Tootfinder

Spectrometry of Captured Highly Charged Ions Produced Following Antiproton Annihilations
F. P. Gustafsson, M. Volponi, J. Zielinski, A. Asare, I. Hwang, S. Alfaro Campos, M. Auzins, D. Bhanushali, A. Bhartia, M. Berghold, R. S. Brusa, K. Calik, A. Camper, R. Caravita, F. Castelli, G. Cerchiari, S. Chandran, A. Chehaimi, S. Choudapurkar, R. Ciury{\l}o, P. Conte, G. Consolati, M. Doser, R. Ferguson, M. Germann, A. Giszczak, L. T. Gl\"oggler, {\L}. Graczykowski, M. Grosbart, F. Guati…

Spectrometry of Captured Highly Charged Ions Produced Following Antiproton Annihilations
We report the first capture and time-of-flight spectrometry of highly charged ions produced following antiproton annihilations in a Penning-Malmberg trap. At the AEgIS experiment, we employed a multi-step nested-trap technique to isolate ions from antiproton annihilations with ultra-low-density helium and argon gas. The capture and identification of highly-charged argon ions in charge-states up to $Ar^{5+}$ demonstrates a new method for in-trap synthesis. This work establishes a clear path towa…

Bidirectional Representations Augmented Autoregressive Biological Sequence Generation:Application in De Novo Peptide Sequencing
Xiang Zhang, Jiaqi Wei, Zijie Qiu, Sheng Xu, Zhi Jin, ZhiQiang Gao, Nanqing Dong, Siqi Sun
https://arxiv.org/abs/2510.08169

Bidirectional Representations Augmented Autoregressive Biological Sequence Generation:Application in De Novo Peptide Sequencing
Autoregressive (AR) models, common in sequence generation, are limited in many biological tasks such as de novo peptide sequencing and protein modeling by their unidirectional nature, failing to capture crucial global bidirectional token dependencies. Non-Autoregressive (NAR) models offer holistic, bidirectional representations but face challenges with generative coherence and scalability. To transcend this, we propose a hybrid framework enhancing AR generation by dynamically integrating rich c…

If you are an anti-fascist, you are against petroleum. Petroleum funds fascism globally. It is at the heart of the military industrial complex driving global imperialism, from both the US and Russia. Motonormitivity is fascist, both in it's elitist roots and in it's ties to historical fascism (Hitler hated bikes, just on principle). Oil is militarism.
Oil is the dominant resource which drives war, both in terms of it being the primary spoil wars are fought over and in terms of fueling the military vehicles and weapons that carry out those wars. Practically every war since (and including) WWII has been over oil. Genocides are carried out to secure oil. Gaza is over oil, in more ways than one.
Oil is the absolute enemy, and AI is simply an extension of that: an attempt to atomize us so we can't resist the oil-centric global order, one last grasp at the control over our lives oil has given to those whose power is now threatened by a solar punk future.
"I haven't written for a few weeks now. As I write the closing chapter and begin rewriting previous sections, everything feels both more distant and more immediate. The working title [Kairos] has only continued to feel more and more resonant, both during the writing and during my pause."
Now is the time to resist by making something different, by creating a world fundamentally opposed to these systems of oppression.
This is the last in my Kairos series. From here on out I'll be editing to try and make it more of a book than a series of posts. Thanks to everyone who has helped so far. All editing is welcome (typos, spell checks, questions and challenges). Between ADHD and dyslexia, it's always hard for my brain to notice mistakes in my own text so I always appreciate the support of those who can.
https://anarchoccultism.org/building-zion/kairos

Decoupled Multimodal Fusion for User Interest Modeling in Click-Through Rate Prediction
Alin Fan, Hanqing Li, Sihan Lu, Jingsong Yuan, Jiandong Zhang
https://arxiv.org/abs/2510.11066

Decoupled Multimodal Fusion for User Interest Modeling in Click-Through Rate Prediction
Modern industrial recommendation systems improve recommendation performance by integrating multimodal representations from pre-trained models into ID-based Click-Through Rate (CTR) prediction frameworks. However, existing approaches typically adopt modality-centric modeling strategies that process ID-based and multimodal embeddings independently, failing to capture fine-grained interactions between content semantics and behavioral signals. In this paper, we propose Decoupled Multimodal Fusion (…

A Quantum Generative Framework for Modeling Single-Cell Transcriptomes with Gene-Gene and Cell-Cell Interactions
Selim Romero, Vignesh Kumar, Robert S. Chapkin, James J. Cai
https://arxiv.org/abs/2510.12776

A Quantum Generative Framework for Modeling Single-Cell Transcriptomes with Gene-Gene and Cell-Cell Interactions
Single-cell RNA sequencing (scRNA-seq) data simulation is limited by classical methods that rely on linear correlations, failing to capture the intrinsic, nonlinear dependencies and the simultaneous gene-gene and cell-cell interactions. We introduce qSimCells, a novel hybrid quantum-classical simulator that leverages quantum entanglement to model single-cell transcriptomes. The core innovation is a quantum kernel that uses a parameterized quantum circuit with CNOT gates to encode complex, nonli…

Nonlinear Strain-Mediated Magnetoelectric Coupling in Sub-Microscale Ni/BPZT Thin-Film Devices
Fanfan Meng, Emma Van Meirvenne, Federica Luciano, Xiangyu Wu, Yves Deblock, Kaustuv Banerjee, Peter Rickhaus, Florin Ciubotaru, Christoph Adelmann
https://arxiv.org/abs/2510.09795

Nonlinear Strain-Mediated Magnetoelectric Coupling in Sub-Microscale Ni/BPZT Thin-Film Devices
Strain-mediated magnetoelectric (ME) heterostructures enable electric-field control of magnetism and are promising for ultra-low-power spintronic logic. Yet achieving spatially selective, low-voltage control in thin films and quantifying ME coupling across the full ferroelastic loop remains challenging. Here, we investigate sub-micrometer Ni/BPZT thin-film devices with laterally patterned gates that localize in-plane strain beneath the Ni stripe and modulate its magnetization. We use anisotropi…

Phenome-Wide Multi-Omics Integration Uncovers Distinct Archetypes of Human Aging
Huifa Li, Feilong Tang, Haochen Xue, Yulong Li, Xinlin Zhuang, Bin Zhang, Eran Segal, Imran Razzak
https://arxiv.org/abs/2510.12384

Phenome-Wide Multi-Omics Integration Uncovers Distinct Archetypes of Human Aging
Aging is a highly complex and heterogeneous process that progresses at different rates across individuals, making biological age (BA) a more accurate indicator of physiological decline than chronological age. While previous studies have built aging clocks using single-omics data, they often fail to capture the full molecular complexity of human aging. In this work, we leveraged the Human Phenotype Project, a large-scale cohort of 12,000 adults aged 30--70 years, with extensive longitudinal prof…