#Multiscale Modeling

[girlactionfigure]

1 Nobel Prize in Chemistry - The Development of Multiscale Models for Complex Chemical Systems

2 Nobel Prize in Chemistry - Quasiperiodic Crystals

3 Nobel Prize in Chemistry - Decoding the Structure and The Function of The Ribosome

4 Nobel Prize in Economic Sciences - Repeated Games

5 Nobel Prize in Chemistry – Ubiquitin, Deciding the Fate of Defective Proteins in Living Cells

6 Nobel Prize in Economics - Human Judgment and Decision-Making Under Uncertainty

7 Fields Medal Award in Mathematics

8 Turing Award - Machine Reasoning Under Uncertainty

9 Turing Award - Nondeterministic Decision-Making

10 Turing Award - The Development of Interactive Zero-Knowledge Proofs

11 Turing Award - Developing New Tools for Systems Verification

12 Vine Seeds Discovered from The Byzantine Period

13 The World’s Most Ancient Hebrew Inscription

14 Ancient Golden Treasure Found at Foot of Temple Mount

15 Sniffphone - Mobile Disease Diagnostics

16 Discovering the Gene Responsible for Fingerprints Formation

17 Pillcam - For Diagnosing and Monitoring Diseases in The Digestive System

18 Technological Application of The Molecular Recognition and Assembly Mechanisms Behind Degenerative Disorders

19 Exelon – A Drug for The Treatment of Dementia

20 Azilect - Drug for Parkinson’s Disease

21 Nano Ghosts - A “Magic Bullet” For Fighting Cancer

22 Doxil (Caelyx) For Cancer Treatment

23 The Genetics of Hearing

24 Copaxone - Drug for The Treatment of Multiple Sclerosis

25 Preserving the Dead Sea Scrolls

26 Developing the Biotechnologies of Valuable Products from Red Marine Microalgae

27 A New Method for Recruiting Immune Cells to Fight Cancer

28 Study of Bacterial Mechanisms for Coping with Temperature Change

29 Steering with The Bats 30 Transmitting Voice Conversations Via the Internet

31 Rewalk – An Exoskeleton That Enables Paraplegics to Walk Again

32 Intelligent Computer Systems

33 Muon Detectors in The World's Largest Scientific Experiment

34 Renaissance Robot for Spine and Brain Surgery

35 Mobileye Accident Prevention System

36 Firewall for Computer Network Security

37 Waze – Outsmarting Traffic, Together

38 Diskonkey - USB Flash Drive

39 Venμs Environmental Research Satellite

40 Iron Dome – Rocket and Mortar Air Defense System

41 Gridon - Preventing Power Outages in High Voltage Grids

42 The First Israeli Nanosatellite

43 Intel's New Generation Processors

44 Electroink - The World’s First Electronic Ink for Commercial Printing

45 Development of A Commercial Membrane for Desalination

46 Developing Modern Wine from Vines of The Bible

47 New Varieties of Seedless Grapes

48 Long-Keeping Regular and Cherry Tomatoes

49 Adapting Citrus Cultivation to Desert Conditions

50 Rhopalaea Idoneta - A New Ascidian Species from The Gulf of Eilat

51 Life in The Dead Sea - Various Fungi Discovered in The Brine

52 Drip Technology - The Irrigation Method That Revolutionized Agriculture

53 Repair of Heart Tissues from Algae

54 Proof of The Existence of Imaginary Particles, Which Could Be Used in Quantum Computers

55 Flying in Peace with The Birds

56 Self-Organization of Bacteria Colonies Sheds Light on The Behaviour of Cancer Cells

57 The First Israeli Astronaut, Colonel Ilan Ramon

58 Dr. Chaim Weizmann - Scientist and Statesman, The First President of Israel, One of The Founders of The Modern Field of Biotechnology

59 Aaron Aaronsohn Botanist, Agronomist, Entrepreneur, Zionist Leader, and Head of The Nili Underground Organization

60 Albert Einstein - Founding Father of The Theory of Relativity, Co-Founder of the Hebrew University in Jerusalem

61 Maimonides - Doctor and Philosopher

Source

@TheMossadIL

[materialsscienceandengineering]

Study reveals mechanisms of crystal nucleation in glass-ceramics

A research team consisting of NIMS, AGC Inc., and JASRI has observed partial crystallization of a glass—an initial stage in its transformation into a stronger, more heat resistant glass-ceramic. The study is published in the journal NPG Asia Materials. To investigate this crystal nucleation process, the team performed multiscale structural analysis mainly using synchrotron X-rays. Based on this analysis, the team developed a model capable of explaining the crystal nucleation mechanisms within a glass at different spatial scales, from atomic to nano, without contradiction. To obtain a glass-ceramic, it is necessary to synthesize a pristine glass with a composition designed and controlled to precipitate crystals partially through heat treatment. It is believed that in the structure of glass-ceramics, crystal nuclei, which are the seeds of crystals, form within the glass matrix, from which crystal particles grow.

Read more.

[spacetimewithstuartgary]

New insights into an enigmatic form of magnetic reconnection

In magnetic reconnection, adjacent magnetic field lines break and snap together to form new lines. This process converts magnetic energy to both thermal energy, or heat, and kinetic energy, or the acceleration of particles, creating jets of electrons and ions. Magnetic reconnection plays a key role in many outer space events such as solar flares and auroras, as well as in laboratory methods related to nuclear fusion.

Several years ago, observations of Earth's magnetic field by NASA's Magnetospheric Multiscale mission led to the discovery that magnetic reconnection can occur with only electron jets, without also involving the acceleration of ions. These events also have a relatively high reconnection rate, meaning the involved magnetic field lines snap together quickly. Now Cheng‐Yu Fan and colleagues report the results of new simulations that deepen the understanding of these electron-only events.

The researchers applied a computational method known as particle-in-cell simulation to model the behavior of ions and electrons during magnetic reconnection. They ran 12 simulations to explore what factors might underlie electron-only reconnection. The results are published in Geophysical Research Letters.

The simulations revealed that the electron-only status of reconnection occurs when field lines outside of the electron diffusion region do not bend enough, leading to an underdeveloped ion diffusion region. This atypical bending happens in the early stage and may continue throughout the process if the entire system size (the size of the area in which reconnection occurs) is smaller than the radius of the path along which the ions travel.

The team also realized that magnetic reconnection and field line bending may not develop at the same pace. A relatively thin initial current sheet allows the reconnection rate to peak before field lines are fully bent, leading to calculations of high reconnection rates if they are normalized by ion parameters. However, the calculations of the reconnection rate are more typical when they are normalized by electron parameters.

These findings could help clarify the fundamental physics of magnetic reconnection, the authors suggest.

IMAGE: New simulations help to clarify the physics behind a recent discovery made by NASA’s Magnetospheric Multiscale mission spacecraft. Credit: NASA Goddard Space Flight Center

[wetdreamdrops]

Multiscale Bioprinting of Vascularized Models - Amir K. Miri, Akbar Khalilpour, Berivan Cecen, Sushila Maharjan

[drmikewatts]

IEEE Transactions on Fuzzy Systems, Volume 33, Issue 6, June 2025

1) Brain-Inspired Fuzzy Graph Convolution Network for Alzheimer's Disease Diagnosis Based on Imaging Genetics Data

Author(s): Xia-An Bi, Yangjun Huang, Wenzhuo Shen, Zicheng Yang, Yuhua Mao, Luyun Xu, Zhonghua Liu

Pages: 1698 - 1712

2) Adaptive Incremental Broad Learning System Based on Interval Type-2 Fuzzy Set With Automatic Determination of Hyperparameters

Author(s): Haijie Wu, Weiwei Lin, Yuehong Chen, Fang Shi, Wangbo Shen, C. L. Philip Chen

Pages: 1713 - 1725

3) A Novel Reliable Three-Way Multiclassification Model Under Intuitionistic Fuzzy Environment

Author(s): Libo Zhang, Cong Guo, Tianxing Wang, Dun Liu, Huaxiong Li

Pages: 1726 - 1739

4) Guaranteed State Estimation for H−/L∞ Fault Detection of Uncertain Takagi–Sugeno Fuzzy Systems With Unmeasured Nonlinear Consequents

Author(s): Masoud Pourasghar, Anh-Tu Nguyen, Thierry-Marie Guerra

Pages: 1740 - 1752

5) Online Self-Learning Fuzzy Recurrent Stochastic Configuration Networks for Modeling Nonstationary Dynamics

Author(s): Gang Dang, Dianhui Wang

Pages: 1753 - 1766

6) ADMTSK: A High-Dimensional Takagi–Sugeno–Kang Fuzzy System Based on Adaptive Dombi T-Norm

Author(s): Guangdong Xue, Liangjian Hu, Jian Wang, Sergey Ablameyko

Pages: 1767 - 1780

7) Constructing Three-Way Decision With Fuzzy Granular-Ball Rough Sets Based on Uncertainty Invariance

Author(s): Jie Yang, Zhuangzhuang Liu, Guoyin Wang, Qinghua Zhang, Shuyin Xia, Di Wu, Yanmin Liu

Pages: 1781 - 1792

8) TOGA-Based Fuzzy Grey Cognitive Map for Spacecraft Debris Avoidance

Author(s): Chenhui Qin, Yuanshi Liu, Tong Wang, Jianbin Qiu, Min Li

Pages: 1793 - 1802

9) Reinforcement Learning-Based Fault-Tolerant Control for Semiactive Air Suspension Based on Generalized Fuzzy Hysteresis Model

Author(s): Pak Kin Wong, Zhijiang Gao, Jing Zhao

Pages: 1803 - 1814

10) Adaptive Fuzzy Attention Inference to Control a Microgrid Under Extreme Fault on Grid Bus

Author(s): Tanvir M. Mahim, A.H.M.A. Rahim, M. Mosaddequr Rahman

Pages: 1815 - 1824

11) Semisupervised Feature Selection With Multiscale Fuzzy Information Fusion: From Both Global and Local Perspectives

Author(s): Nan Zhou, Shujiao Liao, Hongmei Chen, Weiping Ding, Yaqian Lu

Pages: 1825 - 1839

12) Fuzzy Domain Adaptation From Heterogeneous Source Teacher Models

Author(s): Keqiuyin Li, Jie Lu, Hua Zuo, Guangquan Zhang

Pages: 1840 - 1852

13) Differentially Private Distributed Nash Equilibrium Seeking for Aggregative Games With Linear Convergence

Author(s): Ying Chen, Qian Ma, Peng Jin, Shengyuan Xu

Pages: 1853 - 1863

14) Robust Divide-and-Conquer Multiple Importance Kalman Filtering via Fuzzy Measure for Multipassive-Sensor Target Tracking

Author(s): Hongwei Zhang

Pages: 1864 - 1875

15) Fully Informed Fuzzy Logic System Assisted Adaptive Differential Evolution Algorithm for Noisy Optimization

Author(s): Sheng Xin Zhang, Yu Hong Liu, Xin Rou Hu, Li Ming Zheng, Shao Yong Zheng

Pages: 1876 - 1888

16) Impulsive Control of Nonlinear Multiagent Systems: A Hybrid Fuzzy Adaptive and Event-Triggered Strategy

Author(s): Fang Han, Hai Jin

Pages: 1889 - 1898

17) Uncertainty-Aware Superpoint Graph Transformer for Weakly Supervised 3-D Semantic Segmentation

Author(s): Yan Fan, Yu Wang, Pengfei Zhu, Le Hui, Jin Xie, Qinghua Hu

Pages: 1899 - 1912

18) Observer-Based SMC for Discrete Interval Type-2 Fuzzy Semi-Markov Jump Models

Author(s): Wenhai Qi, Runkun Li, Peng Shi, Guangdeng Zong

Pages: 1913 - 1925

19) Network Security Scheme for Discrete-Time T-S Fuzzy Nonlinear Active Suspension Systems Based on Multiswitching Control Mechanism

Author(s): Jiaming Shen, Yang Liu, Mohammed Chadli

Pages: 1926 - 1936

20) Fuzzy Multivariate Variational Mode Decomposition With Applications in EEG Analysis

Author(s): Hongkai Tang, Xun Yang, Yixuan Yuan, Pierre-Paul Vidal, Danping Wang, Jiuwen Cao, Duanpo Wu

Pages: 1937 - 1948

21) Adaptive Broad Network With Graph-Fuzzy Embedding for Imbalanced Noise Data

Author(s): Wuxing Chen, Kaixiang Yang, Zhiwen Yu, Feiping Nie, C. L. Philip Chen

Pages: 1949 - 1962

22) Average Filtering Error-Based Event-Triggered Fuzzy Filter Design With Adjustable Gains for Networked Control Systems

Author(s): Yingnan Pan, Fan Huang, Tieshan Li, Hak-Keung Lam

Pages: 1963 - 1976

23) Fuzzy and Crisp Gaussian Kernel-Based Co-Clustering With Automatic Width Computation

Author(s): José Nataniel A. de Sá, Marcelo R.P. Ferreira, Francisco de A.T. de Carvalho

Pages: 1977 - 1991

24) A Biselection Method Based on Consistent Matrix for Large-Scale Datasets

Author(s): Jinsheng Quan, Fengcai Qiao, Tian Yang, Shuo Shen, Yuhua Qian

Pages: 1992 - 2005

25) Nash Equilibrium Solutions for Switched Nonlinear Systems: A Fuzzy-Based Dynamic Game Method

Author(s): Yan Zhang, Zhengrong Xiang

Pages: 2006 - 2015

26) Active Domain Adaptation Based on Probabilistic Fuzzy C-Means Clustering for Pancreatic Tumor Segmentation

Author(s): Chendong Qin, Yongxiong Wang, Fubin Zeng, Jiapeng Zhang, Yangsen Cao, Xiaolan Yin, Shuai Huang, Di Chen, Huojun Zhang, Zhiyong Ju

Pages: 2016 - 2026

[paul-delsart]

The EL4DEV program by Paul Elvere DELSART

The EL4DEV program, created and directed by Paul Elvere DELSART, is a comprehensive, multidisciplinary, and transnational initiative aimed at reshaping the foundations of human civilization. It is not a conventional development program or institutional reform project, but rather an alternative societal operating system, designed to address systemic dysfunctions across ecological, political, educational, technological, diplomatic, and cultural domains. EL4DEV stands for Elvere for Development, encapsulating its foundational ambition. It represents a fusion of ethical governance, cybernetic systems thinking, participatory engineering, and utopian yet actionable vision, with the goal of catalyzing the emergence of a new planetary civilization rooted in cooperation, balance, and regeneration.

At its core, the EL4DEV program functions as a multiscale and multi-actor engineering framework, one that orchestrates interactions among municipalities, citizens, independent researchers, artists, educators, engineers, and international institutions. It is designed to produce collective intelligence, territorial resilience, and sustainable innovation through the coordination of diverse disciplines and stakeholders. The program does not follow a linear top-down logic; instead, it is built upon the principle of distributed architecture and complex systems theory, where self-organizing local nodes - such as municipalities or community groups - interact through structured feedback mechanisms to produce emergent outcomes at regional, continental, and global levels.

Functionally, EL4DEV is composed of several interlinked subprograms, each with a specific thematic and operational focus, yet all integrated into a larger holistic model. Among these subprograms are "The Municipalities Counter-Attack", which empowers small localities to collectively invest in and co-manage infrastructure projects, and the development of LE PAPILLON SOURCE agroclimatic cities, which serve as ecological, educational, and symbolic centers of the new civilization. These infrastructures are equipped with advanced systems such as the Vegetal Calderas, Bioclimatic Corridors, and Flying Rivers, which together form a climate-engineering and territorial regeneration ecosystem.

The program is animated and coordinated through the Big Smart Data EL4DEV platform, a cybernetic and participatory information system that collects, analyzes, and models data from multiple territories. This platform allows all actors to access territorial intelligence, evaluate progress based on new indicators - such as geo-societal and geo-intellectual density - and participate in decentralized decision-making processes. It enables the real-time co-evolution of all EL4DEV components, ensuring adaptability, responsiveness, and continuous learning across the system.

A unique and defining characteristic of EL4DEV is its integration of immersive fiction and symbolic narrative as both motivational and cognitive tools. The entire program is embedded in the transmedia fictional universe of the Green Empire of the East and the West, in which Paul Elvere DELSART assumes the symbolic role of the Green Emperor of the East and the West. This narrative is not separate from the program’s technical operations; rather, it is a strategic medium for engaging the imagination of participants, giving meaning to their involvement, and anchoring abstract concepts in emotionally resonant stories. Through this fusion of reality and fiction - what Paul Elvere DELSART terms Reality-Fiction - the program becomes more than a governance tool; it becomes a cultural, spiritual, and educational movement.

EL4DEV’s governance model is deliberately decentralized and participatory, rejecting centralized technocratic control in favor of distributed sovereignty and ethical collaboration. Territories and citizens are invited to co-design their own development pathways, aligned with the overarching principles of the program but tailored to local needs, resources, and cultures. This approach fosters autonomy, ownership, and creativity, while still maintaining global coherence through shared infrastructure, values, and strategic coordination. In doing so, EL4DEV acts as both a scaffold for territorial innovation and a diplomatic bridge among nations and cultures.

The program also has a strong educational and philosophical dimension. It redefines education as a lifelong, transdisciplinary, and experiential process embedded in everyday life and community. The infrastructures built under EL4DEV are conceived as civic academies, where people of all ages engage in learning that spans ethics, environmental science, cooperative economics, cybernetics, social engineering, and symbolic literacy. This educational component ensures that the technical transformation of territories is matched by an equally profound transformation of consciousness and behavior.

Economically, the program is financed through cooperative investment models involving public and private actors. It creates alternative revenue streams through educational tourism, ecological engineering, agroecology, and cultural production. These economic mechanisms are designed to break dependence on centralized funding, encourage local entrepreneurship, and reinvest profits into community development and ecological restoration.

In terms of international strategy, EL4DEV proposes the creation of Societal Political Unions - new forms of transnational cooperation based not on geopolitical competition or economic dominance, but on cultural convergence, ethical alignment, and joint participation in territorial projects. These unions, such as the Mediterranean Societal Union or the African Societal Union, function as post-globalist alliances that seek to redefine sovereignty as a shared planetary responsibility.

In conclusion, the EL4DEV program is an unparalleled multidisciplinary initiative that merges systemic innovation, ethical philosophy, territorial regeneration, narrative strategy, and participatory governance into a unified, operational framework. It is a planetary-scale response to the crises of modernity, offering a comprehensive and integrative model for building a new world - not by reforming the old one, but by prototyping a radically different and profoundly human civilization. Its function is not only to coordinate action, but to elevate consciousness, empower communities, and initiate a civilizational renaissance grounded in cooperation, beauty, and planetary care.

Find more information

Boards (French and English)

Beacons (English)

LinkTree (all my blogs in French, English and Spanish)

My books (in French, English and Spanish)

[entomoblog]

Multiscale modelling of European beech decline: the role of interannual climate variability and local environmental factors | European Journal of Forest Research

See on Scoop.it - EntomoNews

Fagus sylvatica L. is a main forest tree species in Europe but has been subjected to massive decline events over the last decades. This phenomenon has been mainly attributed to the increase in drought frequency and intensity, but it is unclear how the local specificities in stand structure, climatic, soil and topographic conditions interact, and if statistical models are able to capture the high spatial and temporal variability in tree decline. To address this challenge, we measured 5380 Fagus sylvatica trees from 308 plots distributed in four regions of France with contrasting environmental conditions, and designed models predicting decline at both regional and national scales. These models aimed at assessing the percentage of stems by plot with at least 50% crown biomass loss based on 229 dendrometric, topographic, soil and climatic variables.The climatic factors explained most of the variability in stand decline, especially the interannual climate variability from the 30-years mean in maximal temperature and in hydric deficit. Regional models were the most efficient in predicting beech decline in their calibration areas (Q2 Stone-Geisser coefficient varied from 0.26 to 0.42) as they better consider the local environmental factors. They were less effective in the other regions, and the national model was an acceptable compromise on a larger scale. These statistical models provide valuable insights for forest managers and could be improved through a more detailed temporal stand monitoring to control the effects of management and decline dynamics.

  ------

via LinkedIn, 06.05.2025

  🌳 𝐄𝐭 𝐬𝐢 𝐥𝐞𝐬 𝐟𝐨𝐫𝐞̂𝐭𝐬 𝐝𝐞́𝐜𝐥𝐢𝐧𝐚𝐢𝐞𝐧𝐭 𝐚𝐮 𝐜œ𝐮𝐫 𝐦𝐞̂𝐦𝐞 𝐝𝐞 𝐥𝐞𝐮𝐫 𝐧𝐢𝐜𝐡𝐞 𝐜𝐥𝐢𝐦𝐚𝐭𝐢𝐪𝐮𝐞 ? Nous venons de publier une étude sur le dépérissement du hêtre en France, avec l’appui de l’hashtag#INRAe et hashtag#Aix-Marseille Université — et les résultats risquent de vous surprendre ou pas 😉 :

📍 5380 arbres analysés sur 308 placettes dans 4 régions 📊 +200 variables testées : climat, sol, topographie, sylviculture 🔎 Objectif : modéliser le % d’arbres fortement dépérissants (déficit foliaire ≥ 50 %) 💥 Résultat central : 𝐜𝐞 𝐧𝐞 𝐬𝐨𝐧𝐭 𝐩𝐚𝐬 𝐥𝐞𝐬 𝐜𝐨𝐧𝐝𝐢𝐭𝐢𝐨𝐧𝐬 𝐦𝐨𝐲𝐞𝐧𝐧𝐞𝐬 𝐪𝐮𝐢 𝐞𝐱𝐩𝐥𝐢𝐪𝐮𝐞𝐧𝐭 𝐥𝐞 𝐝𝐞́𝐩𝐞́𝐫𝐢𝐬𝐬𝐞𝐦𝐞𝐧𝐭, 𝐦𝐚𝐢𝐬 𝐛𝐢𝐞𝐧 𝐥𝐞𝐬 𝐚̀-𝐜𝐨𝐮𝐩𝐬 𝐜𝐥𝐢𝐦𝐚𝐭𝐢𝐪𝐮𝐞𝐬 𝐞𝐱𝐭𝐫𝐞̂𝐦𝐞𝐬 (sécheresses, canicules, anomalies répétées).💥 Leurs impacts peuvent être aggravés ou atténués selon les conditions locales (sol, topographie, gestion forestière). Et le plus frappant 👇 🌡️ 𝐋𝐞𝐬 𝐝𝐞́𝐩𝐞́𝐫𝐢𝐬𝐬𝐞𝐦𝐞𝐧𝐭𝐬 𝐭𝐨𝐮𝐜𝐡𝐞𝐧𝐭 𝐥𝐞 𝐜œ𝐮𝐫 𝐦𝐞̂𝐦𝐞 𝐝𝐞 𝐥𝐚 𝐧𝐢𝐜𝐡𝐞 𝐜𝐥𝐢𝐦𝐚𝐭𝐢𝐪𝐮𝐞 𝐝𝐮 𝐡𝐞̂𝐭𝐫𝐞, dans des zones historiquement favorables. Ce type de résultat n’est pas nouveau. Manion (1981), le fondateur de la spirale des dépérissements écrivait : “𝐼𝑡 𝑖𝑠 𝑖𝑛𝑡𝑒𝑟𝑒𝑠𝑡𝑖𝑛𝑔 𝑡ℎ𝑎𝑡 𝑑𝑒𝑐𝑙𝑖𝑛𝑒𝑠 𝑜𝑐𝑐𝑢𝑟 ���𝑒𝑙𝑙 𝑤𝑖𝑡ℎ𝑖𝑛 𝑡ℎ𝑒 𝑛𝑎𝑡𝑢𝑟𝑎𝑙 𝑔𝑒𝑜𝑔𝑟𝑎𝑝ℎ𝑖𝑐 𝑟𝑎𝑛𝑔𝑒 𝑜𝑓 𝑡ℎ𝑒 𝑠𝑝𝑒𝑐𝑖𝑒𝑠 𝑎𝑛𝑑 𝑛𝑜𝑡 𝑜𝑛 𝑡ℎ𝑒 𝑝𝑒𝑟𝑖𝑝ℎ𝑒𝑟𝑦 𝑜𝑓 𝑡ℎ𝑒 𝑔𝑒𝑜𝑔𝑟𝑎𝑝ℎ𝑖𝑐𝑎𝑙 𝑟𝑎𝑛𝑔𝑒.” 📌 Avec le changement climatique, les événements extrêmes frappent en réalité des arbres non préparés physiologiquement à de tels stress. 📈 Autre enseignement fort : Les modèles régionaux sont plus performants que le modèle national, mais deviennent imprécis hors de leur zone de construction. La transférabilité spatiale a aussi ses limites 😜.

  Jean Lemaire

  ------

NDÉ

L'étude

  Multiscale modelling of European beech decline: the role of interannual climate variability and local environmental factors | European Journal of Forest Research, 05.05.2025 https://link.springer.com/article/10.1007/s10342-025-01767-4

[brookszd]

LTXV 13B open-source video model

LTXV 13B AI Video Generation, A groundbreaking 13B-parameter AI model by Lightricks, revolutionizing video creation with unprecedented speed and quality. LTXV-13B is available under the LTXV Open Weights License. The model and its tools are open source, allowing for community development and customization. 30x faster than comparable models, powered by advanced multiscale rendering technology. The LTXV 13B model builds upon the DiT-based architecture, introducing groundbreaking features like multiscale rendering and improved motion quality. LTXV-13B Video model represents a significant evolution from its predecessor, the LTX Video model, with a notable increase in parameters from 2 billion to 13 billion.

Rapid Video Generation: Produces 5-second, 24 FPS videos at 768x512 resolution in under 4 seconds.

High Video Quality: Utilizes diffusion transformer architecture to ensure smooth motion and eliminate object deformation.

Real-Time Processing: Enables live video generation and instant adjustments for creative flexibility.

Scalability: Supports both short clips and longer, high-quality video projects.

Open-Source Model: Available under OpenRail license on GitHub and Hugging Face, promoting community-driven development.

Hardware Efficiency: Runs effectively on common GPUs, including consumer-grade cards like RTX 4090.

ComfyUI Integration: Comes with native support and custom nodes for seamless use within ComfyUI.

Google Cloud Integration: Leverages cloud infrastructure for efficient data processing and scalability.

[chorusfm]

Spiritbox’s Mike Stringer Launches Signature Guitar

Mike Stringer, guitarist of Spiritbox, has officially launched his first-ever signature guitar line in partnership with Aristides. Mike Stringer, guitarist of two-time GRAMMY-nominated band Spiritbox, has officially launched his first-ever signature guitar line in partnership with Aristides. Introduced at NAMM 2025, The STX Collection is the culmination of nearly a decade of collaboration between Stringer and Aristides, offering a sleek, ergonomic offset design available in 6, 7, and 8-string configurations, with both standard and multiscale options. The launch comes at the heels of Spiritbox’s latest album, Tsunami Sea, which debuted at #1 on the Billboard Top Hard Rock Albums chart. To showcase The STX Collection in action, Stringer has released a playthrough video of “Perfect Soul,” one of the album’s standout tracks, currently at #15 on Billboard’s Mainstream Rock Airplay chart - WATCH. “I first started playing Aristides guitars in 2015, and their instruments have shaped the overall sound of my band, our recordings, and my playing,” shares Stringer. “Today, after 10 years of playing their guitars, I am very proud and honoured to announce the launch of the first ever Aristides artist collaboration line: The STX series. An offset model available in 6, 7, and 8 string configurations, focused on ergonomics, quality and precision. My entire career, I’ve been trying to find the instrument that covers all the ground I need, and we’ve accomplished this with the STX. I cannot wait for guitarists to get their hands on one!”  Pascal Langelaar, CEO of Aristides Instruments adds, “Mike has been a key part of Aristides for over a decade. His ideas and feedback have shaped many of our innovations, and it’s a proud moment for us to launch our very first official artist collaboration line of guitars with someone who’s been such an important part of our journey.”  Designed for versatility, The STX Collection consists of five distinct Aristides models that merge Stringer’s technical demands with Aristides’ innovative craftsmanship. Each guitar is fully compatible with flagship Aristides features, including multiscale EverTune and tremolo bridge options, while introducing new, exclusive design elements unique to the STX line. Engineered for all playing styles, these guitars are built to inspire musicians across genres. A defining feature of The STX Collection is its ergonomic offset body shape, created for comfort and extended fretboard access in both seated and standing positions. The collection also offers customizable options such as Spiritbox-themed inlays, a pickguard choice, a newly designed in-line headstock for straight scale models, and a custom neck profile on the STX6. More than just a signature model, The STX Collection is a true collaboration—each guitar is a blank canvas for players to make their own. With over 200 finish options, a wide range of pickup configurations, personalized setups, and Aristides’ premium custom bridges, The STX Collection ensures every guitarist can build their dream instrument. --- Please consider becoming a member so we can keep bringing you stories like this one. ◎ https://chorus.fm/news/spiritboxs-mike-stringer-launches-signature-guitar/

[jobrxiv]

Postdoc Computational Microbiome Ecology for Fermentation Technologies Technical University of Delft Join a 3-year postdoc to advance a multiscale modeling framework tailored to decipher the ecological dynamics shaping fermentative microbiomes. See the full job description on jobRxiv: https://jobrxiv.org/job/technical-university-of-delft-27778-postdoc-computational-microbiome-ecology-for-fermentation-technologies/?feed_id=91589 #biocomputation #bioprocess_development #computational_metabolomics #Environmental_Biotechnology #fermentation #ScienceJobs #hiring #research

[ai-news]

TL;DR: GenBio AI is advancing biology with Generative AI by developing AI-Driven Digital Organisms (AIDO). The AIDO system integrates multiscale foundation models for DNA, RNA, proteins, and cellular systems, allowing researchers to simulate, predic #AI #ML #Automation

[materialsscienceandengineering]

Generative model unveils secrets of material disorder

National University of Singapore (NUS) scientists have utilized generative machine learning models to explore the different methods in which atoms between adjacent crystals in a piezoelectric material, which are materials that generate a small electrical voltage upon application of mechanical stress, can experience mismatches. This revelation unveils the pathways through which disorder emerges in such materials. In the realm of materials science, a longstanding question involves understanding if different structural disorders in complex materials serve valuable functions, with a key challenge being the identification of the types of disorder within a particular sample. A research team at NUS addressed this challenge by condensing a wide range of structural disorder in domain boundaries of a piezoelectric material into a small set of simple, multiscale probabilistic rules. With these rules, they created a generative machine learning model that spanned three orders of magnitude in length scales, allowing the study of the material's statistical properties beyond practical measurement limits.

Read more.

[spacetimewithstuartgary]

New study unveils breakthrough in understanding cosmic particle accelerators

Scientists have come a step closer to understanding how collisionless shock waves – found throughout the universe – are able to accelerate particles to extreme speeds.

Scientists have come a step closer to understanding how collisionless shock waves – found throughout the universe – are able to accelerate particles to extreme speeds.

These shock waves are one of nature's most powerful particle accelerators and have long intrigued scientists for the role they play in producing cosmic rays – high-energy particles that travel across vast distances in space.

The research, published today in Nature Communications, combines satellite observations from NASA’s MMS (Magnetospheric Multiscale) and THEMIS/ARTEMIS missions with recent theoretical advancements, offering a comprehensive new model to explain the acceleration of electrons in collisionless shock environments.

The paper, ‘Revealing an Unexpectedly Low Electron Injection Threshold via Reinforced Shock Acceleration’, was written by a team of international academics, led by Dr Savvas Raptis of The Johns Hopkins University Applied Physics Laboratory, in the USA, and in collaboration with Northumbria University’s Dr Ahmad Lalti.

This research addresses a long-standing puzzle in astrophysics – how electrons reach extremely high, or relativistic, energy levels.

For decades, scientists have been trying to answer a crucial question in space physics: What processes allow electrons to be accelerated to relativistic speeds?

The main mechanism to explain acceleration of electrons to relativistic energies is called Fermi acceleration or Diffusive Shock Acceleration (DSA). However, this mechanism requires electrons to be initially energized to a specific threshold energy before getting efficiently accelerated by DSA. Trying to address how electrons achieve this initial energy is known as ‘the injection problem’.

This new study provides key insights into the electron injection problem, showing that electrons can be accelerated to high energies through the interaction of various processes across multiple scales.

Using real-time data from the MMS mission, which measures the interaction of Earth’s magnetosphere with the solar wind, and the THEMIS/ARTEMIS mission, which studies the upstream plasma environment near the Moon, the research team observed a large scale, time dependent (i.e. transient) phenomenon, upstream of Earth's bow shock, on December 17, 2017.

During this event, electrons in Earth’s foreshock region – an area where the solar wind is predisturbed by its interaction with the bow shock – reached unprecedented energy levels, surpassing 500 keV.

This is a striking result given that electrons observed in the foreshock region are typically found at energies ~1 keV.

This research suggests that these high-energy electrons were generated by the complex interplay of multiple acceleration mechanisms, including the interaction of electrons with various plasma waves, transient structures in the foreshock, and Earth's bow shock.

All of those mechanisms act together to accelerate electrons from low energies ~ 1keV up to relativistic energies reaching the observed 500 keV, resulting in a particularly efficient electron acceleration process.

By refining the shock acceleration model, this study provides new insight into the workings of space plasmas and the fundamental processes that govern energy transfer in the universe.

As a result, the research opens new pathways for understanding cosmic ray generation and offers a glimpse into how phenomena within our solar system can guide us to understand astrophysical processes throughout the Universe.

Dr. Raptis believes that studying phenomena across different scales is crucial for understanding nature. “Most of our research focuses on either small-scale effects, like wave-particle interactions, or large-scale properties, like the influence of solar wind,” he says.

“However, as we demonstrated in this work, by combining phenomena across different scales, we were able to observe their interplay that ultimately energize particles in space.”

Dr Ahmad Lalti added: “One of the most effective ways to deepen our understanding of the universe we live in is by using our near-Earth plasma environment as a natural laboratory.

“In this work, we use in-situ observation from MMS and THEMIS/ARTEMIS to show how different fundamental plasma processes at different scales work in concert to energize electrons from low energies up to high relativistic energies.

“Those fundamental processes are not restricted to our solar system and are expected to occur across the universe.

“This makes our proposed framework relevant for better understanding electron acceleration up to cosmic-ray energies at astrophysical structures light-years away from our solar system, such as at other stellar systems, supernovae remnants, and active galactic nuclei.”

TOP IMAGE: Composite image of the Tycho Supernova remnant. Shock waves from such explosive events are believed to be the main drivers behind cosmic rays. Credit Credit: MPIA/NASA/Calar Alto Observatory

CENTRE IMAGE: Illustration of Earth’s bow shock and magnetic field environment. Particles coming from the Sun interact with Earth’s magnetic field forming a shock wave (called bow shock – shown in red). Credit Mark Garlick/Science Photo Library via Getty Images

LOWER IMAGE: MMS measurements showing the absence of 100-500 keV (high-energy) electrons. (B): MMS measurements during an event with energetic electrons. The X-axis (horizontal) shows the time while the Y-axis(vertical)  represents the ratio between the background flux (number of electrons passing through a specific area in a given amount of time)  and the actual observation. A value of 1, as shown on the left plot, indicates no energetic particles, whereas the right panel demonstrates a tenfold increase in energetic electrons. Credit Dr Savvas Raptis and Dr Ahmad Lalti

BOTTOM IMAGE: A series of astrophysical bow shocks to the southeast (lower-left) and northwest (upper-right). Image is taken by NASA’s James Webb Space Telescope. Image shows Herbig-Haro 211 showing the details of the outflow of a young star. Herbig-Haro objects are formed when stellar winds or jets of gas spewing from newborn stars form shock waves. Credits: ESA/Webb, NASA, CSA, Tom Ray (Dublin)

[drmikewatts]

IEEE Transactions on Emerging Topics in Computational Intelligence Volume 9, Issue 3, June 2025

1) An Efficient Sampling Approach to Offspring Generation for Evolutionary Large-Scale Constrained Multi-Objective Optimization

Author(s): Langchun Si, Xingyi Zhang, Yajie Zhang, Shangshang Yang, Ye Tian

Pages: 2080 - 2092

2) Long-Tailed Classification Based on Coarse-Grained Leading Forest and Multi-Center Loss

Author(s): Jinye Yang, Ji Xu, Di Wu, Jianhang Tang, Shaobo Li, Guoyin Wang

Pages: 2093 - 2107

3) Two ZNN-Based Unified SMC Schemes for Finite/Fixed/Preassigned-Time Synchronization of Chaotic Systems

Author(s): Yongjun He, Lin Xiao, Linju Li, Qiuyue Zuo, Yaonan Wang

Pages: 2108 - 2121

4) Solving Multiobjective Combinatorial Optimization via Learning to Improve Method

Author(s): Te Ye, Zizhen Zhang, Qingfu Zhang, Jinbiao Chen, Jiahai Wang

Pages: 2122 - 2136

5) Multi-Objective Integrated Energy-Efficient Scheduling of Distributed Flexible Job Shop and Vehicle Routing by Knowledge-and-Learning-Based Hyper-Heuristics

Author(s): YaPing Fu, ZhengPei Zhang, Min Huang, XiWang Guo, Liang Qi

Pages: 2137 - 2150

6) MTMD: Multi-Scale Temporal Memory Learning and Efficient Debiasing Framework for Stock Trend Forecasting

Author(s): Mingjie Wang, Juanxi Tian, Mingze Zhang, Jianxiong Guo, Weijia Jia

Pages: 2151 - 2163

7) Cross-Scale Fuzzy Holistic Attention Network for Diabetic Retinopathy Grading From Fundus Images

Author(s): Zhijie Lin, Zhaoshui He, Xu Wang, Wenqing Su, Ji Tan, Yamei Deng, Shengli Xie

Pages: 2164 - 2178

8) Leveraging Neural Networks and Calibration Measures for Confident Feature Selection

Author(s): Hassan Gharoun, Navid Yazdanjue, Mohammad Sadegh Khorshidi, Fang Chen, Amir H. Gandomi

Pages: 2179 - 2193

9) Modeling of Spiking Neural Network With Optimal Hidden Layer via Spatiotemporal Orthogonal Encoding for Patterns Recognition

Author(s): Zenan Huang, Yinghui Chang, Weikang Wu, Chenhui Zhao, Hongyan Luo, Shan He, Donghui Guo

Pages: 2194 - 2207

10) A Learning-Based Two-Stage Multi-Thread Iterated Greedy Algorithm for Co-Scheduling of Distributed Factories and Automated Guided Vehicles With Sequence-Dependent Setup Times

Author(s): Zijiang Liu, Hongyan Sang, Biao Zhang, Leilei Meng, Tao Meng

Pages: 2208 - 2218

11) A Novel Hierarchical Generative Model for Semi-Supervised Semantic Segmentation of Biomedical Images

Author(s): Lu Chai, Zidong Wang, Yuheng Shao, Qinyuan Liu

Pages: 2219 - 2231

12) PurifyFL: Non-Interactive Privacy-Preserving Federated Learning Against Poisoning Attacks Based on Single Server

Author(s): Yanli Ren, Zhe Yang, Guorui Feng, Xinpeng Zhang

Pages: 2232 - 2243

13) Learning Uniform Latent Representation via Alternating Adversarial Network for Multi-View Clustering

Author(s): Yue Zhang, Weitian Huang, Xiaoxue Zhang, Sirui Yang, Fa Zhang, Xin Gao, Hongmin Cai

Pages: 2244 - 2255

14) Harnessing the Power of Knowledge Graphs to Improve Causal Discovery

Author(s): Taiyu Ban, Xiangyu Wang, Lyuzhou Chen, Derui Lyu, Xi Fan, Huanhuan Chen

Pages: 2256 - 2268

15) MSDT: Multiscale Diffusion Transformer for Multimodality Image Fusion

Author(s): Caifeng Xia, Hongwei Gao, Wei Yang, Jiahui Yu

Pages: 2269 - 2283

16) Adaptive Feature Transfer for Light Field Super-Resolution With Hybrid Lenses

Author(s): Gaosheng Liu, Huanjing Yue, Xin Luo, Jingyu Yang

Pages: 2284 - 2295

17) Broad Graph Attention Network With Multiple Kernel Mechanism

Author(s): Qingwang Wang, Pengcheng Jin, Hao Xiong, Yuhang Wu, Xu Lin, Tao Shen, Jiangbo Huang, Jun Cheng, Yanfeng Gu

Pages: 2296 - 2307

18) Dual-Branch Semantic Enhancement Network Joint With Iterative Self-Matching Training Strategy for Semi-Supervised Semantic Segmentation

Author(s): Feng Xiao, Ruyu Liu, Xu Cheng, Haoyu Zhang, Jianhua Zhang, Yaochu Jin

Pages: 2308 - 2320

19) CVRSF-Net: Image Emotion Recognition by Combining Visual Relationship Features and Scene Features

Author(s): Yutong Luo, Xinyue Zhong, Jialan Xie, Guangyuan Liu

Pages: 2321 - 2333

20) Generative Network Correction to Promote Incremental Learning

Author(s): Justin Leo, Jugal Kalita

Pages: 2334 - 2343

21) A Cross-Domain Recommendation Model Based on Asymmetric Vertical Federated Learning and Heterogeneous Representation

Author(s): Wanjing Zhao, Yunpeng Xiao, Tun Li, Rong Wang, Qian Li, Guoyin Wang

Pages: 2344 - 2358

22) HGRL-S: Towards Heterogeneous Graph Representation Learning With Optimized Structures

Author(s): Shanfeng Wang, Dong Wang, Xiaona Ruan, Xiaolong Fan, Maoguo Gong, He Zhang

Pages: 2359 - 2370

23) Prompt-Based Out-of-Distribution Intent Detection

Author(s): Rudolf Chow, Albert Y. S. Lam

Pages: 2371 - 2382

24) Multi-Graph Contrastive Learning for Community Detection in Multi-Layer Networks

Author(s): Songen Cao, Xiaoyi Lv, Yaxiong Ma, Xiaoke Ma

Pages: 2383 - 2397

25) Observer-Based Event-Triggered Optimal Control for Nonlinear Multiagent Systems With Input Delay via Reinforcement Learning Strategy

Author(s): Xin Wang, Yujie Liao, Lihua Tan, Wei Zhang, Huaqing Li

Pages: 2398 - 2409

26) SODSR: A Three-Stage Small Object Detection via Super-Resolution Using Optimizing Combination

Author(s): Xiaoyong Mei, Kejin Zhang, Changqin Huang, Xiao Chen, Ming Li, Zhao Li, Weiping Ding, Xindong Wu

Pages: 2410 - 2426

27) Toward Automatic Market Making: An Imitative Reinforcement Learning Approach With Predictive Representation Learning

Author(s): Siyuan Li, Yafei Chen, Hui Niu, Jiahao Zheng, Zhouchi Lin, Jian Li, Jian Guo, Zhen Wang

Pages: 2427 - 2439

28) CIGF-Net: Cross-Modality Interaction and Global-Feature Fusion for RGB-T Semantic Segmentation

Author(s): Zhiwei Zhang, Yisha Liu, Weimin Xue, Yan Zhuang

Pages: 2440 - 2451

29) BAUODNET for Class Imbalance Learning in Underwater Object Detection

Author(s): Long Chen, Haohan Yu, Xirui Dong, Yaxin Li, Jialie Shen, Jiangrong Shen, Qi Xu

Pages: 2452 - 2461

30) DFEN: A Dual-Feature Extraction Network-Based Open-Set Domain Adaptation Method for Optical Remote Sensing Image Scene Classification

Author(s): Zhunga Liu, Xinran Ji, Zuowei Zhang, Yimin Fu

Pages: 2462 - 2473

31) Distillation-Based Domain Generalization for Cross-Dataset EEG-Based Emotion Recognition

Author(s): Wei Li, Siyi Wang, Shitong Shao, Kaizhu Huang

Pages: 2474 - 2490

32) NeuronsGym: A Hybrid Framework and Benchmark for Robot Navigation With Sim2Real Policy Learning

Author(s): Haoran Li, Guangzheng Hu, Shasha Liu, Mingjun Ma, Yaran Chen, Dongbin Zhao

Pages: 2491 - 2505

33) Adaptive Constrained IVAMGGMM: Application to Mental Disorders Detection

Author(s): Ali Algumaei, Muhammad Azam, Nizar Bouguila

Pages: 2506 - 2530

34) Visual IoT Sensing Based on Robust Multilabel Discrete Signatures With Self-Topological Regularized Half Quadratic Lifting Functions

Author(s): Bo-Wei Chen, Ying-Hsuan Wu

Pages: 2531 - 2544

35) Heterogeneity-Aware Clustering and Intra-Cluster Uniform Data Sampling for Federated Learning

Author(s): Jian Chen, Peifeng Zhang, Jiahui Chen, Terry Shue Chien Lau

Pages: 2545 - 2556

36) Model-Data Jointly Driven Method for Airborne Particulate Matter Monitoring

Author(s): Ke Gu, Yuchen Liu, Hongyan Liu, Bo Liu, Lai-Kuan Wong, Weisi Lin, Junfei Qiao

Pages: 2557 - 2571

37) Personalized Exercise Group Assembly Using a Two Archive Evolutionary Algorithm

Author(s): Yifei Sun, Yifei Cao, Ziang Wang, Sicheng Hou, Weifeng Gao, Zhi-Hui Zhan

Pages: 2572 - 2583

38) PFPS: Polymerized Feature Panoptic Segmentation Based on Fully Convolutional Networks

Author(s): Shucheng Ji, Xiaochen Yuan, Junqi Bao, Tong Liu, Yang Lian, Guoheng Huang, Guo Zhong

Pages: 2584 - 2596

39) Low-Bit Mixed-Precision Quantization and Acceleration of CNN for FPGA Deployment

Author(s): JianRong Wang, Zhijun He, Hongbo Zhao, Rongke Liu

Pages: 2597 - 2617

40) Bayesian Inference of Hidden Markov Models Through Probabilistic Boolean Operations in Spiking Neuronal Networks

Author(s): Ayan Chakraborty, Saswat Chakrabarti

Pages: 2618 - 2632

[sisiad]

Multiscale mushy layer model for Arctic marginal ice zone dynamics

http://dlvr.it/TCllHh