Articles tagged with Three Dimensional Modeling
A new study found that inhibiting TBK1 increases CAR-T cell activity and makes cancer cells more susceptible to immune cell targeting. The researchers used patient-derived organotypic tumor spheroids (PDOTS) models to investigate the mechanisms of treatment resistance in solid tumors.
Researchers found that taller Japanese black pine trees have deeper roots, making them more resistant to disasters. Shorter trees are more likely to fall due to inadequate root growth.
Researchers at CAMERA have developed an open-source markerless motion capture system using computer vision and deep learning methods. The system estimates joint positions from regular 2D image data, providing unobtrusive analysis of body movements.
Researchers develop a simple fix to an existing technique, enabling the generation of sharp, high-quality 3D shapes that rival top model-generated 2D images. The new approach improves upon previous methods by avoiding costly retraining and complex postprocessing.
Researchers criticize the Digital Twin of Earth concept, highlighting the discrepancy between scientific models and reality. New computer models require new methods for appropriate data analysis and interpretation to ensure accurate knowledge and results.
Researchers have developed a 3D artificial skin model with all three layers, simulating diseases and injuries more accurately. The model can replace animals in toxicological studies of medicines and cosmetics, enabling the development of new treatments without animal testing.
Researchers have developed a mathematical model that provides strong evidence for the cosmic censorship conjecture in three dimensions, suggesting singularities inside black holes will always be hidden. The model has implications for quantum gravity and advances efforts to understand thermodynamic properties of black holes.
Researchers developed a platform to produce mature, uniform organoids using a three-dimensional engineered membrane. This breakthrough enables consistent quality and improved efficiency for practical applications in clinical trials and drug development.
Researchers at Anglia Ruskin University are investigating the complex relationship between fat tissue and colorectal cancer. The study aims to enhance knowledge of the tumour microenvironment, uncover new molecules crucial for cancer growth, and develop more effective treatments.
A new mathematical model of prostate cancer has been developed, revealing key findings on genetic changes and tumour growth. The study shows that strong genetic changes are necessary for aggressive tumours to develop early in the course of tumour development.
A study published in PLOS ONE suggests that 12,000-year-old stones from Israel may have been used as spindle whorls to turn fibers into yarn, representing a key milestone in the development of rotational tools including wheels. The stones feature a circular shape with a central hole, allowing them to rotate faster and more efficiently.
NeuroMechFly v2 simulates how a fruit fly navigates through its environment while reacting to sights, smells, and obstacles. The model can track moving objects visually or navigate towards an odor source, while avoiding obstacles in its path, enabling researchers to study brain-body coordination and animal intelligence.
Researchers developed a high-fidelity computational model to capture octopus arm muscular architecture and its complex movements. The model uses topology, dynamics, and control to simplify muscle contraction patterns and replicate octopus arm capabilities.
A new crowdsourcing system, FireLoc, uses a network of low-cost mobile phones to detect wildfires minutes—even seconds—after they ignite. The system prioritizes privacy and accurately maps wilderness fires to within 180 feet of their origin.
Devin Harris and his team have developed an augmented reality app, STRUCT-AR, that allows students to 'stress test' virtual bridges, beams, frames, and trusses. The app, which is set to be tested this spring, aims to improve students' understanding of structural behavior by providing a more interactive and immersive learning experience.
Researchers at Tel Aviv University demonstrated that bats can navigate great distances in open areas with their eyes closed, using only echolocation. The study found that bats create an acoustic map of their environment, relying on distinct echoes to guide their flight paths.
Researchers at Barrow Neurological Institute collected and displayed Vesalius' anatomical manikins for the first time, showcasing their enduring influence on modern anatomic teaching. The display highlights the significance of these works in revolutionizing anatomical education and training.
A machine learning model predicts soil behavior during earthquakes, identifying areas vulnerable to liquefaction and providing contour maps for safer construction sites. The study uses geological data to create detailed 3D maps of soil layers, improving prediction accuracy by 20%.
A new study published in Science Advances provides insights into the complex and nonlinear transition of mammal evolution from sprawled to upright posture. Researchers used cutting-edge methods to analyze fossil data and biomechanical modeling, revealing that locomotor performance peaked and dipped over millions of years.
Researchers found that chimpanzees have a similarly narrow pelvis to humans, contradicting previous theories. The study proposes a new hypothesis that the obstetrical dilemma developed gradually and became increasingly exacerbated over evolution.
Researchers created a 3D-printed model to mimic the conditions that spur cancer cells' spread, allowing them to visualize this process in real-time. The model revealed a mechanism where low oxygen levels promote metastasis through lowering pH levels.
Parachute fibers' behavior under stress was studied using micro-CT scans, revealing they are not isotropic and respond differently to increasing loads. The findings inform processes like parachute assembly and improve models for screening parachute materials, making industries more cost-effective and time-efficient.
The study of turtle genomes provides crucial information for the development of effective conservation strategies and the understanding of the evolution of sex chromosomes. Researchers have identified a novel three-dimensional chromatin conformation in both lineages, allowing for centromere-telomere interactions.
Researchers created a single cell atlas of prenatal human skin, providing a molecular recipe for building skin. The study also led to the creation of a mini organ model that grows hair, offering insights into scarless skin repair and potential clinical applications in regenerative medicine.
Researchers designed custom-fit PAP masks using computational modelling to reduce air leakage and increase comfort. The masks were tested against commercially available ones, showing promising results.
Researchers have developed a cell culture platform to form two distinct, interconnected vascular networks, replicating human physiology and reducing animal testing costs. This breakthrough enables the study of cellular interactions in vascularized tissues.
A new study published in Scientific Reports reveals the importance of foot movement in early infant development and interaction. By using machine and deep learning techniques, researchers found that AI can accurately classify five-second clips of 3D infant movements, with foot movements showing the highest accuracy rates.
Researchers developed a new model to account for directional anisotropies in land surface temperature (LST) measurements, which are affected by complex topography. The TESKD model outperforms existing methods in accuracy, particularly in mountainous regions.
Researchers at Mizzou have developed Cryo2Struct, a computer program that uses AI to build the three-dimensional atomic structure of large protein complexes from cryo-electron microscopy images. This breakthrough enables scientists to better understand protein interactions, critical for developing effective treatments for diseases like...
A new AI model called Crystalyze can analyze X-ray crystallography data to determine the structure of powdered crystals. The model was trained on a database of over 150,000 materials and successfully predicted structures for over 100 previously unsolved patterns.
Researchers at UCSF used cryogenic electron microscopy to study the protein TGF-Beta, which plays a crucial role in development and cancer. They found that TGF-Beta can signal even when bound to a 'straitjacket' within the cell membrane, challenging decades-old dogma on its function.
Researchers from University of Utah introduced Simulating Travel Rates in Diverse Environments (STRIDE) model to predict walking travel times with unprecedented accuracy. The model considers slope steepness, vegetation density, and ground surface roughness for efficient routes.
Yotam Gingold's NSF-funded project focuses on developing in-air 3D drawing tools, sonification techniques, and verbal 3D editing tools, enabling superhuman abilities in digital shape design and perception.
Researchers at Tel Aviv University used modern technologies to challenge the long-held myth that the Roman siege of Masada lasted three years. The study found that the siege actually lasted no more than a few weeks, using precise measurements and 3D digital modeling to calculate the time it took to build the siege system.
Roman Gaydukov developed a method to model fluid flow around rotating disks with small surface irregularities, reducing computational time and cost. The approach can accurately predict fluid flow behavior in chemical reactions and has potential applications in industry.
Researchers create superhydrophobic array device (SHArD) mimicking the lotus leaf surface structure, enabling high-throughput generation of three-dimensional nanoscale tumor models. This platform helps study metastasis and primary tumors, shedding light on cancer progression.
Researchers at Washington State University developed an AI algorithm that optimizes 3D printing settings, reducing time and cost for engineers. The algorithm improved the accuracy and quality of printed models, particularly for complex biomedical devices like kidneys and prostates.
Engineers at MIT have developed a physics-based model that accurately represents airflow around rotors under extreme conditions. This new theory has the potential to improve rotor blade designs and optimize wind farm layouts for maximum power output and safety.
A Chinese Medical Journal study developed an AI-based system to automate embryo selection and eliminate subjectivity in IVF. The system improved human embryo assessment and selection, achieving higher accuracy in embryo aneuploidy screening than experienced embryologists.
Researchers from POSTECH and KRICT created a 3D artificial lung using bioprinting technology, closely mimicking the human respiratory tract. This model allows for accurate testing of COVID-19 drugs and development of therapeutic treatments, potentially shortening the drug development process to under 5 years.
Researchers developed a technique that leverages component-based reduced order modeling to analyze composite laminates. The 'Lego-like' construction method offers improved speed and accuracy, making it a viable alternative to traditional finite-element analysis.
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.
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 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.
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.