Weaviate’s Post

🌍 Introducing a World First in Particle Analysis Vision Analytical is proud to unveil the world’s first recirculating dry suspension module for particle size and shape analysis — developed for the Raptor Particle Size and Shape Analyzer. Unlike traditional single-pass dry dispersion systems that use high pressure (and risk breaking fragile particles), this new module features a gentle, continuous recirculating design that: 🔸Preserves delicate particles 🔸Enables fully representative sampling 🔸Works perfectly with limited or air-sensitive materials This breakthrough expands what’s possible in dynamic image analysis (DIA) — offering better data quality, sample efficiency, and reliability. 🎥 See the module in action: https://lnkd.in/eNmHj4qa #VisionAnalytical #RaptorAnalyzer #ParticleSize #ParticleShape #DynamicImageAnalysis #PowderAnalysis #MaterialCharacterization #LabInnovation #AnalyticalInstruments

🚀 StiffPredict — Machine learning-based tool for predicting the rotational stiffness (k₀) of semi-rigid beam-to-upright connections in storage rack systems. Developed from validated experimental and numerical data, it offers fast, reliable, and explainable stiffness estimation without full-scale testing. 🎥 Watch the demo video below or request access at 👉 https://lnkd.in/dwgztiCP #StructuralEngineering #MachineLearning #ColdFormedSteel #StorageRacks #StructuralDesign

'Whereas scientific description and approximations very often strip away context and so enable discrete measurement results and simple input-output pairings (dyads), real world interactions always require triads, cycles of input-output-context.' Eastman (2020)

I'm pleased to announce that my R package, DEmixR, has been published on CRAN. This package implements robust methods for deconvoluting 2-component normal and log-normal mixture models, a common challenge in statistical modeling. This release is the first step; an accompanying paper elaborating on its methodology and applications is currently in the works. You can find the package here: https://lnkd.in/dSsknDTX #Statistics #RStats #MixtureModels #ResearchTool

You think lava lamps are just retro eye candy? Think again. Behind the hypnotic blobs is real chemistry—and a Safety Data Sheet (SDS) that reads more “science lab” than “house décor.” In our latest post, we peek at what an SDS reveals about lava lamps: https://lnkd.in/gTV7KEHx

The proteins get folded—locally. ⚛️ In V14.3, BioMoleculePlot3D can now compute protein structures directly on your machine. No API calls, no size limits—just raw computation. https://lnkd.in/gAfaS5-Q

Protein folding remains a fundamental challenge in molecular biology, where physics, chemistry, and AI converge. It’s exciting to see that Mathematica now enables protein structure prediction using neural networks. It also incorporates molecular mechanics principles to verify structural plausibility, accounting for bond stretching, angle bending, torsional strain, van der Waals forces, and electrostatics. This hybrid approach well reflects the spirit of the 2024 Nobel Prize in Chemistry.

"How do you assemble the new OASE® digilab and connect it to OASE® connect?" "How do you measure and analyze a sample using the device?" "How does OASE® digilab help in data tracking and storage for smoother plant operations?" To answer your questions, we've prepared a simple step-by-step tutorial on how to use the new OASE® digilab. If you still have unanswered questions by the end of the video, you can learn more at: https://lnkd.in/dKzWYGSH

5/160:"Implemented an efficient O(n) algorithm to generate the next lexicographical permutation of an array. Optimized for in-place updates with minimal complexity.

*Edited ⚡ When it comes to surface measurement, speed is just as critical as accuracy. That’s why we compared our technology with similar confocal and interferometric systems under the same measurement conditions. ❓ How long does it take to measure a sample of 1.7 mm × 1.4 mm × 50 µm? Using identical resolutions and equivalent objectives, here’s what we found: 🔬 #Interferometry (10× objective – ~1.4 µm lateral resolution, ~1 nm vertical resolution) • S neox: 15 seconds • Other similar systems: more than 5 minutes 🔬 #Confocal (20× objective – ~0.7 µm lateral resolution, ~5 nm vertical resolution) • S neox: 21 seconds • Other similar systems: more than 3 minutes 👉 Whether using Confocal or Interferometry, #Sneox delivers ultrafast measurements without compromising precision, saving valuable time in both R&D and production environments.