Tootfinder

NASA’s Goddard Institute for Space Studies (GISS)
has been a small-but-mighty source of world-changing scientific research for more than a half-century.
NASA scientists first moved into the building,
which another federal agency leases from GISS’s institutional partner, Columbia University, in 1966.
Last month, at the behest of the Trump administration,
NASA officials told GISS it had to move out before the end of May.
In response, more than 100 staffer…

NASA’s Goddard Institute for Space Studies Faces Eviction under Trump Plan
Since 1966 NASA’s Goddard Institute for Space Studies has been at the forefront of Earth and planetary science from its location in upper Manhattan. Now a Trump administration directive is ejecting its scientists to parts unknown

Just in case you haven't already seen this - and the summary: Vaccines are safe, they are tested and there is a robust tracking system to detect possible problems.
https://theconversation.com/im-a-physi

I’m a physician who has looked at hundreds of studies of vaccine safety, and here’s some of what RFK Jr. gets wrong
The health secretary has made many inaccurate statements about vaccines. But the science is clear that vaccines have dramatically reduced childhood illness, disability and death.

Just in case you haven't already seen this - and the summary: Vaccines are safe, they are tested and there is a robust tracking system to detect possible problems.
https://theconversation.com/im-a-physi

I’m a physician who has looked at hundreds of studies of vaccine safety, and here’s some of what RFK Jr. gets wrong
The health secretary has made many inaccurate statements about vaccines. But the science is clear that vaccines have dramatically reduced childhood illness, disability and death.

The Trump administration has terminated National Science Foundation grants for more than 100 research projects related to climate change
amid a widening campaign to slash federal funding for scientists and institutions studying the rising risks of a warming world.
The move will cut off what’s likely to amount to tens of millions of dollars for studies that were previously approved and, in most cases, already in the works. 
Affected projects include efforts to develop cleaner …

The Trump administration has shut down more than 100 climate studies
Tens of millions of dollars in NSF grants have been slashed, and scientists fear the US is about to lose a generation of climate researchers.

Uncovering Bias Mechanisms in Observational Studies
Ilker Demirel, Zeshan Hussain, Piersilvio De Bartolomeis, David Sontag
https://arxiv.org/abs/2506.01191

Uncovering Bias Mechanisms in Observational Studies
Observational studies are a key resource for causal inference but are often affected by systematic biases. Prior work has focused mainly on detecting these biases, via sensitivity analyses and comparisons with randomized controlled trials, or mitigating them through debiasing techniques. However, there remains a lack of methodology for uncovering the underlying mechanisms driving these biases, e.g., whether due to hidden confounding or selection of participants. In this work, we show that the r…

“As is the case with reading and writing a language, code is one of those things where if you don’t use it, you lose it. Early studies indicate that humans who use A.I. could become less creative over time.”
Early studies link: https://dl.acm.org/doi/abs/10.1145/3706598.3714198

Exploring the probing power of gamma-Dor's inertial dip for core magnetism: case of a toroidal field
Lucas Barrault, Lisa Bugnet, St\'ephane Mathis, Joey S. G. Mombarg
https://arxiv.org/abs/2507.00308

Exploring the probing power of gamma-Dor's inertial dip for core magnetism: case of a toroidal field
Gamma-Dor stars are ideal targets for studies of stellar innermost dynamical properties due to their rich asteroseismic spectrum of gravity modes. Integrating internal magnetism to the picture appears as the next milestone of detailed asteroseismic studies, for its prime importance on stellar evolution. The inertial dip in prograde dipole modes period-spacing pattern of gamma-Dors stands out as a unique window on the convective core structure and dynamics. Recent studies have highlighted the de…

European Journal of Jewish Studies Volume 19 (2025): Issue 1
https://ift.tt/i1HGJwy
When did aliens become a problem? The Mediterranean Association for Marine Biology and Oceanology in…
via Input 4 RELCFP

This https://arxiv.org/abs/2505.17072 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Safety Alignment Can Be Not Superficial With Explicit Safety Signals
Recent studies on the safety alignment of large language models (LLMs) have revealed that existing approaches often operate superficially, leaving models vulnerable to various adversarial attacks. Despite their significance, these studies generally fail to offer actionable solutions beyond data augmentation for achieving more robust safety mechanisms. This paper identifies a fundamental cause of this superficiality: existing alignment approaches often presume that models can implicitly learn a …

An Accurate and Efficient Vulnerability Propagation Analysis Framework
Bonan Ruan, Zhiwei Lin, Jiahao Liu, Chuqi Zhang, Kaihang Ji, Zhenkai Liang
https://arxiv.org/abs/2506.01342 …

An Accurate and Efficient Vulnerability Propagation Analysis Framework
Identifying the impact scope and scale is critical for software supply chain vulnerability assessment. However, existing studies face substantial limitations. First, prior studies either work at coarse package-level granularity, producing many false positives, or fail to accomplish whole-ecosystem vulnerability propagation analysis. Second, although vulnerability assessment indicators like CVSS characterize individual vulnerabilities, no metric exists to specifically quantify the dynamic impact…

Spending 5% of GDP on "defence" – in reality, on preparing for war – is an arms race. Historically, arms races have very frequently led to war.
We should be spending at least some of that money on building peace – on building complex webs of social and commercial relationships between rival blocks, and strengthening the international institutions which, if respected, could realise the "rules-based international order".

Entropy and the general theory of peace – Peace Research Institute Oslo (PRIO)
Book chapter in Proceedings of the International Peace Research Association Second Conference. Vol. 1: Studies in Conflicts

Radio Continuum Studies of Ultra-Compact and Short Orbital Period X-Ray Binaries
Kristen C. Dage, Teresa Panurach, Kwangmin Oh, Malu Sudha, Montserrat Armas Padilla, Arash Bahramian, Edward M. Cackett, Timothy J. Galvin, Craig O. Heinke, Renee Ludlam, Angiraben D. Mahida, Richard M. Plotkin, Thomas D. Russell, Susmita Sett, Payaswini Saikia, Aaran W. Shaw, Alexandra J. Tetarenko

Radio Continuum Studies of Ultra-Compact and Short Orbital Period X-Ray Binaries
We present the radio continuum counterparts to the enigmatic ultra-compact X-ray binaries (UCXBs); a black hole or neutron star accreting from a hydrogen-deficient white dwarf donor star, with short orbital periods ($<$ 80 minutes). For the sample of UCXBs hosted by globular clusters (GCs), we search for whether certain GC properties are more likely to enhance UCXB formation. We determine that GCs which host UCXBs are drawn from a distinct population in terms of cluster concentration, core radi…

Electromagnetically Reconfigurable Antennas for 6G: Enabling Technologies, Prototype Studies, and Research Outlook
Pinjun Zheng, Ruiqi Wang, Yuchen Zhang, Md. Jahangir Hossain, Anas Chaaban, Atif Shamim, Tareq Y. Al-Naffouri
https://arxiv.org/abs/2506.00657

Electromagnetically Reconfigurable Antennas for 6G: Enabling Technologies, Prototype Studies, and Research Outlook
The transition to the sixth-generation (6G) network is anticipated to redefine wireless transceiver architectures, demanding higher adaptability and efficiency at the antenna layer. Electromagnetically reconfigurable antennas (ERAs) have emerged as a promising solution capable of dynamically reconfiguring wireless channels to meet these requirements. This article presents an overview of recent advancements in ERA technology, underscoring its transformative potential for 6G applications. Drawing…

A global urban road network self-adaptive simplification workflow from traffic to spatial representation
https://www.nature.com/articles/s41597-025-05164-9
Data for 35 cities. Looks similar to the neatnet method

A global urban road network self-adaptive simplification workflow from traffic to spatial representation - Scientific Data
Urban road network is crucial for understanding and revealing the spatial logic of urban organization and evolution. However, existing urban road network datasets like OpenStreetMap are designed for traffic studies, treating each lane as a distinct spatial unit of mobility, which may not align with urban studies considering each road as an integration space for social and cultural dynamics. This study established a novel workflow to self-adaptively transform the global urban road network from t…

"Fast-growing, global-south cities are ‘strikingly underrepresented’ in climate research"
#Climate #ClimateChange

Fast-growing, global-south cities are ‘strikingly underrepresented’ in climate research - Carbon Brief
Climate change research in urban areas is skewed towards large, well-established global north cities, says analysis of over 50,000 studies.

In his presentation "Exploring and Visualizing Italian Advertising Fliers and Posters through an Iconographical Lens with Linked Open Data" Bruno Sartini is demonstrating how to bridge traditional art historical methods with computational approaches by using structured iconographical data to empirically validate qualitative findings from cultural studies.
paper:

🫦 New, non-opioid molecule acts like a long-lasting anesthetic, relieving chronic pain for three weeks
#pain #drugs #medicine

New, non-opioid molecule acts like a long-lasting anesthetic, relieving chronic pain for three weeks
A new molecule developed by University at Buffalo researchers acts like a local, long-lasting anesthetic, providing robust pain relief for up to three weeks, according to the results of preclinical studies reported recently in the journal Pain.

Querying Attack-Fault-Defense Trees: Property Specification in Smart Grid and Aerospace Case Studies
Reza Soltani, Stefano M. Nicoletti, Milan Lopuha\"a-Zwakenberg, Mari\"elle Stoelinga
https://arxiv.org/abs/2506.23789

Querying Attack-Fault-Defense Trees: Property Specification in Smart Grid and Aerospace Case Studies
This paper introduces AFDL, a logic-based framework for reasoning about safety, security, and defense interactions in Attack-Fault-Defense Trees, which is a model that captures all safety, security, and defense domains in a single framework. We showcase both AFDL and propose a structured domain specific query language, LangAFDL, which enables domain experts to express complex analysis goals through intuitive templates. LangAFDL supports both Boolean and quantified queries as well as minimal cut…

Quantum-like states from classical systems
Gregory D. Scholes
https://arxiv.org/abs/2507.00967 https://arxiv.org/pdf/2507.00967

Quantum-like states from classical systems
This work studies how a suitably-designed classical system generates with a quantum-like (QL) state space mediated by a graph. The graph plays a special dual role by directing the topology of the classical network and defining a state space that comprises superpositions of states in a tensor product basis. The basis for constructing QL graphs and their properties is reviewed and extended. An optimization of the graph product is developed to produce a more compact graph with the essential proper…

Now that’s a beautiful, free coding typeface by @…:
Server Mono
#web #typography #fonts

Server Mono | French Type Design foundry 🔥 We design fonts for blazing hot projects!
We are a Type Design foundry focused on making Variable Fonts with the easiest Font Licensing around. Our fonts are up to trend and will fit your daily design needs.

Vision Transformers for Multi-Variable Climate Downscaling: Emulating Regional Climate Models with a Shared Encoder and Multi-Decoder Architecture
Fabio Merizzi, Harilaos Loukos
https://arxiv.org/abs/2506.22447

Vision Transformers for Multi-Variable Climate Downscaling: Emulating Regional Climate Models with a Shared Encoder and Multi-Decoder Architecture
Global Climate Models (GCMs) are critical for simulating large-scale climate dynamics, but their coarse spatial resolution limits their applicability in regional studies. Regional Climate Models (RCMs) refine this through dynamic downscaling, albeit at considerable computational cost and with limited flexibility. While deep learning has emerged as an efficient data-driven alternative, most existing studies have focused on single-variable models that downscale one variable at a time. This approa…

Spatial Coordinates as a Cell Language: A Multi-Sentence Framework for Imaging Mass Cytometry Analysis
Chi-Jane Chen, Yuhang Chen, Sukwon Yun, Natalie Stanley, Tianlong Chen
https://arxiv.org/abs/2506.01918

Spatial Coordinates as a Cell Language: A Multi-Sentence Framework for Imaging Mass Cytometry Analysis
Image mass cytometry (IMC) enables high-dimensional spatial profiling by combining mass cytometry's analytical power with spatial distributions of cell phenotypes. Recent studies leverage large language models (LLMs) to extract cell states by translating gene or protein expression into biological context. However, existing single-cell LLMs face two major challenges: (1) Integration of spatial information: they struggle to generalize spatial coordinates and effectively encode spatial context as …

Comparative Studies: Cloud-Enabled Adaptive Learning System for Scalable Education in Sub-Saharan
Israel Fianyi, Soonja Yeom, Ju-Hyun Shin
https://arxiv.org/abs/2506.23851

Comparative Studies: Cloud-Enabled Adaptive Learning System for Scalable Education in Sub-Saharan
The integration of cloud computing in education can revolutionise learning in advanced (Australia & South Korea) and middle-income (Ghana & Nigeria) countries, while offering scalable, cost-effective and equitable access to adaptive learning systems. This paper explores how cloud computing and adaptive learning technologies are deployed across different socio-economic and infrastructure contexts. The study identifies enabling factors and systematic challenges, providing insights into how cloud-…

Rethink 3D Object Detection from Physical World
Satoshi Tanaka, Koji Minoda, Fumiya Watanabe, Takamasa Horibe
https://arxiv.org/abs/2507.00190 https://

Rethink 3D Object Detection from Physical World
High-accuracy and low-latency 3D object detection is essential for autonomous driving systems. While previous studies on 3D object detection often evaluate performance based on mean average precision (mAP) and latency, they typically fail to address the trade-off between speed and accuracy, such as 60.0 mAP at 100 ms vs 61.0 mAP at 500 ms. A quantitative assessment of the trade-offs between different hardware devices and accelerators remains unexplored, despite being critical for real-time appl…

This is the modus operandi of most anti-vaxx propaganda and a core characteristic that links it to authoritarianism and Fascism IMHO:
Lies are accepted. "Evidence" only has to look scientific, it doesn't has to be actual science.
No false statement will ever be corrected..
https://

Judgment as Coordination: A Joint Systems View of Visualization Design Practice
Paul C. Parsons, Arran Ridley
https://arxiv.org/abs/2507.01209 https://

Judgment as Coordination: A Joint Systems View of Visualization Design Practice
Professional visualization design has become an increasingly important area of inquiry, yet much of the field's discourse remains anchored in researcher-centered contexts. Studies of design practice often focus on individual designers' decisions and reflections, offering limited insight into the collaborative and systemic dimensions of professional work. In this paper, we propose a systems-level reframing of design judgment grounded in the coordination and adaptation that sustain progress amid …

On Hierarchical Coded Caching with Offline Users
Rashid Ummer N. T., B. Sundar Rajan
https://arxiv.org/abs/2507.00727 https://arxiv.o…

On Hierarchical Coded Caching with Offline Users
This paper studies a two-layer hierarchical network in which some users are offline during the content delivery phase. A two-layer hierarchical network consists of a single server connected to multiple cache-aided mirror sites, and each mirror site is connected to a distinct set of cache-aided users. A scheme for such a hierarchical system with offline users has been proposed recently but considered a special case where all mirror caches have zero memory, which is a significant limitation. We p…

There’ve been articles all over lately, based on a single small (n=55) study that purports to show adverse effects of cannabis use by the elderly. Here’s some evidence to the contrary. A series of studies show improved working memory function with cannabis use for those over 65 years of age. Heading on down to the dispensary as soon as I post this toot. It’s science, friends.

The Benefits of Daily Cannabis for the Middle-Aged Brain
Even daily use of low-level cannabis does not have a negative impact on cognition in older adults, recent research finds.

Control of Power Grids With Switching Equilibria: $\Omega$-Limit Sets and Input-to-State Stability
Mahmoud Abdelgalil, Vishal Shenoy, Guido Cavraro, Emiliano Dall'Anese, Jorge I. Poveda
https://arxiv.org/abs/2507.00240

Control of Power Grids With Switching Equilibria: $Ω$-Limit Sets and Input-to-State Stability
This paper studies a power transmission system with both conventional generators (CGs) and distributed energy assets (DEAs) providing frequency control. We consider an operating condition with demand aggregating two dynamic components: one that switches between different values on a finite set, and one that varies smoothly over time. Such dynamic operating conditions may result from protection scheme activations, external cyber-attacks, or due to the integration of dynamic loads, such as data c…

EmbAdvisor: Adaptive Cache Management for Sustainable LLM Serving
Yuyang Tian, Desen Sun, Yi Ding, Sihang Liu
https://arxiv.org/abs/2505.23970 https://

EmbAdvisor: Adaptive Cache Management for Sustainable LLM Serving
As large language models (LLMs) become widely used, their environmental impact$\unicode{x2014}$especially carbon emissions$\unicode{x2014}$has attracted more attention. Prior studies focus on compute-related carbon emissions. In this paper, we find that storage is another key contributor. LLM caching, which saves and reuses KV caches for repeated context, reduces operational carbon by avoiding redundant computation. However, this benefit comes at the cost of embodied carbon from high-capacity, …

Modules and generalizations of Joyce vertex algebras
Chenjing Bu
https://arxiv.org/abs/2506.00289 https://arxiv.org/pdf/2506.00289

Modules and generalizations of Joyce vertex algebras
Joyce vertex algebras are vertex algebra structures defined on the homology of certain $\mathbb{C}$-linear moduli stacks, and are used to express wall-crossing formulae for Joyce's homological enumerative invariants. This paper studies the generalization of this construction to settings that come from non-linear enumerative problems. In the special case of orthosymplectic enumerative geometry, we obtain twisted modules for Joyce vertex algebras. We expect that our construction will be useful …

Government, brought to you by the people who paid people to take their tests in college....
"Nobody has ever accused RFK Jr. of academic rigor,” said Marion Nestle, a professor emerita of nutrition, food studies and public health at New York University. "The speed (of the MAHA report) suggests that it could not have been vetted carefully and must have been whisked through standard clearance procedures. The citation problem suggests a reliance on AI."

Timing and spectral studies of SRGA J144459.2$-$604207 with NICER, Einstein Probe, IXPE, NuSTAR, Insight-HXMT and INTEGRAL during its 2024 outburst
Zhaosheng Li, Lucien Kuiper, Yuanyue Pan, Renxin Xu, Yong Chen, Mingyu Ge, Yue Huang, Shumei Jia, Xiaobo Li, Liming Song, Jinlu Qu, Shu Zhang, Lian Tao, Hua Feng, Shuang-Nan Zhang, Maurizio Falanga
https:…

Timing and spectral studies of SRGA J144459.2$-$604207 with NICER, Einstein Probe, IXPE, NuSTAR, Insight-HXMT and INTEGRAL during its 2024 outburst
SRGA J144459.2$-$604207 is a newly confirmed accreting millisecond X-ray pulsar and type I X-ray burster. We present the broadband X-ray timing and spectral behaviors of SRGA J144459.2$-$604207 during its 2024 outburst. The data were collected from NICER, Einstein Probe, IXPE, Insight-HXMT, NuSTAR and INTEGRAL observations. X-ray pulsations have been detected for the 1.5$-$90 keV energy range throughout the `ON' phase of the outburst from MJD $\sim 60355-60385$. We refined the orbital and spi…

CONFERENCE> California Buddhist Studies Graduate Student Conference, UCLA, Oct. 10-12
https://ift.tt/4oP2Nkc
Girlhood Studies (Vol. 14, Issue 1) Dear Colleague, Dear Colleague,Dear Colleague, The…
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Emergent symmetry in a two-Higgs-doublet model from quantum information and magic
Giorgio Busoni, John Gargalionis, Ewan N. V. Wallace, Martin J. White
https://arxiv.org/abs/2506.01314

Emergent symmetry in a two-Higgs-doublet model from quantum information and magic
Studies of scattering processes in scalar models with two Higgs doublets have recently hinted at a connection between the absence of flavour-space entanglement in $Φ^+Φ^0$ scattering and an emergent $\mathrm{SO}(8)$ symmetry in the scalar potential. We extend the analysis to all scattering channels with two particles in the external states by treating the process as a four-qubit system in the weak isospin and flavour subspaces of the $2$-particle state. We work with a generic quantum informat…

GRAM: Generative Recommendation via Semantic-aware Multi-granular Late Fusion
Sunkyung Lee, Minjin Choi, Eunseong Choi, Hye-young Kim, Jongwuk Lee
https://arxiv.org/abs/2506.01673

GRAM: Generative Recommendation via Semantic-aware Multi-granular Late Fusion
Generative recommendation is an emerging paradigm that leverages the extensive knowledge of large language models by formulating recommendations into a text-to-text generation task. However, existing studies face two key limitations in (i) incorporating implicit item relationships and (ii) utilizing rich yet lengthy item information. To address these challenges, we propose a Generative Recommender via semantic-Aware Multi-granular late fusion (GRAM), introducing two synergistic innovations. Fir…

MambAttention: Mamba with Multi-Head Attention for Generalizable Single-Channel Speech Enhancement
Nikolai Lund K\"uhne, Jesper Jensen, Jan {\O}stergaard, Zheng-Hua Tan
https://arxiv.org/abs/2507.00966

MambAttention: Mamba with Multi-Head Attention for Generalizable Single-Channel Speech Enhancement
With the advent of new sequence models like Mamba and xLSTM, several studies have shown that these models match or outperform state-of-the-art models in single-channel speech enhancement, automatic speech recognition, and self-supervised audio representation learning. However, prior research has demonstrated that sequence models like LSTM and Mamba tend to overfit to the training set. To address this issue, previous works have shown that adding self-attention to LSTMs substantially improves gen…

Suzaku Observation of Merging Clusters Abell 222 and Abell 223
Yanling Chen, Wei Cui, Aurora Simionescu, Rui Huang, Dan Hu
https://arxiv.org/abs/2506.01289

Suzaku Observation of Merging Clusters Abell 222 and Abell 223
Previous X-ray and optical studies of the galaxy cluster pair Abell 222/223 suggested the possible presence of a filamentary structure connecting the two clusters, a result that appears to be supported by subsequent weak-lensing analyses. This filament has been reported to host a primordial warm-hot intergalactic medium (WHIM), which existed prior to being heated by the interactions of the clusters. In this study, we made an attempt to examine the reported emission feature with data from an arc…

Quanta Magazine Staff Writer Yasemin Saplakoglu describes the various ongoing inter-disciplinary efforts to advance our scientific understanding of the Human brain. Computer scientists and computational neuroscientists collaborate as the latter borrow mathematical models from the former, and studies ways to incorporate new biological data to enhance, or supplant existing computational models.
"AI Is Nothing Like a Brain, and That's OK."

AI Is Nothing Like a Brain, and That’s OK | Quanta Magazine
The brain’s astounding cellular diversity and networked complexity could show how to make AI better.

Towards Efficient Random-Order Enumeration for Join Queries
Pengyu Chen, Zizheng Guo, Jianwei Yang, Dongjing Miao
https://arxiv.org/abs/2507.00489 https://…

Towards Efficient Random-Order Enumeration for Join Queries
In many data analysis pipelines, a basic and time-consuming process is to produce join results and feed them into downstream tasks. Numerous enumeration algorithms have been developed for this purpose. To be a statistically meaningful representation of the whole join result, the result tuples are required to be enumerated in uniformly random order. However, existing studies lack an efficient random-order enumeration algorithm with a worst-case runtime guarantee for (cyclic) join queries. In thi…

A Review on Zeroing Neural Networks
Chengze Jiang, Jie Gui, Long Jin, Shuai Li
https://arxiv.org/abs/2507.00387 https://arxiv.org/pdf…

A Review on Zeroing Neural Networks
Zeroing neural networks (ZNNs) have demonstrated outstanding performance on time-varying optimization and control problems. Nonetheless, few studies are committed to illustrating the relationship among different ZNNs and the derivation of them. Therefore, reviewing the advances for a systematical understanding of this field is desirable. This paper provides a survey of ZNNs' progress regarding implementing methods, analysis theory, and practical applications.

Verifiable Natural Language to Linear Temporal Logic Translation: A Benchmark Dataset and Evaluation Suite
William H English, Chase Walker, Dominic Simon, Sumit Kumar Jha, Rickard Ewetz
https://arxiv.org/abs/2507.00877

Verifiable Natural Language to Linear Temporal Logic Translation: A Benchmark Dataset and Evaluation Suite
Empirical evaluation of state-of-the-art natural-language (NL) to temporal-logic (TL) translation systems reveals near-perfect performance on existing benchmarks. However, current studies measure only the accuracy of the translation of NL logic into formal TL, ignoring a system's capacity to ground atomic propositions into new scenarios or environments. This is a critical feature, necessary for the verification of resulting formulas in a concrete state space. Consequently, most NL-to-TL transla…

A hyperboloidal method for numerical simulations of multidimensional nonlinear wave equations
Oliver Rinne
https://arxiv.org/abs/2507.00674 https://…

A hyperboloidal method for numerical simulations of multidimensional nonlinear wave equations
We consider the scalar wave equation with power nonlinearity in n+1 dimensions. Unlike previous numerical studies, we go beyond the radial case and do not assume any symmetries for n=3, and we only impose an SO(n-1) symmetry in higher dimensions. Our method is based on a hyperboloidal foliation of Minkowski spacetime and conformal compactification. We focus on the late-time power-law decay (tails) of the solutions and compute decay exponents for different spherical harmonic modes, for subcritic…

Pohjoismaiset tutkimukset osoittavat vanhojen metsien merkityksen luonnon monimuotoisuudelle.
Nordic studies show the significance of old-growth forests for biodiversity https://www.sciencedaily.com/releases/2025/05/250527124632.htm

Stellar populations in STARFORGE II: Comparison with observations
Juan P. Farias, Stella S. R. Offner, Ronan Kerr, Michael Y. Grudi\'c
https://arxiv.org/abs/2506.00240

Stellar populations in STARFORGE II: Comparison with observations
Recent studies suggest that most star-forming regions in our Galaxy form stellar associations rather than bound clusters. We analyse models from the STARFORGE simulation suite, a set of magneto-hydrodynamical simulations that include all key stellar feedback and radiative processes following star formation through cloud dispersal. We create synthetic observations by introducing observational biases such as random spurious measurements, unresolved binaries, and photometric sensitivity. These bia…

This looks like an interesting training event for postgrads and doctoral researchers in literary studies: stylometry and keystroke logging analysis using R and AntConc.
https://pala2025.com/summer-school/

Summer School
Computational Literary Studies UK Training School 2025 7-8 July 2025 Aston University, Birmingham Two days of workshops organised by Professor Bas Groes, University of Wolverhampton Workshop Schedu…

This https://arxiv.org/abs/2412.16712 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_grqc_…

Strong deflection of massive particles in spherically symmetric spacetimes
Near a gravitating compact object, massive particles traveling along timelike geodesics are gravitationally deflected similarly to light. In this paper, we study the deflection angles of these particles in the strong deflection limit. This analytical approximation applies when particles in unbound orbits approach the compact object very closely, circle around it at a radius close to that of the unstable circular orbit, and eventually escape. While previous studies have provided results for part…

A bibliometric analysis on the current situation and hot trends of the impact of microplastics on soil based on CiteSpace
Yiran Zheng, Yue Quan, Su Yan, Xinting Lv, Yuguanmin Cao, Minjie Fu, Mingji Jin
https://arxiv.org/abs/2507.01520

A bibliometric analysis on the current situation and hot trends of the impact of microplastics on soil based on CiteSpace
This paper aims to comprehensively grasp the research status and development trends of soil microplastics (MPs). It collects studies from the Web of Science Core Collection covering the period from 2013 to 2024. Employing CiteSpace and VOSviewer, the paper conducts in - depth analyses of literature regarding the environmental impacts of microplastics. These analyses involve keyword co - occurrence, clustering, burst term identification, as well as co - occurrence analysis of authors and institu…

Structural, dielectric, and ferroelectric characteristics of the low-temperature sintered 65PMN-35PT sample for electroceramic applications
B. Ramachandran, N. Sudarshan, G. Mangamma, M. S. Ramachandra Rao
https://arxiv.org/abs/2507.00614

Structural, dielectric, and ferroelectric characteristics of the low-temperature sintered 65PMN-35PT sample for electroceramic applications
A single-phase 65PMN-35PT ceramic was synthesized at a relatively low temperature (875 oC) using a modified columbite method. X-ray diffraction analysis confirmed the single-phase formation of perovskite 65PMN-35PT with a tetragonal structure. Morphological studies indicated that the sample consisted of small grains with a size of about 2 micro-m. The dielectric properties of the material demonstrate its relaxor behavior near the ferroelectric transition temperature, TC = 457 K. The saturation …

Photometric redshift estimation for emission line galaxies of DESI Legacy Imaging Surveys by CNN-MLP
Shirui Wei, Changhua Li, Yanxia Zhang, Chenzhou Cui, Chao Tang, Jingyi Zhang, Yongheng Zhao, Xuebing Wu, Yihan Tao, Dongwei Fan, Shanshan Li, Yunfei Xu, Maoyuan Huang, Xingyu Yang, Zihan Kang, Jinghang Shi
https://arxiv.org/abs/2…

Photometric redshift estimation for emission line galaxies of DESI Legacy Imaging Surveys by CNN-MLP
Emission Line Galaxies (ELGs) are crucial for cosmological studies, particularly in understanding the large-scale structure of the Universe and the role of dark energy. ELGs form an essential component of the target catalogue for the Dark Energy Spectroscopic Instrument (DESI), a major astronomical survey. However, the accurate selection of ELGs for such surveys is challenging due to the inherent uncertainties in determining their redshifts with photometric data. In order to improve the accurac…

This https://arxiv.org/abs/2412.05757 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Global existence of weak solutions to incompressible anisotropic Cahn-Hilliard-Navier-Stokes system
We study the anisotropic, incompressible Cahn-Hilliard-Navier-Stokes system with variable density in a bounded smooth domain $Ω\subset \mathbb{R}^d$. This work extends previous studies on the isotropic case by incorporating anisotropic surface energy, represented by $\mathfrak{F}= \int_Ω \fracε{2}\, Γ^2(\nabla ϕ) $. The thermodynamic consistency of this system, as well as its modeling background and physical motivation, has been established in [3,5,7]. Using a Galerkin approximation scheme…

A reentrancy of motility-induced phase separation in overdamped active Brownian particles
Hiroya Yamamoto
https://arxiv.org/abs/2507.01553 https://

A reentrancy of motility-induced phase separation in overdamped active Brownian particles
In a system of Self-Propelled Particles (SPPs), the combination of self-propulsion and excluded volume effects can result in a phase separation called Motility-Induced Phase Separation (MIPS). Previous studies reported that MIPS is one of the phenomena so-called "reentrant phase separation" ,i.e., MIPS is suppressed when the Péclet number $Pe$ (dimensionless self-propelled speed) is sufficiently large. We used a fundamental model of SPPs, i.e., overdamped Active Brownian Partcles (ABPs), to in…

This https://arxiv.org/abs/2505.21878 has been replaced.
initial toot: https://mastoxiv.page/@ar…

Machine learning assisted speckle and OAM spectrum analysis for enhanced turbulence characterisation
Atmospheric turbulence presents a major obstacle to the performance of free-space optical (FSO) communication and environmental sensing. While most studies focused on robust detection and recognition of transmitted structured light in turbulent media, a critical, yet often underexplored, avenue involves leveraging the structure of light itself to detect and characterize the medium itself. Here we introduce a deep learning framework that synergistically leverages post-transmission intensity spec…

Analyzing Time-Varying Scalar Fields using Piecewise-Linear Morse-Cerf Theory
Amritendu Dhar, Apratim Chakraborty, Vijay Natarajan
https://arxiv.org/abs/2507.00725

Analyzing Time-Varying Scalar Fields using Piecewise-Linear Morse-Cerf Theory
Morse-Cerf theory considers a one-parameter family of smooth functions defined on a manifold and studies the evolution of their critical points with the parameter. This paper presents an adaptation of Morse-Cerf theory to a family of piecewise-linear (PL) functions. The vertex diagram and Cerf diagram are introduced as representations of the evolution of critical points of the PL function. The characterization of a crossing in the vertex diagram based on the homology of the lower links of verti…

Transport Network, Graph, and Air Pollution
Nan Xu
https://arxiv.org/abs/2506.01164 https://arxiv.org/pdf/2506.01164

Transport Network, Graph, and Air Pollution
Air pollution can be studied in the urban structure regulated by transport networks. Transport networks can be studied as geometric and topological graph characteristics through designed models. Current studies do not offer a comprehensive view as limited models with insufficient features are examined. Our study finds geometric patterns of pollution-indicated transport networks through 0.3 million image interpretations of global cities. These are then described as part of 12 indices to investig…

This https://arxiv.org/abs/2505.23449 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csMM_…

CMIE: Combining MLLM Insights with External Evidence for Explainable Out-of-Context Misinformation Detection
Multimodal large language models (MLLMs) have demonstrated impressive capabilities in visual reasoning and text generation. While previous studies have explored the application of MLLM for detecting out-of-context (OOC) misinformation, our empirical analysis reveals two persisting challenges of this paradigm. Evaluating the representative GPT-4o model on direct reasoning and evidence augmented reasoning, results indicate that MLLM struggle to capture the deeper relationships-specifically, cases…

Mapping Brain-Behavior Correlations in Autism Using Heat Kernel Smoothing
Moo K. Chung, Kim M. Dalton, Daniel J. Kelley, Richard J. Davidson
https://arxiv.org/abs/2507.00473

Mapping Brain-Behavior Correlations in Autism Using Heat Kernel Smoothing
This paper presents a streamlined image analysis framework for correlating behavioral measures to anatomical measures on the cortex and detecting the regions of abnormal brain-behavior correlates. We correlated a facial emotion discrimination task score and its response time to cortical thickness measurements in a group of high functioning autistic subjects. Many previous correlation studies in brain imaging neglect to account for unwanted age effect and other variables and the subsequent stati…

Transient dispersion in oscillatory flows: auxiliary-time extension method for concentration moments
Weiquan Jiang, Guoqian Chen
https://arxiv.org/abs/2507.01870

Transient dispersion in oscillatory flows: auxiliary-time extension method for concentration moments
The dispersion phenomenon of mass and heat transport in oscillatory flows has wide applications in environmental, physiological and microfluidic flows. The method of concentration moments is a powerful theoretical tool for analyzing transport characteristics and is well-developed for steady flows. However, the general solutions of moments derived by Barton (J. Fluid Mech., vol. 126, 1983, pp. 205-218) cannot be applied directly to unsteady flows. Prior studies needed to re-solve the governing e…

Distributed Neural Policy Gradient Algorithm for Global Convergence of Networked Multi-Agent Reinforcement Learning
Pengcheng Dai, Yuanqiu Mo, Wenwu Yu, Wei Ren
https://arxiv.org/abs/2505.24113

Distributed Neural Policy Gradient Algorithm for Global Convergence of Networked Multi-Agent Reinforcement Learning
This paper studies the networked multi-agent reinforcement learning (NMARL) problem, where the objective of agents is to collaboratively maximize the discounted average cumulative rewards. Different from the existing methods that suffer from poor expression due to linear function approximation, we propose a distributed neural policy gradient algorithm that features two innovatively designed neural networks, specifically for the approximate Q-functions and policy functions of agents. This distri…

Assessing Future Wind Energy Potential under Climate Change: The Critical Role of Multi-Model Ensembles in Robustness Assessment
Andrea Lira-Loarca, Francesco Ferrari, Andrea Mazzino
https://arxiv.org/abs/2505.24463

Assessing Future Wind Energy Potential under Climate Change: The Critical Role of Multi-Model Ensembles in Robustness Assessment
Accurate projections of wind energy potential under climate change are critical for effective long-term energy planning. While previous studies have highlighted the value of multi-model ensembles, they often fall short in capturing the full spectrum of uncertainties and temporal dynamics relevant to wind resource reliability. This paper presents one of the most comprehensive assessments to date, leveraging a large ensemble of 21 high-resolution RCM-GCM combinations from the EURO-CORDEX initiati…

New Physics Search at the CEPC: a General Perspective
Stefan Antusch, Peter Athron, Daniele Barducci, Long Chen, Mingshui Chen, Xiang Chen, Huajie Cheng, Kingman Cheung, Joao Guimaraes da Costa, Arindam Das, Frank F. Deppisch, P. S. Bhupal Dev, Xiaokang Du, Yong Du, Yaquan Fang, Andrew Fowlie, Yu Gao, Bruce Mellado Garcia, Shao-Feng Ge, Jiayin Gu, Yu-Chen Guo, Jan Hajer, Chengcheng Han, Tao Han, Sven Heinemeyer, Fa Peng Huang, Yanping Huang, Jianfeng Jiang, Shan Jin, Liang Li, Lingfeng…

New Physics Search at the CEPC: a General Perspective
The Circular Electron-Positron Collider (CEPC), a proposed next-generation Higgs factory, provides new opportunities to explore physics beyond the Standard Model (SM). With its clean electron-positron collision environment and the ability to collect large samples of Higgs, W, and Z bosons, the CEPC enables precision measurements and searches for new physics. This white paper outlines the CEPC's discovery potential, including studies of exotic decays of the Higgs, Z, and top quarks, dark matter …

Modeling Data Diversity for Joint Instance and Verbalizer Selection in Cold-Start Scenarios
Mohna Chakraborty, Adithya Kulkarni, Qi Li
https://arxiv.org/abs/2507.00330

Modeling Data Diversity for Joint Instance and Verbalizer Selection in Cold-Start Scenarios
Prompt-based methods leverage the knowledge of pre-trained language models (PLMs) trained with a masked language modeling (MLM) objective; however, these methods are sensitive to template, verbalizer, and few-shot instance selection, particularly in cold-start settings with no labeled data. Existing studies overlook the dependency between instances and verbalizers, where instance-label probabilities depend on verbalizer token proximity in the embedding space. To address this, we propose COLDSEL…

Entanglement Detection with Variational Quantum Interference: Theory and Experiment
Rui Zhang, Zhenhuan Liu, Chendi Yang, Yue-Yang Fei, Xu-Fei Yin, Yingqiu Mao, Li Li, Nai-Le Liu, Yu-Ao Chen, Jian-Wei Pan
https://arxiv.org/abs/2505.24764

Entanglement Detection with Variational Quantum Interference: Theory and Experiment
Entanglement detection serves as a fundamental task in quantum information science, playing a critical role in quantum benchmarking and foundational studies. As the number of controllable qubits continues to increase, there emerges a pressing demand for scalable and robust entanglement detection protocols that can maintain high detection capability while requiring minimal resources. By integrating the positive partial transposition criterion with variational quantum interference, we develop an …

Echoes of AI: Investigating the Downstream Effects of AI Assistants on Software Maintainability
Markus Borg, Dave Hewett, Nadim Hagatulah, Noric Couderc, Emma S\"oderberg, Donald Graham, Uttam Kini, Dave Farley
https://arxiv.org/abs/2507.00788

Echoes of AI: Investigating the Downstream Effects of AI Assistants on Software Maintainability
[Context] AI assistants, like GitHub Copilot and Cursor, are transforming software engineering. While several studies highlight productivity improvements, their impact on maintainability requires further investigation. [Objective] This study investigates whether co-development with AI assistants affects software maintainability, specifically how easily other developers can evolve the resulting source code. [Method] We conducted a two-phase controlled experiment involving 151 participants, 95% o…

System Prompt Extraction Attacks and Defenses in Large Language Models
Badhan Chandra Das, M. Hadi Amini, Yanzhao Wu
https://arxiv.org/abs/2505.23817 https…

System Prompt Extraction Attacks and Defenses in Large Language Models
The system prompt in Large Language Models (LLMs) plays a pivotal role in guiding model behavior and response generation. Often containing private configuration details, user roles, and operational instructions, the system prompt has become an emerging attack target. Recent studies have shown that LLM system prompts are highly susceptible to extraction attacks through meticulously designed queries, raising significant privacy and security concerns. Despite the growing threat, there is a lack of…

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How to Evaluate the Accuracy of Online and AI-Based Symptom Checkers: A Standardized Methodological Framework
Marvin Kopka, Markus A. Feufel
https://arxiv.org/abs/2506.22379

How to Evaluate the Accuracy of Online and AI-Based Symptom Checkers: A Standardized Methodological Framework
Online and AI-based symptom checkers are applications that assist medical laypeople in diagnosing their symptoms and determining which course of action to take. When evaluating these tools, previous studies primarily used an approach introduced a decade ago that lacked any type of quality control. Numerous studies have criticized this approach, and several empirical studies have sought to improve specific aspects of evaluations. However, even after a decade, a high-quality methodological framew…

Partnering with AI: A Pedagogical Feedback System for LLM Integration into Programming Education
Niklas Scholz, Manh Hung Nguyen, Adish Singla, Tomohiro Nagashima
https://arxiv.org/abs/2507.00406

Partnering with AI: A Pedagogical Feedback System for LLM Integration into Programming Education
Feedback is one of the most crucial components to facilitate effective learning. With the rise of large language models (LLMs) in recent years, research in programming education has increasingly focused on automated feedback generation to help teachers provide timely support to every student. However, prior studies often overlook key pedagogical principles, such as mastery and progress adaptation, that shape effective feedback strategies. This paper introduces a novel pedagogical framework for …

A review on recent progresses in the study of low energy $\pi\pi$ and $\pi N$ scatterings
Qu-Zhi Li, Zhiguang Xiao, Han-Qing Zheng
https://arxiv.org/abs/2505.24674

A review on recent progresses in the study of low energy $ππ$ and $πN$ scatterings
We summarize new results on the studies of $ππ$ and $πN$ scatterings. They include the finding of a negative-parity nucleon pole with a mass lower than the nucleon mass, and the pole trajectory of $f_0(500)$ with respect to varying pion masses. The results are obtained from model-independent dispersion analyses. We also study the thermal properties of $f_0(500)$ based on the $O(N)$ $σ$ model and $N/D$ method.

This https://arxiv.org/abs/2401.03276 has been replaced.
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Robust Binary and Multinomial Logit Models for Classification with Data Uncertainties
Binary logit (BNL) and multinomial logit (MNL) models are the two most widely used discrete choice models for travel behavior modeling and prediction. However, in many scenarios, the collected data for those models are subject to measurement errors. Previous studies on measurement errors mostly focus on "better estimating model parameters" with training data. In this study, we focus on using BNL and MNL for classification problems, that is, to ``better predict the behavior of new samples'' when…

The impact of differential rotation on the stochastic excitation of acoustic modes in solar-like pulsators
Gabriel Biscarrat, Le\"ila Bessila, St\'ephane Mathis
https://arxiv.org/abs/2507.00919

The impact of differential rotation on the stochastic excitation of acoustic modes in solar-like pulsators
Acoustic modes are excited by turbulent convection in the outer convective envelope of solar-like stars. Observational results from asteroseismic studies show that 44% of solar-like stars do not present detectable stochastically-excited acoustic modes. This phenomenon appears to be related to their rotation rate and magnetic activity. In a first paper, we showed that uniform rotation tends to diminish the mode amplitudes significantly. However, convective envelopes in solar-type stars are diffe…

Simulating Complex Crossectional and Longitudinal Data using the simDAG R Package
Robin Denz, Nina Timmesfeld
https://arxiv.org/abs/2506.01498 https://

Simulating Complex Crossectional and Longitudinal Data using the simDAG R Package
Generating artificial data is a crucial step when performing Monte-Carlo simulation studies. Depending on the planned study, complex data generation processes (DGP) containing multiple, possibly time-varying, variables with various forms of dependencies and data types may be required. Simulating data from such DGP may therefore become a difficult and time-consuming endeavor. The simDAG R package offers a standardized approach to generate data from simple and complex DGP based on the definition …

Fast Simulation of Damage Diffusion Distribution in Scanning Transmission Electron Microscopy
Amir Javadi Rad, Amirafshar Moshtaghpour, Dongdong Chen, Angus I. Kirkland
https://arxiv.org/abs/2507.00294

Fast Simulation of Damage Diffusion Distribution in Scanning Transmission Electron Microscopy
Scanning Transmission Electron Microscopy (STEM) is a critical tool for imaging the properties of materials and biological specimens at atomic scale, yet our understanding of relevant electron beam damage mechanisms is incomplete. Recent studies suggest that certain types of damage can be modelled as a diffusion process. However, numerical simulation of such diffusion processes has remained computationally intensive. This work introduces a high-performance C++ framework for simulating damage di…

XMAD-Bench: Cross-Domain Multilingual Audio Deepfake Benchmark
Ioan-Paul Ciobanu, Andrei-Iulian Hiji, Nicolae-Catalin Ristea, Paul Irofti, Cristian Rusu, Radu Tudor Ionescu
https://arxiv.org/abs/2506.00462

XMAD-Bench: Cross-Domain Multilingual Audio Deepfake Benchmark
Recent advances in audio generation led to an increasing number of deepfakes, making the general public more vulnerable to financial scams, identity theft, and misinformation. Audio deepfake detectors promise to alleviate this issue, with many recent studies reporting accuracy rates close to 99%. However, these methods are typically tested in an in-domain setup, where the deepfake samples from the training and test sets are produced by the same generative models. To this end, we introduce XMAD-…

New insights on low-mass dark matter subhalo tidal tracks via numerical simulations
Alejandra Aguirre-Santaella, Miguel A. S\'anchez-Conde, Go Ogiya
https://arxiv.org/abs/2506.01152

New insights on low-mass dark matter subhalo tidal tracks via numerical simulations
Many studies assert that dark matter (DM) subhaloes without a baryonic counterpart and with an inner cusp always survive no matter the strength of the tidal force they undergo. In this work, we perform a suite of numerical simulations specifically designed to analyse the evolution of $V_\mathrm{max}$, $r_\mathrm{max}$ and concentration of low-mass DM subhaloes due to tidal stripping. We employ the improved version of the DASH code, introduced in our previous work arXiv:2207.08652 to investigate…

Proxy Target: Bridging the Gap Between Discrete Spiking Neural Networks and Continuous Control
Zijie Xu, Tong Bu, Zecheng Hao, Jianhao Ding, Zhaofei Yu
https://arxiv.org/abs/2505.24161

Proxy Target: Bridging the Gap Between Discrete Spiking Neural Networks and Continuous Control
Spiking Neural Networks (SNNs) offer low-latency and energy-efficient decision making through neuromorphic hardware, making them compelling for Reinforcement Learning (RL) in resource-constrained edge devices. Recent studies in this field directly replace Artificial Neural Networks (ANNs) by SNNs in existing RL frameworks, overlooking whether the RL algorithm is suitable for SNNs. However, most RL algorithms in continuous control are designed tailored to ANNs, including the target network soft …

Minimal Construction of Graphs with Maximum Robustness
Haejoon Lee, Dimitra Panagou
https://arxiv.org/abs/2507.00415 https://arxiv.or…

Minimal Construction of Graphs with Maximum Robustness
The notions of network $r$-robustness and $(r,s)$-robustness have been earlier introduced in the literature to achieve resilient control in the presence of misbehaving agents. However, while higher robustness levels provide networks with higher tolerances against the misbehaving agents, they also require dense communication structures, which are not always desirable for systems with limited capabilities and energy capacities. Therefore, this paper studies the fundamental structures behind $r$-r…

Quantum state reconstruction with variational quantum circuit
Shabnam Jabeen, Dmytro Kurdydyk, Aadi Palnitkar, Mihir Talati, Jeffrey Yan, Jinghong Yang
https://arxiv.org/abs/2507.01246

Quantum state reconstruction with variational quantum circuit
Reconstructing quantum states from measurement data represents a formidable challenge in quantum information science, especially as system sizes grow beyond the reach of traditional tomography methods. While recent studies have explored quantum machine learning (QML) for quantum state tomography (QST), nearly all rely on idealized assumptions, such as direct access to the unknown quantum state as quantum data input, which are incompatible with current hardware constraints. In this work, we pres…

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach
Melika Sepidband, Hamed Taherkhani, Song Wang, Hadi Hemmati
https://arxiv.org/abs/2505.23953

Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach
Automatic code generation has gained significant momentum with the advent of Large Language Models (LLMs) such as GPT-4. Although many studies focus on improving the effectiveness of LLMs for code generation, very limited work tries to understand the generated code's characteristics and leverage that to improve failed cases. In this paper, as the most straightforward characteristic of code, we investigate the relationship between code complexity and the success of LLM generated code. Using a la…

Shaping Ultrafast Pulses for Enhanced Resonant Nonlinear Interactions
Omri Meron, Snir Nehemia, Uri Arieli, Haim Suchowski
https://arxiv.org/abs/2507.00568

Shaping Ultrafast Pulses for Enhanced Resonant Nonlinear Interactions
Coherent control with shaped ultrafast pulses is a powerful approach for steering nonlinear light-matter interactions. Previous studies in quantum control have shown that, beyond transform-limited pulses, those with antisymmetric spectral phases can drive nonresonant multiphoton transitions with comparable efficiency. However, in resonant multiphoton transitions, the material's spectral-phase response introduces dispersion that degrades nonlinear efficiency. Pre-shaping the pulse to compensate …

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TRiMM: Transformer-Based Rich Motion Matching for Real-Time multi-modal Interaction in Digital Humans
Yueqian Guo, Tianzhao Li, Xin Lyu, Jiehaolin Chen, Zhaohan Wang, Sirui Xiao, Yurun Chen, Yezi He, Helin Li, Fan Zhang
https://arxiv.org/abs/2506.01077

TRiMM: Transformer-Based Rich Motion Matching for Real-Time multi-modal Interaction in Digital Humans
Large Language Model (LLM)-driven digital humans have sparked a series of recent studies on co-speech gesture generation systems. However, existing approaches struggle with real-time synthesis and long-text comprehension. This paper introduces Transformer-Based Rich Motion Matching (TRiMM), a novel multi-modal framework for real-time 3D gesture generation. Our method incorporates three modules: 1) a cross-modal attention mechanism to achieve precise temporal alignment between speech and gesture…

Social Robots for People with Dementia: A Literature Review on Deception from Design to Perception
Fan Wang, Giulia Perugia, Yuan Feng, Wijnand IJsselsteijn
https://arxiv.org/abs/2507.00963

Social Robots for People with Dementia: A Literature Review on Deception from Design to Perception
As social robots increasingly enter dementia care, concerns about deception, intentional or not, are gaining attention. Yet, how robotic design cues might elicit misleading perceptions in people with dementia, and how these perceptions arise, remains insufficiently understood. In this scoping review, we examined 26 empirical studies on interactions between people with dementia and physical social robots. We identify four key design cue categories that may influence deceptive impressions: cues r…

Epitome: Pioneering an Experimental Platform for AI-Social Science Integration
Jingjing Qu, Kejia Hu, Jun Zhu, Wenhao Li, Teng Wang, Zhiyun Chen, Yulei Ye, Chaochao Lu, Aimin Zhou, Xiangfeng Wang, James Evan
https://arxiv.org/abs/2507.01061

Epitome: Pioneering an Experimental Platform for AI-Social Science Integration
The integration of Large Language Models (LLMs) into social science experiments represents a transformative approach to understanding human-AI interactions and their societal impacts. We introduce Epitome, the world's first open experimental platform dedicated to the deep integration of artificial intelligence and social science. Rooted in theoretical foundations from management, communication studies, sociology, psychology, and ethics, Epitome focuses on the interactive impacts of AI on indivi…

A studentized permutation test for the treatment effect in individual participant data meta-analysis
Phuc Thien Tran, Long-Hao Xu, Christian R\"over, Tim Friede
https://arxiv.org/abs/2505.24774

A studentized permutation test for the treatment effect in individual participant data meta-analysis
Meta-analysis is a well-established tool used to combine data from several independent studies, each of which usually compares the effect of an experimental treatment with a control group. While meta-analyses are often performed using aggregated study summaries, they may also be conducted using individual participant data (IPD). Classical meta-analysis models may be generalized to handle continuous IPD by formulating them within a linear mixed model framework. IPD meta-analyses are commonly bas…

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Interplay of prompt and non-prompt photons in photon-triggered jet observables
Chathuranga Sirimanna (JETSCAPE Collaboration), Yasuki Tachibana (JETSCAPE Collaboration), Abhijit Majumder (JETSCAPE Collaboration), Aaron Angerami (JETSCAPE Collaboration), Ritu Arora (JETSCAPE Collaboration), Steffen Bass (JETSCAPE Collaboration), Yi Chen (JETSCAPE Collaboration), Ritoban Datta (JETSCAPE Collaboration), Lipei Du (JETSCAPE Collaboration), Raymond Ehlers (JETSCAPE Collaboration), Hannah Elf…

Interplay of prompt and non-prompt photons in photon-triggered jet observables
Prompt photons are important yet challenging to observe in relativistic heavy-ion collisions, as they are produced in the early stages and traverse almost the entire QGP medium without interaction. Experimental analyses typically employ isolation cuts, in the hope to identify prompt photons. Most theoretical studies consider only events with actual prompt photons, assuming no contribution from isolated non-prompt photons to reduce computational cost. For the first time, we present a study that …

Missing Data in Signal Processing and Machine Learning: Models, Methods and Modern Approaches
A. Hippert-Ferrer, A. Sportisse, A. Javaheri, M. N. El Korso, D. P. Palomar
https://arxiv.org/abs/2506.01696

Missing Data in Signal Processing and Machine Learning: Models, Methods and Modern Approaches
The goal of this tutorial is to provide an overview of recent methods for handling missing data in signal processing methods, from their origins to the challenges ahead. Missing data approaches are grouped by three main categories: i) missing-data imputation, ii) estimation with missing values and iii) prediction with missing values. We focus on methodological and experimental results through specific case studies on real-world applications. Promising and future research directions, including a…

Supervised Quantum Machine Learning: A Future Outlook from Qubits to Enterprise Applications
Srikanth Thudumu, Jason Fisher, Hung Du
https://arxiv.org/abs/2505.24765

Supervised Quantum Machine Learning: A Future Outlook from Qubits to Enterprise Applications
Supervised Quantum Machine Learning (QML) represents an intersection of quantum computing and classical machine learning, aiming to use quantum resources to support model training and inference. This paper reviews recent developments in supervised QML, focusing on methods such as variational quantum circuits, quantum neural networks, and quantum kernel methods, along with hybrid quantum-classical workflows. We examine recent experimental studies that show partial indications of quantum advantag…

Coverage-Guided Testing for Deep Learning Models: A Comprehensive Survey
Hongjing Guo, Chuanqi Tao, Zhiqiu Huang, Weiqin Zou
https://arxiv.org/abs/2507.00496

Coverage-Guided Testing for Deep Learning Models: A Comprehensive Survey
As Deep Learning (DL) models are increasingly applied in safety-critical domains, ensuring their quality has emerged as a pressing challenge in modern software engineering. Among emerging validation paradigms, coverage-guided testing (CGT) has gained prominence as a systematic framework for identifying erroneous or unexpected model behaviors. Despite growing research attention, existing CGT studies remain methodologically fragmented, limiting the understanding of current advances and emerging t…

Energy-dependent temporal study of GX 13 1 with AstroSat observation
Arbind Pradhan, Sree Bhattacherjee, Biplob Sarkar
https://arxiv.org/abs/2507.00626 htt…

Energy-dependent temporal study of GX 13+1 with AstroSat observation
In this work, we performed an energy-dependent study of low-frequency oscillations observed in GX 13+1 using \textit{AstroSat} (Large Area X-ray Proportional Counter and Soft X-ray Telescope). The hardness-intensity diagram (HID) of the observation resembles a `$ν$'-shaped track, while the color-color diagram exhibits a `$<$'-shaped track, similar to the horizontal and normal branches of the Z source. We conducted flux-resolved temporal studies focusing on low-frequency variability and divided…

Teaching Programming in the Age of Generative AI: Insights from Literature, Pedagogical Proposals, and Student Perspectives
Clemente Rubio-Manzano, Jazna Meza, Rodolfo Fernandez-Santibanez, Christian Vidal-Castro
https://arxiv.org/abs/2507.00108

Teaching Programming in the Age of Generative AI: Insights from Literature, Pedagogical Proposals, and Student Perspectives
Computer programming is undergoing a true transformation driven by powerful new tools for automatic source code generation based on large language models. This transformation is also manifesting in introductory programming courses at universities around the world, generating an in-depth debate about how programming content should be taught, learned, and assessed in the context of generative artificial intelligence. This article aims, on the one hand, to review the most relevant studies on thi…

CONFERENCE> California Buddhist Studies Graduate Student Conference, UCLA, Oct. 10-12 https://networks.h-net.org/group/announcements/20071768/california-buddhist-studies-graduate-student-conference

Unified study of two-meson and axion-meson production from semileptonic tau decays within resonance chiral framework
Jin Hao, Chun-Gui Duan, Zhi-Hui Guo
https://arxiv.org/abs/2507.00383

Unified study of two-meson and axion-meson production from semileptonic tau decays within resonance chiral framework
We carry out the joint study of the semileptonic tau decays into the two-meson and axion-meson channels, viz. $τ^-\to (P_1P_2)^-ν_τ$ and $τ^-\to π^-(K^-) aν_τ$ within the framework of resonance chiral theory by including the model-independent axion-gluon-gluon interaction. By utilizing the $π^0$-$η$-$η'$-axion mixing matrix elements from recent studies, we calculate the pertinent two-pseudoscalar boson form factors. To simultaneously fit the experimental spectra measured in the Cabibb…

MGS3: A Multi-Granularity Self-Supervised Code Search Framework
Rui Li, Junfeng Kang, Qi Liu, Liyang He, Zheng Zhang, Yunhao Sha, Linbo Zhu, Zhenya Huang
https://arxiv.org/abs/2505.24274

MGS3: A Multi-Granularity Self-Supervised Code Search Framework
In the pursuit of enhancing software reusability and developer productivity, code search has emerged as a key area, aimed at retrieving code snippets relevant to functionalities based on natural language queries. Despite significant progress in self-supervised code pre-training utilizing the vast amount of code data in repositories, existing methods have primarily focused on leveraging contrastive learning to align natural language with function-level code snippets. These studies have overlooke…

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