Lifeboat Foundation

Nonlinear optics explores how powerful light (e.g. lasers) interacts with materials, resulting in the output light changing colour (i.e. frequency) or behaving differently based on the intensity of the incoming light. This field is crucial for developing advanced technologies such as high-speed communication systems and laser-based applications. Nonlinear optical phenomena enable the manipulation of light in novel ways, leading to breakthroughs in fields like telecommunications, medical imaging, and quantum computing. Two-dimensional (2D) materials, such as graphene—a single layer of carbon atoms in a hexagonal lattice—exhibit unique properties due to their thinness and high surface area. Graphene’s exceptional electronic properties, related to relativistic-like Dirac electrons and strong light-matter interactions, make it promising for nonlinear optical applications, including ultrafast photonics, optical modulators, saturable absorbers in ultrafast lasers, and quantum optics.

Dr. Habib Rostami, from the Department of Physics at the University of Bath, has co-authored pioneering research published in Advanced Science. This study involved an international collaboration between an experimental team at Friedrich Schiller University Jena in Germany and theoretical teams at the University of Pisa in Italy and the University of Bath in the UK. The research aimed to investigate the ultrafast opto-electronic and thermal tuning of nonlinear optics in graphene.

This study discovers a new way to control high-harmonic generation in a graphene-based field-effect transistor. The team investigated the impact of lattice temperature, electron doping, and all-optical ultrafast tuning of third-harmonic generation in a hexagonal boron nitride-encapsulated graphene opto-electronic device. They demonstrated up to 85% modulation depth along with gate-tuneable ultrafast dynamics, a significant improvement over previous static tuning. Furthermore, by changing the lattice temperature of graphene, the team could enhance the modulation of its optical response, achieving a modulation factor of up to 300%. The experimental fabrication and measurement took place at Friedrich Schiller University Jena. Dr. Rostami played a crucial role in the study by crafting theoretical models. These models were developed in collaboration with another theory team at the University of Pisa to elucidate new effects observed in graphene.

Introduction Artificial intelligence has rapidly evolved over the last decade, leading to breakthroughs in natural language processing (NLP), machine learning, and multimodal applications. OpenAI’s O1 model exemplifies this innovation, offering capabilities that extend beyond traditional AI models. O1 is not just a tool; it is a revolutionary framework that brings advanced language understanding, multimodal integration, and real-time adaptability to the table. This comprehensive guide explores the intricacies of OpenAI’s O1 model, its applications, benefits, limitations, and how to optimize related content for search engine visibility.

We can expect to see more recommendations for VR in catastrophic injury cases.

Immersive Virtual Reality (IVR or VR) as a tool in rehabilitation is changing at pace and has far reaching consequences that will increasingly be seen in the claims space.

Combined with AI powered treatment planning and smart home devices for daily rehabilitation, innovative technologies are now evident in all aspects of rehabilitation.

In a unique demonstration of brain implants that incorporate living cells, the devices were able to connect with the brains of live mice.

By Jeremy Hsu

The Bubble Universe: A Bold New Theory

Researchers at Uppsala University in Sweden have introduced a revolutionary theory suggesting that our Universe exists as a four-dimensional bubble within a higher-dimensional space. This bubble concept is part of an attempt to unravel the mystery of dark energy, the enigmatic force causing the Universe’s rapid expansion.

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.