Most people consider smell their least important sense, surveys suggest. Dogs, however, feel their way through the world with their noses. Humans already employ the animals' olfactory acuity for contraband and explosives detection. More recently it has also proved uncannily good at sensing cancers, diabetes--and even COVID-19. Exactly how dogs detect diseases is a mystery, but that has not stopped researchers from mimicking this prowess with an artificial-intelligence-based noninvasive diagnostic tool.
London, February 9: Researchers have developed a new Machine Learning (ML) technique to more accurately identify patients with a mix of psychotic and depressive symptoms. While patients with depression as a primary illness are more likely to be diagnosed accurately, patients with depression and psychosis rarely experience symptoms of purely one or the other illness. Those with psychosis with depression have symptoms which most frequently tend towards the depression dimension. Historically, this has meant that mental health clinicians give a diagnosis of a'primary' illness, but with secondary symptoms. "The majority of patients have comorbidities, so people with psychosis also have depressive symptoms and vice versa," said lead author Paris Alexandros Lalousis from the University of Birmingham in the UK.
When scientists carry out research on a given topic, they often start by reviewing previous study findings. Conducting systematic literature reviews or meta-analyses can be very challenging and time consuming, as there are often huge amounts of research focusing on different topics, which may not always be relevant to a researcher's work. Researchers at Utrecht University have recently developed a machine learning framework that could significantly speed up this process, by automatically browsing through numerous past studies and compiling high quality literature reviews. This framework, called ASReview, could prove particularly useful for conducting research during the COVID-19 pandemic. "Researchers and experts face a major challenge to stay up-to-date with the latest developments in their field nowadays," Jonathan de Bruin, lead engineer involved in the study, told TechXplore.
From Hugh Heffner to Donald Trump, many male celebrities are known for their tendency to date younger women. Now, a new study has revealed that as many as one in five British men choose to date women at least five years younger. Researchers trawled through 120,000 dating profiles to understand whether men really do live up to the stereotype of preferring younger women. Their findings indicate that the stereotype is very much true, with men citing good looks and health as the main reasons they prefer ladies their junior. Many male celebrities are known for their tendency to date younger women.
The core idea is deceptively simple: every observable phenomenon in the entire universe can be modeled by a neural network. And that means, by extension, the universe itself may be a neural network. Vitaly Vanchurin, a professor of physics at the University of Minnesota Duluth, published an incredible paper last August entitled "The World as a Neural Network" on the arXiv pre-print server. It managed to slide past our notice until today when Futurism's Victor Tangermann published an interview with Vanchurin discussing the paper. We discuss a possibility that the entire universe on its most fundamental level is a neural network.
Unlike their canine counterparts, cats may be'too socially inept' to stand with their owners against someone treating their human poorly, a study has warned. Researchers from Japan found that our feline friends will as gladly take food from someone who hinders their owner as one who helps them or acts neutrally. However, this might not be a simple case of treachery, the team said -- instead, it is possible that cats cannot read human social interactions the same way dogs can. Domestic cats evolved from solitary hunters, meaning that they likely lacked the kind of original social skills dogs were able to build on during domestication. Unlike their canine counterparts, cats may be'too socially inept' to stand with their owners against someone treating their human poorly, a study has warned (stock image) In the study, animal behaviour scientist Hitomi Chijiiwa of Kyoto University and colleagues had cat owners try -- unsuccessfully -- to open a transparent container to take out an object while their cats watched.
IMAGE: Modeling an algorithmic controller in your car that talks to stoplights and integrates HD maps means energy savings and a safer driving environment. Simulation results show that the cooperative automated... view more Imagine you're driving up a hill toward a traffic light. The light is still green so you're tempted to accelerate to make it through the intersection before the light changes. Then, a device in your car receives a signal from the controller mounted on the intersection alerting you that the light will change in two seconds -- clearly not enough time to beat the light. You take your foot off the gas pedal and decelerate, saving on fuel.
In an amazing show of self-control, cuttlefish can resist the impulse to eat a morsel of food if it means getting to eat two morsels later on, a new study shows. In experiments, the marine molluscs passed a variation of the'marshmallow test' – originally used in the 1970s to measure a child's ability to delay gratification. In the original Stanford experiment, pre-school kids were given one marshmallow and told they could eat it straight away, or, if they waited 20 minutes, have two marshmallows instead. For this new study, scientists performed a'fishy version' of the legendary experiment using shrimp instead of marshmallows. They found the creatures could wait over two minutes to get their preferred type of shrimp – and that the cuttlefish that could delay gratification the longest were the most intelligent, as determined by a another learning task.
The interdisciplinary study was led by Idan Fishel, a joint master student under the joint supervision of Dr. Ben M. Maoz of the Iby and Aladar Fleischman Faculty of Engineering and the Sagol School of Neuroscience, Prof. Yossi Yovel and Prof. Amir Ayali, experts from the School of Zoology and the Sagol School of Neuroscience together with Dr. Anton Sheinin, Idan, Yoni Amit, and Neta Shavil. The results of the study were published in the journal Sensors. The researchers explain that at the beginning of the study, they sought to examine how the advantages of biological systems could be integrated into technological systems, and how the senses of dead locust could be used as sensors for a robot. "We chose the sense of hearing, because it can be easily compared to existing technologies, in contrast to the sense of smell, for example, where the challenge is much greater," says Dr. Maoz. "Our task was to replace the robot's electronic microphone with a dead insect's ear, use the ear's ability to detect the electrical signals from the environment, in this case vibrations in the air, and, using a special chip, convert the insect input to that of the robot."
This article is based on an in-depth study of the data science efforts in three large, private-sector Indian banks with collective assets exceeding $200 million. The study included onsite observations; semistructured interviews with 57 executives, managers, and data scientists; and the examination of archival records. The five obstacles and the solutions for overcoming them emerged from an inductive analytical process based on the qualitative data. More and more companies are embracing data science as a function and a capability. But many of them have not been able to consistently derive business value from their investments in big data, artificial intelligence, and machine learning.1 Moreover, evidence suggests that the gap is widening between organizations successfully gaining value from data science and those struggling to do so.2