Tootfinder

(To the tune of "Rock me Amadeus")
Chamomile, chamomile, chamomile,
Chamomile, chamomile, chamomile,
Chamomile, chamomile, oh, oh, oh chamomile.
Come and calm me chamomile.

SDLC stands for Software Delivery Lithuanian Commonwealth

🦠 Microbes may remove more than half of groundwater methane, curbing global emissions
https://phys.org/news/2025-10-microbes-groundwater-methane-curbing-global.html

Microbes may remove more than half of groundwater methane, curbing global emissions
Groundwater commonly contains methane, but the amount of this important greenhouse gas that can escape to surface waters or the atmosphere is highly uncertain. A team from the Max Planck Institute for Biogeochemistry and University of Jena has shown that microbes in groundwater significantly reduce methane emissions, as revealed in a study published in PNAS.

Estrogen? Hot drinks will suffice!
"""
Naturally, cold water cooled. For that reason it was used in mania and frenzy, sicknesses of heat where the spirits were in ebullition, solids tightened and liquids were heated to the point of evaporation, leaving the brain of the patient ‘dry and brittle’, as anatomists regularly demonstrated. Reasonably enough Boissieu includes cold water among his list of refreshing cures: baths were the foremost ‘antiphlogistic’, purifying the body of any excessive igneous particles to be found there. Taken as a drink, it was a ‘dilutive procastinant’ that diminished the resistance of fluids to the action of solids, thereby indirectly lowering the general heat of the body.
But it was also said that cold water brought heat and that hot water cooled. Such at least was the thesis defended by Darut. Cold baths chased the blood from the periphery of the body and pushed it ‘with increased vigour towards the heart’. As the heart was the seat of natural heat, the blood was warmed there, all the more so as “the heart, which struggles alone against all the other parts, makes renewed efforts to expel the blood and overcome capillary resistance. What results is a greater intensity of circulation, the division of the blood, the fluidity of the humours, the destruction of congestions, an increase in the strength of the natural heat, of the appetite of the digestive forces, and the activity of the body and the mind.” A symmetrical paradox operated regarding hot baths: blood was attracted to the extremities of the body, as were the humours, sweat, and all forms of liquid, both beneficial and harmful. The vital centres were therefore deserted, the heart slowed and the organism thus began to cool down. This fact was confirmed by the ‘fainting, lipothymia… weakness, nonchalance, lassitude, and lack of vigour’ that generally accompanied excessive bathing with hot water.
But there was more. So great was the polyvalence of water, so great was its aptitude to submit itself to the qualities that it carried, that it sometimes lost its efficacy as a liquid and acted as a desiccant instead. Water could Prevent dampness. In part, this was the old principle of similia similibus, but in another sense, and by the intermediary of a visible mechanism. For some, it was cold water that brought dryness, as heat kept water humid. Heat dilated the pores of the organism, distended its membranes, and allowed humidity to impregnate them as a secondary effect. Liquids made their way through heat. For that reason, the hot drinks so widely used in the seventeenth century risked becoming a danger, and those who took too many risked relaxation, general dampness and a weakness of the whole organism. As these were traits commonly associated with the feminine body, as opposed to the dry, virile solidity of the male, the abuse of hot drinks could lead to a general feminisation of the human race: “Not without reason, the reproach is made to the majority of men that they have softened and degenerated, taking on the habits and inclinations of women – the only thing lacking is a physical resemblance. The abuse of humectants could accelerate the metamorphosis, and render the two sexes almost identical both physically and morally. Woe betide the human race if this prejudice ever spreads to the masses: there will be no more labourers, artisans or soldiers, as they will have lost the strength and vigour necessary for their profession.” [Pressavin]
"""
(Michel Foucault, History of Madness)

Enhancing 3D Point Cloud Classification with ModelNet-R and Point-SkipNet
Mohammad Saeid, Amir Salarpour, Pedram MohajerAnsari
https://arxiv.org/abs/2509.05198 https://

Enhancing 3D Point Cloud Classification with ModelNet-R and Point-SkipNet
The classification of 3D point clouds is crucial for applications such as autonomous driving, robotics, and augmented reality. However, the commonly used ModelNet40 dataset suffers from limitations such as inconsistent labeling, 2D data, size mismatches, and inadequate class differentiation, which hinder model performance. This paper introduces ModelNet-R, a meticulously refined version of ModelNet40 designed to address these issues and serve as a more reliable benchmark. Additionally, this pap…

Learning Mixtures of Linear Dynamical Systems (MoLDS) via Hybrid Tensor-EM Method
Lulu Gong, Shreya Saxena
https://arxiv.org/abs/2510.06091 https://arxiv.o…

Learning Mixtures of Linear Dynamical Systems (MoLDS) via Hybrid Tensor-EM Method
Mixtures of linear dynamical systems (MoLDS) provide a path to model time-series data that exhibit diverse temporal dynamics across trajectories. However, its application remains challenging in complex and noisy settings, limiting its effectiveness for neural data analysis. Tensor-based moment methods can provide global identifiability guarantees for MoLDS, but their performance degrades under noise and complexity. Commonly used expectation-maximization (EM) methods offer flexibility in fitting…

Decade-long Emission Forecasting with an Ensemble Model in Taiwan
Gordon Hung, Salinna Abdullah
https://arxiv.org/abs/2510.05548 https://arxiv.org/pdf/2510…

Decade-long Emission Forecasting with an Ensemble Model in Taiwan
Taiwan's high population and heavy dependence on fossil fuels have led to severe air pollution, with the most prevalent greenhouse gas being carbon dioxide (CO2). There-fore, this study presents a reproducible and comprehensive case study comparing 21 of the most commonly employed time series models in forecasting emissions, analyzing both univariate and multivariate approaches. Among these, Feedforward Neural Network (FFNN), Support Vector Machine (SVM), and Random Forest Regressor (RFR) achie…

karate: Zachary Karate Club
Network of friendships among members of a university karate club. Includes metadata for faction membership after a social partition. Note: there are two versions of this network, one with 77 edges and one with 78, due to an ambiguous typo in the original study. (The most commonly used is the one with 78 edges.).
This network has 34 nodes and 77 edges.
Tags: Social, Offline, Unweighted

Consistent Updates for Scalable Microservices
Devora Chait-Roth, Kedar S. Namjoshi, Thomas Wies
https://arxiv.org/abs/2508.04829 https://arxiv.org/pdf/2508…

Consistent Updates for Scalable Microservices
Online services are commonly implemented with a scalable microservice architecture, where isomorphic worker processes service client requests, recording persistent state in a backend data store. To maintain service, any modifications to the service functionality must be made on the fly -- i.e., as the service continues to process client requests -- but doing so is challenging. The central difficulty is that of avoiding potential inconsistencies caused by ''mixed mode'' operation, where workers …

Extracting Uncertainty Estimates from Mixtures of Experts for Semantic Segmentation
Svetlana Pavlitska, Beyza Keskin, Alwin Fa{\ss}bender, Christian Hubschneider, J. Marius Z\"ollner
https://arxiv.org/abs/2509.04816

Extracting Uncertainty Estimates from Mixtures of Experts for Semantic Segmentation
Estimating accurate and well-calibrated predictive uncertainty is important for enhancing the reliability of computer vision models, especially in safety-critical applications like traffic scene perception. While ensemble methods are commonly used to quantify uncertainty by combining multiple models, a mixture of experts (MoE) offers an efficient alternative by leveraging a gating network to dynamically weight expert predictions based on the input. Building on the promising use of MoEs for sema…