Rapid urbanization and its associated pollution can affect water quality in mosquito breeding habitats and, as a result, the ecology and control of mosquito vectors. To understand the effects of pollution on mosquito vectors, an accurate assessment of water quality in breeding habitats is needed. Presently, water quality assessment of mosquito breeding habitats is usually based on the measurement of individual physicochemical parameters. However, several parameters are sometimes difficult to interpret or may not give a clear picture of the overall water quality of the breeding habitats, especially when the pollutants are in complex mixtures. This study employed the use of Laser-Induced Fluorescence (LIF) spectroscopy to assess water quality in breeding habitats of Anopheles, Aedes, and Culex mosquitoes in urban areas in Cape Coast, Ghana. The LIF spectra, using a 445-nm diode laser, were measured from field-collected water samples in the laboratory. The LIF spectra showed the presence of dissolved organic matter (DOM) and chlorophyll in the breeding habitats. The DOM and chlorophyll fluorescence signals were normalised by the Raman vibrational signals to determine water quality in each habitat. The overall water quality was better in Aedes breeding habitats than in Anopheles and Culex breeding habitats. The poor water quality in Anopheles and Culex breeding habitats was due to the presence of high fulvic acid and chlorophyll content, which often reflect pollutants from anthropogenic sources. Anopheles and Aedes habitats were made up of mainly An. coluzzii and Ae. aegypti respectively while Culex species were identified to genus level. The results add up to the growing concern about the breeding of Anopheles in polluted habitats. The study demonstrated for the first time the ability of LIF spectroscopy to assess water quality in mosquito breeding habitats.

A method combining laser-induced fluorescence and principal component analysis to detect and discriminate between algal and fungal growth on insulator materials has been studied. Eight fungal cultures and four insulator materials have been analyzed. Multivariate classifications were utilized to characterize the insulator material, and fungal growth could readily be distinguished from a clean surface. The results of the principal component analyses make it possible to distinguish between algae infected, fungi infected, and clean silicone rubber materials. The experiments were performed in the laboratory using a fiber-optic fluorosensor that consisted of a nitrogen laser and an optical multi-channel analyzer system.

This study investigated the pore characterization of polyurethane (PU) foam as a necessary step in water filtration membrane fabrication. Porous material characterization is essential for predicting membrane performance, strength, durability, surface feel, and to understand the transport mechanisms using modeling and simulations. Most existing pore characterization techniques are relatively costly, time-consuming, subjective, and have cumbersome sample preparations. This study focused on using three relatively inexpensive imaging systems: a black box, Canon camera (EOS760D), and LaserJet scanner (M1132 MFP). Two standard, state-of-the-art imaging systems were used for comparison: a stereomicroscope and a scanning electron microscope. Digital images produced by the imaging systems were used with a MATLAB algorithm to determine the surface porosity, pore area, and shape factor of the polyurethane foam in an efficient manner. The results obtained established the compatibility of the image analysis algorithm with the imaging systems. The black box results were found to be more comparable to both the stereomicroscope and SEM systems than those of the Canon camera and scanner imaging systems. Indeed, the current research effort demonstrates the possibility of substrate characterization with inexpensive imaging systems.

An experiment to study an exotic atom with infrared spectroscopy will measure a fundamental parameter related to the spatial dimensions of a proton.