Tootfinder

"‘An enormous scar’: the battle over solar farms and pylons as Reform UK takes aim at net zero"
#UK #UnitedKingdom #NetZero

Automatically describe data and models as text using the {report} package. #rstats

"Restoration, protection aim to save Belize’s coral reef from extreme heat and disease"
#Belize #Environment #CoralReef

Restoration, protection aim to save Belize’s coral reef from extreme heat and disease
PLACENCIA, Belize — After Hurricane Iris decimated the coral reef at Laughing Bird Caye National Park in 2001, many wrote off the UNESCO World Heritage site as a coral graveyard. But a small group from the coastal village of Placencia, Belize, about 18 kilometers (11 miles) from the island, saw hope. In 2006, the park […]

Efficiently Verifiable Proofs of Data Attribution
Ari Karchmer, Seth Neel, Martin Pawelczyk
https://arxiv.org/abs/2508.10866 https://arxiv.org/pdf/2508.108…

Efficiently Verifiable Proofs of Data Attribution
Data attribution methods aim to answer useful counterfactual questions like "what would a ML model's prediction be if it were trained on a different dataset?" However, estimation of data attribution models through techniques like empirical influence or "datamodeling" remains very computationally expensive. This causes a critical trust issue: if only a few computationally rich parties can obtain data attributions, how can resource-constrained parties trust that the provided attributions are inde…

STEP: Stepwise Curriculum Learning for Context-Knowledge Fusion in Conversational Recommendation
Zhenye Yang, Jinpeng Chen, Huan Li, Xiongnan Jin, Xuanyang Li, Junwei Zhang, Hongbo Gao, Kaimin Wei, Senzhang Wang
https://arxiv.org/abs/2508.10669

STEP: Stepwise Curriculum Learning for Context-Knowledge Fusion in Conversational Recommendation
Conversational recommender systems (CRSs) aim to proactively capture user preferences through natural language dialogue and recommend high-quality items. To achieve this, CRS gathers user preferences via a dialog module and builds user profiles through a recommendation module to generate appropriate recommendations. However, existing CRS faces challenges in capturing the deep semantics of user preferences and dialogue context. In particular, the efficient integration of external knowledge graph…

Robustness and Diagnostic Performance of Super-Resolution Fetal Brain MRI
Ema Masterl, Tina Vipotnik Vesnaver, \v{Z}iga \v{S}piclin
https://arxiv.org/abs/2509.10257 https://

Robustness and Diagnostic Performance of Super-Resolution Fetal Brain MRI
Fetal brain MRI relies on rapid multi-view 2D slice acquisitions to reduce motion artifacts caused by fetal movement. However, these stacks are typically low resolution, may suffer from motion corruption, and do not adequately capture 3D anatomy. Super-resolution reconstruction (SRR) methods aim to address these limitations by combining slice-to-volume registration and super-resolution techniques to generate high-resolution (HR) 3D volumes. While several SRR methods have been proposed, their co…

MimicDroid: In-Context Learning for Humanoid Robot Manipulation from Human Play Videos
Rutav Shah, Shuijing Liu, Qi Wang, Zhenyu Jiang, Sateesh Kumar, Mingyo Seo, Roberto Mart\'in-Mart\'in, Yuke Zhu
https://arxiv.org/abs/2509.09769

MimicDroid: In-Context Learning for Humanoid Robot Manipulation from Human Play Videos
We aim to enable humanoid robots to efficiently solve new manipulation tasks from a few video examples. In-context learning (ICL) is a promising framework for achieving this goal due to its test-time data efficiency and rapid adaptability. However, current ICL methods rely on labor-intensive teleoperated data for training, which restricts scalability. We propose using human play videos -- continuous, unlabeled videos of people interacting freely with their environment -- as a scalable and diver…

Beyond Token Limits: Assessing Language Model Performance on Long Text Classification
Mikl\'os Seb\H{o}k, Viktor Kov\'acs, Martin B\'an\'oczy, Daniel M{\o}ller Eriksen, Nathalie Neptune, Philippe Roussille
https://arxiv.org/abs/2509.10199

Beyond Token Limits: Assessing Language Model Performance on Long Text Classification
The most widely used large language models in the social sciences (such as BERT, and its derivatives, e.g. RoBERTa) have a limitation on the input text length that they can process to produce predictions. This is a particularly pressing issue for some classification tasks, where the aim is to handle long input texts. One such area deals with laws and draft laws (bills), which can have a length of multiple hundred pages and, therefore, are not particularly amenable for processing with models tha…

Empirical Evaluation of Memory-Erasure Protocols
Reynaldo Gil-Pons, Sjouke Mauw, Rolando Trujillo-Rasua
https://arxiv.org/abs/2509.10224 https://arxiv.org/…

Empirical Evaluation of Memory-Erasure Protocols
Software-based memory-erasure protocols are two-party communication protocols where a verifier instructs a computational device to erase its memory and send a proof of erasure. They aim at guaranteeing that low-cost IoT devices are free of malware by putting them back into a safe state without requiring secure hardware or physical manipulation of the device. Several software-based memory-erasure protocols have been introduced and theoretically analysed. Yet, many of them have not been tested fo…

Improving quantum communication rates with permutation-invariant codes
Sujeet Bhalerao, Felix Leditzky
https://arxiv.org/abs/2508.09978 https://arxiv.org/p…

Improving quantum communication rates with permutation-invariant codes
In this work we improve the quantum communication rates of various quantum channels of interest using permutation-invariant quantum codes. We focus in particular on parametrized families of quantum channels and aim to improve bounds on their quantum capacity threshold, defined as the lowest noise level at which the quantum capacity of the channel family vanishes. These thresholds are important quantities as they mark the noise level up to which faithful quantum communication is theoretically po…

Data Depth as a Risk
Arturo Castellanos, Pavlo Mozharovskyi
https://arxiv.org/abs/2507.08518 https://arxiv.org/pdf/2507.08518

Data Depth as a Risk
Data depths are score functions that quantify in an unsupervised fashion how central is a point inside a distribution, with numerous applications such as anomaly detection, multivariate or functional data analysis, arising across various fields. The halfspace depth was the first depth to aim at generalising the notion of quantile beyond the univariate case. Among the existing variety of depth definitions, it remains one of the most used notions of data depth. Taking a different angle from the q…

Trump’s newly signed tax and spending law, eviscerated Biden-era incentives for clean technologies such as wind and solar power.
Now Democrats aim to flip the usual partisan energy debate
by portraying Republicans as the party of electricity shortages and rising prices.
Their targets would include the moderate Republicans who spent months urging Congress to preserve the Biden tax breaks because of their projected economic gains for GOP-held districts
— only to fold a…

Google Assistant ain't no fun.
"Starting a religion with the aim of taking over the world isn't something I can advise on. My purpose is to be helpful and harmless, and that includes not encouraging actions that could lead to manipulation or harm."

»The aim of PYGMALION was to create an independent European technological base for the applications, algorithms and software aspects of neurocomputing. The project led to the coordination of research on connectionist computing techniques and provided the means for developing the necessary software tools for productive research.«
Project end date: February 1st, 1991.
Source:

Eleanor Holmes Norton keeps a low profile as Trump takes aim at DC (Nicholas Wu/Politico)
https://www.politico.com/news/2025/08/13/eleanor-holmes-norton-trump-dc-00506273
http://www.memeorandum.com/250813/p67#a250813p67

On the stability of the quaternion projective space
Crina-Daniela Neac\c{s}u
https://arxiv.org/abs/2508.09315 https://arxiv.org/pdf/2508.09315

On the stability of the quaternion projective space
The aim of this note is to prove that the index of the identity map on a quaternion space form of constant quaternion sectional curvature $c$ is zero, provided that $c<0$. As an immediate consequence, it is established that any compact quaternion space form of negative quaternion sectional curvature is stable and it is emphasized that, on the contrary (but in agreement with some known results), any quaternion projective space is unstable.

AnalogSeeker: An Open-source Foundation Language Model for Analog Circuit Design
Zihao Chen, Ji Zhuang, Jinyi Shen, Xiaoyue Ke, Xinyi Yang, Mingjie Zhou, Zhuoyao Du, Xu Yan, Zhouyang Wu, Zhenyu Xu, Jiangli Huang, Li Shang, Xuan Zeng, Fan Yang
https://arxiv.org/abs/2508.10409

AnalogSeeker: An Open-source Foundation Language Model for Analog Circuit Design
In this paper, we propose AnalogSeeker, an effort toward an open-source foundation language model for analog circuit design, with the aim of integrating domain knowledge and giving design assistance. To overcome the scarcity of data in this field, we employ a corpus collection strategy based on the domain knowledge framework of analog circuits. High-quality, accessible textbooks across relevant subfields are systematically curated and cleaned into a textual domain corpus. To address the complex…

Confluent hypergeometric kernel determinant on multiple large intervals
Taiyang Xu, Lun Zhang, Zhengyang Zhao
https://arxiv.org/abs/2508.10463 https://arxi…

Confluent hypergeometric kernel determinant on multiple large intervals
The confluent hypergeometric point process represents a universality class which arises in a variety of different but related areas. It particularly describes the local statistics of eigenvalues in the bulk of spectrum near a Fisher-Hartwig singular point for a broad class of unitary ensembles. It is the aim of this work to investigate large gap asymptotics of this process over a union of disjoint intervals $\cup_{j=0}^{n}(sa_j,sb_j)$, where $a_0

Learning to Transmit Over Unknown Erasure Channels with Empirical Erasure Rate Feedback
Haricharan Balasundaram, Krishna Jagannathan
https://arxiv.org/abs/2507.08599

Learning to Transmit Over Unknown Erasure Channels with Empirical Erasure Rate Feedback
We address the problem of reliable data transmission within a finite time horizon $T$ over a binary erasure channel with unknown erasure probability. We consider a feedback model wherein the transmitter can query the receiver infrequently and obtain the empirical erasure rate experienced by the latter. We aim to minimize a regret quantity, i.e. how much worse a strategy performs compared to an oracle who knows the probability of erasure, while operating at the same block error rate. A learning …

Detectability via observability in a nonuniform framework: dual relationship with controllability and stabilizability
Ignacio Huerta, Pablo Monz\'on
https://arxiv.org/abs/2508.09918

Detectability via observability in a nonuniform framework: dual relationship with controllability and stabilizability
In this paper we propose a new observability property for nonautonomous linear control systems in finite dimension: the nonuniform complete observability, which is more general than the uniform complete observability. A dual relationship is established between this new notion of observability and the recently defined nonuniform complete controllability property, with the aim of obtaining the main result, which proves that nonuniform complete observability guarantees the nonuniform exponential d…

The Rosetta Stone Project. I. A suite of radiative magnetohydrodynamics simulations of high-mass star-forming clumps
Ugo Lebreuilly, Alessio Traficante, Alice Nucara, Ngo-Duy Tung, Patrick Hennebelle, Sergio Molinari, Ralf S. Klessen, Leonardo Testi, Veli-Matti Pelkonen, Milena Benedettini, Alessandro Coletta, Davide Elia, Chiara Mininni, Stefania Pezzuto, Juan D. Soler, Paolo Suin, Claudia Toci

The Rosetta Stone Project. I. A suite of radiative magnetohydrodynamics simulations of high-mass star-forming clumps
Context. Star formation and, in particular, high-mass star formation are key astrophysical processes that are far from being fully understood. Unfortunately, progress in these fields is slow because observations are hard to interpret as they cannot be directly compared to numerical simulations. Synthetic observations are therefore necessary to better constrain the models. Aims. With the Rosetta Stone project, we aim to develop an end-to-end pipeline to compare star formation simulations with ob…

Geno, Crosby flash obscene gestures at hecklers https://www.espn.com/nfl/story/_/id/45929244/raiders-smith-crosby-aim-obscene-gestures-hecklers-seattle

SPINT: Spatial Permutation-Invariant Neural Transformer for Consistent Intracortical Motor Decoding
Trung Le, Hao Fang, Jingyuan Li, Tung Nguyen, Lu Mi, Amy Orsborn, Uygar S\"umb\"ul, Eli Shlizerman
https://arxiv.org/abs/2507.08402

SPINT: Spatial Permutation-Invariant Neural Transformer for Consistent Intracortical Motor Decoding
Intracortical Brain-Computer Interfaces (iBCI) aim to decode behavior from neural population activity, enabling individuals with motor impairments to regain motor functions and communication abilities. A key challenge in long-term iBCI is the nonstationarity of neural recordings, where the composition and tuning profiles of the recorded populations are unstable across recording sessions. Existing methods attempt to address this issue by explicit alignment techniques; however, they rely on fixed…

Replaced article(s) found for cs.SI. https://arxiv.org/list/cs.SI/new
[1/1]:
- Investigating Human Values in Online Communities
Nadav Borenstein, Arnav Arora, Lucie-Aim\'ee Kaffee, Isabelle Augenstein

The invariance of group occupation across the cosmic web
Vicente Izzo Dominguez, Facundo Rodriguez, Antonio D. Montero-Dorta
https://arxiv.org/abs/2509.09800 https://

The invariance of group occupation across the cosmic web
Recent efforts to identify secondary variations in the Halo Occupation Distribution (HOD) have primarily focused on simulations examining the role of large-scale cosmic environments such as superclusters, filaments, and underdense regions or voids. If present, these variations could yield valuable insights into galaxy formation mechanisms, halo assembly processes, and the influence of external factors on cosmic structure. We aim to test whether secondary trends in the HOD driven by the large-sc…

The Paradigm of Massive Wireless Human Sensing: Concept, Architecture and Challenges
Mauro De Sanctis
https://arxiv.org/abs/2508.09756 https://arxiv.org/pd…

The Paradigm of Massive Wireless Human Sensing: Concept, Architecture and Challenges
This article is a position paper which introduces the paradigm of ``Massive Wireless Human Sensing'', i.e. an infrastructure for wireless human sensing based on a plethora of heterogeneous wireless communication signals. More specifically, we aim to exploit signal diversity in the time, frequency, and space domains using opportunistically both device-free and device-based wireless sensing approaches, with the objective of enhancing human sensing capabilities in terms of accuracy and service ava…

Impacts of the duration and intensity of grazing cycle on vegetation population dynamics in semi-arid ecosystems with seasonal succession
Junhong Gan, Xiaoli Wang, Guohong Zhang
https://arxiv.org/abs/2508.09760

Impacts of the duration and intensity of grazing cycle on vegetation population dynamics in semi-arid ecosystems with seasonal succession
A novel vegetation model involving seasonal succession to distinguish the dryperiod, growth period and grazing period is proposed. The main aim is to explore the effects of duration and intensity of grazing season on the dynamic behaviors of a single vegetation population and the competitive outcomes between two competing vegetation species. The critical duration of drought period and grazing period that enable the persistence of a single vegetation population is obtained. Further, we found tha…

Impact of stochastic star-formation histories and dust on selecting quiescent galaxies with JWST photometry
K. Lisiecki, D. Donevski, A. W. S. Man, I. Damjanov, M. Romano, S. Belli, A. Long, G. Lorenzon, K. Ma{\l}ek, Junais, C. C. Lovell, A. Nanni, C. Bertemes, W. Pearson, O. Ryzhov, M. Koprowski, A. Pollo, S. Dey, H. Thuruthipilly
https://

Impact of stochastic star-formation histories and dust on selecting quiescent galaxies with JWST photometry
While the James Webb Space Telescope (JWST) now allows identifying quiescent galaxies (QGs) out to early epochs, the photometric selection of quiescent galaxy candidates (QGCs) and the derivation of key physical quantities are highly sensitive to the assumed star-formation histories (SFHs). We aim to quantify how the inclusion of JWST/MIRI data and different SFH models impacts the selection and characterisation of QGCs. We test the robustness of the physical properties inferred from the spectra…

The first batch of prototypes of the new fully electric police patrol cars for the Netherlands is now being trialled. The aim is for a third of the police fleet to be electric by the end of the decade. #EV
https://

Nederlandse politie voelt Skoda Enyaq aan de tand
Sinds begin augustus heeft de politie de beschikking over drie proefmodellen van de Skoda Enyaq. De politie gaat deze elektrische SUV testen.

Comparison of Data Reduction Criteria for Online Gaussian Processes
Thore Wietzke, Knut Graichen
https://arxiv.org/abs/2508.10815 https://arxiv.org/pdf/250…

Comparison of Data Reduction Criteria for Online Gaussian Processes
Gaussian Processes (GPs) are widely used for regression and system identification due to their flexibility and ability to quantify uncertainty. However, their computational complexity limits their applicability to small datasets. Moreover in a streaming scenario, more and more datapoints accumulate which is intractable even for Sparse GPs. Online GPs aim to alleviate this problem by e.g. defining a maximum budget of datapoints and removing redundant datapoints. This work provides a unified comp…

Networked Observatory for Virtual Astronomy (NOVA): Teaching astronomy with AI
Jorge Pinochet
https://arxiv.org/abs/2507.08195 https://arxiv.org/pdf/2507.0…

Networked Observatory for Virtual Astronomy (NOVA): Teaching astronomy with AI
The term artificial intelligence (AI) first appeared in the mid-20th century. It wasn't until well into the 21st century that AI began to flourish. Today, AI has found very diverse applications. One area that is just beginning to be explored is physics education. The aim of this work is to contribute to this burgeoning educational field through a ChatGPT application named Networked Observatory for Virtual Astronomy (NOVA). This application provides students with simulated astronomical data in a…

Investigating Language Model Capabilities to Represent and Process Formal Knowledge: A Preliminary Study to Assist Ontology Engineering
Hanna Abi Akl
https://arxiv.org/abs/2509.10249

Investigating Language Model Capabilities to Represent and Process Formal Knowledge: A Preliminary Study to Assist Ontology Engineering
Recent advances in Language Models (LMs) have failed to mask their shortcomings particularly in the domain of reasoning. This limitation impacts several tasks, most notably those involving ontology engineering. As part of a PhD research, we investigate the consequences of incorporating formal methods on the performance of Small Language Models (SLMs) on reasoning tasks. Specifically, we aim to orient our work toward using SLMs to bootstrap ontology construction and set up a series of preliminar…

> New partnership sees Google Cloud agree to work with the UK government in helping public services use advanced tech to shake off decades old ‘ball and chain’ legacy contracts which leave essential services vulnerable to cyberattack.
"ball and chain" being a government code term for Windows?

New Google partnership will help rid taxpayer of ‘ball and chain’ legacy tech and aim to upskill 100,000 civil servants in tech and AI
New partnership with Google Cloud will help modernise outdated government IT, upskill 100,000 civil servants in digital and AI by 2030, and secure better tech deals for the taxpayer.

🇺🇦 #NowPlaying on #BBC6Music's #DonLettsCultureClashRadio
Aim:
🎵 Fall Break
#Aim
https://aim1970.bandcamp.com/track/fall-break-remastered
https://open.spotify.com/track/0tIy6tqHyE1Fv5C5ZnZrud

Adaptive Personalized Conversational Information Retrieval
Fengran Mo, Yuchen Hui, Yuxing Tian, Zhaoxuan Tan, Chuan Meng, Zhan Su, Kaiyu Huang, Jian-Yun Nie
https://arxiv.org/abs/2508.08634

Adaptive Personalized Conversational Information Retrieval
Personalized conversational information retrieval (CIR) systems aim to satisfy users' complex information needs through multi-turn interactions by considering user profiles. However, not all search queries require personalization. The challenge lies in appropriately incorporating personalization elements into search when needed. Most existing studies implicitly incorporate users' personal information and conversational context using large language models without distinguishing the specific requ…

Profiles, linear spaces, and unirationality of complete intersections
Raymond Cheng
https://arxiv.org/abs/2508.08395 https://arxiv.org/pdf/2508.08395

Profiles, linear spaces, and unirationality of complete intersections
Complete intersections may be unexpectedly simple over fields of positive characteristic: for instance, they may be unirational despite being of general type. One explanation is given by profiles, structure that tracks the special shape of polynomials, refining the degree. The aim of this work is to show that complete intersections with small profile should be considered simple by generalizing two classical results on low degree complete intersections: First, the basic geometry of Fano schemes …

EU aims to mobilize up to $12 billion for Ukraine's recovery under new agreements: https://benborges.xyz/2025/07/10/eu-aims-to-mobilize-up.html

A profile of 6-year-old Ramp, which has grown to a $22.5B valuation as it expanded beyond corporate cards to tools for expense reporting, bill payment, and more (Leo Schwartz/Fortune)
https://fortune.com/article/ramp-american-express-corp…

Ramp is taking aim at American Express by upending corporate credit cards. Can the $22.5 billion startup live up to the hype?
With $1 billion in revenue, Ramp has grown at hyperspeed amid the AI boom and corner-office financial anxiety.

Dallas Cowboys look to repeat history against Super Bowl champ Eagles in NFL opener https://www.si.com/nfl/cowboys/news/dallas-cowboys-aim-repeat-history-super-bowl-champ-eagles-spoiler-nfl-opener

Fundamentals of Lie categories and Yang-Mills theory for multiplicative Ehresmann connections
\v{Z}an Grad
https://arxiv.org/abs/2507.08220 https://…

Fundamentals of Lie categories and Yang-Mills theory for multiplicative Ehresmann connections
The first and shorter part of the thesis deals with the structural assumption of invertibility in a Lie groupoid. When this assumption is dropped, we obtain the notion of a Lie category: a small category, endowed with a compatible differentiable structure. We introduce various examples of Lie categories, examine their differences and similarities with Lie groupoids, and research the notions emerging naturally from the lack of invertibility of arrows. The aim of the second and principal part of …

Viewing heat through ice: an infrared camera monitors hydrogel freezing and thawing during cryoapplication
Gennadiy O. Kovalov (Institute for Problems of Cryobiology and Cryomedicine of the National Academy of Sciences of Ukraine), Mykola O. Chyzh (Institute for Problems of Cryobiology and Cryomedicine of the National Academy of Sciences of Ukraine), Vyacheslav Yu. Globa (Institute for Problems of Cryobiology and Cryomedicine of the National Academy of Sciences of Ukraine), Oleksandr F…

Viewing heat through ice: an infrared camera monitors hydrogel freezing and thawing during cryoapplication
Cryosurgery employs a safe and relatively simple technique of exposure and is an advantageous and highly rated method. For its effective application, it is necessary to control both the volume of the expanding freezing zone and volumetric thermal field dynamics. The aim of this study was to perform a thermal imaging study of freezing and thawing in a model system (gel phantom) to predict the dynamics of the freezing zone during cryodestruction of biological tissues in vivo. Here, the thermal im…

🦾 Robotic frames offer new insights into honeybee behavior and honey storage
#science

Robotic frames offer new insights into honeybee behavior and honey storage
EPFL researchers are developing robotic beehive frames that help locate honey stores inside of beehives over time, without relying on cameras. The aim is to develop new observation tools to study honeybee behavior that better fit the bees' natural way to occupy space compared to current methods.

Solving unimportant problems with poorly-supported browser APIs.
https://www.rossng.eu/posts/2025-08-09-where-should-i-aim/

AIM 2025 Challenge on High FPS Motion Deblurring: Methods and Results
George Ciubotariu, Florin-Alexandru Vasluianu, Zhuyun Zhou, Nancy Mehta, Radu Timofte, Ke Wu, Long Sun, Lingshun Kong, Zhongbao Yang, Jinshan Pan, Jiangxin Dong, Jinhui Tang, Hao Chen, Yinghui Fang, Dafeng Zhang, Yongqi Song, Jiangbo Guo, Shuhua Jin, Zeyu Xiao, Rui Zhao, Zhuoyuan Li, Cong Zhang, Yufeng Peng, Xin Lu, Zhijing Sun, Chengjie Ge, Zihao Li, Zishun Liao, Ziang Zhou, Qiyu Kang, Xueyang Fu, Zheng-Jun Zha, Yuq…

AIM 2025 Challenge on High FPS Motion Deblurring: Methods and Results
This paper presents a comprehensive review of the AIM 2025 High FPS Non-Uniform Motion Deblurring Challenge, highlighting the proposed solutions and final results. The objective of this challenge is to identify effective networks capable of producing clearer and visually compelling images in diverse and challenging conditions, by learning representative visual cues for complex aggregations of motion types. A total of 68 participants registered for the competition, and 9 teams ultimately submitt…

Beyond LambdaCDM: How the Hubble tension challenges early universe physics
Gawain Simpson, Krzysztof Bolejko, Stephen Walters
https://arxiv.org/abs/2507.08479

Beyond LambdaCDM: How the Hubble tension challenges early universe physics
Differences in the values of the Hubble constant obtained from the local universe and the early universe have resulted in a significant tension. This tension signifies that our understanding of cosmology (physical processes and/or cosmological data) is incomplete. Some of the suggested solutions include physics of the early Universe. In this paper we aim to investigate common features of various early universe solutions to the Hubble constant tension. The physics of the early universe affects t…

Intracortical bipolar stimulation allows selective activation of neuronal populations in the cortex #BCI

Intracortical bipolar stimulation allows selective activation of neuronal populations in the cortex
Background Intracortical electrical stimulation has emerged as a promising approach for sensory restoration, such as a cortical visual prosthesis, yet its effectiveness is limited by current spread and electrode density constraints. Objective To determine whether intracortical bipolar current steering—via modulation of the return electrode position—can enhance neural activation selectivity compared to traditional monopolar stimulation, with the aim of improving spatial precision in sensory…

Uncovering High-Order Cohesive Structures: Efficient (k,g)-Core Computation and Decomposition for Large Hypergraphs
Dahee Kim, Hyewon Kim, Song Kim, Minseok Kim, Junghoon Kim, Yeon-Chang Lee, Sungsu Lim
https://arxiv.org/abs/2507.08328

Uncovering High-Order Cohesive Structures: Efficient (k,g)-Core Computation and Decomposition for Large Hypergraphs
Hypergraphs, increasingly utilised to model complex and diverse relationships in modern networks, have gained significant attention for representing intricate higher-order interactions. Among various challenges, cohesive subgraph discovery is one of the fundamental problems and offers deep insights into these structures, yet the task of selecting appropriate parameters is an open question. To address this question, we aim to design an efficient indexing structure to retrieve cohesive subgraphs …

UV-irradiated outflows from low-mass protostars in Ophiuchus with JWST/MIRI
I. M. Skretas, A. Karska, L. Francis, W. R. M. Rocha, M. L. van Gelder, {\L}. Tychoniec, M. Figueira, M. Sewi{\l}o, F. Wyrowski, P. Schilke
https://arxiv.org/abs/2509.10256

UV-irradiated outflows from low-mass protostars in Ophiuchus with JWST/MIRI
The main accretion phase of protostars is characterized by the ejection of material in the form of jets/outflows. External UV irradiation can potentially have a significant impact on the excitation conditions within these outflows. High-resolution observations in the mid-infrared allow us to investigate the details of those energetic processes through the emission of shock-excited H$_2$ . Our aim is to spatially resolve H$_2$ and ionic/atomic emission within the outflows of low-mass protostars,…

Top court takes aim at fossil fuels in sweeping ruling #fossilfuel

Top court takes aim at fossil fuels in sweeping ruling
A historic climate ruling by the world's highest court could make it legally riskier for fossil fuel companies to do business and embolden lawsuits against oil and gas expansion, experts say.

Exploring Palette based Color Guidance in Diffusion Models
Qianru Qiu, Jiafeng Mao, Xueting Wang
https://arxiv.org/abs/2508.08754 https://arxiv.org/pdf/250…

Exploring Palette based Color Guidance in Diffusion Models
With the advent of diffusion models, Text-to-Image (T2I) generation has seen substantial advancements. Current T2I models allow users to specify object colors using linguistic color names, and some methods aim to personalize color-object association through prompt learning. However, existing models struggle to provide comprehensive control over the color schemes of an entire image, especially for background elements and less prominent objects not explicitly mentioned in prompts. This paper prop…

Memo: HFPA members voted to oust President Helen Hoehne from her role and also ejected her from its board, as members aim to reverse HFPA's 2023 dissolution (Benjamin Lindsay/The Wrap)
https://www.thewrap.com/hfpa-ousts-president-helen-hoehne/

HFPA President Helen Hoehne Ousted as Members Aim to Reverse Dissolution
Hoehne, who oversaw the organization through boycotts over diversity and its Eldridge acquisition, was also ejected from its board.

Leveraging LLMs for Privacy-Aware Predictions in Participatory Budgeting
Juan Zambrano, Cl\'ement Contet, Jairo Gudi\~no, Felipe Garrido-Lucero, Umberto Grandi, Cesar A Hidalgo
https://arxiv.org/abs/2508.06577

Leveraging LLMs for Privacy-Aware Predictions in Participatory Budgeting
Participatory Budgeting (PB) empowers citizens to propose and vote on public investment projects. Yet, despite its democratic potential, PB initiatives often suffer from low participation rates, limiting their visibility and perceived legitimacy. In this work, we aim to strengthen PB elections in two key ways: by supporting project proposers in crafting better proposals, and by helping PB organizers manage large volumes of submissions in a transparent manner. We propose a privacy-preserving app…

The Dynamics of Cosmic Evolution: Insights from Bouncing Cosmology
M. Sharif, M. Zeeshan Gul, Ahmad Nawaz
https://arxiv.org/abs/2508.06586 https://arxiv.or…

The Dynamics of Cosmic Evolution: Insights from Bouncing Cosmology
The primary aim of this work is to explore feasible bouncing cosmological solutions in the framework of $f(\mathcal{Q}, \mathcal{C})$ gravity, where $\mathcal{Q}$ denotes non-metricity and $\mathcal{C}$ indicates the boundary term. To achieve this, we analyze the dynamics of a Bianchi type-I spacetime with perfect fluid distribution. We consider various functional forms of $f(\mathcal{Q,C})$ theory to assess how this modified gravity framework influences cosmic evolution. Additionally, we exami…

Approximate DBSCAN under Differential Privacy
Yuan Qiu, Ke Yi
https://arxiv.org/abs/2508.08749 https://arxiv.org/pdf/2508.08749

Approximate DBSCAN under Differential Privacy
This paper revisits the DBSCAN problem under differential privacy (DP). Existing DP-DBSCAN algorithms aim at publishing the cluster labels of the input points. However, we show that both empirically and theoretically, this approach cannot offer any utility in the published results. We therefore propose an alternative definition of DP-DBSCAN based on the notion of spans. We argue that publishing the spans actually better serves the purposes of visualization and classification of DBSCAN. Then we …

Apropos of nothing, AR-15s fire little bullets that can be thrown around by the wind. They're basically high velocity 22s, which makes them garbage for accuracy at range. Snipers use big heavy ammo like 30.06, which are incredibly common for hunting.
To bring down a big animal like a deer, you use a big round and aim at the center of mass.

Exponential Runge-Kutta methods for parabolic equations with state-dependent delay
Qiumei Huang, Alexander Ostermann, Gangfan Zhong
https://arxiv.org/abs/2509.08902 https://

Exponential Runge-Kutta methods for parabolic equations with state-dependent delay
The aim of this paper is to construct and analyze exponential Runge-Kutta methods for the temporal discretization of a class of semilinear parabolic problems with arbitrary state-dependent delay. First, the well-posedness of the problem is established. Subsequently, first and second order schemes are constructed. They are based on the explicit exponential Runge-Kutta methods, where the delayed solution is approximated by a continuous extension of the time discrete solution. Schemes of arbitrary…

Koza and Koza-Hub for born-interoperable knowledge graph generation using KGX
Daniel R Korn, Patrick Golden, Aaron Odell, Katherina Cortes, Shilpa Sundar, Kevin Schaper, Sarah Gehrke, Corey Cox, Harry Caufield, Justin Reese, Evan Morris, Christopher J Mungall, Melissa Haendel
https://arxiv.org/abs/2509.09096

Koza and Koza-Hub for born-interoperable knowledge graph generation using KGX
Knowledge graph construction has become an essential domain for the future of biomedical research. But current approaches demand a high amount of redundant labor. These redundancies are the result of the lack of data standards and "knowledge-graph ready" data from sources. Using the KGX standard, we aim to solve these issues. Herein we introduce Koza and the Koza-Hub, a Python software package which streamlines ingesting raw biomedical information into the KGX format, and an associated set of c…

If you get an invite to this generative art software engineering call, note that if you submit something and it gets accepted, as far as I can tell it would cost you $3000 in open access fees... unless you want it to languish behind a paywall (you'd then only be allowed to share an unedited draft, and even then would have to advertise the paywall on it). They don't seem to want to make this clear in their call.

AI is flooding libraries with generated content just as budgets and staff are at their most precarious. This Thursday at 10am EDT my ASIS&T webinar asks if we need to ban it, label it, absorb it—or rethink the library itself.
https://www.asist.org/meetings-events/webi

The Impact of Team Diversity in Agile Development Education
Marco Torchiano, Riccardo Coppola, Antonio Vetro', Xhoi Musaj
https://arxiv.org/abs/2509.08389 https://

The Impact of Team Diversity in Agile Development Education
Software Engineering is mostly a male-dominated sector, where gender diversity is a key feature for improving equality of opportunities, productivity, and innovation. Other diversity aspects, including but not limited to nationality and ethnicity, are often understudied.In this work we aim to assess the impact of team diversity, focusing mainly on gender and nationality, in the context of an agile software development project-based course. We analyzed 51 teams over three academic years, measuri…

The Raiders Aim to Build a Dynamic Offense https://www.si.com/nfl/raiders/las-vegas-kolton-miller-chip-kelly-pete-carroll

Creative Commons launches “CC Signals”. Quote:
“TL;DR – What are CC signals?
“CC signals are a proposed framework to help content stewards express how they want their works used in AI training—emphasizing reciprocity, recognition, and sustainability in machine reuse. They aim to preserve open knowledge by encouraging responsible AI behavior without limiting innovation.”

CC Signals: A New Social Contract for the Age of AI - Creative Commons
TL;DR – What are CC signals? CC signals are a proposed framework to help content stewards express how they want their works used in AI training—emphasizing reciprocity, recognition, and sustainability in machine reuse. They aim to preserve open knowledge by encouraging responsible AI behavior without limiting innovation. 💗Love it! How can I show my support?…

Inside science labs trying to survive in the Trump era
Anastasia Khvorova is perched at the edge of a massive scientific opportunity.
Her laboratory at the University of Massachusetts Chan Medical School deploys cutting-edge RNA biology with one aim:
to cure diseases — the ones that rob people of their memories or endanger pregnant women.

Lately, she sees peril all around her.

In the hallway, she bumps into one world-class chemist, then another, whose salaries…

Inside science labs trying to survive in the Trump era
Anastasia Khvorova’s lab at U-Mass. Chan Medical School shows how quickly the administration is dismantling an 80-year partnership that made the U.S. a scientific superpower.

TIL about DNS.
#til #sysadmin #dns

Optimization-Free Fast Optimal Control: Bang-Ride Property, Monotonicity, and Applications to Fast Battery Charging
Shengling Shi, Jacob Sass, Jiaen Wu, Minsu Kim, Yingjie Ma, Sungho Shin, Richard D. Braatz
https://arxiv.org/abs/2508.09010

Optimization-Free Fast Optimal Control: Bang-Ride Property, Monotonicity, and Applications to Fast Battery Charging
Single-input fast optimal control problems, which aim to achieve the optimal objective as fast as possible, occur in various real-world applications. In the case of fast battery charging, the associated optimal control problem becomes computationally challenging when detailed battery models are used. A recent heuristic optimization-free algorithm can significantly reduce the computational cost and provide an approximate solution, consistent with many heuristic input profiles in practice. These …

"Public strongly backs aim of 30% of land and sea set aside for nature, poll finds"
#Oceans #Environment #Nature

Luminaries in the Sky: The TESS Legacy Sample of Bright Stars. I. Asteroseismic detections in naked-eye main-sequence and sub-giant solar-like oscillators
Mikkel N. Lund, Ashley Chontos, Frank Grundahl, Savita Mathur, Rafael A. Garc\'ia, Daniel Huber, Derek Buzasi, Timothy R. Bedding, Marc Hon, Yaguang Li
https://arxiv.org/abs/2508.086…

Luminaries in the Sky: The TESS Legacy Sample of Bright Stars. I. Asteroseismic detections in naked-eye main-sequence and sub-giant solar-like oscillators
We aim to detect and characterise solar-like oscillations in bright naked-eye (V<6) main-sequence (MS) and subgiant stars observed by TESS. We seek to expand the current benchmark sample of oscillators, provide accurate global asteroseismic parameters for these bright targets, and assess their potential for future detailed investigations -- including missions such as the HWO and PLATO. Our sample of bright stars was selected from the Hipparcos/Tycho catalogues. We analysed TESS 120-s and 20-s c…

CAPOS: The bulge Cluster APOgee Survey VIII. Final ASPCAP results for all clusters
Doug Geisler, Cesar Mu\~noz, Sandro Villanova, Roger E. Cohen, Dante Minniti, Antonela Monachesi, Steven R. Majewski, Andrea Kunder, Beatriz Barbuy, Katia Cunha, Verne Smith, Carolina Montecinos, Wisthon Haro Moya, Nicolas Barrera, Matias Bla\~na
https://arx…

CAPOS: The bulge Cluster APOgee Survey VIII. Final ASPCAP results for all clusters
Bulge globular clusters(BGCs) are exceptional tracers of the formation and chemodynamical evolution of this oldest Galactic component.However, until now, observational difficulties have prevented us from taking full advantage of these powerful Galactic archeological tools. CAPOS, the bulge Cluster APOgee Survey, addresses this key topic by observing a large number of BGCs, most of which have been poorly studied. We aim to obtain accurate mean values for metallicity,[alpha/Fe],and radial velocit…

'Coalition of the willing' moves to finalize command structure for future reassurance force in Ukraine: https://benborges.xyz/2025/07/10/coalition-of-the-willing-moves.html

Now that more details are known about the three #V2G propositions (🇩🇪 BMW/E.ON, 🇫🇷 Mobilize/Renault/Mobility House, 🇬🇧 Octopus) currently available or announced in Europe, it is time to compare them.
All three aim to enable the average user to drive for free with an annual mileage of 11,000–14,000 km

Israeli cybersecurity company Cato Networks acquires Aim Security, sources say for ~$350M, its first acquisition, says it passed $300M in ARR, and raised $50M (Steven Scheer/Reuters)
https://www.reuters.com/world/middle-east/

Biden takes aim at Trump as 'existential' threat to Black Americans in speech to lawyers group (Fox News)
https://www.foxnews.com/politics/biden-takes-aim-trump-existential-threat-black-americans-speech-lawyers-group
http://www.memeorandum.com/250801/p6#a250801p6

Membership Inference Attacks with False Discovery Rate Control
Chenxu Zhao, Wei Qian, Aobo Chen, Mengdi Huai
https://arxiv.org/abs/2508.07066 https://arxiv…

Membership Inference Attacks with False Discovery Rate Control
Recent studies have shown that deep learning models are vulnerable to membership inference attacks (MIAs), which aim to infer whether a data record was used to train a target model or not. To analyze and study these vulnerabilities, various MIA methods have been proposed. Despite the significance and popularity of MIAs, existing works on MIAs are limited in providing guarantees on the false discovery rate (FDR), which refers to the expected proportion of false discoveries among the identified p…

Color it, Code it, Cancel it: k-local dynamical decoupling from classical additive codes
Minh T. P. Nguyen, Maximilian Rimbach-Russ, Stefano Bosco
https://arxiv.org/abs/2508.08213

Color it, Code it, Cancel it: k-local dynamical decoupling from classical additive codes
Dynamical decoupling is a central technique in quantum computing for actively suppressing decoherence and systematic imperfections through sequences of single-qubit operations. Conventional sequences typically aim to completely freeze system dynamics, often resulting in long protocols whose length scales exponentially with system size. In this work, we introduce a general framework for constructing time-optimal, selectively-tailored sequences that remove only specific local interactions. By com…

Developing a Transferable Federated Network Intrusion Detection System
Abu Shafin Mohammad Mahdee Jameel, Shreya Ghosh, Aly El Gamal
https://arxiv.org/abs/2508.09060 https://

Developing a Transferable Federated Network Intrusion Detection System
Intrusion Detection Systems (IDS) are a vital part of a network-connected device. In this paper, we develop a deep learning based intrusion detection system that is deployed in a distributed setup across devices connected to a network. Our aim is to better equip deep learning models against unknown attacks using knowledge from known attacks. To this end, we develop algorithms to maximize the number of transferability relationships. We propose a Convolutional Neural Network (CNN) model, along wi…

Towards Precision Cosmology With Improved PNLF Distances Using VLT-MUSE. III. Impact of Stellar Populations in Early-Type Galaxy
Azlizan A. Soemitro, Lucas M. Valenzuela, Martin M. Roth, Robin Ciardullo, George H. Jacoby, Magda Arnaboldi, Guilherme S. Couto, C. Jakob Walcher
https://arxiv.org/abs/2509.10175…

Towards Precision Cosmology With Improved PNLF Distances Using VLT-MUSE. III. Impact of Stellar Populations in Early-Type Galaxy
Distance measurements using the planetary nebula luminosity function (PNLF) rely on the bright-end power-law cut-off magnitude ($M^*$), which is defined by a number of the [OIII]$\lambda5007$-brightest planetary nebulae (PNe). In early-type galaxies (ETGs), the formation of these PNe is enigmatic; the population is typically too old to form the expected $M^*$ PNe from single star evolution. We aim to give a solution to this problem. We selected five ETGs with known MUSE-PNLF distances. The MUSE…

Membership and Memorization in LLM Knowledge Distillation
Ziqi Zhang, Ali Shahin Shamsabadi, Hanxiao Lu, Yifeng Cai, Hamed Haddadi
https://arxiv.org/abs/2508.07054 https://

Membership and Memorization in LLM Knowledge Distillation
Recent advances in Knowledge Distillation (KD) aim to mitigate the high computational demands of Large Language Models (LLMs) by transferring knowledge from a large ''teacher'' to a smaller ''student'' model. However, students may inherit the teacher's privacy when the teacher is trained on private data. In this work, we systematically characterize and investigate membership and memorization privacy risks inherent in six LLM KD techniques. Using instruction-tuning settings that span seven NLP t…

Multi-institutional assessment of Peer Instruction implementation and impacts using the Framework for Interactive Learning in Lectures
Ibukunoluwa Bukola, Meagan Sundstrom, Justin Gambrell, Olive Ross, Adrienne L. Traxler, Eric Brewe
https://arxiv.org/abs/2508.08422

Multi-institutional assessment of Peer Instruction implementation and impacts using the Framework for Interactive Learning in Lectures
Substantial research indicates that active learning methods improve student learning more than traditional lecturing. Accordingly, current studies aim to characterize and evaluate different instructors' implementations of active learning methods. Peer Instruction is one of the most commonly used active learning methods in undergraduate physics instruction and typically involves the use of classroom response systems (e.g., clickers) where instructors pose conceptual questions that students answe…

Permutation-Based Distances for Groups and Group-Valued Time Series
Jos\'e M. Amig\'o, Roberto Dale
https://arxiv.org/abs/2509.09191 https://arxiv.…

Permutation-Based Distances for Groups and Group-Valued Time Series
Permutations on a set, endowed with function composition, build a group called a symmetric group. In addition to their algebraic structure, symmetric groups have two metrics that are of particular interest to us here: the Cayley distance and the Kendall tau distance. In fact, the aim of this paper is to introduce the concept of distance in a general finite group based on them. The main tool that we use to this end is Cayley's theorem, which states that any finite group is isomorphic to a subgro…

AMP-based Joint Activity Detection and Channel Estimation for Massive Grant-Free Access in OFDM-based Wideband Systems
Zhiyan Li, Ying Cui, Danny H. K. Tsang
https://arxiv.org/abs/2508.06540

AMP-based Joint Activity Detection and Channel Estimation for Massive Grant-Free Access in OFDM-based Wideband Systems
To realize orthogonal frequency division multiplexing (OFDM)-based grant-free access for wideband systems under frequency-selective fading, existing device activity detection and channel estimation methods need substantial accuracy improvement or computation time reduction. In this paper, we aim to resolve this issue. First, we present an exact time-domain signal model for OFDM-based grant-free access under frequency-selective fading. Then, we present a maximum a posteriori (MAP)-based device a…

Now that more details are known about the three #V2G propositions (🇩🇪 BMW/E.ON, 🇫🇷 Mobilize/Renault/Mobility House, 🇬🇧 Octopus) currently available or announced in Europe, it is time to compare them.
All three aim to enable the average user to drive for free with an annual mileage of 11,000–14,000 km

Learning an Implicit Physics Model for Image-based Fluid Simulation
Emily Yue-Ting Jia, Jiageng Mao, Zhiyuan Gao, Yajie Zhao, Yue Wang
https://arxiv.org/abs/2508.08254 https://

Learning an Implicit Physics Model for Image-based Fluid Simulation
Humans possess an exceptional ability to imagine 4D scenes, encompassing both motion and 3D geometry, from a single still image. This ability is rooted in our accumulated observations of similar scenes and an intuitive understanding of physics. In this paper, we aim to replicate this capacity in neural networks, specifically focusing on natural fluid imagery. Existing methods for this task typically employ simplistic 2D motion estimators to animate the image, leading to motion predictions that …

Social and Telepresence Robots for Accessibility and Inclusion in Small Museums
Nello Balossino, Rossana Damiano, Cristina Gena, Alberto Lillo, Anna Maria Marras, Claudio Mattutino, Antonio Pizzo, Alessia Prin, Fabiana Vernero
https://arxiv.org/abs/2508.05946

Social and Telepresence Robots for Accessibility and Inclusion in Small Museums
There are still many museums that present accessibility barriers, particularly regarding perceptual, cultural, and cognitive aspects. This is especially evident in low-density population areas. The aim of the ROBSO-PM project is to improve the accessibility of small museums through the use of social robots and social telepresence robots, focusing on three museums as case studies: the Museum of the Holy Shroud in Turin, a small but globally known institution, and two lesser known mountain museum…

A probabilistic approach to spectral analysis of Cauchy-type inverse problems: Convergence and stability analysis
Iulian C\^impean, Andreea Grecu, Liviu Marin
https://arxiv.org/abs/2508.08215

A probabilistic approach to spectral analysis of Cauchy-type inverse problems: Convergence and stability analysis
A comprehensive convergence and stability analysis of some probabilistic numerical methods designed to solve Cauchy-type inverse problems is performed in this study. Such inverse problems aim at solving an elliptic partial differential equation (PDE) or a system of elliptic PDEs in a bounded Euclidean domain, subject to incomplete boundary and/or internal conditions, and are usually severely ill-posed. In a very recent paper \cite{CiGrMaI}, a probabilistic numerical framework has been developed…

An analysis finds Chinese firms aim to buy 115K US-sanctioned Nvidia H100 and H200 chips for 39 data centers across China's western deserts, mostly in Xinjiang (Bloomberg)

How the Raiders Aim to Prove Anything is Possible https://www.si.com/nfl/raiders/las-vegas-elandon-roberts-maxx-crosby-geno-smith-pete-carroll

Dual prototype attentive graph network for cross-market recommendation
Li Fan, Menglin Kong, Yang Xiang, Chong Zhang, Chengtao Ji
https://arxiv.org/abs/2508.05969 https://

Dual prototype attentive graph network for cross-market recommendation
Cross-market recommender systems (CMRS) aim to utilize historical data from mature markets to promote multinational products in emerging markets. However, existing CMRS approaches often overlook the potential for shared preferences among users in different markets, focusing primarily on modeling specific preferences within each market. In this paper, we argue that incorporating both market-specific and market-shared insights can enhance the generalizability and robustness of CMRS. We propose a …

Policy Newton methods for Distortion Riskmetrics
Soumen Pachal, Mizhaan Prajit Maniyar, Prashanth L. A
https://arxiv.org/abs/2508.07249 https://arxiv.org/p…

Policy Newton methods for Distortion Riskmetrics
We consider the problem of risk-sensitive control in a reinforcement learning (RL) framework. In particular, we aim to find a risk-optimal policy by maximizing the distortion riskmetric (DRM) of the discounted reward in a finite horizon Markov decision process (MDP). DRMs are a rich class of risk measures that include several well-known risk measures as special cases. We derive a policy Hessian theorem for the DRM objective using the likelihood ratio method. Using this result, we propose a natu…

Breaking down ‘EchoLeak’, the First Zero-Click AI Vulnerability Enabling Data Exfiltration from Microsoft 365 Copilot.
Aim Labs reported CVE-2025-32711 against Microsoft 365 Copilot back in January, and the fix is now rolled out.
This is an extended variant of the prompt injection exfiltration attacks we've seen in a dozen different products already:
an attacker gets malicious instructions into an LLM system which cause it to access private data and then embed that in …

Differential rotation of solar {\alpha}-sunspots and implications for stellar light curves
Emily Joe L\"o{\ss}nitz, Alexander G. M. Pietrow, Hritam Chakraborty, Meetu Verma, Ioannis Kontogiannis, Horst Balthasar, Carsten Denker, Monika Lendl
https://arxiv.org/abs/2508.08196

Differential rotation of solar α-sunspots and implications for stellar light curves
Differential rotation is a key driver of magnetic activity and dynamo processes in the Sun and other stars, especially as the rate differs across the solar layers, but also in active regions. We aim to accurately quantify the velocity at which round α-spots traverse the solar disk as a function of their latitude, and compare these rates to those of the quiet-Sun and other sunspot types. We then extend this work to other stars and investigate how differential rotation affects the modulation of …

Aim High, Stay Private: Differentially Private Synthetic Data Enables Public Release of Behavioral Health Information with High Utility
Mohsen Ghasemizade, Juniper Lovato, Christopher M. Danforth, Peter Sheridan Dodds, Laura S. P. Bloomfield, Matthew Price, Team LEMURS, Joseph P. Near
https://arxiv.org/abs/2507.02971

Aim High, Stay Private: Differentially Private Synthetic Data Enables Public Release of Behavioral Health Information with High Utility
Sharing health and behavioral data raises significant privacy concerns, as conventional de-identification methods are susceptible to privacy attacks. Differential Privacy (DP) provides formal guarantees against re-identification risks, but practical implementation necessitates balancing privacy protection and the utility of data. We demonstrate the use of DP to protect individuals in a real behavioral health study, while making the data publicly available and retaining high utility for downst…

Trump's latest executive order banning 'debanking' takes aim at an industry that cheered his return (Business Insider)
https://www.businessinsider.com/trump-debanking-executive-order-2025-8
http://www.memeorandum.com/250808/p2#a250808p2

Tight Bounds for Schr\"odinger Potential Estimation in Unpaired Image-to-Image Translation Problems
Nikita Puchkin, Denis Suchkov, Alexey Naumov, Denis Belomestny
https://arxiv.org/abs/2508.07392 …

Tight Bounds for Schrödinger Potential Estimation in Unpaired Image-to-Image Translation Problems
Modern methods of generative modelling and unpaired image-to-image translation based on Schrödinger bridges and stochastic optimal control theory aim to transform an initial density to a target one in an optimal way. In the present paper, we assume that we only have access to i.i.d. samples from initial and final distributions. This makes our setup suitable for both generative modelling and unpaired image-to-image translation. Relying on the stochastic optimal control approach, we choose an Or…

"More than 200 lobbyists at UN’s plastic treaty talks will limit progress, campaigners warn"
#UN #UnitedNations #Plastic

Binary clusters in the Galactic disk I: Systematic identification and classification using Gaia DR3
Guimei Liu, Yu Zhang, Jing Zhong, Songmei Qin, Yueyue Jiang, Li Chen
https://arxiv.org/abs/2508.09127

Binary clusters in the Galactic disk I: Systematic identification and classification using Gaia DR3
Aims. We aim to identify and classify BCs using high-precision astrometric and kinematic data, and to investigate their physical properties, mutual gravitational interactions, and formation rates. Methods. We used a comprehensive star cluster catalog that contains 4,084 high-quality clusters. Based on spatial and kinematic proximity, we identified 400 cluster pairs involving 686 unique clusters. These pairs were classified into three types: primordial BCs, systems formed through tidal capture o…

Not Only Consistency: Enhance Test-Time Adaptation with Spatio-temporal Inconsistency for Remote Physiological Measurement
Xiao Yang, Yuxuan Fan, Can Liu, Houcheng Su, Weichen Guo, Jiyao Wang, Dengbo He
https://arxiv.org/abs/2507.07908

Not Only Consistency: Enhance Test-Time Adaptation with Spatio-temporal Inconsistency for Remote Physiological Measurement
Remote photoplethysmography (rPPG) has emerged as a promising non-invasive method for monitoring physiological signals using the camera. Although various domain adaptation and generalization methods were proposed to promote the adaptability of deep-based rPPG models in unseen deployment environments, considerations in aspects like privacy concerns and real-time adaptation restrict their application in real-world deployment. Thus, we aim to propose a novel fully Test-Time Adaptation (TTA) strate…

Trump and other Republicans have long criticized states that take weeks to count their ballots after election day.
This year has seen a flurry of activity to address it.
Part of Trump’s executive order on elections, signed in March but held up by lawsuits,
takes aim at one of the main reasons for late vote counts:
Many states allow mailed ballots to be counted even if they arrive after election day.
⚠️ The U.S. Supreme Court last month said it would consider w…

"Powering change: UK battery firms aim to unlock the way to net zero"
#UK #UnitedKingdom #NetZero #Batteries

Concept Unlearning by Modeling Key Steps of Diffusion Process
Chaoshuo Zhang, Chenhao Lin, Zhengyu Zhao, Le Yang, Qian Wang, Chao Shen
https://arxiv.org/abs/2507.06526

Concept Unlearning by Modeling Key Steps of Diffusion Process
Text-to-image diffusion models (T2I DMs), represented by Stable Diffusion, which generate highly realistic images based on textual input, have been widely used. However, their misuse poses serious security risks. While existing concept unlearning methods aim to mitigate these risks, they struggle to balance unlearning effectiveness with generative retainability.To overcome this limitation, we innovatively propose the Key Step Concept Unlearning (KSCU) method, which ingeniously capitalizes on th…

Forecasting Russian Equipment Losses Using Time Series and Deep Learning Models
Jonathan Teagan
https://arxiv.org/abs/2509.07813 https://arxiv.org/pdf/2509…

Forecasting Russian Equipment Losses Using Time Series and Deep Learning Models
This study applies a range of forecasting techniques,including ARIMA, Prophet, Long Short Term Memory networks (LSTM), Temporal Convolutional Networks (TCN), and XGBoost, to model and predict Russian equipment losses during the ongoing war in Ukraine. Drawing on daily and monthly open-source intelligence (OSINT) data from WarSpotting, we aim to assess trends in attrition, evaluate model performance, and estimate future loss patterns through the end of 2025. Our findings show that deep learning …