Reseachers benchmarked 22 classification methods that automatically assign cell identities including single-cell-specific and general-purpose classifiers. The performance of the methods is evaluated using 27 publicly available single-cell RNA sequencing datasets of different sizes, technologies, species, and levels of complexity. The general-purpose support vector machine classifier has overall the best performance across the different experiments. Researchers present a novel algorithm for predicting genetic ancestry using only variables that are routinely captured in electronic health records (EHRs), such as self-reported race and ethnicity, and condition billing codes. Using patients that have both genetic and clinical information at Columbia University / New York-Presbyterian Irving Medical Center, they developed a pipeline that uses only clinical data to predict the genetic ancestry of all patients of which more than 80% identify as other or unknown.

How are you enjoying the International Year of the Periodic Tables so far? Yes, tables – we should probably have been using the plural all along. Since Dmitri Mendeleev (and others) first sketched out the periodic relationships between the elements in the 1860s, it has been estimated that around a thousand different tables have appeared in print – and that's before considering all those on the internet. Even the T-shirts handed out at the opening ceremony in January (I grabbed one, naturally) offered a new version, courtesy of the European Chemical Society, with the elements colour-coded and given different-sized boxes according to their abundance and availability. Mostly these tables embody careful deliberation about what to put where, which information to prioritise, which message to convey.

Music is the most popular art form that is performed and listened to by billions of people every day. There are many genres of music such as pop, classical, jazz, folk etc. Each genre has different music instruments, tone, rhythm, beats, flow etc. Digital music and online streaming have become very popular these days due to the increase in the number of users. To create a machine learning model, which classifies music samples into different genres. To classify a music sample or song manually, the person has to listen to the song and select the genre.

Bengaluru-based parent-tech startup Parentof has raised $1 million in a seed funding round to evolve its technology and expand its partner network. The recent funding round was led by angel investors V Srinivas and other existing investors. Founded in 2015, Parentof is a decision sciences organization that provides insights into child growth and decision analytics. The company creates an ecosystem for parents to easily access technology-enabled solutions to help drive better outcomes for children. It believes that applying research and technologies like Artificial Intelligence and Machine Learning can bridge the gap between the realities and assumptions of parenting.

The UK's success in the field of robotic surgery could be hampered if the country loses its research partnerships with Europe after Brexit, according to a new study. The study's authors said there was a "consensus" that Brexit was likely to "undermine the UK's status as a global leader in science and innovation". Robotic surgery has been touted as one of the technologies that is key to future growth in the UK, according to the Imperial College London study, and international collaboration is key to that success. Dr George Garas, lead author of the study from the department of surgery and cancer at Imperial College London, said: "There is a consensus within the scientific and healthcare communities that Brexit is likely to undermine the UK's status as a global leader in science and innovation. "We need to understand what the impact of losing the existing valuable EU links would be so as to tactically plan the UK's research and innovation strategy after Brexit." The UK currently ranks third in the world for robotic surgery innovation, behind Italy and the US. The best scenario following Brexit would be for the UK to continue its research partnerships with the EU, the study's authors suggested. If this isn't possible, the UK should look to collaborate with the US. But under this scenario the UK's research impact would ultimately suffer unless its new US partners were the top-performing ones in the field, the study found. "Our research shows that in the field of robotic surgery research, replacing EU partners with top US collaborators might maintain or even improve the UK's position," Dr Garas said. "Unfortunately, in the short term this could be difficult and costly.

Wine, spirits and craft beer retailer Fine Wine Delivery is using IBM's Watson artificial intelligence (AI) to help customers choose products from its range. It says, through IBM Watson, consumers are now able to access a level of expert product knowledge to "assist them in their discovery of the complex world of wine, craft beer and spirits" from their smartphone or tablet. Fine Wine Delivery operates an independent, expert tasting panel that creates tasting notes on all of its more than 2000 products. The company says it wanted to make that knowledge more accessible to customers and create an online experience that was as informative as chatting to their expert team in-store. To achieve this it worked with Auckland-based AI specialist, Spacetime to create a natural language search by ingesting the original tasting notes and using IBM Watson Virtual Assistant to provide customised advice online.

All the same, it's one thing employers love to hate. Whenever an employer hires a worker, the understanding is that they have offered a fair wage for what you have to offer. Therefore, any time spent outside work should be for recuperating (recreation and sleep) from the busy day. That has been the thinking: "Eight hours labour, eight hours recreation, eight hours rest." It might have worked in the early 20th century, during the industrial revolution, but a rethink for the demands of the 21st century is long due.

All the same, it's one thing employers love to hate. Whenever an employer hires a worker, the understanding is that they have offered a fair wage for what you have to offer. Therefore, any time spent outside work should be for recuperating (recreation and sleep) from the busy day. That has been the thinking: "Eight hours labour, eight hours recreation, eight hours rest." It might have worked in the early 20th century, during the industrial revolution, but a rethink for the demands of the 21st century is long due.

A fundamental problem in geostatistical modeling is to infer the heterogeneous geological field based on limited measurements and some prior spatial statistics. Semantic inpainting, a technique for image processing using deep generative models, has been recently applied for this purpose, demonstrating its effectiveness in dealing with complex spatial patterns. However, the original semantic inpainting framework incorporates only information from direct measurements, while in geostatistics indirect measurements are often plentiful. To overcome this limitation, here we propose a physics-informed semantic inpainting framework, employing the Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) and jointly incorporating the direct and indirect measurements by exploiting the underlying physical laws. Our simulation results for a high-dimensional problem with 512 dimensions show that in the new method, the physical conservation laws are satisfied and contribute in enhancing the inpainting performance compared to using only the direct measurements.

Machine learning (ML) classification is increasingly used in safety-critical systems. Protecting ML classifiers from adversarial examples is crucial. We propose that the main threat is that of an attacker perturbing a confidently classified input to produce a confident misclassification. To protect against this we devise an adversarial bound (AB) for a Gaussian process classifier, that holds for the entire input domain, bounding the potential for any future adversarial method to cause such misclassification. This is a formal guarantee of robustness, not just an empirically derived result. We investigate how to configure the classifier to maximise the bound, including the use of a sparse approximation, leading to the method producing a practical, useful and provably robust classifier, which we test using a variety of datasets.