Article
Physics, Multidisciplinary
Pierre A. Haas, Raymond E. Goldstein
Summary: The diffusive threshold for true Turing instabilities in reaction-diffusion systems may be lower for N > 2, as shown by analysis of random matrices describing the dynamics. As N increases, the diffusive threshold becomes more likely to be smaller and physical, with many-species instabilities unable to be described by reduced models with fewer diffusing species in most cases.
PHYSICAL REVIEW LETTERS
(2021)
Article
Biophysics
Jeremy B. A. Green
Summary: Biophysical modeling of development began with Alan Turing's radical but powerful two-morphogen reaction-diffusion model, which has been validated at the molecular level in various systems. The precision and robustness of reaction-diffusion patterning, despite being dependent on boundary conditions, continue to be active areas of investigation in developmental biology.
BIOPHYSICAL JOURNAL
(2021)
Review
Cell Biology
Thurston C. Lacalli
Summary: This article provides a brief account of Turing's ideas on biological pattern and their significance in biology. Periodic patterns, especially 2D arrays of oriented stripes, play a crucial role in investigating developmental pattern. Turing's theory emphasizes the concept of pattern arising from selective amplification of spatial components hidden in random disorder. Understanding the nature of fluctuations, the location of the amplifier, and the timescale of selective amplification is essential in analyzing biological examples. The article also discusses the potential application of Turing's ideas in the complexities of brain development and consciousness, suggesting that neuroscience could be the most important field for further extension of his theory.
FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY
(2022)
Review
Behavioral Sciences
Damian G. Kelty-Stephen, Madhur Mangalam
Summary: Turing's metaphor of the mind and brain as a computer has inspired decades of empirical investigation. His concept of cascade instability offers a geometric framework driven by power laws and can be studied using multifractal formalism and multiscale probability density function analysis. Research reveals the characteristics and consequences of cascade instability on perception, action, and cognition.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
(2022)
Article
Chemistry, Multidisciplinary
Mohammed Almijalli, Moustafa Ibrahim, Ali Saad, Mazen Saad
Summary: This paper focuses on the chemotaxis model for drug delivery purposes, investigating the pattern formation for a volume-filling with nonlinear diffusive terms. The proposed mathematical model describes the interaction between cell density and chemoattractant concentration, analyzed using Turing's principle and linear stability analysis. Numerical results demonstrate promising progress in understanding the process of controlling and designing targeted drug delivery.
APPLIED SCIENCES-BASEL
(2021)
Article
Physics, Multidisciplinary
Ting Li, Yihong Li, Yongxin Zhang, Yunfei Wang, Xiao-Feng Luo
Summary: This paper presents a possible method for model selection based on Turing's diffusive thresholds of a spatial epidemic model. The region between the inherent and practical diffusive thresholds has both realistic and mathematical significance. Our approach may offer a new insight into the selection of spatial epidemic models.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2023)
Editorial Material
Multidisciplinary Sciences
Andrew L. Krause, Eamonn A. Gaffney, Philip K. Maini, Vaclav Klika
Summary: Elucidating pattern forming processes is a crucial issue in physical, chemical, and biological sciences. Turing's theory on spatial patterns emerging from homogeneous chemical mixtures has been extensively studied mathematically and experimentally for over half a century. Recent research has pushed the boundaries of Turing's original theory to more realistic and complex settings.
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
(2021)
Article
Engineering, Civil
Xiaocai Zhang, Xiuju Fu, Zhe Xiao, Haiyan Xu, Zheng Qin
Summary: This paper discusses the impact of growing maritime IoT data and traffic volume on driving artificial intelligence studies, particularly focusing on vessel trajectory prediction. It provides an overview of existing approaches, including state-of-the-art deep learning, and outlines future research directions in this field.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Manufacturing
Dimitris Fotakis, Jannik Matuschke, Orestis Papadigenopoulos
Summary: Malleable job scheduling allows jobs to be executed simultaneously on multiple machines, and the processing time depends on the number of allocated machines. This study explores generalizations of malleable job scheduling inspired by standard scheduling on unrelated machines, introducing a general model and presenting polynomial-time algorithms.
JOURNAL OF SCHEDULING
(2023)
Editorial Material
Microbiology
Sicong Lu, Yujia Cai
Summary: Researchers have developed a protein delivery vector resembling a syringe from natural endo-symbiotic bacteria, which shows potential for drug delivery into host cells.
CELL HOST & MICROBE
(2023)
Article
Humanities, Multidisciplinary
Tomas Hauer
Summary: Research on autonomous intelligent systems and evolving AI platforms has raised ethical and legal issues. This study examines current trends and specific ethical problems related to AI, providing recommendations and emphasizing the ethical dimension of AI development and its impact on society.
HUMANITIES & SOCIAL SCIENCES COMMUNICATIONS
(2022)
Article
Physics, Multidisciplinary
Yichen Huang, Joel E. Moore
Summary: We study the representational power of Boltzmann machines in quantum many-body systems and prove that any local tensor network state can be represented by a local neural network. Despite difficulties in representing chiral topological states using local tensor networks, we successfully construct a quasilocal neural network representation for a chiral p-wave superconductor, demonstrating the strength of Boltzmann machines.
PHYSICAL REVIEW LETTERS
(2021)
Article
Computer Science, Information Systems
Wenzhe Liu, Zhuo Su, Li Liu
Summary: The study introduces a novel Random Pixel Difference Convolution (RPDC) method to extract discriminative and diverse facial features for face recognition, facial expression recognition, and race categorization. By efficiently searching RPDC, the S-RaPiDiNet is built and achieves promising and extensive results in experiments.
Article
Multidisciplinary Sciences
Shengzhu Yi, Liu Wang, Zhipeng Chen, Jian Wang, Xingyi Song, Pengfei Liu, Yuanxi Zhang, Qingqing Luo, Lelun Peng, Zhigang Wu, Chuan Fei Guo, Lelun Jiang
Summary: This study proposes a facile fabrication strategy that transforms 2D magnetic sheets into 3D soft magneto-active machines with customized geometries by incorporating origami folding. Based on automated roll-to-roll processing, this approach allows for the high-throughput fabrication of soft magneto-origami machines with a variety of characteristics, showcasing several potential applications.
NATURE COMMUNICATIONS
(2022)
Article
Chemistry, Inorganic & Nuclear
Meng-Meng Lun, Chang-Yuan Su, Qiang-Qiang Jia, Zhi-Xu Zhang, Jie Li, Hai-Feng Lu, Yi Zhang, Da-Wei Fu
Summary: Crown-ether-based molecular rotors, a significant branch of artificial molecular machines, have attracted substantial attention since the 2016 Nobel Prize in Chemistry. However, their optical and electric properties tend to deteriorate with increasing temperature due to dynamic molecular motion. In this study, a molecular rotator is successfully constructed through precise molecular modification strategies, leading to an infrequent phase transition and significant improvement in electric and optical properties.
INORGANIC CHEMISTRY FRONTIERS
(2023)