Tootfinder

with the bar for safe bike infrastructure as low as it is, it's hard to strike the right balance after a project between "hooray! it's so much better!" and "this, that, and the other thing still suck."
Streetsblog SF often errs on the latter side... I'm happier than ever with #ValenciaStreet, but their critiques are not wrong.

SFMTA Leaves Valencia Bike Lanes Unfinished - Streetsblog San Francisco
The center-running lane is long gone and some finishing touches are coming to the parking-protected section from 15th to 23rd, but the lack of concrete infrastructure remains problematic. And then there's the last four blocks from 23rd to Cesar Chavez, which is still just a striped lane wedged between parked cars and moving traffic.

Personalized Feature Translation for Expression Recognition: An Efficient Source-Free Domain Adaptation Method
Masoumeh Sharafi, Soufiane Belharbi, Houssem Ben Salem, Ali Etemad, Alessandro Lameiras Koerich, Marco Pedersoli, Simon Bacon, Eric Granger
https://arxiv.org/abs/2508.09202

Personalized Feature Translation for Expression Recognition: An Efficient Source-Free Domain Adaptation Method
Facial expression recognition (FER) models are employed in many video-based affective computing applications, such as human-computer interaction and healthcare monitoring. However, deep FER models often struggle with subtle expressions and high inter-subject variability, limiting their performance in real-world applications. To improve their performance, source-free domain adaptation (SFDA) methods have been proposed to personalize a pretrained source model using only unlabeled target domain da…

Photonic Rails in ML Datacenters
Eric Ding, Chuhan Ouyang, Rachee Singh
https://arxiv.org/abs/2507.08119 https://arxiv.org/pdf/2507.0…

Photonic Rails in ML Datacenters
Rail-optimized network fabrics have become the de facto datacenter scale-out fabric for large-scale ML training. However, the use of high-radix electrical switches to provide all-to-all connectivity in rails imposes massive power, cost, and complexity overheads. We propose a rethinking of the rail abstraction by retaining its communication semantics, but realizing it using optical circuit switches. The key challenge is that optical switches support only one-to-one connectivity at a time, limiti…

Adaptive Pareto-Optimal Token Merging for Edge Transformer Models in Semantic Communication
Omar Erak, Omar Alhussein, Hatem Abou-Zeid, Mehdi Bennis
https://arxiv.org/abs/2509.09168

Adaptive Pareto-Optimal Token Merging for Edge Transformer Models in Semantic Communication
Large-scale transformer models have emerged as a powerful tool for semantic communication systems, enabling edge devices to extract rich representations for robust inference across noisy wireless channels. However, their substantial computational demands remain a major barrier to practical deployment in resource-constrained 6G networks. In this paper, we present a training-free framework for adaptive token merging in pretrained vision transformers to jointly reduce inference time and transmissi…

Tunable chiral and nematic states in the triple-Q antiferromagnet Co$_{1/3}$TaS$_2$
Erik Kirstein, Pyeongjae Park, Woonghee Cho, Cristian D. Batista, Je-Geun Park, Scott A. Crooker
https://arxiv.org/abs/2507.08148

Tunable chiral and nematic states in the triple-Q antiferromagnet Co$_{1/3}$TaS$_2$
Complex spin configurations in magnetic materials, ranging from collinear single-Q to noncoplanar multi-Q states, exhibit rich symmetry and chiral properties. However, their detailed characterization is often hindered by the limited spatial resolution of neutron diffraction techniques. Here we employ magnetic circular dichroism (MCD) and magnetic linear dichroism (MLD) to investigate the triangular lattice antiferromagnet Co$_{1/3}$TaS$_2$, revealing three-state (Z3) nematicity and also spin ch…

Generalizable 7T T1-map Synthesis from 1.5T and 3T T1 MRI with an Efficient Transformer Model
Zach Eidex, Mojtaba Safari, Tonghe Wang, Vanessa Wildman, David S. Yu, Hui Mao, Erik Middlebrooks, Aparna Kesewala, Xiaofeng Yang
https://arxiv.org/abs/2507.08655

Generalizable 7T T1-map Synthesis from 1.5T and 3T T1 MRI with an Efficient Transformer Model
Purpose: Ultra-high-field 7T MRI offers improved resolution and contrast over standard clinical field strengths (1.5T, 3T). However, 7T scanners are costly, scarce, and introduce additional challenges such as susceptibility artifacts. We propose an efficient transformer-based model (7T-Restormer) to synthesize 7T-quality T1-maps from routine 1.5T or 3T T1-weighted (T1W) images. Methods: Our model was validated on 35 1.5T and 108 3T T1w MRI paired with corresponding 7T T1 maps of patients with c…

Electric and spin current vortices in altermagnets
A. A. Herasymchuk, Karl Bergson Hallberg, Erik Wegner Hodt, Jacob Linder, E. V. Gorbar, Pavlo Sukhachov
https://arxiv.org/abs/2507.08072

Electric and spin current vortices in altermagnets
Altermagnets constitute a class of collinear magnets with momentum-dependent spin splitting and vanishing net magnetization. Direct observation of the characteristic altermagnetic spin splitting, however, remains challenging. Indirect signatures can be obtained via transport studies, which so far have only considered homogeneous fields driving currents. We propose to leverage nonuniform electric fields and spin density gradients to probe the shape and the spin polarization of altermagnetic Ferm…

Evaluating recognition and recall formats of social network surveys in physics education research
Meagan Sundstrom, Justin Gambrell, Adrienne L. Traxler, Eric Brewe
https://arxiv.org/abs/2508.08417

Evaluating recognition and recall formats of social network surveys in physics education research
An increasing number of studies in physics education research use social network analysis to quantify interactions among students. These studies typically gather data through online surveys using one of two different survey formats: recognition, where students select peers' names from a provided course roster, and recall, where students type their peers' names from memory as an open response. These survey formats, however, may be subject to two possible systematic errors. First, students may re…

Quantum sensing with a spin ensemble in a two-dimensional material
Souvik Biswas, Giovanni Scuri, Noah Huffman, Eric I. Rosenthal, Ruotian Gong, Thomas Poirier, Xingyu Gao, Sumukh Vaidya, Abigail J. Stein, Tsachy Weissman, James H. Edgar, Tongcang Li, Chong Zu, Jelena Vu\v{c}kovi\'c, Joonhee Choi
https://arxiv.org/abs/2509.08984…

Quantum sensing with a spin ensemble in a two-dimensional material
Quantum sensing with solid-state spin defects has transformed nanoscale metrology, offering sub-wavelength spatial resolution with exceptional sensitivity to multiple signal types. Maximizing these advantages requires minimizing both the sensor-target separation and detectable signalthreshold. However, leading platforms such as nitrogen-vacancy (NV) centers in diamond suffer performance degradation near surfaces or in nanoscale volumes, motivating the search for optically addressable spin senso…

Knowledge Graph-Based approach for Sustainable 6G End-to-End System Design
Akshay Jain, Sylvaine Kerboeuf, Sokratis Barmpounakis, Crist\'obal Vinagre Z., Stefan Wendt, Dinh Thai Bui, Pol Alemany, Riccardo Nicolicchia, Jos\'e Mar\'ia Jorquera Valero, Dani Korpi, Mohammad Hossein Moghaddam, Mikko A. Uusitalo, Patrik Rugeland, Abdelkader Outtagarts, Karthik Upadhya, Panagiotis Demestichas, Raul Mu\~noz, Manuel Gil P\'erez, Daniel Adanza, Ricard Vilalta

Knowledge Graph-Based approach for Sustainable 6G End-to-End System Design
Previous generations of cellular communication, such as 5G, have been designed with the objective of improving key performance indicators (KPIs) such as throughput, latency, etc. However, to meet the evolving KPI demands as well as the ambitious sustainability targets for the ICT industry, 6G will need to be designed differently. Concretely, 6G will need to consider both the performance and sustainability targets for the various use cases it will serve. Moreover, like previous generations, 6G w…