Lifeboat Foundation

Artificial intelligence, AI, is rapidly transforming work also in the financial sector. Conducted at the University of Eastern Finland, a recent study explored how integrating AI into the work of sales teams affects the interpersonal communication competence required of sales managers. The study found that handing routine tasks over to AI improved efficiency and freed up sales managers’ time for more complex tasks. However, as the integration of AI progressed, sales managers faced new kind of communication challenges, including those related to overcoming fears and resistance to change.

“Members of sales teams needed encouragement in the use AI, and their self-direction also needed support. Sales managers’ contribution was also vital in adapting to constant digital changes and in maintaining trust within the team,” says Associate Professor Jonna Koponen of the University of Eastern Finland.

The longitudinal study is based on 35 expert interviews conducted over a five-year period in 2019–2024, as well as on secondary data gathered from one of Scandinavia’s largest financial groups. The findings show that besides traditional managerial interpersonal communication competence, consideration of ethical perspectives and adaptability were significant when integrating AI into the work of sales teams.

Studies using mouse models of lung adenocarcinoma identify an association between age, iron homeostasis and tumour initiation potential that involves NUPR1 and lipocalin-2.

With the imaging spectrograph blocking out the bright light from the region at the heart of the quasar, Hubble was able to see the structure around the black hole like never before.

Bin Ren of the Côte d’Azur Observatory and Université Côte d’Azur in France explained in a NASA statement that Hubble found lots of “weird things” around the feeding supermassive black hole powering 3C 273.

“We’ve got a few blobs of different sizes and a mysterious L-shaped filamentary structure,” Ren said. “This is all within 16,000 light-years of the black hole.”

Image classification is one of AI’s most common tasks, where a system is required to recognize an object from a given image. Yet real life requires us to recognize not a single standalone object but rather multiple objects appearing together in a given image.

This reality raises the question: what is the best strategy to tackle multi-object classification? The common approach is to detect each object individually and then classify them. But new research challenges this customary approach to multi-object classification tasks.

In an article published today in Physica A: Statistical Mechanics and its Applications, researchers from Bar-Ilan University in Israel show how classifying objects together, through a process known as Multi-Label Classification (MLC), can surpass the common detection-based classification.

Even matter ejected by black holes can run into objects in the dark. Using NASA’s Chandra X-ray Observatory, astronomers have found an unusual mark from a giant black hole’s powerful jet striking an unidentified object in its path.

The discovery was made in a galaxy called Centaurus A (Cen A), located about 12 million light-years from Earth. Astronomers have long studied Cen A because it has a supermassive black hole in its center sending out spectacular jets that stretch out across the entire galaxy. The black hole launches this jet of high-energy particles not from inside the black hole, but from intense gravitational and magnetic fields around it.

Continue reading “Chandra sees black hole jet stumble into something in the dark” »

This discrepancy, known as the Hubble Tension, has challenged our understanding of the universe’s fundamental nature.

Now, new observations from the powerful James Webb Space Telescope (JWST) has deepened this perplexing enigma.

Continue reading “Webb telescope provides new clues to universe’s expansion mystery” »

Globally, approximately 139 million people are expected to have Alzheimer’s disease (AD) by 2050. Magnetic resonance imaging (MRI) is an important tool for identifying changes in brain structure that precede cognitive decline and progression with disease; however, its cost limits widespread use.

A new study by investigators from Massachusetts General Hospital (MGH), a founding member of the Mass General Brigham health care system, demonstrates that a simplified, low magnetic field (LF) MRI machine, augmented with machine learning tools, matches conventional MRI in measuring brain characteristics relevant to AD. Findings, published in Nature Communications, highlight the potential of the LF-MRI to help evaluate those with cognitive symptoms.

“To tackle the growing, global health challenge of dementia and cognitive impairment in the aging population, we’re going to need simple, bedside tools that can help determine patients’ underlying causes of cognitive impairment and inform treatment,” said senior author W. Taylor Kimberly, MD, Ph.D., chief of the Division of Neurocritical Care in the Department of Neurology at MGH.

Failing hearts nearly returned to full function in laboratory pigs after they received an experimental gene therapy.

New research shows the gene therapy didn’t just prevent heart failure from worsening in four lab pigs, but actually prompted hearts to repair and grow stronger.

“Even though the animals are still facing stress on the heart to induce heart failure, we saw recovery of heart function and that the heart also stabilizes or shrinks,” said co-senior researcher Dr. TingTing Hong, an associate professor of pharmacology and toxicology at the University of Utah.

In a recent study published in the journal Nature Aging, researchers identified plasma proteomic biomarkers and dynamic changes associated with brain aging, leveraging a multimodal approach combining brain age gap (BAG) and proteome-wide association analysis.

Background

The global aging population is expected to exceed 1.5 billion individuals aged 65 and above by 2050, highlighting the urgent need to address aging-associated challenges.