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Based on a systematic review of convolutional neural networks (CNN), this study explores the efficacy of small imaging sensors in monitoring the real-time presence of cyanotoxins and hazardous contaminants in urban ecosystems. To develop a machine learning-based CNN, this study first investigated the relationships between the prevalence of hazardous algal blooms (HABs) and faecal indicator bacteria (FIB) in waterways and aquifers of certain semi-arid zones of Sri Lanka, Sweden and New York (United States). By incorporating a popularly known AbspectroscoPY framework to effectively process the spectrophotometric data of the obtained samples, the formulation subsequently reveals strong positive correlations between FIB coliforms and nutrient loads (particularly nitrate and phosphate). A corroborative association with the incidence of chronic kidney disease of uncertain aetiology (CKDu) among the residents of the studied regions further affirms the reliability of the methodology. These findings underline the need for policymakers to consider the geographical and land-use traits of urban habitats in strategies aimed at reducing water-borne health hazards. [ABSTRACT FROM AUTHOR]

The spread of infectious diseases such as COVID-19 depends on complex fluid dynamics interactions between pathogens and fluid phases, including individual droplets and multiphase clouds. Understanding these interactions is crucial for predicting and controlling disease spread. This applies to human and animal exhalations, such as coughs and sneezes, as well as bursting bubbles that create micron-sized droplets in various indoor and outdoor environments. By exploring case studies in this regard, this study examines the emerging field of fluid dynamics in disease transmission, focusing on multiphase flows, interfacial flows, turbulence, pathogens, human traffic, aerosol transmission, ventilation, and breathing microenvironments. These results indicate that increased ventilation rates and local ventilation methods can effectively reduce the concentration of SARS-CoV-2-laden aerosols in the immediate breathing spaces between individuals. In a displacement-ventilated room, both neutral and unstable conditions were more effective in removing breathed SARS-CoV-2-laden aerosols from the air, regardless of the presence of test subjects. However, stable conditions may increase the risk of infection in individuals living in confined spaces. Thus, the findings of this study are useful for providing practical guidance for managing the spread of airborne infections. [ABSTRACT FROM AUTHOR]

Electrical resistivity of commercially produced plain carbon manganese steel has been experimentally measured at room temperature (28–30°C) using four-probe method. Resulting data were used to generate both regression based and artificial neural network-based models for prediction of electrical resistivity from the chemical composition of steel. It was found that both models were capable of predicting the resistivity within ±5% error band. Analysis of data also indicated carbon to be the most influential element to increase resistivity followed by manganese and silicon. A comprehensive literature review indicates no such advanced resistivity prediction model is available in the public literature for commercially produced steel with wide variation in carbon content (0.03 0.85 wt-%), manganese content (0.35–1.50 wt-%) and silicon content (0.015–0.90 wt-%). [ABSTRACT FROM AUTHOR]

It was attempted to produce galvannealed dual-phase (DP) steel through a commercial continuous galvanizing line (CGL). The main challenge was to form the DP microstructure even with the slow cooling rate after annealing in the CGL. A two-pronged approach was adopted for this, viz. design of the steel chemistry with calculations and optimization of the CGL parameters with simulation using Gleeble-3800 thermomechanical simulator. The steel thus produced in CGL revealed ferrite and 18 ± 2% martensite microstructure, with tensile strength exceeding 600 MPa and 24% total elongation along with good formability. Weldability study using resistance spot welding indicated the possibility of achieving sound joint with a 4-kA width in weld time-current lobe despite the high carbon equivalence. [ABSTRACT FROM AUTHOR]

Conventional testing of fracture toughness measurement for thin metallic sheets is not possible owing to the large plastic zone ahead of the crack tip. Hence, the critical-crack tip opening angle $$(\hbox {CTOA}_\mathrm{c})$$ has been considered to be the key parameter to evaluate resistance of a thin sheet against stable crack propagation. In the present work, attempt has been made to measure the $$\hbox {CTOA}_\mathrm{c}$$ of interstitial free high strength steel (IFHS) with 1 mm thickness using compact tension C(T) specimen. A high speed camera has been used for monitoring and imaging the progress of the crack length and crack tip angle during loading. The CTOA $$_\mathrm{c}$$ measured from these photographs found to be $$12^{\circ }\,\pm \,1.5^{\circ }$$ . In these experiments, the crack tip velocity was also varied from 1.9 to 960 mm/min and no changes in the $$\hbox {CTOA}_\mathrm{c}$$ value were observed. The high ductility of IFHS steel along with prevailing plane stress condition might be the reason of appreciably large $$\hbox {CTOA}_\mathrm{c}$$ value. [ABSTRACT FROM AUTHOR]