Retired Army Transportation Operations Machinist Toolmaker welder, Robotics, MSN Programming and Technology DOD certified soldering board builder desi Python

Tacoma, WA
Replying to @paul4jennii
A physics/control-domain diagram: SUN │ ┌───────────┴───────────┐ │ │ PHOTONS SOLAR WIND │ │ ▼ ▼ Optical state R E-sail voltage V │ │ ▼ ▼ F_SRP, τ_SRP F_E │ │ └──────────┬────────────┘ ▼ CONTROL ALLOCATOR │ ┌────────────┼────────────┐ ▼ ▼ ▼ RCD/optical SMA/kirigami Petal sweep │ │ │ └────────────┼────────────┘ ▼ SPACECRAFT STATE │ ┌──────────┼──────────┐ ▼ ▼ ▼ Orbit Attitude Thermal That would communicate the entire paper in one image.
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A smooth takeoff from the green 🟢✈️ Ramp, what a view!
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Turbine hotsection assembly complete!
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🖼️🛰️ Multi-Attitude Hybrid #Network for Remote Sensing #Hyperspectral Images #SuperResolution ✍️ Chi Chen et al. 🔗 brnw.ch/21x5XeD
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Ufoliumで群論と解析力学のシリーズが始まりました!
群論のエッセンス 「第1回 群とは何か、ケーリー図」を公開しました!
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☄️🌲 In 1908, the sky over Siberia exploded. A space rock estimated at roughly 50–60 meters across entered Earth’s atmosphere and exploded before reaching the ground. The resulting Tunguska airburst devastated an enormous forest area, flattening millions of trees. Now look ahead to 2029: asteroid Apophis will make a remarkably close flyby of Earth—but it is not expected to impact us. Two cosmic encounters. More than a century apart. Space rocks don’t need to hit the ground to leave a mark. 🌍💥
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Will we ever see Term limits? I think a candidate that supports that might gain quite a bit of popularity from the people, but lose it in Congress…so probably not.
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For the first time, a group of researchers — including scientists from @GoogleResearch and HHMI Janelia — built the first complete brain map for a male fruit fly. Together, we mapped every single neural connection in a male fruit fly brain and central nervous system, amounting to more than 166,000 neurons. Here’s why we did it.
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A Spectral Theory of Grokking: Weight Decay induces Feature Learning Lenz Pracher, Pascal de Jong, Oskar Lieshaus, Alan Jeffares, Steffen Rulands arxiv.org/abs/2609.26679 [𝚌𝚜.𝙻𝙶 𝚌𝚜.𝙰𝙸]
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Orion and the Geminids ✨☄️
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The Lanczos potential in the Plebanski paradigm of gravity Daniel Espín, Alejandro Jiménez Cano, Javier Olmedo, António Torres Manso arxiv.org/abs/2609.29434 [𝚐𝚛-𝚚𝚌]
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Magnetic quantum oscillations give insights into the Fermi surface properties of altermagnetic chromium antimonide. In Physical Review B, researchers confirm its predicted electronic band structure using pulsed magnetic fields — up to 68 T. Learn more: go.aps.org/4xIFHuO
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A magnetic storm on the Sun, frozen in a single dark eye. This sunspot looks black only by comparison. Its umbra is still thousands of degrees hot — just cooler than the boiling photosphere around it, because intense magnetic fields stand almost straight out of the surface and choke the rising columns of superheated plasma. Those same convective cells, blocked inside the spot, keep bubbling freely outside it, stitching the restless, rice-grain pattern of granulation you see at the edges. The image was taken in near-ultraviolet light at 396.8 nm — close to the calcium H line — on 2 July 2010 with the Swedish 1-metre Solar Telescope at Roque de los Muchachos on La Palma. Credit: Swedish 1-m Solar Telescope / Luc Rouppe van der Voort
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The Standard Model is less like a list of “tiny particles” and more like a map of what matter and forces are made from. It contains 12 fermions, 5 gauge bosons, and the Higgs boson. Quarks carry color charge and never appear isolated, while the Higgs has spin 0 and a mass of about 125 GeV/c². One important detail: there is no physical W⁰. The neutral weak field mixes with the B field to produce the photon and Z boson. The deeper lesson is that the Standard Model describes fields first, and particles are their observable excitations.
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BJT Basics in Real Circuits: What Actually Matters 📍 BJTs often get overlooked next to MOSFETs. But in real-world designs, they're still everywhere: switching, driving loads, protection circuits, delays, and simple control paths. The problem isn't understanding what a BJT does. The real challenge is knowing how it's actually used. Here's what matters in practice 👇 🟠 Switching = Cutoff or Saturation Most BJTs act as switches, not amplifiers. They're current-driven (unlike MOSFETs). That makes base drive design critical. Only two states matter: • Cutoff → OFF • Saturation → fully ON Anything in between just burns power. 🟠 NPN vs PNP – Not Interchangeable • NPN → low-side switching • PNP → high-side switching It's not about the symbol. It's about current flow and reference levels. 🟠 Base Resistor Is Not Optional It sets base current, protects the device, and ensures saturation. Goal: enough current for reliable turn-on, but controlled and predictable. 🟠 Never Leave the Base Floating A floating base = reliability risk. Add a pull-up or pull-down resistor to: • Define a known OFF state • Prevent false triggering • Improve turn-off behavior Small detail, big reliability difference. 🟠 Inductive Loads Need a Discharge Path Relays, coils, buzzers → energy must go somewhere when the transistor turns off. No flyback path = voltage spikes, device stress, poor reliability. Protection isn't optional – it's part of the design. 🟠 A BJT Is Still Analog Even as a switch, it's not ideal: • V_BE varies • Gain changes with temp and current • Saturation ≠ zero loss Real behavior often differs from textbook assumptions. 📌 DFM Reality Check From a PCB and production view: • Weak base drive → incomplete saturation • Missing discharge paths → slow turn-off • Poor grounding → erratic switching • Inductive load layout → voltage spikes Small schematic details become big bring-up problems. Bottom line: BJTs aren't obsolete. They're still the go-to for simplicity, cost, and predictable behavior – especially in switching and control circuits. #BJT #Transistor #PCBDesign #HardwareEngineering #AnalogDesign #PowerElectronics #DFM #ElectronicsEngineering
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Did you know that random forests are useful not only for prediction and classification, but also for imputing missing data? They can model complex, nonlinear relationships that many traditional methods fail to capture. The plot below shows how well random forest imputation preserves the structure of the observed values. Instead of relying on a single regression line, the model combines information from many decision trees. This allows it to capture interactions and patterns that simpler approaches often miss. As a result, the imputed values stay close to the real distribution and reflect the underlying data more accurately. If you want to learn how to apply random forest imputation and other missing data techniques in practice, check out my online course Missing Data Imputation in R. More information: statisticsglobe.com/online-c… #DataVisualization #programmer #datastructure #RStats #DataAnalytics
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Can The Sun's Heat Produce Cold? ☀️❄️🤔 How to build your own 100% solar-powered DIY freezer (that reaches -48°C 🥶), with basic hardware store parts, in a single afternoon 👇
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