Tootfinder

UN sees world's emissions falling 10% by 2035, far short of 60% goal #environment

UN sees world's emissions falling 10% by 2035, far short of 60% goal
Global emissions of planet-warming greenhouse gases are expected to fall by about 10% by 2035, compared with 1990 levels, representing the first decline ever forecast by the United Nations. But the world remains well off course to keeping global warming below the 1.5 C leaders committed to when they signed the Paris Agreement a decade ago.

"UK’s richest set to produce 13 times more transport emissions than poorest by 2035"
#UK #UnitedKingdom #Climate

Experimental Study of Magnetic Near-Field Microstrip Electronic Probe for PCB EMC Emission Measurement
Hongchuan Jia (NUIST), Fayu Wan (NUIST), Vladimir Mordachev (ICB), J\'er\^ome Rossignol (ICB), Glauco Fontagalland (PIMENT), Nour Murad (PIMENT), Blaise Ravelo (NUIST)
https://arxiv.org/abs/2509.24944

Experimental Study of Magnetic Near-Field Microstrip Electronic Probe for PCB EMC Emission Measurement
An experimental study on magnetic near-field (NF) scanning of printed circuit board (PCB) emission radiation is developed in this paper. The design and installation of the electromagnetic (EM) NF scanner is introduced. The test bed of magnetic NF emission in the microwave frequency range is described. The methodology of the microstrip magnetic NF probe is discussed. The probe calibration process was performed following the IEC 61967-1 NF scanning standard. The NF scanner functioning is tested w…

Potatoes are mutant hybrids with... tomatoes.
https://edition.cnn.com/2025/07/31/science/potato-evolution-origins-tomato

The modern potato evolved from a wild tomato fling 9 million years ago, scientists say
A chance encounter between a wild tomato and a potato-like plant 9 million years ago is why we have modern-day potatoes, according to new research.

🇺🇦 #NowPlaying on BBCRadio3's #RoundMidnight
Ensemble C:
🎵 That Nabongo Feeling
#EnsembleC
https://open.spotify.com/track/0sUNXMaGiCDqeASxFlRdIw

Structural, optical, and electrical properties of Cu-doped NiO films synthesized by spray pyrolysis for potential gas sensing applications
Eka Nurfani, Grace Grace, Mahardika Yoga Darmawan, Resti Marlina, Jumaeda Jatmika, Asnan Rinovian, Aditya Rianjanu
https://arxiv.org/abs/2509.24197

Structural, optical, and electrical properties of Cu-doped NiO films synthesized by spray pyrolysis for potential gas sensing applications
Cu-doped NiO thin films were deposited on ITO substrates via spray pyrolysis at 450 °C for 1.5 minutes. XRD confirmed a cubic NiO structure, with Cu incorporation reducing crystallite size, increasing interplanar spacing, and expanding the lattice parameter, indicating successful substitution of Cu ions. Optical analysis showed a slight bandgap reduction from 3.70 to 3.65 eV, while PL revealed lower emission intensity, suggesting enhanced defect states and suppressed carrier recombination. Ram…

A Survey of Scientific Large Language Models: From Data Foundations to Agent Frontiers
Ming Hu, Chenglong Ma, Wei Li, Wanghan Xu, Jiamin Wu, Jucheng Hu, Tianbin Li, Guohang Zhuang, Jiaqi Liu, Yingzhou Lu, Ying Chen, Chaoyang Zhang, Cheng Tan, Jie Ying, Guocheng Wu, Shujian Gao, Pengcheng Chen, Jiashi Lin, Haitao Wu, Lulu Chen, Fengxiang Wang, Yuanyuan Zhang, Xiangyu Zhao, Feilong Tang, Encheng Su, Junzhi Ning, Xinyao Liu, Ye Du, Changkai Ji, Cheng Tang, Huihui Xu, Ziyang Chen, Ziyan Hu…

A Survey of Scientific Large Language Models: From Data Foundations to Agent Frontiers
Scientific Large Language Models (Sci-LLMs) are transforming how knowledge is represented, integrated, and applied in scientific research, yet their progress is shaped by the complex nature of scientific data. This survey presents a comprehensive, data-centric synthesis that reframes the development of Sci-LLMs as a co-evolution between models and their underlying data substrate. We formulate a unified taxonomy of scientific data and a hierarchical model of scientific knowledge, emphasizing the…

Spin-State Engineering of Single Titanium Adsorbates on Ultrathin Magnesium Oxide
Soo-hyon Phark, Hong Thi Bui, We-hyo Seo, Yaowu Liu, Valeria Sheina, Curie Lee, Christoph Wolf, Andreas J. Heinrich, Roberto Robles, Nicolas Lorente
https://arxiv.org/abs/2507.23299

Spin-State Engineering of Single Titanium Adsorbates on Ultrathin Magnesium Oxide
Single atomic adsorbates on ultrathin insulating films provide a promising route toward bottom-up quantum architectures based on atomically identical yet individually addressable spin qubits on solid surfaces. A key challenge in engineering quantum-coherent spin nanostructures lies in understanding and controlling the spin state of individual adsorbates. In this work, we investigate single titanium (Ti) atoms adsorbed on MgO/Ag(100) surfaces using a combined scanning tunneling microscopy and el…

GRB 250702B: Discovery of a Gamma-Ray Burst from a Black Hole Falling into a Star
Eliza Neights, Eric Burns, Chris L. Fryer, Dmitry Svinkin, Suman Bala, Rachel Hamburg, Ramandeep Gill, Michela Negro, Megan Masterson, James DeLaunay, David J. Lawrence, Sophie E. D. Abrahams, Yuta Kawakubo, Paz Beniamini, Christian Aa. Diget, Dmitry Frederiks, John Goldsten, Adam Goldstein, Alexander D. Hall-Smith, Erin Kara, Alison M. Laird, Gavin P. Lamb, Oliver J. Roberts, Ryan Seeb, V. Ashley Villar,…

GRB 250702B: Discovery of a Gamma-Ray Burst from a Black Hole Falling into a Star
Gamma-ray bursts are the most luminous electromagnetic events in the universe. Their prompt gamma-ray emission has typical durations between a fraction of a second and several minutes. A rare subset of these events have durations in excess of a thousand seconds, referred to as ultra-long gamma-ray bursts. Here, we report the discovery of the longest gamma-ray burst ever seen with a ~25,000 s gamma-ray duration, GRB 250702B, and characterize this event using data from four instruments in the Int…

BALLAST: Bayesian Active Learning with Look-ahead Amendment for Sea-drifter Trajectories under Spatio-Temporal Vector Fields
Rui-Yang Zhang, Henry B. Moss, Lachlan Astfalck, Edward Cripps, David S. Leslie
https://arxiv.org/abs/2509.26005

BALLAST: Bayesian Active Learning with Look-ahead Amendment for Sea-drifter Trajectories under Spatio-Temporal Vector Fields
We introduce a formal active learning methodology for guiding the placement of Lagrangian observers to infer time-dependent vector fields -- a key task in oceanography, marine science, and ocean engineering -- using a physics-informed spatio-temporal Gaussian process surrogate model. The majority of existing placement campaigns either follow standard `space-filling' designs or relatively ad-hoc expert opinions. A key challenge to applying principled active learning in this setting is that Lagra…