Tootfinder

ViPSN 2.0: A Reconfigurable Battery-free IoT Platform for Vibration Energy Harvesting
Xin Li, Mianxin Xiao, Xi Shen, Jiaqing Chu, Weifeng Huang, Jiashun Li, Yaoyi Li, Mingjing Cai, Jiaming Chen, Xinming Zhang, Daxing Zhang, Congsi Wang, Hong Tang, Bao Zhao, Qitao Lu, Yilong Wang, Jianjun Wang, Minyi Xu, Shitong Fang, Xuanyu Huang. Chaoyang Zhao, Zicheng Liu, Yaowen Yang, Guobiao Hu, Junrui Liang, Wei-Hsin Liao

ViPSN 2.0: A Reconfigurable Battery-free IoT Platform for Vibration Energy Harvesting
Vibration energy harvesting is a promising solution for powering battery-free IoT systems; however, the instability of ambient vibrations presents significant challenges, such as limited harvested energy, intermittent power supply, and poor adaptability to various applications. To address these challenges, this paper proposes ViPSN2.0, a modular and reconfigurable IoT platform that supports multiple vibration energy harvesters (piezoelectric, electromagnetic, and triboelectric) and accommodates…

🇺🇦 #NowPlaying on BBCRadio3's #NightTracks
Wolfgang Amadeus Mozart & Armida Quartett:
🎵 String Quartet in B flat major K.172 (3rd mvt)
#WolfgangAmadeusMozart #ArmidaQuartett
https://open.spotify.com/track/0sG7UZ3veHi1o3BkNqmigG

DP-Fusion: Token-Level Differentially Private Inference for Large Language Models
Rushil Thareja, Preslav Nakov, Praneeth Vepakomma, Nils Lukas
https://arxiv.org/abs/2507.04531

DP-Fusion: Token-Level Differentially Private Inference for Large Language Models
Large language models (LLMs) can leak sensitive information from their context through generated outputs, either accidentally or when prompted adversarially. Existing defenses that aim to preserve context privacy during inference either lack formal guarantees or suffer from a poor utility/privacy trade-off. We propose DP-Fusion, a token-level Differentially Private Inference (DPI) mechanism that provably bounds how much an LLM's outputs reveal about sensitive tokens in its context. We demonstra…

Archetype-Aware Predictive Autoscaling with Uncertainty Quantification for Serverless Workloads on Kubernetes
Guilin Zhang, Srinivas Vippagunta, Raghavendra Nandagopal, Suchitra Raman, Jeff Xu, Marcus Pfeiffer, Shree Chatterjee, Ziqi Tan, Wulan Guo, Hailong Jiang
https://arxiv.org/abs/2507.05653

Archetype-Aware Predictive Autoscaling with Uncertainty Quantification for Serverless Workloads on Kubernetes
High-performance extreme computing (HPEC) platforms increasingly adopt serverless paradigms, yet face challenges in efficiently managing highly dynamic workloads while maintaining service-level objectives (SLOs). We propose **AAPA**, an archetype-aware predictive autoscaling system that leverages weak supervision to automatically classify 300\,000\,+ workload windows into four archetypes (PERIODIC, SPIKE, RAMP, STATIONARY\_NOISY) with 99.8\% accuracy. Evaluation on publicly available Azure Func…

ViFusion: In-Network Tensor Fusion for Scalable Video Feature Indexing
Yisu Wang, Yixiang Zhu, Xinjiao Li, Yulong Zhang, Ruilong Wu, Dirk Kutscher
https://arxiv.org/abs/2506.16258

ViFusion: In-Network Tensor Fusion for Scalable Video Feature Indexing
Large-scale video feature indexing in datacenters is critically dependent on efficient data transfer. Although in-network computation has emerged as a compelling strategy for accelerating feature extraction and reducing overhead in distributed multimedia systems, harnessing advanced networking resources at both the switch and host levels remains a formidable challenge. These difficulties are compounded by heterogeneous hardware, diverse application requirements, and complex multipath topologies…

Convergence of Mean Shift Algorithms for Large Bandwidths and Simultaneous Accurate Clustering
Susovan Pal, Praneeth Vepakomma
https://arxiv.org/abs/2506.19837

Convergence of Mean Shift Algorithms for Large Bandwidths and Simultaneous Accurate Clustering
The mean shift (MS) is a non-parametric, density-based, iterative algorithm that has prominent usage in clustering and image segmentation. A rigorous proof for its convergence in full generality remains unknown. Two significant steps in this direction were taken in the paper \cite{Gh1}, which proved that for \textit{sufficiently large bandwidth}, the MS algorithm with the Gaussian kernel always converges in any dimension, and also by the same author in \cite{Gh2}, proved that MS always converge…

Cosmological bounds on dark matter annihilation using dark ages 21-cm signal
Vivekanand Mohapatra
https://arxiv.org/abs/2506.20648 https://

Cosmological bounds on dark matter annihilation using dark ages 21-cm signal
We investigate the impact of dark matter (DM) annihilation on the global 21-cm signal during the dark ages and cosmic dawn eras. The 21-cm line provides a complementary probe for studying the nature of dark matter beyond standard cosmological observables. In the standard $Λ$CDM framework, the expected absorption amplitude of the dark ages global 21-cm signal is approximately $-42\, \rm mK$. However, energy injection from DM annihilation can significantly heat and ionize the intergalactic mediu…

🇺🇦 Auf radioeins läuft...
M83:
🎵 Reunion
#NowPlaying #M83
https://billysteevesandthewindblown.bandcamp.com/track/m83-reunion
https://open.spotify.com/track/6vi4I2vZkN5mDePmVSSVTq

Balancing the cellular budget: lessons in metabolism from microbes to cancer
B. Vibishan (Department of Bioengineering, Indian Institute of Science, Bengaluru, India), Mohit Kumar Jolly (Department of Bioengineering, Indian Institute of Science, Bengaluru, India), Akshit Goyal (International Centre for Theoretical Sciences, Tata Institute of Fundamental Research, Bengaluru, India)

Balancing the cellular budget: lessons in metabolism from microbes to cancer
Cancer cells are often seen to prefer glycolytic metabolism over oxidative phosphorylation even in the presence of oxygen-a phenomenon termed the Warburg effect. Despite significant strides in the decades since its discovery, a clear basis is yet to be established for the Warburg effect and why cancer cells show such a preference for aerobic glycolysis. In this review, we draw on what is known about similar metabolic shifts both in normal mammalian physiology and overflow metabolism in microbes…

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Stateless:
🎵 Visions
#Stateless
https://open.spotify.com/track/4n4gZr1VEBUG0N9zuyDuk6