish candle which suggests that the momentum could take a pause.

The Nifty climbed its crucial resistance level of 10400 on Tuesday but lost momentum towards the close of the session and made a ‘Doji’ type of candlestick pattern on the daily charts.

The index formed a Doji type of pattern after a strong bullish candle which suggests that the momentum could take a pause; hence, for bulls to remain control Nifty should hold above 10,348 levels.

A ‘Doji’ is formed when the index opens and then closes approximately around the same level but remain volatile throughout the day which is indicated by its long shadow on either side. It appears like a cross or a plus sign.

The Nifty index opened at 10412 and rose to an intraday high of 10424. It slipped below 10400 in intraday trade to record its intraday low of 10381 before closing the day at 10,402, up 22 points.

 “Despite positive global cues Nifty lacked follow-through buying which should be a cause for concern as it registered a Doji kind of indecisive formation after moving in an extremely narrow range of around 45 points,” Mazhar Mohammad, Chief Strategist – Technical Research & Trading Advisory, Chartviewindia.in, told Moneycontrol.

“The Nifty may be in need of a breather as momentum oscillators on short-term charts are in an extremely overbought zone and hence unless it gets past its 50-Day Simple Moving Average, whose value is placed around 10438, which successfully curtailed its up move in the past,” he said.

Mohammad further added that bulls may not pick up momentum going forward and a close below 10348 shall confirm short-term weakness in the indices. Hence, it looks prudent for traders to book profits and remain on sidelines till such a breakout occurs above 10450 on a closing basis.

India VIX fell down up 2.51 percent at 14.49. A decline in VIX suggests a range bound move with limited upside as well downside in the market.

We have collated the top 15 data points to help you spot profitable trades:

Key support and resistance level for Nifty

The Nifty closed at 10,402.2 on Tuesday. According to Pivot charts, the key support level is placed at 10,380.87, followed by 10,359.53. If the index starts moving upwards, key resistance levels to watch out are 10,424.17 and 10,446.13.

Nifty Bank

The Nifty Bank index closed at 25,226.8. The important Pivot level, which will act as crucial support for the index, is placed at 25,138.04, followed by 25,049.27. On the upside, key resistance levels are placed at 25,297.74, followed by 25,368.67.

Call Options data

In terms of open interest, the 10,500 call option has seen the most call writing so far at 41.66 lakh contracts. This could act as a crucial resistance level for the index in the April series.

The second-highest buildup has taken place in the 11,000 Call option, which has seen 38.76 lakh contracts getting written so far. The 10,700 Call option has accumulated 36.25 lakh contracts.

Call writing was seen at the strike price of 10,500, which added 2.03 lakh contracts, followed by 10,600, which added 1.13 lakh contracts, and 10,400, which added 1 lakh contracts.

Call unwinding was seen at the strike price of 10,300, which shed 2.89 lakh contracts.

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Put Options data

Maximum open interest in put options was seen at a strike price of 10,000, in which 45.66 lakh contracts been added till date. This could be a crucial resistance level for the index in April series.

The 10,200 put option comes next, having added 39.24 lakh contracts so far, and the 10,300 put option, which has now accumulated 38.76 lakh contracts.

During the session, put writing was seen the most at a strike price of 10,400, with 9.73 lakh contracts being added, followed by 10,300, which added 6.33 lakh contracts and 10,200 with 3.01 lakh contracts.

There was hardly any Put unwinding seen.

Image2

FII & DII data:

Foreign institutional investors (FIIs) sold shares worth Rs 684.99 crore, while domestic institutional investors bought shares worth Rs 653.65 crore in the Indian equity market, as per provisional data available on the NSE.

Fund flow picture:

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Stocks with high delivery percentage:

High delivery percentage suggests that investors are accepting delivery of the stock, which means that investors are bullish on it.

Image4

68 stocks saw long buildup

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38 stocks saw short covering:

A decrease in open interest along with an increase in price mostly indicates short covering.

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57 stocks saw short build-up:

An increase in open interest along with a decrease in price mostly indicates build-up of short positions.

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45 stocks saw long unwinding

Image8

Bulk Deals:

VRL Logistics Limited: Morgan Stanley Mauritius Company Ltd sold 5,26,393 shares at Rs 389.22 per share

Apl Apollo Tubes Ltd: WF Asian Reconnaissance Fund Limited bought 2,64,000 shares at Rs 2140 per share

Supreme Industries Ltd: Smallcap World Fund INC sold 17,99,545 shares at Rs 1205 per share.

(For more bulk deals click here)

Analyst or Board Meet/Briefings:

Indian Hotels: At a public event, the company met around 17 institutional investors on April 10, 2018.

Mahindra & Mahindra: BOB Capital Markets along with several other funds and investors will meet the company between April 11 and 12, 2018.

Stocks in news:

Tech Mahindra: Balbix tie up with the company for artificial intelligence-based cyber security platform

Dr Reddy’s Labs: Company gets EIR from USFDA for Cuernavaca plant in Mexico

Punjab National Bank: Fitch has Downgraded PNB’s Viability Rating To ‘BB-‘; Maintains Rating Watch Negative

Calix, Infosys Enter Strategic CoCreation Partnership to Accelerate Time to Market for New Capabilities on AXOS Platform

Max Life: Company leads race to buy IDBI Federal Life stake

MRPL: Company trims oil purchase deal with Saudi Aramco: Sources

JSW Steel, AION get creditors’ nod for Monnet Ispat takeover

2 stocks under ban period on NSE

Security in ban period for the next day’s trade under the F&O segment includes companies in which the security has crossed 95 percent of the market-wide position limit.

For April 11, 2018 Jet Airways and Balrampur Chini are present in this list.

This entry was posted in Market.

Buy, Sell, Hold: 6 stocks and 2 sectors are on investors’ radar on April 10, 2018

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Tata Motors, Wipro and Adani Ports, among others, are being tracked by analysts on Tuesday.

Moneycontrol News@moneycontrolcom

Tata Motors

Brokerage: Kotak Sec | Rating: Maintain Buy | Target: Cut to Rs 465 from Rs 520

The brokerage house highlighted how weakness in UK and Europe hit JLR sales and volumes there declined by 8 percent year on year in March. It further stated that the outperformance by new models was offset by steep decline in volumes of existing models. It has lowered its FY19-20 consolidated EPS estimates by 17-22 percent. Going forward, it expects JLR’s overall volume to increase 3.5% yoy in FY2019 led by growth in China JV. It is also building in 6.3-6.4 percent EBIT margin for JLR in its estimates.

Adani Ports

Brokerage: Kotak Sec | Rating: Upgrade to Buy from Add | Target: Cut to Rs 450 from Rs 475

Kotak Securities said that the revised target is factoring in worst case business impact of closure of Mundra plant. It highlighted that ports data for key cargo classes suggests a healthy 3-9% yoy vol growth for FY18. It has cut estimates by 10 percent to factor nil imported coal volumes for Mundra power plant.

Hindalco

Brokerage: Credit Suisse | Rating: Maintain Outperform | Target: Rs 310

Credit Suisse said that aluminium prices have bounced back sharply driven by news of sanctions on Rusal, but the impact of the same is unclear. It also said that the stock is trading near the lowest EV/EBITDA multiples since 2012.

IT

Brokerage: CLSA

CLSA expects cross-currency benefits to support growth and margin for Indian IT companies, even as they are seen to be reporting the strongest March quarter in four years. It expects revenue for the quarter to grow 2.1-3.1 percent, while the margin may expand by 50-260 basis points. While overall demand trends haven’t improved, deal signings are better, it observed.

Among stocks, it expects Infosys to guide for 6-8 percent growth in dollar terms, while maintaining a margin of 23-25 percent. For HCL Tech, it sees a guidance of 10.5-12.5 percent growth in dollar terms, while the margin is seen at 19.5-20.5 percent. For Wipro, it sees growth guidance of 0.5-2.5 percent in dollar terms on a QoQ basis for the first quarter of next year. The brokerage has maintained a buy call on HCL Tech, Infosys, TCS, & Sell Ratings On Tech Mah & Wipro.

Wipro

Brokerage: Morgan Stanley | Rating: Underweight | Target: Rs 290

The global research firm highlighted the company’s exchange filing, which said that one of its telecom service provider clients in India filed a petition to initiate insolvency resolution process with the National Company Law Tribunal in February 2018. It subsequently admitted its claim in March 2018.

Since then, Wipro has been engaged with the client to discuss the potential outcome of the process. It has now estimated that this development will have an adverse impact on both revenue and profitability.

The impact would be 0.65-0.75% of consolidated revenues at the net income level for 4Q18, the brokerage cited Wipro’s filing. “We believe impact on IT Services revenues for the quarter is likely to be less than the impact on profitability, given the likelihood of provisions against receivables hitting the bottom line. We think the company may still report revenues within the guided range,” the research note from Morgan Stanley added.

SAIL

Brokerage: HSBC | Rating: Upgrade to Hold from Reduce | Target: Raised to Rs 88 form Rs 84

The global financial services firm pointed that domestic steel sector is witnessing one of the best time in many years. Steel prices trending higher on the back of uptick in demand, while both flat and long prices are up 15 and 20 percent quarter on quarter, respectively. The crude steel production run rate is also steady at about 4.5 percent for six months.

HSBC said that SAIL has shown a remarkable turnaround with the company posting a profit in Q3. All of its major plants are profitable at EBIT level and finished steel capacity has increased by 45 percent.

Going forward, it expects the company to report an average volume growth of 11 percent and EBITDA growth of 46 percent for FY19-20. It is also expecting the company to return to profitability for the first time in four years.

Axis Bank

Brokerage: CLSA

CLSA said that change of top management can also drive discussion around M&A possibilities. It further said that appointment of successor will be key to stability & valuation. Having said that, it sees limited risk to earnings of the bank.

Banks

Brokerage: UBS

UBS said that stressed corporate debt has largely been flat since March 2015. Further, around 15.5 percent of loans needed a haircut, of which 3.6 percent are yet to be recognised as NPL.

It pointed out that a fresh wave of NPLs rose following PNB fraud and new RBI rules as well. It has cut loan growth and earnings estimate by 0-22 percent for Fy19.

It is removing ICICI Bank from its Asia Pacific key call list and has retained anti-consensus cautious views on Yes Bank, State Bank of India, Punjab National Bank and IndusInd Bank. It prefers ICICI, HDFC Bank and Kotak Mahindra Bank.

On their earnings, it cited RBI rules being a new threat and the results could be 27 percent lower in a downside scenario.

This entry was posted in Market.

5 changes you need to focus while computing your taxes for filing tax returns this year

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As a taxpayer, it is necessary for you to keep abreast of the latest amendments to enable a salaried individual to compute taxes and file individual tax returns.

Navneet Dubey@imNavneetDubey

The financial year 2017-18 has just come to an end on 31 March. Soon, it will be time to file your tax returns, the initial deadline for which would be July 31, 2018. As a taxpayer, it is necessary for you to keep abreast of the latest amendments to enable a salaried individual to compute taxes and file individual tax returns.

Homi Mistry, Partner, Deloitte India told Moneycontrol that salaried individuals should keep these 6 things into consideration before computing their taxes for the AY 2018-19.

=> The applicable slab rate with respect to an individual having taxable income between Rs 2.5 lakh to Rs 5 lakhs has been reduced from 10% to 5%. However, there has been no change in the tax rates for other slabs.

=> Earlier, an individual having taxable income up to Rs 5 lakhs was entitled to a tax rebate. Now, this limit has been reduced to Rs 3.5 lakhs. Also, the tax rebate has been reduced from Rs 5,000 to Rs 2,500.

=> Where an individual has taxable income of more than Rs 50 lakhs but not exceeding Rs 1 crore, a surcharge of 10% is also applicable. Further surcharge of 15% continues for individuals having an income of more than Rs 1 crore.

=> Until AY 2017-2018, there was no restriction on the setting off of losses on the rented property or a deemed to be let-out property (arising on account of claiming interest payable on loan taken) against other income arising in the same financial year. Now with effect from AY 2018-2019, such losses can be set off only up to Rs 200,000 against other income. Any excess loss can be carried forward for set-off against income from house property over the following eight tax years.

=> For an individual having long-term capital gains arising from the sale of property, there is a change in the base year for indexation purpose from April 1, 1981 to April 1, 2001. Accordingly, the government has notified new cost inflation indexes. In the case of sale of immovable property, there has been a relaxation in the holding period from 3 years to 2 years, to be considered as long-term capital gains.

=> Further, in case an individual misses filing his income tax returns by the due date, a fee of Rs 5,000 will be levied if the return is filed on or before 31 December 2018; Rs 10,000 will be levied for returns filed after December 31, 2018. However, if the total income does not exceed Rs 5 Lakhs, a fee of Rs 1,000 will be levied.

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The Difference Between Artificial Intelligence, Machine Learning, and Deep Learning

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Simple explanations of Artificial Intelligence, Machine Learning, and Deep Learning and how they’re all different. Plus, how AI and IoT are inextricably connected.

We’re all familiar with the term “Artificial Intelligence.” After all, it’s been a popular focus in movies such as The Terminator, The Matrix, and Ex Machina (a personal favorite of mine). But you may have recently been hearing about other terms like “Machine Learning” and “Deep Learning,” sometimes used interchangeably with artificial intelligence. As a result, the difference between artificial intelligence, machine learning, and deep learning can be very unclear.

I’ll begin by giving a quick explanation of what Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) actually mean and how they’re different. Then, I’ll share how AI and the Internet of Things are inextricably intertwined, with several technological advances all converging at once to set the foundation for an AI and IoT explosion.

So what’s the difference between AI, ML, and DL?

Artificial Intelligence

First coined in 1956 by John McCarthy, AI involves machines that can perform tasks that are characteristic of human intelligence. While this is rather general, it includes things like planning, understanding language, recognizing objects and sounds, learning, and problem solving.

We can put AI in two categories, general and narrow. General AI would have all of the characteristics of human intelligence, including the capacities mentioned above. Narrow AI exhibits some facet(s) of human intelligence, and can do that facet extremely well, but is lacking in other areas. A machine that’s great at recognizing images, but nothing else, would be an example of narrow AI.

Machine learning

At its core, machine learning is simply a way of achieving AI.

Arthur Samuel coined the phrase not too long after AI, in 1959, defining it as, “the ability to learn without being explicitly programmed.” You see, you can get AI without using machine learning, but this would require building millions of lines of codes with complex rules and decision-trees.

So instead of hard coding software routines with specific instructions to accomplish a particular task, machine learning is a way of “training” an algorithm so that it can learnhow. “Training” involves feeding huge amounts of data to the algorithm and allowing the algorithm to adjust itself and improve.

To give an example, machine learning has been used to make drastic improvements to computer vision (the ability of a machine to recognize an object in an image or video). You gather hundreds of thousands or even millions of pictures and then have humans tag them. For example, the humans might tag pictures that have a cat in them versus those that do not. Then, the algorithm tries to build a model that can accurately tag a picture as containing a cat or not as well as a human. Once the accuracy level is high enough, the machine has now “learned” what a cat looks like.

Deep learning

Deep learning is one of many approaches to machine learning. Other approaches include decision tree learning, inductive logic programming, clustering, reinforcement learning, and Bayesian networks, among others.

Deep learning was inspired by the structure and function of the brain, namely the interconnecting of many neurons. Artificial Neural Networks (ANNs) are algorithms that mimic the biological structure of the brain.

In ANNs, there are “neurons” which have discrete layers and connections to other “neurons”. Each layer picks out a specific feature to learn, such as curves/edges in image recognition. It’s this layering that gives deep learning its name, depth is created by using multiple layers as opposed to a single layer.

AI and IoT are Inextricably Intertwined

I think of the relationship between AI and IoT much like the relationship between the human brain and body.

Our bodies collect sensory input such as sight, sound, and touch. Our brains take that data and makes sense of it, turning light into recognizable objects and turning sounds into understandable speech. Our brains then make decisions, sending signals back out to the body to command movements like picking up an object or speaking.

All of the connected sensors that make up the Internet of Things are like our bodies, they provide the raw data of what’s going on in the world. Artificial intelligence is like our brain, making sense of that data and deciding what actions to perform. And the connected devices of IoT are again like our bodies, carrying out physical actions or communicating to others.

Unleashing Each Other’s Potential

The value and the promises of both AI and IoT are being realized because of the other.

Machine learning and deep learning have led to huge leaps for AI in recent years. As mentioned above, machine learning and deep learning require massive amounts of data to work, and this data is being collected by the billions of sensors that are continuing to come online in the Internet of Things. IoT makes better AI.

Improving AI will also drive adoption of the Internet of Things, creating a virtuous cycle in which both areas will accelerate drastically. That’s because AI makes IoT useful.

On the industrial side, AI can be applied to predict when machines will need maintenance or analyze manufacturing processes to make big efficiency gains, saving millions of dollars.

On the consumer side, rather than having to adapt to technology, technology can adapt to us. Instead of clicking, typing, and searching, we can simply ask a machine for what we need. We might ask for information like the weather or for an action like preparing the house for bedtime (turning down the thermostat, locking the doors, turning off the lights, etc.).

Converging Technological Advancements Have Made this Possible

Shrinking computer chips and improved manufacturing techniques means cheaper, more powerful sensors.

Quickly improving battery technology means those sensors can last for years without needing to be connected to a power source.

Wireless connectivity, driven by the advent of smartphones, means that data can be sent in high volume at cheap rates, allowing all those sensors to send data to the cloud.

And the birth of the cloud has allowed for virtually unlimited storage of that data and virtually infinite computational ability to process it.

Of course, there are one or two concerns about the impact of AI on our society and our future. But as advancements and adoption of both AI and IoT continue to accelerate, one thing is certain; the impact is going to be profound

This entry was posted in SCI & TECH, Tech.

Blockchain

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Blockchain technology is commonly associated with Bitcoin and other cryptocurrencies, but that’s really only the tip of the iceberg. Some people think blockchain could end up transforming a number of important industries, from health care to politics.

Whether you’re simply looking to invest in Bitcoin, trade some Ethereum, or are just intrigued about what the heck blockchain actually is, you’ve come to the right place.

Blockchain isn’t just for Bitcoin

While blockchain technology isn’t simple when you dig into the nitty-gritty, the basic idea isn’t so opaque. It’s effectively a database that’s validated by a wider community, rather than a central authority. It’s a collection of records that has a lot of people give it the thumbs up, rather than relying on a single entity, like a bank or government, which most likely hosts data on a particular server.

Each “block” represents a number of transactional records, and the “chain” component links them all together with a hash function. As records are created, they are confirmed by a distributed network of computers and paired up with the previous entry in the chain, thereby creating a chain of blocks, or a blockchain.

The entire blockchain is retained on this large network of computers, meaning that no one person has control over its history. That’s an important component, because it certifies everything that has happened in the chain prior, and it means that no one person can go back and change things. It makes the blockchain a public ledger that cannot be easily tampered with, giving it a built-in layer of protection that isn’t possible with a standard, centralized database of information.

While traditionally we have needed these central authorities to trust one another, and fulfil the needs of contracts, the blockchain makes it possible to have our peers guarantee that for us in an automated, secure fashion.

That’s the innovation of blockchain, and it’s why you may hear it used to reference things other than Bitcoin and other cryptocurrency. Though generally not used for it yet, blockchain could be used to maintain a variety of information. An organization called Follow My Vote is attempting to use it for an electronic voting system that’s more secure than modern versions, and healthcare providers might one day use it to handle patient records.

Where did blockchain come from?

Although blockchain technology has only been effectively employed in the past decade, its roots can be traced back far further. A 1976 paper on New Directions in Cryptography discussed the idea of a mutual distributed ledger, which is what the blockchain effectively acts as. That was later built upon in the 1990s with a paper entitled “How to Time-Stamp a Digital Document.” It would take another few decades and the combination of powerful modern computers, with the clever implementation with a cryptocurrency to make these ideas viable.

In order to validate the blocks in the same manner as a traditional private ledger, the blockchain employs complicated calculations. That, in turn, requires powerful computers, which are expensive to own, operate, and keep cool. That’s part of the reason that bitcoin acted as such a great starting point for the introduction of blockchain technology, because it could reward those taking part in the process with something of financial value.

Bitcoin ultimately made its first appearance in 2009, bringing together the classic idea of the mutual distributed ledger, the blockchain, with an entirely digital currency that wasn’t controlled by any one individual or organization. Developed by the still effectively anonymous “Satoshi Nakamoto,” the cryptocurrency allowed for a method of conducting transactions while protecting them from interference by the use of the blockchain.

How do cryptocurrencies use the blockchain?

Although bitcoin and the alternative currencies all utilize blockchain technology, they do so in differing manners. Since bitcoin was first invented it has undergone a few changes at the behest of its core developers and the wider community, and other alt-coins have been created to improve upon bitcoin, operating in slightly different ways.

In the case of bitcoin, a new block in its blockchain is created roughly every ten minutes. That block verifies and records, or “certifies” new transactions that have taken place. In order for that to happen, “miners” utilize powerful computing hardware to provide a proof-of-work — a calculation that effectively creates a number which verifies the block and the transactions it contains. Several of those confirmations must be received before a bitcoin transaction can be considered effectively complete, even if technically the actual bitcoin is transferred near-instantaneously.

dont worry about bitcoin regulation it cant be stopped hong kong finance economy

Anthony WallaceAFP/Getty Images

This is where bitcoin has run into problems in recent months. As the number of bitcoin transactions increases, the relatively-hard 10-minute block creation time means that it can take longer to confirm all of the transactions and backlogs can occur.

With certain alt-coins, that’s a little different. With Litecoin it’s more like two and a half minutes, while with Ethereum the block time is just 10-20 seconds, so confirmations tend to happen far faster. There are obvious benefits of such a change, though by having blocks generate at a faster rate there is a greater chance of errors occurring. If 51 percent of computers working on the blockchain record an error, it becomes near-permanent, and generating faster blocks means fewer systems working on them.

What’s the catch?

Blockchain technology has a lot of exciting potential, but there are some serious considerations that need to be addressed before we can say it’s the technology of the future.

Remember all that computing power required to verify transactions? Those computers need electricity. Bitcoin is a poster child of the problematic escalation in power demanded from a large blockchain network. Although getting exact statistics on the power requirements of bitcoin is difficult, it’s regularly compared to small countries in its current state. That’s not appealing given today’s concerns about climate change, the availability of power in developing countries, and reliability of power in developed nations.

Transaction speed is also an issue. As we noted above, blocks in a chain must be verified by the distributed network, and that can take time. A lot of time. At its worse, bitcoin’s average transaction time exceeded 41 hours. Ethereum is much more efficient, but its average time is around 15 seconds — which would be an eternity in a checkout line at your local grocery store. Blockchains used for purposes other than cryptocurrency could run into similar problems. You can imagine how frustrating it would be to wait 15 seconds every time you wanted to change a database entry.

These problems will need to be resolved as blockchain becomes more popular. However, considering we’re less than a decade on from the blockchain’s first implementation, and we’re already on the road to developing new uses for it, we remain optimistic that those involved will work out it.

 

 

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Trade Setup for Monday: Top 15 things to know before Opening Bell

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Bias has now tilted in favour of bears and a break below 200-day moving average in the coming week could extend selling pressure.

Bears took control of D-Street from the word go as a Nifty break below crucial support levels one after the other on Friday and made a strong bearish candle which closely resembles Bearish Belt Hold kind of pattern on the daily charts.

The bias has now tilted in favour of the bears and a break below 200-day moving average in the coming week could extend the selling pressure.

The Nifty took support near its 200-DMA on last two occasions (7th and 8th March) and then bounced back. Now, a break below this level which is placed around 10,160 could push the index towards its next crucial support level placed at 10,000.

The index reversed gains after hitting an intraday high of 10,478.60 levels when Nifty made a ‘Shooting Star’ kind of pattern on the daily candlestick charts.

 “The Nifty50 appears to have resumed its downtrend as it registered a robust bear candle with a cut of around 160 points which is threatening the recent lows of 10,140 levels,” Mazhar Mohammad, Chief Strategist – Technical Research & Trading Advisory, Chartviewindia.in told Moneycontrol.

“If a fresh leg of the downtrend is in progress from the highs of 10,478 levels then ideally it should breach the recent lows of 10,140 and then initially head towards its 200-Day Exponential Moving Averages whose value is placed around 10,114 kinds of levels,” he said.

Mohammad further added that in between multiple support points are available in the zone of 10,160 – 10,140 levels which may provide some temporary relief to bulls from the current carnage.

“For time being upsides shall get capped around 10,350 kind of levels and rally towards 10,300 can be sold into for initial targets placed in the zone of 10,040-9,980 kind of levels,” he said.

India VIX moved up by 6.21 percent at 15.22. Rise in volatility after the recent consolidation seen in the last five sessions has given an upper hand to bears which suggest more weakness. A fall in Put Call Ratio also points to the same direction.

We have collated the top 16 data points to help you spot profitable trades:

Key support and resistance level for Nifty

The Nifty closed at 10,134.83 on Friday. According to Pivot charts, the key support level is placed at 10,074.47, followed by 10,134.83. If the index starts moving upwards, key resistance levels to watch out are 10,300.93 and 10,406.67.

Nifty Bank

The Nifty Bank index closed at 24,489.6 on Friday. The important Pivot level, which will act as crucial support for the index, is placed at 24,357.43, followed by 24,225.27. On the upside, key resistance levels are placed at 24,703.54, followed by 24,917.47.

Call Options data

In terms of open interest, the 10,500 call option has seen the most call writing so far at 58.31 lakh contracts. This could act as a crucial resistance level for the index in the March series.

The second-highest buildup has taken place in the 10,400 Call option, which has seen 48.81 lakh contracts getting written so far. The 10,700 Call option has accumulated 42.28 lakh contracts.

During the session, Call writing was most seen at the strike price of 10,300, which saw an addition of 15.47 lakh contracts, followed by 10,200, in which 14.98 lakh contracts were added, and 10,500, in which 7.40 lakh contracts were added.

There was hardly any Call unwinding seen.

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Put Options data

Maximum open interest in put options was seen at a strike price of 10,000, in which 46.36 lakh contracts have been added till date. This will act as a crucial base for the index in the March series.

The 10,200 put option comes next, having added 39.77 lakh contracts so far, and the 10,100 put option, which has now accumulated 33.47 lakh contracts.

During the session, put writing was seen the most at a strike price of 10,200, with 2.43 lakh contracts being added, followed by 9,900, which added 1.24 lakh contracts.

Put unwinding was seen at a strike price of 10,400, in which 15.01 lakh contracts were shed, followed by 10,300, in which 8.3 lakh contracts were shed. The 10,500 put option saw 2.35 lakh contracts getting shed.

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FII & DII data:

Foreign institutional investors (FIIs) sold shares worth Rs 150.46 crore, while domestic institutional investors sold shares worth Rs 770.53 crore in the Indian equity market, as per provisional data available on the NSE.

Fund flow picture:

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Stocks with high delivery percentage:

High delivery percentage suggests that investors are accepting delivery of the stock, which means that investors are bullish on it.

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16 stocks saw long build-up:

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17 stocks saw short covering:

A decrease in open interest along with an increase in price mostly indicates short covering.

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104 stocks saw short build-up:

An increase in open interest along with a decrease in price mostly indicates build-up of short positions.

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73 stocks saw long unwinding:

Long unwinding happens when there is a decrease in OI as well as in price.

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Bulk Deals:

Capital First: Vanguard Group has purchased over 9 lakh shares at Rs 648.65 apiece.

Eris Lifesciences: Vanguard Group has purchased over 10 lakh shares at Rs 814.88 apiece.

Gateway Distriparks: Morgan Stanley has purchased over 10 lakh shares in the firm at Rs 201.

Graphite India: Vanguard Group has purchased over 13.5 lakh shares in the company at Rs 776.06.

Jaiprakash Associates: Adroit Financial Services has traded over 2 crore shares in four transactions at around Rs 21.

TeamLease: HDFC Mutual Fund Prudence sold 3.8 lakh shares at Rs 2,050

(For more bulk deals click here)

Analyst or Board Meet/Briefings:

HDFC Life: The company participated in the investor conference organised by Haitong Securities in Mumbai.

ACC: The company met mutual fund house such as Sundaram Mutual Fund, IDFC Mutual Fund and GIC Re on March 16.

Ambuja Cement: The company met Goldman Sachs AMC on March 16, 2018.

Astral: First Voyager Advisors met the management on March 16, 2018.

Stocks in news:

Axis Bank: Reviewed and retained MCLR rates across all tenors. The one-year MCLR has been set at 8.4 percent.

Ramky Infra: The company has bagged an EPC order of Rs 939.4 crore From NHAI In Srinagar.

YES Bank: The company has said that Life Insurance Corporation has raised stake in firm By 2.03% To 9.62%.

Speciality Restaurants: Anjan Chatterjee to hand over operations to son, reports Mint.

Eight stocks under ban period on NSE

Security in ban period for the next day’s trade under the F&O segment includes companies in which the security has crossed 95 percent of the market-wide position limit.

Securities which are banned for trading include names such as Bank of India, BEML, DHFL, HDIL, IDBI Bank, JP Associates, SAIL and TV18 Broadcast.

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Project Soli

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Project Soli is developing a new interaction sensor using radar technology. The sensor can track sub-millimeter motions at high speed and accuracy. It fits onto a chip, can be produced at scale and built into small devices and everyday objects.

 

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Top 10 IoT(Internet Of Things) Projects Of All Time | 2018

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