These are the world's best universities by subject 06-23

If you want to pick the the best university for your chosen field of study, go to the U.S.

The QS World University Rankings show U.S. universities hold the top spot for virtually all subjects.

Harvard, Stanford and the Massachusetts Institute of Technology dominate in engineering and technology; natural sciences; and social sciences and management.

Arts and humanities and life sciences and medicine are the exceptions, with two UK universities – Oxford and Cambridge – in the top three for those areas.

The rankings group 48 disciplines into the five broad subject categories. They highlight the best universities in each category using research citations and surveys of employers and academics. In total, 1,200 universities in 78 locations are listed.

Outside of the top slots, Asian universities also get a good showing, in particular Nanyang Technological University Singapore and the National University of Singapore. 

Western universities have dominated the top tier of higher education tables for years, but providers in Asia are becoming increasingly visible players in the elite and funding for education is on the rise.

Globalisation is rapidly changing the education sector. As the global middle class expands, there will be increasing demand for higher education, particularly in China and India.

The battle to host international students – and benefit from the income and expertise they bring – is already on. Governments from the UK to Japan are bringing in measures to attract the best minds.

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3 technologies that could define the next decade of cybersecurity 06-22

In little over a decade, cybercrime has moved from being a specialist and niche-crime type to one of the most significant strategic risks facing the world today, according to the World Economic Forum Global Risks Report 2019. Nearly every technologically advanced state and emerging economy in the world has made it a priority to mitigate the impact of financially motivated cybercrime. 

The global experience of the past decade has largely been dominated by the emergence of a professional underground economy that provides scale, significant return-on-investment and entry points for criminals to turn a technical specialist crime into a global volume crime. The cybersecurity landscape in the past decade has been shaped by the targeting of financial institutions, notably with malware configured to harvest payment information and target financial platforms. The early cybercrime market that gave rise to the criminal online ecosystem was centred on the trading of harvested stolen credit cards, and some of the most high-profile and sophisticated global attacks focus on the penetration and manipulation of the internal networks of complex global payment systems. 

The Russian-speaking world has not been immune from these trends. Cyberattacks on financial organizations in Russia, Central Asia and Eastern Europe by some of the most sophisticated cybercrime gangs in the world have targeted clients, digital channels and networks. The Russian-speaking underground economy is one of the most active globally, with hundreds of fora and tens of thousands of users. Criminal groups exploit the margins of co-operation to conduct global campaigns, and their threat capacity is always adapting as groups work together in a borderless environment to combat technical defences. 

The past 10 years mark only the start of the global cybersecurity journey. New architectures and cooperation are required as we stand at the brink of a new era of cybercrime, which will be empowered by new and emergent technology. These three technologies might very well define the next 10 years of global cybersecurity: 

1. 5G networks and infrastructure convergence

A new generation of 5G networks will be the single most challenging issue for the cybersecurity landscape. It is not just faster internet; the design of 5G will mean that the world will enter into an era where, by 2025, 75 billion new devices will be connecting to the internet every year, running critical applications and infrastructure at nearly 1,000 times the speed of the current internet. This will provide the architecture for connecting whole new industries, geographies and communities - but at the same time it will hugely alter the threat landscape, as it potentially moves cybercrime from being an invisible, financially driven issue to one where real and serious physical damage will occur at a 5G pace. 

5G will potentially provide any attacker with instant access to vulnerable networks. When this is combined with the enterprise and operational technology, a new generation of cyberattacks will emerge, some of which we are already seeing. The recent ransomware attack against the US city of Baltimore, for example, locked 10,000 employees out of their workstations. In the near future, smart city infrastructures will provide interconnected systems at a new scale, from transport systems for driverless cars, automated water and waste systems, to emergency workers and services, all interdependent and - potentially - as highly vulnerable as they are highly connected. In 2017, the WannaCry attack that took parts of the UK’s National Health Service down took days to spread globally, but in a 5G era the malware would spread this attack at the speed of light. It is clear that 5G will not only enable great prosperity and help to save people’s lives, it will also have the capacity to thrust cybercrime into the real world at a scale and with consequences yet unknown. 

2. Artificial intelligence

To build cyber defences capable of operating at the scale and pace needed to safeguard our digital prosperity, artificial intelligence (AI) is a critical component in how the world can build global immunity from attacks. Given the need for huge efficiencies in detection, provision of situational awareness and real-time remediation of threats, automation and AI-driven solutions are the future of cybersecurity. Critically, however, the experience of cybercrime to-date shows that any technical developments in AI are quickly seized upon and exploited by the criminal community, posing entirely new challenges to cybersecurity in the global threat landscape. 

The use of AI by criminals will potentially bypass – in an instant – entire generations of technical controls that industries have built up over decades. In the financial services sector we will soon start to see criminals deploy malware with the ability to capture and exploit voice synthesis technology, mimicking human behaviour and biometric data to circumvent authentication of controls for people’s bank accounts, for example. But this is only the beginning. Criminal use of AI will almost certainly generate new attack cycles, highly targeted and deployed for the greatest impact, and in ways that were not thought possible in industries never previously targeted: in areas such as biotech, for the theft and manipulation of stored DNA code; mobility, for the hijacking of unmanned vehicles; and healthcare, where ransomware will be timed and deployed for maximum impact. 

3. Biometrics

To combat these emerging threats, biometrics is being widely introduced in different sectors and with various aims around the world, while at the same time raising significant challenges for the global security community. Biometrics and next-generation authentication require high volumes of data about an individual, their activity and behaviour. Voices, faces and the slightest details of movement and behavioural traits will need to be stored globally, and this will drive cybercriminals to target and exploit a new generation of personal data. Exploitation will no longer be limited to the theft of people’s credit card number, but will target theft of their being – their fingerprints, voice identification and retinal scans. 

Most experts agree that three-factor authentication is the best available option, and that two-factor authentication is a must. ‘Know’ (password), ‘have’ (token) and ‘are’ (biometrics) are the three factors for authentication, and each one makes this process stronger and more secure. For those charged with defending our digital future, however, understanding an entire ecosystem of biometric software, technology and storage points makes it still harder to defend the rapidly and ever-expanding attack surface.

What next?

Over the past decade, criminals have been able to seize on a low-risk, high-reward landscape in which attribution is rare and significant pressure is placed on the traditional levers and responses to crime. In the next 10 years, the cybersecurity landscape could change significantly, driven by a new generation of transformative technology. To understand how to secure our shared digital future we must first understand how the security community believes the cyberthreat will change and how the consequent risk landscape will be transformed. This critical and urgent analysis must be based on evidence and research, and must leverage the expertise of those in academia, the technical community and policymakers 

around the world. By doing this, the security ecosystem can help build a new generation of cybersecurity defences and partnerships that will enable global prosperity. 

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Bill that seeks to lift green card cap amended to protect US 06-21

Eliminating the country quota from the most sought-after Green Cards will end the current discrimination in the US labour market, but would allow countries like India and China to dominate the path to American citizenship, according to the latest Congressional report.
Having a Green Card allows a person to live and work permanently in the United States.
Indian-Americans, most of whom are highly skilled and come to the US mainly on the H-1B work visas, are the worst sufferers of the current immigration system which imposes a seven per cent per country quota on allotment of Green Cards or the Legal Permanent Residency (LPR).

The bipartisan Congressional Research Service (CRS), an independent research wing of Congress, said if the per-country cap for employment-based immigrants was removed, many expects that Indian and Chinese nationals would dominate the flow of new employment-based LPRs for as many years as needed to clear out the accumulated queue of prospective immigrants from those countries.

This queue would include those with approved employment-based immigrant petitions waiting to file either a visa  .. 

The CRS regularly prepares reports on various issues for the lawmakers to take informed decisions.

A copy of the report 'Permanent Employment-Based Immigration and the Per-country Ceiling' dated December 21 was made available to PTI, ahead of the new Congress beginning January 3, wherein several lawmakers are planning to introduce a legislation to eliminate per-country quota for issuing Green Cards to foreign nationals. 

As of April 2018, a total of 306,601 Indian nationals – mostly IT professionals – were waiting in line for Green Cards, according to the USCIS figures. 

Indians constitute 78 per cent of the 395,025 foreign nationals waiting for Green Cards in just one category of employment-based LPR applications.

Due to the cap, the current wait period for the majority of Indians to get a Green Card is nine and half years, the CRS said, adding this could increase or decrease further depending on the number of new applications every year. India is followed by China with 67,031 in line for Green Cards.

Lawmakers favouring eliminating the per-country cap contend that such circumstances effectively encourage employers to sponsor prospective employment-based immigrants primarily from India.

Proponents argue that removing the per-country ceiling from employment-based immigrants would "level the playing field" by making immigrants from all countries more equally attractive to employers, the CRS said. 

According to the CRS, eliminating the per-country ceiling would reduce certain queues of prospective immigrants more quickly, and remove the perceived employer incentive to choose nationals from these countries over other countries. 

"Shorter wait times for LPR status might actually incentivise greater numbers of nationals from India, China and the Philippines to seek employment-based LPR status. If that were to occur, the reduction in the number of approved petitions pending might be short-lived.

"A handful of countries could conceivably dominate employment-based immigration, possibly benefitting certain industries that employ foreign workers from those countries, at the expense of foreign workers from other countries and other industries that might employ them," the CRS said. 

Because the Immigration and Nationality Act (INA) grants LPRs the ability to sponsor family members through its family-sponsorship provisions, removing the per-country ceiling would alter, to an unknown extent, the country-of-origin composition of subsequent family-based immigrants acquiring LPR status each year, it said. 

Changes in the country's demographic profile tilted towards people from one part of the world, was one of the prime reasons for the current per country quota. This, on the other hand, restricts the flow of the best talented foreign workers.

The INA allocates 140,000 visas annually for all five employment-based LPR categories, roughly 12 per cent of the 1.1 million LPRs admitted in fiscal 2017. It further limits each immigrant-sending country to an annual maximum of seven per cent of all employment-based LPR admissions, known as the per-country ceiling, or "cap". 

Two popular employment-based pools of foreign nationals, who have been approved as employment-based immigrants but must wait for statutorily limited visa numbers, totalled in excess of 900,000 as of mid-2018. Most originate from India, followed by China and the Philippines, the CRS said.

Some employers maintain that they continue to need skilled foreign workers to remain internationally competitive and to keep their firms in the US, it said. 

Proponents of increasing employment-based immigration levels argue it is vital for economic growth. Opponents cite the lack of compelling evidence of labour shortages and argue that the presence of foreign workers can negatively impact wages and working conditions in the US, the CRS said.

"Some argue that eliminating the per-country ceiling would increase the flow of high-skilled immigrants from countries such as India and China, who are often employed in the US technology sector, without increasing the total annual admission of employment-based LPRs," it added.

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AI analyzes language to predict schizophrenia 06-21

AI analyzes language to predict schizophrenia.....

A machine learning method found out a hidden clue in people’s language that can predict psychosis episodes. 

A machine learning method uncovered a hidden clue in people’s language predictive of the later manifestation of psychosis: the frequent use of words associated with sound. A paper published by the journal npj Schizophrenia released the findings by scientists from Emory University and Harvard University.

Hidden details

The researchers developed a new machine-learning methodology to more precisely quantify the semantic richness of people’s conversational language (a known indicator for psychosis). Their results indicated that automated analysis of the two language variables (more frequent use of words associated with sound and speaking with low semantic density, or vagueness) can predict if an at-risk person will later develop psychosis with an impressive 93 percent accuracy.

Trained clinicians had not noticed how individuals at risk for psychosis use more words associated with sound than the average population, though abnormal auditory perception is a pre-clinical symptom.

“Voices: Living with Schizophrenia” by WebMD, YouTube.

Machine learning can spot patterns in people’s use of language that even doctors who have undergone training to diagnose and treat those at risk of psychosis may not notice. “Trying to hear these subtleties in conversations with people is like trying to see microscopic germs with your eyes,” says first study author Neguine Rezaii, a fellow in the Department of Neurology at Harvard Medical School. That being said, it is possible to use machine learning to find subtle patterns hiding in people’s language. “It’s like a microscope for warning signs of psychosis,” she adds. Rezaii started working on the study while she was a resident in the Department of Psychiatry and Behavioral Sciences at Emory University School of Medicine.

“Trying to hear these subtleties in conversations with people is like trying to see microscopic germs with your eyes,” Neguine Rezaii, fellow in the Department of Neurology at Harvard Medical School.

Behind the data

Researchers first used machine learning to establish “norms” for conversational language. They fed a computer software program the online

conversations of 30,000 users of Reddit, a popular social media platform where people have informal discussions about a wide array of sujects. The software program, known as Word2Vec, utilizes an algorithm to change individual words to vectors, assigning each one a location in a semantic space based on its meaning. Such with similar meanings are positioned closer together than those with different meanings.

They also developed a computer program to perform “vector unpacking,” or analysis of the semantic density of word usage. Previous work has measured semantic coherence between sentences. Vector unpacking enabled the researchers to quantify how much information was packed into each sentence. After generating a baseline of “normal” data, the researchers applied the same techniques to diagnostic interviews of 40 participants that had been conducted by trained clinicians, as part of the multi-site North American Prodrome Longitudinal Study (NAPLS), funded by the National Institutes of Health. 

Vector unpacking enabled the researchers to quantify how much information was packed into each sentence.

The automated analyses of the participant samples were then compared to the normal baseline sample and the longitudinal data on whether the participants converted to psychosis.

"This research is interesting not just for its potential to reveal more about mental illness, but for understanding how the mind works” concludes senior author Phillip Wolff, a professor of psychology at Emory.

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An unexpected connection between insulin receptor and gene expression opens new doors 04-10

 The discovery of insulin in the 1920s marked the breakthrough in the almost 3,500-year-long mystery of diabetes, a disease first described in ancient Egyptian papyruses.

Until its discovery, physicians struggled to explain how symptoms such as sugary urine, constant thirst and frequent urination could lead to ailments ranging from blindness and nerve damage to coma and death.

Over the past century, scientists have detailed the hormone’s central role as a regulator of blood sugar, mapped its cell-signaling pathways and established its involvement in diabetes and a staggering array of other chronic conditions, including neurodegeneration, cardiovascular disease and cancer.

Still, many aspects of insulin signaling remain unclear, particularly its long-term effects on cells, and there are currently no effective cures for the hundreds of millions of people around the world living with diabetes.

Now, researchers from Harvard Medical School have made key new insights into the molecular behavior of insulin. Reporting online in Cell on April 4, they describe an unexpected mechanism by which insulin triggers changes to the expression of thousands of genes throughout the genome.

Their analyses show that the insulin receptor—a protein complex at the cell surface—physically relocates to the cell nucleus after it detects and binds insulin. Once there, it helps initiate the expression of genes involved in insulin-related functions and diseases. This process was impaired in mice with insulin resistance.

The results outline a set of potential therapeutic targets for insulin-related diseases and establish a wide range of future avenues of research on insulin signaling, including potential clues toward the underlying biological mechanisms that differentiate type 1 and type 2 diabetes.

“Our findings open the door for a new field of study on the insulin receptor, a remarkable protein complex expressed in almost all cells and implicated in major chronic diseases that affect hundreds of millions of people,” said senior study author John Flanagan, professor of cell biology at HMS.

“Understanding the fundamental mechanisms of how cells work can help us design new drugs or improve existing ones, and the insulin receptor certainly has potential for tremendous returns on investment,” Flanagan added.

Produced by specialized cells in the pancreas, the hormone insulin serves as the main signal to cells to absorb glucose from the bloodstream and begin the production and metabolism of carbohydrates, fats and proteins. This process is essential for normal cell function, growth and nutrient storage.

Dysfunctions in insulin signaling give rise to a number of serious chronic diseases. In type 1 diabetes, pancreatic cells fail to produce enough insulin, and in type 2 diabetes—the far more common form of the condition—cells become resistant to insulin. Without proper insulin signaling, glucose accumulates in the blood where it damages tissues and organs. Insulin resistance has also been implicated in neurodegenerative diseases such as Alzheimer’s and Parkinson’s, and excessive insulin signaling contributes to a variety of cancers.

Strange bedfellows

Flanagan and colleagues were broadly interested in studying how cell surface receptors communicate with the interior of a cell and performed screens to identify proteins associated with the insulin receptor.

Their experiments suggested that one of the most prominent such proteins is RNA polymerase, an enzyme responsible for transcribing DNA into RNA—the first step in gene expression.

This was unexpected, said Flanagan, because RNA polymerase functions inside the nucleus of a cell—far away from surface of the cell where the insulin receptor is located. Additional analyses revealed an unexpected explanation.

The team found that after the insulin receptor binds insulin, it moves from the cell surface to the nucleus via a yet unidentified mechanism. Once there, it binds to RNA polymerase on chromatin—the protein-DNA complex that cells use to store their genomes.

A genome-wide search revealed around 4,000 genomic regions where the insulin receptor bound with a degree of specificity that essentially makes random chance impossible. The striking majority of these sites were at promoters—sequences of DNA that initiate the expression of genes.

A high proportion of targeted genes were involved in insulin-related functions, particularly the synthesis and storage of lipids and proteins. Certain subsets of genes appeared to be unique to different tissue types. The analyses also identified numerous disease-related genes, including ones linked with diabetes, cancer and neurodegeneration.

Lipid paradox

Counterintuitively, the researchers found the insulin receptor does not specifically target genes involved in carbohydrate metabolism—one of the primary functions of insulin signaling.

This was an intriguing result for many reasons, Flanagan said, particularly because of the observed differences between the two major forms of diabetes. Both types involve problems with carbohydrate synthesis and storage. However, if left untreated, patients with type 1 diabetes lose weight, while type 2 diabetes is associated with obesity.

“The excessive lipid storage seen in type 2 diabetes compared with type 1 is a bit of a paradox because disrupted insulin signaling should cause issues with both lipid synthesis and storage in either condition,” he said.

“The finding that genes downstream of the pathway we identified are involved in lipid metabolism but not carbohydrate metabolism potentially gives us a window into that differential effect between carbohydrate and lipid,” Flanagan said. “But we won’t know until we perform further experiments.” 

New paths

The researchers made a number of other insights on how the insulin receptor regulates genes.

They identified several additional proteins that play a role in this process. One of particular interest was HCF-1 (host cell factor-1), which is expressed in all cells and is involved in regulating cell cycle and growth. It appears to play a critical role in recruiting the insulin receptor and other proteins to the location of a promoter to initiate gene activation.

The team also studied the effects of insulin resistance on this pathway. Giving mice glucose to trigger a rise in blood insulin led to an increase in insulin receptor-chromatin binding. Mice with insulin-resistance, however, showed 30-fold reduction in receptor-chromatin binding, an observation that suggests a high degree of sensitivity to insulin resistance.

While the insulin receptor has been studied intensely for decades, these findings represent a new pathway for insulin signaling function and shed light on potential mechanisms for the long-term effects of insulin in the body.

Intriguingly, as far back as the 1970s, scientists had clues that the insulin receptor and other members of the same class of cell surface receptors, known as receptor tyrosine kinases, can be found within the cell nucleus. These observations remained poorly understood, and the process behind them never fully described.

The identification of this pathway opens new avenues of investigation into the insulin receptor and other receptor tyrosine kinases, which function as key “on” or “off” switches for a wide range of important cellular processes.

“We were surprised to find such strong evidence that the entire insulin receptor complex moves to the nucleus, and we were initially very skeptical,” Flanagan said. “We still don’t know how exactly this happens, but we’ve pinned down the details of much of this process on a genome-wide scale.”

“A better understanding will help us improve our knowledge of the biology of insulin signaling in health and in disease, as well as other receptor tyrosine kinases, which are attractive targets for drug therapies due to their involvement in such a broad range of diseases,” Flanagan added.

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