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Biohybrid Magnetically Driven Microrobots for Sustainable Removal of Micro/Nanoplastics from the Aquatic Environment
(WILEY-V C H VERLAG GMBH, 2024-01-15) Peng, Xia; Urso, Mario; Koláčková, Martina; Húska, Dalibor; Pumera, Martin
The proliferation of micro/nanoplastics derived from the fragmentation of plastic waste released in the environment represents an increasingly alarming issue with adverse implications for aquatic ecosystems worldwide. Conventional approaches for mitigating such contamination are inadequate in removing plastic fragments with exceptionally tiny sizes. Therefore, it is highly urgent to develop efficient strategies to address the threats posed by micro/nanoplastics. Here, biohybrid microrobots, integrating the magnetic properties of Fe3O4 nanoparticles, are investigated for the dynamic removal of micro/nanoplastics from various aquatic environments via high-precision magnetic actuation and reliable electrostatic interactions. After the surface decoration with Fe3O4 nanoparticles, algae cells can achieve precise locomotion and wireless manipulation by regulating an external magnetic field. Taking advantage of this active movement, magnetic algae robots (MARs) display considerable capture and removal efficiencies for micro/nanoplastics in water with extensive application scenarios. The reusability of MARs is also investigated, proving great recyclable performance. The growth and cell viability experiments elucidate that the presence of Fe3O4 nanoparticles may result in hormesis stimulation of algae growth. Such recyclable microrobots with eco-friendly and low-cost characteristics offer an attractive strategy for sustainably tackling micro/nanoplastics pollution. Bioinspired magnetically powered microrobots, based on microalgae cells modified with magnetic nanoparticles, are introduced. Upon being decorated with Fe3O4 nanoparticles, microalgae cells can achieve precise movement and wireless manipulation by controlling an external magnetic field. Leveraging the active mobility, the magnetic algae-robots exhibit substantial efficiency in capturing and removing micro/nanoplastics, offering extensive applicability across various scenarios.image
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Structural Phenomena Introduced by Rotary Swaging: A Review
(MDPI, 2024-01-18) Kunčická, Lenka
Rotary swaging is an industrially applicable intensive plastic deformation method. Due to its versatility, it is popular, especially in the automotive industry. Similar to the well-known methods of severe plastic deformation (SPD), rotary swaging imparts high shear strain into the swaged materials and thus introduces grain refinement down to a very fine, even ultra-fine, level. However, contrary to SPD methods, one of the primary characteristics of which is that they retain the shapes and dimensions of the processed sample, rotary swaging enables the imparting of required shapes and dimensions of workpieces (besides introducing structure refinement and the consequent enhancement of properties and performance). Therefore, under optimized conditions, swaging can be used to process workpieces of virtually any metallic material with theoretically any required dimensions. The main aim of this review is to present the principle of the rotary swaging method and its undeniable advantages. The focus is primarily on assessing its pros and cons by evaluating the imparted microstructures.
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Comparison of Trenchless and Excavation Technologies in the Restoration of a Sewage Network and Their Carbon Footprints
(MDPI, 2024-01-15) Chorazy, Tomáš; Hlavínek, Petr; Raček, Jakub; Pietrucha-Urbanik, Katarzyna; Tchórzewska-Cieślak, Barbara; Keprdová, Šárka; Dufek, Zdeněk
The restoration of aging sewer networks is a fundamental remediation approach with the aim of renewing or improving existing systems. Remediation methods include repair, renovation, and replacement (renewal). The restoration of a sewer network itself can be performed using either excavation or trenchless technologies. While these technologies offer various advantages, they also present disadvantages. The choice of a restoration technology depends on numerous parameters, including economic factors and local conditions (such as the construction of the existing sewage network, available working space, traffic load, and environmental safety restrictions). In addition to the parameters influencing the choice of restoration technology, recent considerations have been given to constraints related to greenhouse gas emissions and the corresponding carbon footprint. Carbon footprint serves as an indicator of the restoration activity’s dependence on fossil fuels, both during implementation and operation. In the 21st century, concerns regarding carbon footprints have rapidly escalated. The reduction in carbon footprints is a crucial objective from both an economic and an ecological point of view. This article specifically addresses the prospects of monitoring the carbon footprint concerning the partial restoration of a sewer network within the historical core of the city of Brno, located in the Czech Republic.
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Calibration of pedestrian ingress model based on CCTV surveillance data using machine learning methods
(Public Library of Science, 2024-01-18) Pálková, Martina; Uhlík, Ondřej; Apeltauer, Tomáš
Machine learning methods and agent-based models enable the optimization of the operation of high capacity facilities. In this paper, we propose a method for automatically extracting and cleaning pedestrian traffic detector data for subsequent calibration of the ingress pedestrian model. The data was obtained from the waiting room traffic of a vaccination center. Walking speed distribution, the number of stops, the distribution of waiting times, and the locations of waiting points were extracted. Of the 9 machine learning algorithms, the random forest model achieved the highest accuracy in classifying valid data and noise. The proposed microscopic calibration allows for more accurate capacity assessment testing, procedural changes testing, and geometric modifications testing in parts of the facility adjacent to the calibrated parts. The results show that the proposed method achieves state-of-the-art performance on a violent-flows dataset. The proposed method has the potential to significantly improve the accuracy and efficiency of input model predictions and optimize the operation of high-capacity facilities.
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Energy gap measurements based on enhanced absorption coefficient calculation from transmittance and reflectance raw data
(Elsevier, 2024-01-18) Allaham, Mohammad Mahmoud; Dallaev, Rashid; Burda, Daniel; Sobola, Dinara; Nebojsa, Alois; Knápek, Alexandr; Mousa, Marwan; Kolařík, Vladimír
The absorption coefficient plays an important role in studying and characterizing semiconducting materials. It is an important parameter to study the mechanism of photons absorption within the structure of the studied material. Thus, it helps to study the several types of charge carrier transport along with the energy band structure and its defects. In literature, a formula was reported to precisely calculate the absorption coefficient from raw data of transmittance and reflectance of electromagnetic radiation. However, the reported formula has several issues limiting its validity in the literature. In this paper, we provide a more mathematically accurate form of this equation to precisely obtain the absorption coefficient from the raw data, by considering the total internal reflection at the different interfaces. Moreover, the equation is tested by simulated data and is applied to study the optical characteristics of a single-component epoxy resin from its transmittance and reflectance raw data.