India’s booming business centres and gleaming shopping malls mask a grimmer reality. While one section of the population gets richer, another section gets poorer. In the countryside, farmers and others ‘left behind’ by the economic surge find themselves in increasingly desperate circumstances. In many cases their plight, exacerbated by crippling debt, has led to suicide.
‘Big data’ study finds that children from families with limited education have strongest long-term response to teacher encouragement, and are more likely to progress to university as a result.
Dr Jag Srai, Head of the Centre for International Manufacturing at Cambridge's Institute for Manufacturing, and colleagues are developing new ways to help companies embrace the challenges and opportunities of digitalising the extended supply chain. Here, he provides a glimpse of this digital future.
It’s long been associated with anger and coarseness but profanity can have another, more positive connotation. Psychologists have learned that people who frequently curse are being more honest. Writing in the journal Social Psychological and Personality Science a team of researchers from the Netherlands, the UK, the USA and Hong Kong report that people who use profanity are less likely to be associated with lying and deception.
An algorithm which models how proteins inside cells interact with each other will enhance the study of biology, and sheds light on how proteins work together to complete tasks such as turning food into energy.
A Cambridge-led project aiming to develop a new architecture for future computing based on superconducting spintronics - technology designed to increase the energy-efficiency of high-performance computers and data storage - has been announced.
First ‘big data’ research approach to graduate earnings reveals significant variations depending on student background, degree subject and university attended.
Data from location-based social networks may be able to predict when a neighbourhood will go through the process of gentrification, by identifying areas with high social diversity and high deprivation.
Desislava Hristova (Computer Laboratory) discusses how data from location-based social networks can be used to predict when a neighbourhood will go through the process of gentrification.