We present findings in an experiment where we obtain stationary ramified transportation networks in a macroscopic nonbiological system. Our purpose here is to introduce the phenomenology of the experiment. We describe the dynamical formation of the network which consists of three growth stages: (I) strand formation, (II) boundary formation, and (III) geometric expansion. We find that the system forms statistically robust network features, like the number of termini and the number of branch points. We also find that the networks are usually trees, meaning that they lack closed loops; indeed, we find that loops are unstable in the network. Finally, we find that the final topology of the network is sensitive to the initial conditions of the particles, in particular to its geometry.
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http://dx.doi.org/10.1073/pnas.0406025102 | DOI Listing |
Sci Rep
January 2025
School of Environmental Science and Engineering, Yancheng Institute of Technology, Yancheng, 224051, People's Republic of China.
MXenes, as a novel two-dimensional lamellar material, has attracted much attention. However, MXenes lamellar are prone to collapse and stacking under hydrogen bonding and interlayer van der Waals forces, which affects their electrochemical and capacitive deionization performance. A three-dimensional Ni-1,3,5-benzenetricarboxylate/TiCT (Ni-BTC/TiCT) composite electrode material was developed to enhance the electrochemical and capacitive deionization performance.
View Article and Find Full Text PDFNat Mater
January 2025
Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
Cells use 'active' energy-consuming motor and filament protein networks to control micrometre-scale transport and fluid flows. Biological active materials could be used in dynamically programmable devices that achieve spatial and temporal resolution that exceeds current microfluidic technologies. However, reconstituted motor-microtubule systems generate chaotic flows and cannot be directly harnessed for engineering applications.
View Article and Find Full Text PDFEnviron Sci Technol
January 2025
Intelligent Transportation Thrust, Systems Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511455, China.
Integrating mobile monitoring data with street view images (SVIs) holds promise for predicting local air pollution. However, algorithms, sampling strategies, and image quality introduce extra errors due to a lack of reliable references that quantify their effects. To bridge this gap, we employed 314 taxis to monitor NO, NO, PM, and PM, and extracted features from ∼382,000 SVIs at multiple angles (0°, 90°, 180°, 270°) and buffer radii (100-500 m).
View Article and Find Full Text PDFJ Acoust Soc Am
January 2025
Urban Construction Center of Lucheng District of Wenzhou, Wenzhou, 325000, China.
The identification of vibration and reconstruction of sound fields of plate structures are important for understanding the vibroacoustic characteristics of complex structures. This paper presents a data-physics driven (DPD) model integrated with transfer learning (DPDT) for high-precision identification and reconstruction of vibration and noise radiation of plate structures. The model combines the Kirchhoff-Helmholtz integral equation with convolutional neural networks, leveraging physical information to reduce the need for extensive data.
View Article and Find Full Text PDFInt J Surg
January 2025
Department of Orthopedics, the First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
Abstract: To evaluate the safety and efficacy of various surgical treatments for long bone defects. Despite numerous observational studies, randomized controlled trials (RCTs), and meta-analyses, the optimal surgical treatment for long bone defects remains undetermined.
Methods: A network meta-analysis (NMA) was conducted.
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