First release: the charge-pump fractional-N loop, noise, delta-sigma, tuning-curve, lock and measurement-planning machinery distilled from a monolithic GaN-on-SOI HEMT-varactor PLL co-design study, generalized to any technology that fits a charge-pump loop -- CMOS, SiGe, GaN or board-level. The physics-informed-ML and...
Tanvir M. Mahim· Zenodo (CERN European Organi...· 0 citations
This dataset provides transportation mode-specific inter-county shortest-path distances along the real-world highway and railway networks in the contiguous United States. The dataset was generated using a QGIS–RStudio crosswalk that integrates geographic information system processing with network-based analysis to tran...
Yongxin Cai, Xinyan Li, Deniz Karakoç· Figshare· 0 citations
A resting cortical spectrum carries a narrow peak near 10 Hz, a weaker and equally narrow peak near 20 Hz, and a broad 1/f background running beneath and above them. Mechanistic accounts locate each rhythm in a relaxation time, so a second band requires a second circuit, the ratio of the two amplitudes is predicted by...
Pascal Moser· Zenodo (CERN European Organi...· 0 citations
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Real-time estimation of full unsteady aerodynamic flow fields $\mathbf{u}(\mathbf{x}, t) = (u, v)$ from ultra-sparse discrete sensor observations (e.g., $M \le 10$ point velocity probes across thousands of grid cells) is a foundational challenge in active flow control, wind tunnel telemetry, and unmanned aerial vehicle...
A. Emre Cetin· Zenodo (CERN European Organi...· 0 citations
WHAT THIS PACKAGE DOES This reproducibility package accompanies the methods manuscript "Exact Permutation Moments for Walsh Interaction-Order Energies: A Projector Specialization of Quadratic-Form Randomization Theory" (J600, Roshankumar Chandaliya, QDL project). It provides the complete open-source implementation, exh...
Roshankumar chandaliya· Zenodo (CERN European Organi...· 0 citations
24,126 computational IR, Raman, UV–Vis, fluorescence, ¹H/¹³C NMR, and C/N/O/F K-edge XANES records for 2,991 organic molecules, with a chemistry-constrained agent for reproducible workflows.
Ben Wang, Chenyang Du, Lulu Li et al.· Zenodo (CERN European Organi...· 0 citations
Jaeger's Petersen coloring conjecture (1988), which asserted that every bridgeless cubic graph admits an edge map onto the Petersen graph sending every vertex star onto a vertex star, was refuted in August 2026: Putman exhibited two nonisomorphic 112-vertex counterexamples with SAT-solver certificates, Jooken gave a hu...
Felipe Santibañez-Leal· Zenodo (CERN European Organi...· 1 citation
Two clinically decisive cardiac quantities cannot be measured where they are needed: the heart-surface potential map (measured only with an invasive electrode cage) and the intra-vascular pressure field (measured only with a catheter). Each is tied by a governing equation to a quantity measurable non-invasively, the bo...
Felipe Santibañez-Leal· Zenodo (CERN European Organi...· 0 citations
Added IsotropicDamage1D, IsotropicDamagePlaneStrain and IsotropicDamagePlaneStress, so a Truss and a Planar model can carry damage. Under plane stress the out-of-plane strain follows the in-plane one and contributes to the tangent. TransverseIsotropicElasticityPlaneStress and TransverseIsotropicElasticityPlaneStrain, s...
Nils Meyer· Zenodo (CERN European Organi...· 0 citations
This code-only package accompanies the manuscript “Federated Edge Learning over Optical-UAV Access Links With Deterministic-Payload Compression and Packetized Scheduling.”The software implements static mixed-resolution compression with error feedback (SMR-EF) and PacketFair scheduling for simulated federated learning o...
Federated Learning (FL) enables privacy-preserving distributed machine learning by keeping raw data local. However, conventional Artificial Neural Networks (ANNs) impose high computational and energy costs. Spiking Neural Networks (SNNs), inspired by biological neurons, provide energy-efficient computation via sparse s...
Samrajji N· Zenodo (CERN European Organi...· 0 citations
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 2, 2026