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Moody Urbanity - Manmade Confinements ⛑️
情绪化城市 - 人造禁锢 ⛑️
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🦎 City lizards turn out to be surprisingly social
#lizards

City lizards turn out to be surprisingly social
Streets, walls, concrete—cities may seem like a harsh environment. Yet some animals adapt remarkably well. A new study published in Biology Letters from Bielefeld University shows that common wall lizards (Podarcis muralis) behave far more socially in urban areas than in the countryside.

Chinese silicon wafer manufacturers like Eswin have rapidly gained market share by undercutting global leaders, such as Japan's Shin-Etsu Chemical, on price (Nikkei Asia)
https://asia.nikkei.com/business/technology…

In silicon wafers, China's emerging local stars rattle global giants
Japan has long led in key chip material, but Chinese rivals like Eswin catch up

Dynamic roughening of cities driven by multiplicative noise
Martin Hendrick, Gabriele Manoli
https://arxiv.org/abs/2510.02904 https://arxiv.org/pdf/2510.02…

Dynamic roughening of cities driven by multiplicative noise
The evolution of urban landscapes is rapidly altering the surface of our planet. Yet, our understanding of the urbanisation phenomenon remains far from complete. A fundamental challenge is to describe spatiotemporal changes in the built environment. A dynamic theory of urban evolution should account for both vertical and horizontal city expansion, analogous to the dynamical behaviour of surface growth in physical and biological systems. Here we show that building-height dynamics in cities aroun…

Smart Routing for EV Charge Point Operators in Mega Cities: Case Study of Istanbul
Onur Yenigun, Gozde Karatas Baydogmus, Kazim Yildiz
https://arxiv.org/abs/2509.21369 https://

Smart Routing for EV Charge Point Operators in Mega Cities: Case Study of Istanbul
The rapidly increasing use of electric vehicles (EVs) has made it even more important to manage the charging infrastructure sustainably. The expansion of charging station networks, especially in large cities, creates serious logistical challenges for charging point operators (CPOs) in planning maintenance and repair activities. Inefficient field personnel management can lead to time loss, high operational costs, and resource waste. This study presents an integrated method to optimize the planni…

Energy Efficiency in Cloud-Based Big Data Processing for Earth Observation: Gap Analysis and Future Directions
Adhitya Bhawiyuga, Serkan Girgin, Rolf A. de By, Raul Zurita-Milla
https://arxiv.org/abs/2510.02882

Energy Efficiency in Cloud-Based Big Data Processing for Earth Observation: Gap Analysis and Future Directions
Earth observation (EO) data volumes are rapidly increasing. While cloud computing are now used for processing large EO datasets, the energy efficiency aspects of such a processing have received much less attention. This issue is notable given the increasing awareness of energy costs and carbon footprint in big data processing, particularly with increased attention on compute-intensive foundation models. In this paper we identify gaps in energy efficiency practices within cloud-based EO big data…

Average-Case Complexity of Quantum Stabilizer Decoding
Andrey Boris Khesin, Jonathan Z. Lu, Alexander Poremba, Akshar Ramkumar, Vinod Vaikuntanathan
https://arxiv.org/abs/2509.20697

Average-Case Complexity of Quantum Stabilizer Decoding
Random classical linear codes are widely believed to be hard to decode. While slightly sub-exponential time algorithms exist when the coding rate vanishes sufficiently rapidly, all known algorithms at constant rate require exponential time. By contrast, the complexity of decoding a random quantum stabilizer code has remained an open question for quite some time. This work closes the gap in our understanding of the algorithmic hardness of decoding random quantum versus random classical codes. We…

How built environment shapes cycling experience: A multi-scale review in historical urban contexts
Haining Ding, Chenxi Wang, Michal Gath-Morad
https://arxiv.org/abs/2509.15657 …

How built environment shapes cycling experience: A multi-scale review in historical urban contexts
Understanding how built environments shape human experience is central to designing sustainable cities. Cycling provides a critical case: it delivers health and environmental benefits, yet its uptake depends strongly on the experience of cycling rather than infrastructure alone. Research on this relationship has grown rapidly but remains fragmented across disciplines and scales, and has concentrated on network-level analyses of routes and connectivity. This bias is especially problematic in his…

Kant: An Efficient Unified Scheduling System for Large-Scale AI Clusters
Lingling Zeng, Gen Zhang, Jialin Peng, Xiang Xu, Yuan Xu, Lijun Ma
https://arxiv.org/abs/2510.01256 http…

Kant: An Efficient Unified Scheduling System for Large-Scale AI Clusters
As AI cluster sizes continue to expand and the demand for large-language-model (LLM) training and inference workloads grows rapidly, traditional scheduling systems face significant challenges in balancing resource utilization, scheduling efficiency, and service quality. This paper presents and evaluates Kant: an efficient unified scheduling platform designed for large-scale AI container clusters, supporting the co-scheduling of both training and inference jobs. Based on the practical implementa…

Cronus: Efficient LLM inference on Heterogeneous GPU Clusters via Partially Disaggregated Prefill
Yunzhao Liu, Qiang Xu, Y. Charlie Hu
https://arxiv.org/abs/2509.17357 https://

Cronus: Efficient LLM inference on Heterogeneous GPU Clusters via Partially Disaggregated Prefill
Efficient LLM inference is critical for real-world applications, especially within heterogeneous GPU clusters commonly found in organizations and on-premise datacenters as GPU architecture rapidly evolves. Current disaggregated prefill strategies, which separate the prefill and decode stages of LLM inference across different GPUs, often suffer from suboptimal performance due to imbalances between GPU capabilities and workload demands. On the other hand, extending conventional data parallelism a…