Tootfinder

Ultrasound system for precise neuromodulation of human deep brain circuits #tFUS

Ultrasound system for precise neuromodulation of human deep brain circuits - Nature Communications
Modulating deep brain structure can lead to therapies for neurological conditions. Here, the authors show a transcranial ultrasound stimulation (TUS) system featuring a 256-element helmet-shaped transducer array for modulation of the LGN and connected visual cortex regions

HDMI: Learning Interactive Humanoid Whole-Body Control from Human Videos
Haoyang Weng, Yitang Li, Nikhil Sobanbabu, Zihan Wang, Zhengyi Luo, Tairan He, Deva Ramanan, Guanya Shi
https://arxiv.org/abs/2509.16757

HDMI: Learning Interactive Humanoid Whole-Body Control from Human Videos
Enabling robust whole-body humanoid-object interaction (HOI) remains challenging due to motion data scarcity and the contact-rich nature. We present HDMI (HumanoiD iMitation for Interaction), a simple and general framework that learns whole-body humanoid-object interaction skills directly from monocular RGB videos. Our pipeline (i) extracts and retargets human and object trajectories from unconstrained videos to build structured motion datasets, (ii) trains a reinforcement learning (RL) policy …

This doesn't seem too surprising. Human nature?
"[...] some reviewers may give a more favourable review if they are cited in the article [...]"
https://osf.io/preprints/osf/wdvr9_v1
Related, and anecdotally my sense is that authors may over-cite their own prior work. Not …

Planned for months, but only been away for a few days and new deep memories for a lifetime: Visiting, revisiting and documenting some personal bucket list places in Tyrol/Vinschgau, Sondrio (Valmalenco) and the Engadin, collecting references & research... Landscapes too large & overwhelming, mountain passes (and the human ingenuity to traverse them), vast valleys full of ancient history & struggles (with nature and each other), disappearing glaciers leaving behind incredible stru…

Micro-variations in timing and loudness affect music-evoked mental imagery https://www.nature.com/articles/s41598-025-12604-4 "repetitive quasi-isochronous drumming enhanced mental imagery vividness, with a stronger effect observed when the drumming contained random micro-variat…

Micro-variations in timing and loudness affect music-evoked mental imagery - Scientific Reports
Music can shape the vividness, sentiment, and content of directed mental imagery. Yet, the role of specific musical features in these effects remains elusive. One important aspect of human musical performances is the presence of micro-variations—small deviations in timbre, pitch, and timing, driven by motor and attentional processes. These variations enhance perceived “naturalness” compared to mechanical playing without such variations. Here, we investigated whether random micro-variation…

A Nascent Taxonomy of Machine Learning in Intelligent Robotic Process Automation
Lukas Laakmann, Seyyid A. Ciftci, Christian Janiesch
https://arxiv.org/abs/2509.15730 https://…

A Nascent Taxonomy of Machine Learning in Intelligent Robotic Process Automation
Robotic process automation (RPA) is a lightweight approach to automating business processes using software robots that emulate user actions at the graphical user interface level. While RPA has gained popularity for its cost-effective and timely automation of rule-based, well-structured tasks, its symbolic nature has inherent limitations when approaching more complex tasks currently performed by human agents. Machine learning concepts enabling intelligent RPA provide an opportunity to broaden th…

Eine neue Studie zeigt die negativen Auswirkungen menschlicher Aktivitäten auf die biologische Vielfalt für alle Arten und Ökosysteme.
Menschliche Aktivitäten treiben den Verlust der biologischen Vielfalt sowohl direkt, als auch indirekt voran.
Via @…

The global human impact on biodiversity - Nature
Key measures of biodiversity were quantified and found to be affected by human pressures that shifted community composition and decreased local diversity across terrestrial, freshwater and marine ecosystems.

"Human connection to nature has declined 60% in 200 years, study finds"
#Nature #Environment #Wildlife

Human connection to nature has declined 60% in 200 years, study finds https://www.theguardian.com/environment/2025/aug/09/human-connection-to-nature-has-declined-60-in-200-years-study-finds

Cognitive scientist Margaret Boden, whose books helped shape the philosophical conversation about human intelligence and AI, passed away on July 18 at age 88 (Michael S. Rosenwald/New York Times)
https://www.nytimes.com/2025/08/14/science…

Margaret Boden, Philosopher of Artificial Intelligence, Dies at 88
A cognitive scientist, she used the language of computers to explore the nature of human thought and creativity, offering prescient insights about A.I.

Looking on my feed I start to feel that war against a <thing> is just a human nature.
#warOnThoughts #lol

A foundation model to predict and capture human cognition.
https://www.nature.com/articles/s41586-025-09215-4
And the reaction and criticism,

A foundation model to predict and capture human cognition - Nature
A computational model called Centaur, developed by fine-tuning a language model on a huge dataset called Psych-101, can predict and simulate human nature in experiments expressible in natural language, even in previously unseen situations.

Is General-Purpose AI Reasoning Sensitive to Data-Induced Cognitive Biases? Dynamic Benchmarking on Typical Software Engineering Dilemmas
Francesco Sovrano, Gabriele Dominici, Rita Sevastjanova, Alessandra Stramiglio, Alberto Bacchelli
https://arxiv.org/abs/2508.11278

Is General-Purpose AI Reasoning Sensitive to Data-Induced Cognitive Biases? Dynamic Benchmarking on Typical Software Engineering Dilemmas
Human cognitive biases in software engineering can lead to costly errors. While general-purpose AI (GPAI) systems may help mitigate these biases due to their non-human nature, their training on human-generated data raises a critical question: Do GPAI systems themselves exhibit cognitive biases? To investigate this, we present the first dynamic benchmarking framework to evaluate data-induced cognitive biases in GPAI within software engineering workflows. Starting with a seed set of 16 hand-cra…

🇺🇦 #NowPlaying on KEXP's #JazzTheatre
Vijay Iyer:
🎵 Human Nature
#VijayIyer
https://vijayiyer.bandcamp.com/track/human-nature
https://open.spotify.com/track/6vT6GhO6th2JE3NBQRlhKL

"Margaret Boden, a British philosopher and cognitive scientist who used the language of computers to explore the nature of thought and creativity, leading her to prescient insights about the possibilities and limitations of artificial intelligence, died on July 18."
https://www.nytimes.com/202…

Margaret Boden, Philosopher of Artificial Intelligence, Dies at 88
A cognitive scientist, she used the language of computers to explore the nature of human thought and creativity, offering prescient insights about A.I.

From Mimicry to True Intelligence (TI) - A New Paradigm for Artificial General Intelligence
Meltem Subasioglu, Nevzat Subasioglu
https://arxiv.org/abs/2509.14474 https://…

From Mimicry to True Intelligence (TI) - A New Paradigm for Artificial General Intelligence
The debate around Artificial General Intelligence (AGI) remains open due to two fundamentally different goals: replicating human-like performance versus replicating human-like cognitive processes. We argue that current performance-based definitions are inadequate because they provide no clear, mechanism-focused roadmap for research, and they fail to properly define the qualitative nature of genuine intelligence. Drawing inspiration from the human brain, we propose a new paradigm that shifts the…

Clarity Dawns: Human Beings, Nature, and Becoming
#becoming #BeBetter
https://muz4now.com/2019/clari…

Clarity Dawns: Human Beings, Nature, and Becoming
Stan Stewart - @muz4now

Bilateral Collaboration with Large Vision-Language Models for Open Vocabulary Human-Object Interaction Detection
Yupeng Hu, Changxing Ding, Chang Sun, Shaoli Huang, Xiangmin Xu
https://arxiv.org/abs/2507.06510

Bilateral Collaboration with Large Vision-Language Models for Open Vocabulary Human-Object Interaction Detection
Open vocabulary Human-Object Interaction (HOI) detection is a challenging task that detects all triplets of interest in an image, even those that are not pre-defined in the training set. Existing approaches typically rely on output features generated by large Vision-Language Models (VLMs) to enhance the generalization ability of interaction representations. However, the visual features produced by VLMs are holistic and coarse-grained, which contradicts the nature of detect…

For more than a century, putrid fumes emanated from
the “sewer of the Ruhr”,
creating a pungent whiff that assaulted towns throughout Germany’s industrial heartland.
But today, the Emscher bears little resemblance to Europe’s dirtiest river.
Water that used to be fouled by factory waste and human excrement have been free from effluent since 2021.
The river system, the main part of which was once considered biologically dead, is witnessing the return of an abun…

City Features VII 🏙️
城市特征 VII 🏙️
📷 Nikon FE
🎞️Ilford FP4 Plus, expired 1994
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

Optimizing the Variant Calling Pipeline Execution on Human Genomes Using GPU-Enabled Machines
Ajay Kumar, Praveen Rao, Peter Sanders
https://arxiv.org/abs/2509.09058 https://

Optimizing the Variant Calling Pipeline Execution on Human Genomes Using GPU-Enabled Machines
Variant calling is the first step in analyzing a human genome and aims to detect variants in an individual's genome compared to a reference genome. Due to the computationally-intensive nature of variant calling, genomic data are increasingly processed in cloud environments as large amounts of compute and storage resources can be acquired with the pay-as-you-go pricing model. In this paper, we address the problem of efficiently executing a variant calling pipeline for a workload of human genomes…

Decoupling geographical constraints from human mobility
https://www.nature.com/articles/s41562-025-02282-7
Finally out, very cool work, congrats to the authors @…

CogniAlign: Survivability-Grounded Multi-Agent Moral Reasoning for Safe and Transparent AI
Hasin Jawad Ali, Ilhamul Azam, Ajwad Abrar, Md. Kamrul Hasan, Hasan Mahmud
https://arxiv.org/abs/2509.13356

CogniAlign: Survivability-Grounded Multi-Agent Moral Reasoning for Safe and Transparent AI
The challenge of aligning artificial intelligence (AI) with human values persists due to the abstract and often conflicting nature of moral principles and the opacity of existing approaches. This paper introduces CogniAlign, a multi-agent deliberation framework based on naturalistic moral realism, that grounds moral reasoning in survivability, defined across individual and collective dimensions, and operationalizes it through structured deliberations among discipline-specific scientist agents. …

Direct observation of the crossed interhemispheric transfer of the left-right mirror-images in human vision
Albert Le Floch, Guy Ropars
https://arxiv.org/abs/2507.08703

Direct observation of the crossed interhemispheric transfer of the left-right mirror-images in human vision
Symmetry breaking is common in animal and human brains where the lack of asymmetry often perturbs behavioral and cognitive functions. In particular, the ubiquity of mirror-image confusion in young children, which often persists in dyslexia, is established. However, the very existence of these symmetric mirror-images and their perceptual or memory nature remain controversial. Here, using the noise-activated afterimage method, we demonstrate that a dyslexic with mirror-images is an ideal candidat…

Why Report Failed Interactions With Robots?! Towards Vignette-based Interaction Quality
Agnes Axelsson, Merle Reimann, Ronald Cumbal, Hannah Pelikan, Divesh Lala
https://arxiv.org/abs/2508.10603

Why Report Failed Interactions With Robots?! Towards Vignette-based Interaction Quality
Although the quality of human-robot interactions has improved with the advent of LLMs, there are still various factors that cause systems to be sub-optimal when compared to human-human interactions. The nature and criticality of failures are often dependent on the context of the interaction and so cannot be generalized across the wide range of scenarios and experiments which have been implemented in HRI research. In this work we propose the use of a technique overlooked in the field of HRI, eth…

🧠 Strangers whose brains respond alike to movie clips often become friends later, study finds
https://medicalxpress.com/news/2025-08-strangers-brains-alike-movie-friends.html

Strangers whose brains respond alike to movie clips often become friends later, study finds
People often bond with strangers over the books they read or the movies they watch and build friendships that last. Scientists may now have some insight into why this happens. A study published in Nature Human Behaviour found that participants who responded similarly to the same movie clips even before meeting were more likely to become friends later.

Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study
Karisa Parkington, Bazen G. Teferra, Marianne Rouleau-Tang, Argyrios Perivolaris, Alice Rueda, Adam Dubrowski, Bill Kapralos, Reza Samavi, Andrew Greenshaw, Yanbo Zhang, Bo Cao, Yuqi Wu, Sirisha Rambhatla, Sridhar Krishnan, Venkat Bhat
https:/…

Human vs. LLM-Based Thematic Analysis for Digital Mental Health Research: Proof-of-Concept Comparative Study
Thematic analysis provides valuable insights into participants' experiences through coding and theme development, but its resource-intensive nature limits its use in large healthcare studies. Large language models (LLMs) can analyze text at scale and identify key content automatically, potentially addressing these challenges. However, their application in mental health interviews needs comparison with traditional human analysis. This study evaluates out-of-the-box and knowledge-base LLM-based t…

"While crop seed vaults are common around the world, nurseries for wild and native plants are rare, and many plant species quietly become extinct. This marks #Gurukula out as a Noah’s ark for endangered plant species."

While I'm copying yesterday's photos to my computer, I'll just share some more photos from my recent blog post.
I tried to put the bushes at the lake as framing elements into the #photos. I think it worked out quite okay. -- And while we were on this walk I imagined all the time where and how this could look at sunset or with fog.
Maybe I should go there a again a couple o…

SVGauge: Towards Human-Aligned Evaluation for SVG Generation
Leonardo Zini, Elia Frigieri, Sebastiano Aloscari, Marcello Generali, Lorenzo Dodi, Robert Dosen, Lorenzo Baraldi
https://arxiv.org/abs/2509.07127

SVGauge: Towards Human-Aligned Evaluation for SVG Generation
Generated Scalable Vector Graphics (SVG) images demand evaluation criteria tuned to their symbolic and vectorial nature: criteria that existing metrics such as FID, LPIPS, or CLIPScore fail to satisfy. In this paper, we introduce SVGauge, the first human-aligned, reference based metric for text-to-SVG generation. SVGauge jointly measures (i) visual fidelity, obtained by extracting SigLIP image embeddings and refining them with PCA and whitening for domain alignment, and (ii) semantic consistenc…

Hues and Cues: Human vs. CLIP
Nuria Alabau-Bosque, Jorge Vila-Tom\'as, Paula Daud\'en-Oliver, Pablo Hern\'andez-C\'amara, Jose Manuel Ja\'en-Lorites, Valero Laparra, Jes\'us Malo
https://arxiv.org/abs/2509.02305

Hues and Cues: Human vs. CLIP
Playing games is inherently human, and a lot of games are created to challenge different human characteristics. However, these tasks are often left out when evaluating the human-like nature of artificial models. The objective of this work is proposing a new approach to evaluate artificial models via board games. To this effect, we test the color perception and color naming capabilities of CLIP by playing the board game Hues & Cues and assess its alignment with humans. Our experiments show that …

Why higher ed teaching is hard, and always will be. But we don't do it because it is easy, and we are trusted to do it well because we have hard earned expertise in our fields. Let's not undervalue that, hey?

11Plus-Bench: Demystifying Multimodal LLM Spatial Reasoning with Cognitive-Inspired Analysis
Chengzu Li, Wenshan Wu, Huanyu Zhang, Qingtao Li, Zeyu Gao, Yan Xia, Jos\'e Hern\'andez-Orallo, Ivan Vuli\'c, Furu Wei
https://arxiv.org/abs/2508.20068

11Plus-Bench: Demystifying Multimodal LLM Spatial Reasoning with Cognitive-Inspired Analysis
For human cognitive process, spatial reasoning and perception are closely entangled, yet the nature of this interplay remains underexplored in the evaluation of multimodal large language models (MLLMs). While recent MLLM advancements show impressive performance on reasoning, their capacity for human-like spatial cognition remains an open question. In this work, we introduce a systematic evaluation framework to assess the spatial reasoning abilities of state-of-the-art MLLMs relative to human pe…

On The Road - To Xi’An/Human Intervention 🚶
在路上 - 去西安/人类遗迹 🚶
📷 Pentax MX
🎞️Lucky SHD 400
#filmphotography #Photography #blackandwhite

Human Mobility in Epidemic Modeling
Xin Lu, Jiawei Feng, Shengjie Lai, Petter Holme, Shuo Liu, Zhanwei Du, Xiaoqian Yuan, Siqing Wang, Yunxuan Li, Xiaoyu Zhang, Yuan Bai, Xiaojun Duan, Wenjun Mei, Hongjie Yu, Suoyi Tan, Fredrik Liljeros
https://arxiv.org/abs/2507.22799

Human Mobility in Epidemic Modeling
Human mobility forms the backbone of contact patterns through which infectious diseases propagate, fundamentally shaping the spatio-temporal dynamics of epidemics and pandemics. While traditional models are often based on the assumption that all individuals have the same probability of infecting every other individual in the population, a so-called random homogeneous mixing, they struggle to capture the complex and heterogeneous nature of real-world human interactions. Recent advancements in da…

"The most worrying possibility behind Earth’s [accelerating warming] is how the general nature of clouds may be changing in response to climbing temperatures. It’s a feedback loop that could potentially exacerbate warming and is one of the single biggest uncertainties in predicting future climate."

Global Warming Is Speeding Up and the World Is Feeling the Effects
Human-caused global warming has been increasing faster and faster since the 1970s.

Invariant inter-subject relational structures in high order human visual cortex #neuroscience

Invariant inter-subject relational structures in high order human visual cortex - Nature Communications
The neuronal coding principles that underlie inter-individual perceptual similarities remains unclear. Here, the authors compared the stability of relational similarity versus activation patterns across brains and found that relational similarity was preferentially consistent across individuals, potentially underlying shared inter-subject perception.

Discerning and quantifying high frequency activities in EEG under normal and epileptic conditions
Jyotiraj Nath, Shreya Banerjee, Bhaswati Singha Deo, Mayukha Pal, Prasanta K. Panigrahi
https://arxiv.org/abs/2508.12670

Discerning and quantifying high frequency activities in EEG under normal and epileptic conditions
We investigate the nature of the modifications in the temporal dynamics manifested in the high-frequency EEG spectra of the normal human brain in comparison to the diseased brain undergoing epilepsy. For this purpose, the Fourier reconstruction is efficaciously made use of after Welch's transform, which helped identify the relevant frequency components undergoing significant changes in the case of epilepsy. The temporal dynamics involved in the EEG signals and their associated variations showed…

Vibe Coding: Is Human Nature the Ghost in the Machine?
Cory Knobel, Nicole Radziwill
https://arxiv.org/abs/2508.20918 https://arxiv.org/pdf/2508.20918

Vibe Coding: Is Human Nature the Ghost in the Machine?
This exploratory study examined the consistency of human-AI collaboration by analyzing three extensive "vibe coding" sessions between a human product lead and an AI software engineer. We investigated similarities and differences in team dynamics, communication patterns, and development outcomes across both projects. To our surprise, later conversations revealed that the AI agent had systematically misrepresented its accomplishments, inflating its contributions and systematically downplaying imp…

i reminded myself of an acronym i learned from a book i bought over 30 years ago
there was an amazing amount of _pnambic_ AI going on in the years before the launch of ChatGPT
i wonder how much of it still exists
eg i know there are two people employed as remote-operator drivers per google “driverless” car

Flexible Morphing Aerial Robot with Inflatable Structure for Perching-based Human-Robot Interaction
Ayano Miyamichi, Moju Zhao, Kazuki Sugihara, Junichiro Sugihara, Masanori Konishi, Kunio Kojima, Kei Okada, Masayuki Inaba
https://arxiv.org/abs/2509.07496

Flexible Morphing Aerial Robot with Inflatable Structure for Perching-based Human-Robot Interaction
Birds in nature perform perching not only for rest but also for interaction with human such as the relationship with falconers. Recently, researchers achieve perching-capable aerial robots as a way to save energy, and deformable structure demonstrate significant advantages in efficiency of perching and compactness of configuration. However, ensuring flight stability remains challenging for deformable aerial robots due to the difficulty of controlling flexible arms. Furthermore, perching for hum…

Quantifying Cross-Attention Interaction in Transformers for Interpreting TCR-pMHC Binding
Jiarui Li, Zixiang Yin, Haley Smith, Zhengming Ding, Samuel J. Landry, Ramgopal R. Mettu
https://arxiv.org/abs/2507.03197

Quantifying Cross-Attention Interaction in Transformers for Interpreting TCR-pMHC Binding
CD8+ "killer" T cells and CD4+ "helper" T cells play a central role in the adaptive immune system by recognizing antigens presented by Major Histocompatibility Complex (pMHC) molecules via T Cell Receptors (TCRs). Modeling binding between T cells and the pMHC complex is fundamental to understanding basic mechanisms of human immune response as well as in developing therapies. While transformer-based models such as TULIP have achieved impressive performance in this domain, their black-box nature …

Half-Physics: Enabling Kinematic 3D Human Model with Physical Interactions
Li Siyao, Yao Feng, Omid Tehari, Chen Change Loy, Michael J. Black
https://arxiv.org/abs/2507.23778 ht…

Half-Physics: Enabling Kinematic 3D Human Model with Physical Interactions
While current general-purpose 3D human models (e.g., SMPL-X) efficiently represent accurate human shape and pose, they lacks the ability to physically interact with the environment due to the kinematic nature. As a result, kinematic-based interaction models often suffer from issues such as interpenetration and unrealistic object dynamics. To address this limitation, we introduce a novel approach that embeds SMPL-X into a tangible entity capable of dynamic physical interactions with its surround…

The Nature of Reasoning in Theology, Philosophy, and Mathematics
Chad R. Mangum
https://arxiv.org/abs/2508.20297 https://arxiv.org/pdf/2508.20297

The Nature of Reasoning in Theology, Philosophy, and Mathematics
This article supports the epistemological claim that sound human reasoning about ultimate knowledge is either foundational or circularly justified. In particular, questions which naturally arise in theology, philosophy, and related disciplines, to the extent that they rationally treat ultimate knowledge, are necessarily supported in one of these ways. Comparisons with, contrasts to, and analogies from mathematics are given to illustrate and enhance this central claim.

RedCoder: Automated Multi-Turn Red Teaming for Code LLMs
Wenjie Jacky Mo, Qin Liu, Xiaofei Wen, Dongwon Jung, Hadi Askari, Wenxuan Zhou, Zhe Zhao, Muhao Chen
https://arxiv.org/abs/2507.22063

RedCoder: Automated Multi-Turn Red Teaming for Code LLMs
Large Language Models (LLMs) for code generation (i.e., Code LLMs) have demonstrated impressive capabilities in AI-assisted software development and testing. However, recent studies have shown that these models are prone to generating vulnerable or even malicious code under adversarial settings. Existing red-teaming approaches rely on extensive human effort, limiting their scalability and practicality, and generally overlook the interactive nature of real-world AI-assisted programming, which of…

The Human Capital Ontology (Extended Abstract)
Shane Babcock, Maxwell Farrington, John Gugliotti
https://arxiv.org/abs/2507.21175 https://arxiv.org/pdf/250…

The Human Capital Ontology (Extended Abstract)
The Human Capital Ontology (HCO) is an ontology that represents data standards maintained and employed by the Office of Personnel Management (OPM) to represent Human Capital Operations and to classify job positions. The HCO is an extension of the Common Core Ontologies and the upper level Basic Formal Ontology (BFO). HCO provides representation of OPM Nature of Action (NOA) codes that are used to describe human resource personnel actions. HCO also represents Occupational Groups and Job Families…

Nonlinear Model Predictive Control-Based Reverse Path-Planning and Path-Tracking Control of a Vehicle with Trailer System
Xincheng Cao, Haochong Chen, Bilin Aksun-Guvenc, Levent Guvenc, Brian Link, Peter J Richmond, Dokyung Yim, Shihong Fan, John Harber
https://arxiv.org/abs/2509.01820

Nonlinear Model Predictive Control-Based Reverse Path-Planning and Path-Tracking Control of a Vehicle with Trailer System
Reverse parking maneuvers of a vehicle with trailer system is a challenging task to complete for human drivers due to the unstable nature of the system and unintuitive controls required to orientate the trailer properly. This paper hence proposes an optimization-based automation routine to handle the path-planning and path-tracking control process of such type of maneuvers. The proposed approach utilizes nonlinear model predictive control (NMPC) to robustly guide the vehicle-trailer system into…

Decoding Polyphenol-Protein Interactions with Deep Learning: From Molecular Mechanisms to Food Applications
Qiang Liu, Tiantian Wang, Binbin Nian, Feiyang Ma, Siqi Zhao, Andr\'es F. V\'asquez, Liping Guo, Chao Ding, Mehdi D. Davari
https://arxiv.org/abs/2508.03456

Decoding Polyphenol-Protein Interactions with Deep Learning: From Molecular Mechanisms to Food Applications
Polyphenols and proteins are essential biomolecules that influence food functionality and, by extension, human health. Their interactions -- hereafter referred to as PhPIs (polyphenol-protein interactions) -- affect key processes such as nutrient bioavailability, antioxidant activity, and therapeutic efficacy. However, these interactions remain challenging due to the structural diversity of polyphenols and the dynamic nature of protein binding. Traditional experimental techniques like nuclear m…

Whatever success Trump had in his career was built on insight
-- not into the workings of capitalism but into the darker corners of human nature.
He succeeded through scams, lies, and bullying,
using the power he had over others to enrich himself at their expense.
So no one should be surprised that he brings the same spirit to policymaking.
In his second term, Trump is at last unleashed to fully realize his vision,
and on economics, that means a new kind…

Chairman Trump's Great Grift Forward
Move over, Mao.

Hear what the muse has to say: The muse is present. Stan Stewart is a pianist, composer, and songwriter. https://muz4now.com

Stan Stewart - aka @muz4now - the muse is present
Stan Stewart is a poet, musician, and human being who enjoys connecting with people and nature. Since his focus is on improvisational music, the inspiration he gets from these connections is often the source of his music.

Study of Robust Features in Formulating Guidance for Heuristic Algorithms for Solving the Vehicle Routing Problem
Bachtiar Herdianto, Romain Billot, Flavien Lucas, Marc Sevaux
https://arxiv.org/abs/2508.06129

Study of Robust Features in Formulating Guidance for Heuristic Algorithms for Solving the Vehicle Routing Problem
The Vehicle Routing Problem (VRP) is a complex optimization problem with numerous real-world applications, mostly solved using metaheuristic algorithms due to its $\mathcal{NP}$-Hard nature. Traditionally, these metaheuristics rely on human-crafted designs developed through empirical studies. However, recent research shows that machine learning methods can be used the structural characteristics of solutions in combinatorial optimization, thereby aiding in designing more efficient algorithms, pa…

A Semantic-Aware Framework for Safe and Intent-Integrative Assistance in Upper-Limb Exoskeletons
Yu Chen, Shu Miao, Chunyu Wu, Jingsong Mu, Bo OuYang, Xiang Li
https://arxiv.org/abs/2508.10378

A Semantic-Aware Framework for Safe and Intent-Integrative Assistance in Upper-Limb Exoskeletons
Upper-limb exoskeletons are primarily designed to provide assistive support by accurately interpreting and responding to human intentions. In home-care scenarios, exoskeletons are expected to adapt their assistive configurations based on the semantic information of the task, adjusting appropriately in accordance with the nature of the object being manipulated. However, existing solutions often lack the ability to understand task semantics or collaboratively plan actions with the user, limiting …

Weird Greco 🇬🇷
怪异希腊 🇬🇷
📷 Nikon FE
🎞️FOMAPAN Action 400
buy me ☕️ ?/请我喝杯☕️？
#filmphotography

"The Amazon Rainforest Approaches a Point of No Return"
#AmazonRainforest #Trees #Nature #Environment

The Amazon Rainforest Approaches a Point of No Return
In “Amazon Tipping Point” — Third-Place Winner of the 2025 Yale Environment 360 Film Contest — Brazilian filmmakers capture striking images of clear-cutting and explore how human activity is so damaging the world’s largest rainforest that it will not be able to recover.

ALFred: An Active Learning Framework for Real-world Semi-supervised Anomaly Detection with Adaptive Thresholds
Shanle Yao, Ghazal Alinezhad Noghre, Armin Danesh Pazho, Hamed Tabkhi
https://arxiv.org/abs/2508.09058

ALFred: An Active Learning Framework for Real-world Semi-supervised Anomaly Detection with Adaptive Thresholds
Video Anomaly Detection (VAD) can play a key role in spotting unusual activities in video footage. VAD is difficult to use in real-world settings due to the dynamic nature of human actions, environmental variations, and domain shifts. Traditional evaluation metrics often prove inadequate for such scenarios, as they rely on static assumptions and fall short of identifying a threshold that distinguishes normal from anomalous behavior in dynamic settings. To address this, we introduce an active le…

Exploring the Potential of LLMs for Serendipity Evaluation in Recommender Systems
Li Kang, Yuhan Zhao, Li Chen
https://arxiv.org/abs/2507.17290 https://arx…

Exploring the Potential of LLMs for Serendipity Evaluation in Recommender Systems
Serendipity plays a pivotal role in enhancing user satisfaction within recommender systems, yet its evaluation poses significant challenges due to its inherently subjective nature and conceptual ambiguity. Current algorithmic approaches predominantly rely on proxy metrics for indirect assessment, often failing to align with real user perceptions, thus creating a gap. With large language models (LLMs) increasingly revolutionizing evaluation methodologies across various human annotation tasks, we…

Network-driven discovery of repurposable drugs targeting hallmarks of aging
Bnaya Gross, Joseph Ehlert, Vadim N. Gladyshev, Joseph Loscalzo, Albert-L\'aszl\'o Barab\'asi
https://arxiv.org/abs/2509.03330

Network-driven discovery of repurposable drugs targeting hallmarks of aging
Despite the thousands of genes implicated in age-related phenotypes, effective interventions for aging remain elusive, a lack of advance rooted in the multifactorial nature of longevity and the functional interconnectedness of the molecular components implicated in aging. Here, we introduce a network medicine framework that integrates 2,358 longevity-associated genes onto the human interactome to identify existing drugs that can modulate aging processes. We find that genes associated with each …

Generative AI and the future of scientometrics: current topics and future questions
Benedetto Lepori, Jens Peter Andersen, Karsten Donnay
https://arxiv.org/abs/2507.00783

Generative AI and the future of scientometrics: current topics and future questions
The aim of this paper is to review the use of GenAI in scientometrics, and to begin a debate on the broader implications for the field. First, we provide an introduction on GenAI's generative and probabilistic nature as rooted in distributional linguistics. And we relate this to the debate on the extent to which GenAI might be able to mimic human 'reasoning'. Second, we leverage this distinction for a critical engagement with recent experiments using GenAI in scientometrics, including topic lab…

EconAgentic in DePIN Markets: A Large Language Model Approach to the Sharing Economy of Decentralized Physical Infrastructure
Yulin Liu, Mocca Schweitzer
https://arxiv.org/abs/2508.21368

EconAgentic in DePIN Markets: A Large Language Model Approach to the Sharing Economy of Decentralized Physical Infrastructure
The Decentralized Physical Infrastructure (DePIN) market is revolutionizing the sharing economy through token-based economics and smart contracts that govern decentralized operations. By 2024, DePIN projects have exceeded \$10 billion in market capitalization, underscoring their rapid growth. However, the unregulated nature of these markets, coupled with the autonomous deployment of AI agents in smart contracts, introduces risks such as inefficiencies and potential misalignment with human value…

High-level visual representations in the human brain are aligned with large language models https://www.nature.com/articles/s42256-025-01072-0
News release: Using AI to "see" what we see

Learning User Preferences for Image Generation Model
Wenyi Mo, Ying Ba, Tianyu Zhang, Yalong Bai, Biye Li
https://arxiv.org/abs/2508.08220 https://arxiv.or…

Learning User Preferences for Image Generation Model
User preference prediction requires a comprehensive and accurate understanding of individual tastes. This includes both surface-level attributes, such as color and style, and deeper content-related aspects, such as themes and composition. However, existing methods typically rely on general human preferences or assume static user profiles, often neglecting individual variability and the dynamic, multifaceted nature of personal taste. To address these limitations, we propose an approach built upo…

Data Humanism Decoded: A Characterization of its Principles to Bridge Data Visualization Researchers and Practitioners
Ibrahim Al-Hazwani, Ke Er Zhang, Laura Garrison, J\"urgen Bernard
https://arxiv.org/abs/2509.00440

Data Humanism Decoded: A Characterization of its Principles to Bridge Data Visualization Researchers and Practitioners
Data Humanism is a human-centered design approach that emphasizes the personal, contextual, and imperfect nature of data. Despite its growing influence among practitioners, the 13 principles outlined in Giorgia Lupi's visual manifesto remain loosely defined in research contexts, creating a gap between design practice and systematic application. Through a mixed-methods approach, including a systematic literature review, multimedia analysis, and expert interviews, we present a characterization of…

Safe and Non-Conservative Contingency Planning for Autonomous Vehicles via Online Learning-Based Reachable Set Barriers
Rui Yang, Lei Zheng, Shuzhi Sam Ge, Jun Ma
https://arxiv.org/abs/2509.07464

Safe and Non-Conservative Contingency Planning for Autonomous Vehicles via Online Learning-Based Reachable Set Barriers
Autonomous vehicles must navigate dynamically uncertain environments while balancing the safety and driving efficiency. This challenge is exacerbated by the unpredictable nature of surrounding human-driven vehicles (HVs) and perception inaccuracies, which require planners to adapt to evolving uncertainties while maintaining safe trajectories. Overly conservative planners degrade driving efficiency, while deterministic approaches may encounter serious issues and risks of failure when faced with …

Rethinking Ecological Measures Of Functional Diversity
Ines Meraoumia, Adji Bousso Dieng
https://arxiv.org/abs/2506.17839 https://arx…

Rethinking Ecological Measures Of Functional Diversity
Understanding functional diversity, the range and variability of species' roles and actions within their communities, is key to predicting and preserving the functions that sustain both nature and human well-being. In this paper, we provide a comprehensive review of the literature on functional diversity measurement. We begin by consolidating essential criteria that effective measures of functional diversity should meet. We then evaluate fifteen widely used functional diversity metrics against …

On The Road - To Xi’An 🗿
在路上 - 去西安 🗿
📷 Minolta Hi-Matic AF
🎞️Kentmere Pan 200
#filmphotography #Photography #blackandwhite

(World) Building Transformation: Students and Teachers as CoCreators in OpenXR Learning Environments
Abigail Greenbaum, Elizabeth Strickler, Victoria Patterson, Bolu Oluleye
https://arxiv.org/abs/2506.22988

(World) Building Transformation: Students and Teachers as CoCreators in OpenXR Learning Environments
Emerging extended reality (XR) tools and platforms offer an exciting opportunity to align learning experiences in higher education with the futures in which students will pursue their goals. However, the dynamic nature of XR as subject matter challenges hierarchies and classroom practices typical of higher education. This instructional design practice paper reflects on how our team of faculty, learning experience designers, and user experience (UX) researchers implemented human-centered design …

"She was useful, but a bit too optimistic": Augmenting Design with Interactive Virtual Personas
Paluck Deep, Monica Bharadhidasan, A. Baki Kocaballi
https://arxiv.org/abs/2508.19463

"She was useful, but a bit too optimistic": Augmenting Design with Interactive Virtual Personas
Personas have been widely used to understand and communicate user needs in human-centred design. Despite their utility, they may fail to meet the demands of iterative workflows due to their static nature, limited engagement, and inability to adapt to evolving design needs. Recent advances in large language models (LLMs) pave the way for more engaging and adaptive approaches to user representation. This paper introduces Interactive Virtual Personas (IVPs): multimodal, LLM-driven, conversational …

An Introduction to Silent Paralinguistics
Zhao Ren, Simon Pistrosch, Buket Co\c{s}kun, Kevin Scheck, Anton Batliner, Bj\"orn W. Schuller, Tanja Schultz
https://arxiv.org/abs/2508.18127

An Introduction to Silent Paralinguistics
The ability to speak is an inherent part of human nature and fundamental to our existence as a social species. Unfortunately, this ability can be restricted in certain situations, such as for individuals who have lost their voice or in environments where speaking aloud is unsuitable. Additionally, some people may prefer not to speak audibly due to privacy concerns. For such cases, silent speech interfaces have been proposed, which focus on processing biosignals corresponding to silently produce…

Structuring GUI Elements through Vision Language Models: Towards Action Space Generation
Yi Xu, Yesheng Zhang, jiajia Liu, Jingdong Chen
https://arxiv.org/abs/2508.16271 https:/…

Structuring GUI Elements through Vision Language Models: Towards Action Space Generation
Multimodal large language models (MLLMs) have emerged as pivotal tools in enhancing human-computer interaction. In this paper we focus on the application of MLLMs in the field of graphical user interface (GUI) elements structuring, where they assist in processing user instructions based on screen contents. Despite the promise of MLLMs, their performance in precisely generating UI element coordinates, a critical aspect of GUI understanding, is hindered by the nature of next-token prediction trai…

Multimodal Behavioral Patterns Analysis with Eye-Tracking and LLM-Based Reasoning
Dongyang Guo, Yasmeen Abdrabou, Enkeleda Thaqi, Enkelejda Kasneci
https://arxiv.org/abs/2507.18252

Multimodal Behavioral Patterns Analysis with Eye-Tracking and LLM-Based Reasoning
Eye-tracking data reveals valuable insights into users' cognitive states but is difficult to analyze due to its structured, non-linguistic nature. While large language models (LLMs) excel at reasoning over text, they struggle with temporal and numerical data. This paper presents a multimodal human-AI collaborative framework designed to enhance cognitive pattern extraction from eye-tracking signals. The framework includes: (1) a multi-stage pipeline using horizontal and vertical segmentation alo…