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Blurred Magnitude Homology of Functional Connectome for ASD Diagnosis
Frontiers in Psychiatry. 2026. Vol. 16. Article 1677282.
Autism spectrum disorder (ASD) is one of the most common neurodevelopmental disorders. Existing studies show that adults with ASD may experience accelerated or altered neurocognitive aging. Consequently, cognitive decline in people with ASD can be delayed if timely measures are taken to treat this disorder. This study focuses on the development of a new algorithm for the early prediction of ASD from fMRI images. Autism spectrum disorder alters functional connectivity between brain regions. Therefore, it is important to develop methods for diagnosing this condition based on the analysis of a brain network. Functional brain networks are usually studied using undirected correlations, while functional connections in the brain are inherently directed. Blurred magnitude homology is an algebro-topological tool that enables the analysis of directed graphs, including directed functional connectomes. The method proposed in this work is based on applying a fully connected neural network to blurred magnitude homology-based features of a directed functional connectivity network. Experiments on empirically derived connectomes from fMRI images show that blurred magnitude homology is a useful invariant for distinguishing directed brain networks of individuals with ASD and typically developing individuals.
Language:
English
Sergey Slavnov, / Series math "arxiv.org". 2026.
A prototypical example of categorial grammars are those based on Lambek calculus, i.e. noncommutative intuitionistic linear logic. However, it has been noted that purely noncommutative operations are often not sufficient for modeling even very simple natural language phenomena. Therefore a number of alternative formalisms are considered in the literature: those using purely ``commutative'' linear logic ...
Added: October 29, 2026
Чернявский А. А., Психиатрия 2026 Т. 24 № 2 С. 131–151
Background: existing tools for assessing depression do not take into account its contextualized nature. One of the prevailing spheres of human activity is labor activity, which may cause the occurrence of depression associated with professional activity. Occupational depression is a depressive state associated with chronic work stress. Because occupational activity may be a significant factor ...
Added: October 28, 2026
[б.и.], 2026.
While Large Language Models (LLMs) have revolutionized NLP, they remain prone to hallucinations, reasoning “mode-collapse” in open-ended generation, and a lack of factual provenance. The Automated Knowledge Base Construction (AKBC) workshop addresses a key missing piece of the generative era: structured knowledge. Knowledge Bases (KBs) serve as ground truth for fact verification, the semantic backbone ...
Added: October 28, 2026
Шахнович Е. Б., Кербиков О. Б., Kulaga E., Современная онкология 2015 Т. 17 № 1 С. 50–54
Гепатоцеллюлярный рак (гЦр) является одним из наиболее распространенных онкологических заболеваний в мире. Успех терапии гЦр напрямую зависит от диагностики заболевания на ранней стадии и своевременного назначения правильного лечения пациентам. согласно современным рекомендациям системная стандартная лекарственная химиотерапия не является оптимальным вариантом лечения пациентов с распространенным гЦр. в настоящее время единственным одобренным таргетным препаратом для лечения гЦр ...
Added: October 28, 2026
Nikitiuk B., Lenev D., Pisarev V. et al., Journal of Colloid and Interface Science 2026 Vol. 718 Article 140444
Hypothesis:Accurate determination of interfacial tension values is crucial for many modeling applications in the oil and gas industry. However, many of the presently used empirical and theoretical models show poor prediction accuracy and do not allow for direct consideration of the concentrations of gases and salts dissolved in the system as well as the specific ...
Added: October 28, 2026
Deshchenya V., Nikolay D. Kondratyuk, Sivakova A. et al., Chemical Engineering Sciences 2027 Vol. 337 Article 124616
Accurate prediction of complex formulation viscosity is crucial for the lubricant industry and engineering processes. However, developing generalizable models remains challenging due to the complexity of industrial mixtures and the scarcity of public experimental data, often resulting from corporate proprietary restrictions. This study presents a machine-learning workflow for viscosity estimation from a proprietary pseudonymized dataset, ...
Added: October 28, 2026
Zubov A., Zubov A., Малявко, Я. et al., Computer Physics Communications 2025 Vol. 317 Article 109860
The concept of representative volume (REV, or RVE in material sciences) is the cornerstone of continuum scale models – one needs to get the volume big enough so that it could be represented with an averaged value (scalar, vector or tensorial, etc.). While REV should be established in all larger scale simulations, this is rarely ...
Added: October 28, 2026
Roman Prosvirnin, Suslov A., Aleksei Soldatov et al., Computation 2026 Vol. 14 No. 10 Article 261
Abstract
Safety-aligned language models often encode that a request is harmful yet still comply with it. We turn this gap between internal recognition and observable behavior into an inference-time defense. The proposed activation-steering method uses a multiplicative operator that amplifies the residual-stream component along a harm-recognition direction. Intervention strength scales with the model’s own assessment of ...
Added: October 27, 2026
Aleksei Samarin, Nazarenko A., Nazarenko D. et al., Big Data and Cognitive Computing 2026 Vol. 10 No. 11 P. 1–52
Camera traps are a key tool for non-invasive wildlife monitoring, yet models trained on existing benchmarks often generalize poorly to new regions due to domain shift, class imbalance, and natural variability in illumination, season, and background. We introduce PACTraD, a benchmark of 116,973 annotated camera trap images collected in a protected area of the Baikal ...
Added: October 27, 2026
IEEE, 2026.
Proceedings of the X Scientific School "Dynamics of Complex Networks and their Applications"
(DCNA'2026) contain papers of reports of scientists and specialists in the field of intelligent technologies,
engineering education, research and design of complex networks.
DCNA'2026 was held from 10 to 12 September 2026 in Moscow, Russia, as a part of the International
Forum on Artificial Intelligence and ...
Added: October 26, 2026
Maddalena L., Yildiz B., Del Vecchio Blanco F. et al., Scientific data 2026 P. 1–20
We addressed the task of chemical characterization of the aerosol emitted by heated tobacco products (HTPs) and of the smoke emitted by conventional/commercial cigarettes, usually adopted as a reference. Emphasis was placed on quantifying constituents for enabling the identification of novel compounds through targeted and untargeted analyses, and the evaluation of reductions in toxicant exposure under ...
Added: October 26, 2026
Flamarion M. V., Pelinovsky E., Wave Motion 2027 Vol. 148 Article 103867
We consider the interaction of two solitary waves in the modified Benjamin–Bona–Mahony
(mBBM) equation in a regime where a small parameter measures the departure from the classical
modified Korteweg–de Vries (mKdV) equation. A regular perturbation method is used to
analyze the modification of the two-soliton wave field induced by the weak non-integrability of
the mBBM equation. We show that, ...
Added: October 23, 2026
Obsie E. Y., Zhan Y., Liu Y., Engineering Research Express 2026 Article 7
Maintaining plant health is crucial for crop quality, food security, and agricultural productivity. Although deep learning methods have shown strong potential for species, disease, and severity classification, most existing approaches tackle these tasks separately, failing to exploit shared representations and interdependencies among them. Furthermore, the variability of disease symptoms, such as subtle differences in size, ...
Added: October 22, 2026
Lev Pyatko, Sergey Aksenov, Regular and Chaotic Dynamics 2026 Vol. 31 No. 5 P. 794–813
In the circular restricted three-body problem, families of periodic and quasi-periodic orbits exist in the vicinity of the libration points and are of significant interest for practical applications. This work presents a neural network-based algorithm for orbit construction and station-keeping, applicable to both periodic and quasi-periodic orbits near collinear libration points. The method employs a ...
Added: October 19, 2026
Vorontsova T., М.: Академия, 2025.
The textbook has been prepared in accordance with the requirements of the federal state educational standards for secondary vocational education and is intended for studying the professional modules “Information Security in Information and Telecommunication Systems and Networks Using Software and Hardware‑Software Tools, Including Cryptographic Protection Tools” and “Information Security in Automated Systems Using Software and ...
Added: October 19, 2026
Vasilii A. Gromov, Dang Q. N., Asel S. Erbolova, Complexity 2025 Vol. 2025 No. 1 Article 9659172
The present paper employs topological data analysis methods to reveal ‘holes’ (stable persistent homologies) in the semantic spaces of words, bigrams, and trigrams of the English and Russian languages, and to ascertain their boundaries. Furthermore, the paper selects those holes that belong to the large‐scale (coarse‐grained) structure of the language that are not just local ...
Added: November 11, 2025
Абрамов А. С., Chernyshev V. L., Mikhaylets E. et al., / Series Social Science Research Network "Social Science Research Network". 2025.
Computer vision is one of the most relevant modern research areas with broad practical applications. However, traditional solutions based on deep learning have signicant limitations and can be misleading. Topological data analysis, on the other hand, is a modern approach to solving similar problems using mathematically deterministic methods of algebraic topology that reduce the risk ...
Added: September 23, 2025
Vallverdú J., Alshanskaia E., BioNanoScience 2025 Vol. 15 Article 406
Artificial intelligence (AI) systems have predominantly mirrored neurotypical brain architectures (NBA), optimizing for efficiency, predictability, and standardized cognitive patterns. However, non-neurotypical brains (NNB) exhibit unique neurochemical, hormonal, and functional mechanisms that underpin divergent thinking, creativity, and alternative problem-solving strategies. Drawing from evolutionary biology, we emphasize how neurodiversity serves as a critical mechanism for adaptability, survival, ...
Added: June 14, 2025
Kudrjashov S., Karpik O., Klyshinskiy E., , in: Analysis of Images, Social Networks and Texts, 12th International Conference, AIST 2024, Bishkek, Kyrgyzstan, October 17–19, 2024, Revised Selected PapersVol. 15419.: Springer, 2024. P. 120–130.
Added: May 29, 2025
Sergei Kudriashov, Veronika Zykova, Stepanova A. et al., , in: Advances in Neural Computation, Machine Learning, and Cognitive Research VIII, Selected Papers from the XXVI International Conference on Neuroinformatics, October 21-25, 2024, Moscow, RussiaVol. VIII.: Cham: Springer, 2024. P. 13–22.
The interpretation of deep learning models is a rapidly growing field,
with particular interest in language models. There are various approaches to this
task, including training simpler models to replicate neural network predictions and
analyzing the latent space of the model. The latter method allows us to not only
identify patterns in the model’s decision-making process, but also understand ...
Added: October 24, 2024
Vasilii A. Gromov, Nikita S. Borodin, Asel S. Yerbolova, Complexity 2024 Vol. 2024 No. 1 Article 8863360
Te present paper introduces a novel object of study, a language fractal structure; we hypothesize that a set of embeddings of all n-grams of a natural language constitutes a representative sample of this fractal set. (We use the term Hailonakea to refer to the sum total of all language fractal structures, over all n). Te ...
Added: June 29, 2024
Cherniavskii D., Tulchinskii E., Mikhailov V. et al., , in: Findings of the Association for Computational Linguistics: EMNLP 2022.: Association for Computational Linguistics, 2022. Ch. 7 P. 88–107.
Added: February 17, 2023
Sorokin K., Ayzenberg A., Анохин К. В. et al., / Series Computer Science "arxiv.org". 2022.
In present paper we test different approaches to reconstructing the topology of the physical space from neural activity data in A1 fields of mice brains, in particular, having a Cognitome-focused approach in mind. Animals were placed in different new environments and discovered them while their physical and neural activity was recorded. We discuss possible approaches ...
Added: November 17, 2022
Magai German, Ayzenberg A., / Series CS "https://arxiv.org/". 2022.
Despite significant advances in the field of deep learning in applications to various fields, explaining the inner processes of deep learning models remains an important and open question. The purpose of this article is to describe and substantiate the geometric and topological view of the learning process of neural networks. Our attention is focused on ...
Added: November 14, 2022