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"Philippines approves world’s largest solar project for grid connection"
#Philippines #SolarPower #Energy #Renewables

Philippines approves world’s largest solar project for grid connection
The Energy Regulatory Commission (ERC) of the Philippines has given the MTerra Solar Project permission to develop its own dedicated transmission facilities and connect to the Luzon grid. The first phase, encompassing 2.5 GW of solar and 3.3 MWh of battery storage, is due for completion in 2026.

NanoTag: Systems Support for Efficient Byte-Granular Overflow Detection on ARM MTE
Mingkai Li, Hang Ye, Joseph Devietti, Suman Jana, Tanvir Ahmed Khan
https://arxiv.org/abs/2509.22027

NanoTag: Systems Support for Efficient Byte-Granular Overflow Detection on ARM MTE
Memory safety bugs, such as buffer overflows and use-after-frees, are the leading causes of software safety issues in production. Software-based approaches, e.g., Address Sanitizer (ASAN), can detect such bugs with high precision, but with prohibitively high overhead. ARM's Memory Tagging Extension (MTE) offers a promising alternative to detect these bugs in hardware with a much lower overhead. However, in this paper, we perform a thorough investigation of Google Pixel 8, the first production i…

Subthermal Mean Transverse Energies Induced by Electron Refraction on the Jump in Mass at the Surface of Multialkali Photocathodes
S. A. Rozhkov, V. V. Bakin, H. E. Scheibler, V. S. Rusetsky, D. V. Gorshkov, D. A. Kustov, V. A. Golyashov, V. L. Alperovich, O. E. Tereshchenko
https://arxiv.org/abs/2510.02897…

Subthermal Mean Transverse Energies Induced by Electron Refraction on the Jump in Mass at the Surface of Multialkali Photocathodes
The search for photocathode materials with low mean transverse energies (MTEs) and, hence, low intrinsic emittance is of crucial importance for various fields of particle and solid state physics. Here, we demonstrate that polycrystalline multialkali Na$_{2}$KSb(Cs,Sb) photocathodes with negative effective electron affinity (NEA) have MTE values at room temperature by a factor of 2 lower than those of monocrystalline \textit{p}-GaAs(Cs,O) photocathodes. These low MTE values are due to the electr…

PTEB: Towards Robust Text Embedding Evaluation via Stochastic Paraphrasing at Evaluation Time with LLMs
Manuel Frank, Haithem Afli
https://arxiv.org/abs/2510.06730 https://

PTEB: Towards Robust Text Embedding Evaluation via Stochastic Paraphrasing at Evaluation Time with LLMs
Current evaluations of sentence embedding models typically rely on static test beds such as the Massive Text Embedding Benchmark (MTEB). While invaluable, repeated tuning on a fixed suite can inflate reported performance and obscure real-world robustness. We introduce the Paraphrasing Text Embedding Benchmark (PTEB), a dynamic protocol that stochastically generates meaning-preserving paraphrases at evaluation time and aggregates results across multiple runs. Using a cost-efficient LLM-based met…

Multiplicative Turing Ensembles, Pareto's Law, and Creativity
Alexander Kolpakov, Aidan Rocke
https://arxiv.org/abs/2510.04167 https://arxiv.org/pdf/25…

Multiplicative Turing Ensembles, Pareto's Law, and Creativity
We study integer-valued multiplicative dynamics driven by i.i.d. prime multipliers and connect their macroscopic statistics to universal codelengths. We introduce the Multiplicative Turing Ensemble (MTE) and show how it arises naturally - though not uniquely - from ensembles of probabilistic Turing machines. Our modeling principle is variational: taking Elias' Omega codelength as an energy and imposing maximum entropy constraints yields a canonical Gibbs prior on integers and, by restriction, o…

EmbeddingGemma: Powerful and Lightweight Text Representations
Henrique Schechter Vera, Sahil Dua, Biao Zhang, Daniel Salz, Ryan Mullins, Sindhu Raghuram Panyam, Sara Smoot, Iftekhar Naim, Joe Zou, Feiyang Chen, Daniel Cer, Alice Lisak, Min Choi, Lucas Gonzalez, Omar Sanseviero, Glenn Cameron, Ian Ballantyne, Kat Black, Kaifeng Chen, Weiyi Wang, Zhe Li, Gus Martins, Jinhyuk Lee, Mark Sherwood, Juyeong Ji, Renjie Wu, Jingxiao Zheng, Jyotinder Singh, Abheesht Sharma, Divya Sreepat, Aashi …

EmbeddingGemma: Powerful and Lightweight Text Representations
We introduce EmbeddingGemma, a new lightweight, open text embedding model based on the Gemma 3 language model family. Our innovative training recipe strategically captures knowledge from larger models via encoder-decoder initialization and geometric embedding distillation. We improve model robustness and expressiveness with a spread-out regularizer, and ensure generalizability by merging checkpoints from varied, optimized mixtures. Evaluated on the Massive Text Embedding Benchmark (MTEB) across…