A new study suggests that the rising earth in Antarctica will impact future sea level rise, depending on how much global warming is controlled. If humans lower greenhouse gas emissions, upward shifts in solid earth could reduce Antarctica's contribution to sea level rise by about 40%, bolstering best-case scenarios for global sea level...
An AI model developed by King's College London has produced realistic synthetic images of the human brain, supporting medical research on brain diseases like dementia, stroke, and multiple sclerosis. The high-resolution images accurately reflect clinical factors and can be used to tailor treatment plans for individual patients.
A team of scientists has created a 3D-printed model of human hair follicles to test new treatments against hair follicle infections. The model, which replicates the natural environment of hair follicles, allows for early-stage testing of drug candidates without animal testing.
A model simulates the group motion of fish based on visual cues, showing that each fish selects a single target and traces its motion. The model reproduces various collective patterns, including rotating vortexes and turning motions.
Researchers have created a detailed 3D atlas of the African clawed frog's development, revealing key changes during metamorphosis. The atlas uses X-ray microtomography to show the transformation from tadpole to mature adult frog.
A team of astronomers used NASA's Hubble Space Telescope to create the most accurate three-dimensional understanding of stars' movements within the Draco dwarf galaxy. This allowed them to build a more precise model of dark matter distribution, which aligns with cosmological models and suggests a cusp-like structure.
The e-COL+ project aims to capture and reconstruct France's natural history collections in 3D, covering nearly 6% of the world's total natural specimens. The project will provide modern equipment, create a comprehensive dataset of 3D models, and build AI tools to improve model reconstruction.
Researchers developed a flexible-yet-sturdy morphing structure inspired by the starfish skeleton with 4D morphing features. The structure exhibits self-locking, continuous bending, self-healing, and shape memory features, making it suitable for industry applications in robotics, aviation, and biomedical devices.
A new radiative transfer modeling framework using Helios 3D software simulates RGB, multispectral, thermal, and depth images of plants with high accuracy. The framework reduces the need for manual data collection, enabling efficient training of deep learning models for high-throughput plant phenotyping and advancing agricultural research.
A new imaging technique allows scientists to visualize the Earth's rocky interior using GPS data, revealing details about the planet's crust and mantle. This method has the potential to improve earthquake predictions by combining it with other techniques.
Researchers at U of T have developed a deep-learning model called PepFlow that can predict the full range of conformations for peptides, which are shorter than proteins but perform similar biological functions. The model combines machine learning and physics to capture precise and accurate conformations within minutes.
Researchers from Florida Atlantic University developed a novel approach using wearable sensors and machine learning to assess balance. The method achieved high accuracy and strong correlation with ground truth balance scores, suggesting it is effective and reliable in estimating balance.
A new study published in Science Advances documents the first case of Down syndrome in Neandertals, named 'Tina', and reveals that they provided extensive care for a young child with severe hearing loss. The discovery sheds light on the existence of true altruism among Neandertals.
Researchers at NTNU have developed a way to reconstruct 3D models of the colon using single images taken by capsule endoscopy cameras. These models can aid in detecting abnormalities and signs of disease, enabling specialists to make diagnoses faster.
Researchers use laser scanning to generate 3D models of sugar beet plants, capturing essential characteristics for AI-assisted crop improvement. The 3D models are reproducible and freely available, enabling efficient and cost-effective plant breeding in resource-poor settings.
Researchers at ETH Zurich create a 3D in vitro model to study brittle bone disease, using healthy cells initially and planning to use cells from patients with the condition. The model successfully emulates bone development, allowing for the discovery of malfunctioning processes and potential treatments.
Researchers created a virtual rodent with an artificial brain that can move like a real rodent, simulating complex behaviors using biomechanical data from real rats. The model uses deep reinforcement learning and AI to predict neural activity across behaviors.
Texas A&M University researchers have developed a 3D visualization technology to identify potential outcomes of hurricane flooding before it occurs. This allows for improved safety and reduced damage costs. The technology can also model specific buildings, accounting for basements, back entrances, and windows.
A new method for detecting defects in additively manufactured components uses deep machine learning, generating synthetic defects for training and testing on physical parts. The algorithm accurately identifies hundreds of defects, even those unseen by the model before.
Researchers at New York University create a new method to see inside crystals, revealing the position of every unit and creating dynamic three-dimensional models. This technique allows scientists to study crystals' chemical history and form, paving the way for better crystal growth and photonic materials.
Researchers developed a predictive model that maps soil-bearing layer distribution, enabling city planners to assess site suitability and optimize building design. The model improves prediction accuracy by combining geotechnical data and geographic coordinates.
The study enhances shape-from-shading technique to create detailed models of lunar terrain with higher resolutions and faster production speeds. Researchers use advanced computer algorithms to automate the process, resulting in more accurate maps that show subtle features and variations of lunar surface terrain.
A new study suggests that the sun's magnetic field could arise from instabilities in the outermost layers of the sun, rather than deep within. This finding may enable scientists to better forecast solar activity and space weather.
Researchers at the University of Bonn improved 3D ocean circulation models using supercomputing resources to analyze ocean tide changes and their impact on coastal regions. The study found that a warming ocean surface enhances baroclinic tides, leading to significant energy transfer.
Scientists have developed a functional model of thoracic aortic aneurysm using human cells in laboratory rats, offering new avenues for drug development and effective screening. The model successfully mimics dilation of the human aorta and has potential applications for treating this potentially fatal condition.
Researchers used supercomputer simulations and machine learning to map diamond's phonon stability boundary in six dimensional strain space. This framework guides the engineering of materials through elastic strain engineering, enabling the development of new devices such as computer chips and quantum sensors.
Researchers developed Tripath to analyze 3D tissue samples, predicting clinical outcomes based on 3D morphological features. This approach outperformed traditional methods, providing promising potential for guiding critical treatment decisions.
Researchers developed a novel 3D printing technology that can print multi-material tubular structures as thin as 50 micrometers. The technology, called Polar-coordinate Line-projection Light-curing Production (PLLP), uses a rotating mandrel and patterned light illumination to create complex structures.
The study, published in Cell Stem Cell, improves the growth of nephron progenitor cells (NPCs) using a chemical cocktail, enabling sustained growth in a simple 2-dimensional format. The breakthrough has potential for advancing kidney research and discovering new treatments.
Researchers at Insilico Medicine developed COSMIC, a new framework for molecular conformation space modeling that provides accurate insights into molecule positioning and activity. This enables faster and more efficient drug design decisions.
Using AI software called SLEAP, scientists at Salk Institute are designing climate-saving plants with optimized root systems that can store more carbon. This approach enables researchers to analyze plant features and connect desirable traits to targetable genes, accelerating the development of carbon-capturing plants.
A new paper argues that Venus, with its surface temperatures hot enough to melt lead and a toxic atmosphere, can provide valuable lessons about the potential for life on other planets. The study highlights the importance of understanding the conditions that make Earth habitable, as well as the risks of runaway greenhouse effects.
A new study models the impact of high thermal conductivity paper on power transformer performance and life. The research aims to improve transformer efficiency by reducing hotspot temperatures, potentially doubling or tripling lifespan. Researchers used Stampede2 supercomputer simulations to test the effectiveness of engineered paper.
A multidisciplinary team is developing computational models to predict heart valve leakage in children with specific birth defects. The models use 2D and 3D echocardiogram data to simulate the shape of valves and potential weak spots, enabling surgeons to plan surgeries more effectively.
A University of Melbourne expedition revealed that wind is a key cause of colossal rogue waves. The team's observations confirmed theories and provided critical information for future rogue wave prediction models.
Jos Malda receives ERC grant to crack cartilage code and create regenerative treatments. By studying cartilage 'organ-on-a-chip' models and animal cartilages, researchers aim to recreate the intricate internal structure of cartilage.
A new 3D printer developed by researchers at MIT and NIST can automatically identify the parameters for printing with unknown materials. This allows for the use of renewable or recyclable materials that were previously difficult to characterize, reducing the environmental impact of additive manufacturing.
Researchers develop a computational approach to predict mutations leading to better proteins, with potential applications in neuroscience research and gene therapy. The technique uses a convolutional neural network to create a fitness landscape, enabling faster optimization of proteins.
Researchers develop AI-powered method to rapidly predict multiple protein configurations, understanding protein dynamics and functions. This breakthrough has the potential to revolutionize drug discovery by uncovering more targets for new treatments.
Researchers at University of Missouri are developing software that allows drones to fly independently, perceiving and interacting with their environment while achieving specific goals. This technology has the potential to assist in mapping and monitoring applications, such as 3D or 4D advanced imagery for disaster response.
Researchers at MIT have developed a method to analyze the behavior of granular materials, revealing their internal forces and shapes in 3D detail. This breakthrough may lead to better understanding of landslides and industrial processes.
A team of researchers has developed the world's first 3D-printed brain phantom, which can be imaged using dMRI. The brain model is made up of microchannels that mimic nerve cells in the brain, allowing for more accurate analysis and research into neurodegenerative diseases.
A team of researchers from Kyoto University has developed a microfluidic co-culture vasculature chip that mimics the microenvironment of alveolar soft part sarcoma (ASPS), a rare cancer. The chip enables scientists to study cell-to-cell interactions and angiogenic mechanisms, which may lead to new strategies for treating ASPS patients.
The study integrates Computational Intelligence (CI) into 3D plant canopy modeling to capture detailed morphological data. It demonstrates the method's ability to simulate effects of planting density on canopy structure, including shading and adjustments in leaf angles.
Researchers have developed a vascularized organoid model (VOM) that accurately replicates the actual vasculature and environment of gastric cancer, enabling patient-specific predictions of response to anticancer drugs. The VOM demonstrates high cell viability rates and similarity to actual gastric cancer conditions.
A new AI-powered tool developed by the University of Copenhagen and 3Shape predicts how teeth will move, allowing orthodontists to ensure braces are neither too loose nor too tight. The tool uses scanned imagery of teeth and bone structures to simulate how braces should fit, reducing trial and error.
Researchers developed a custom-built, low-cost mesoscope that can adapt to different neuroimaging experiments in live mice and rats. The system offers excellent spatial and temporal resolutions, achieved through its reversible tandem lens configuration, which enables flexible experimentation.
Researchers developed a machine-learning model to assess prostate cancer biopsy samples, overcoming limitations of traditional methods. The new model, nnU-Net, provides accurate 3D segmentation of glandular tissue structures, leading to better prognostic analyses and potential improvements in patient outcomes.
This study introduces a computational model that uncovers the genetic architecture of tree growth in Populus euphratica, focusing on above- and below-ground traits. The model successfully delineates genetic contributions and network topology driving phenotypic formation, highlighting distinct time-varying growth characteristics.
Researchers at Salk Institute have created a novel organoid model of the human brain that includes mature, functional astrocytes. This allows for the study of inflammation and stress in aging and diseases like Alzheimer's with greater clarity, revealing a relationship between astrocyte dysfunction and inflammation.
Astronomers have discovered a massive, wave-shaped structure in the Milky Way, which is oscillating through space-time. The Radcliffe Wave is approximately 9,000 light years long and moves like a traveling wave, with star clusters along its path moving up and down.
Researchers have confirmed a new method for precise body composition analysis using 3D surface scans and dual-energy X-ray absorptiometry. This approach yields accurate measurements of fat, lean muscle, and bone, surpassing commercial software in clinical settings.
A new study using computational models suggests that a subduction zone below the Gibraltar Strait will migrate into the Atlantic, contributing to an Atlantic ring of fire. This process, called subduction invasion, is expected to happen in approximately 20 million years.
A new model developed by MIT engineers predicts how certain shoe properties will affect a runner's performance, incorporating factors like stiffness and springiness. The model aims to help designers create high-performing shoes with novel properties.
A new 3D bioprinted liver tissue model has been developed to study nonalcoholic steatohepatitis (NASH), a serious complication of nonalcoholic fatty liver disease (NAFLD). The model, created using liver cells from healthy or NASH-diseased donors, displays all characteristics of the disease, including fibrosis.
Researchers from Purdue University used deep learning to generate growth models for various tree species, both with and without leaves. The AI models can produce complex tree models with detailed geometry, improving digital forest endeavors.
UAB researchers have created a 3D, three-layer nanomatrix vascular sheet that mimics human atherosclerosis, enabling high-throughput drug screening. The model replicates key features of the disease and has been validated with two classic atherosclerosis drugs.
The review discusses the optical aspects of QPAT, including mathematical models for light propagation and interaction with biological tissues. The authors outline two approaches to estimating chromophore concentrations from absorbed optical energy density data, highlighting the challenges associated with practical implementation, such ...
A team of astronomers created the first-ever 3D map of magnetic field structures within a spiral arm of the Milky Way galaxy, showing that magnetic fields break away from the general picture and impact star-forming regions. The findings suggest that magnetic fields played a role in creating our own solar system.
A new study reveals that microplastic fibers settle substantially slower than spherical particles in the atmosphere, allowing them to reach remote regions such as Arctic glaciers. The research suggests that these fibers could even reach the stratosphere, with potential implications for cloud processes and ozone depletion.