The accuracy, reliability, speed and cost of the methods used for malaria diagnosis are key to the diseases’ treatment and eventual eradication. However, improvement in any one of these requirements can lead to deterioration of the rest due to their interdependence. We propose an optical method that provides fast detection of malaria-infected red blood cells (RBCs) at a lower cost. The method is based on the combination of deconvolution, topography and three-dimensional (3D) refractive index reconstruction of the malaria-infected RBCs by use of the transport of intensity equation. Using our method, healthy RBCs were identified by their biconcave shape, quasi-uniform spatial distribution of their refractive indices and quasi-uniform concentration of hemoglobin. The values of these optical and biochemical parameters were found to be in agreement with the values reported in the literature. Results for the malaria-infected RBCs were significantly different from those of the healthy RBCs. The topography of the cells and their optical and biochemical parameters enabled identification of their stages of infection. This work introduces a significant method of analyzing malaria-infected RBCs at a lower cost and without the use of fluorescent labels for the parasites.

Computational fluid dynamic and experimental approaches have been compared in the prediction of reaction performance in the preparation of a pharmaceutical intermediate.

A comparison between the commonly used absorption spectrophotometry and a more recent approach known as structured laser illumination planar imaging (SLIPI) is presented for the characterization of scattering and absorbing liquids. Water solutions of milk and coffee are, respectively, investigated for 10 different levels of turbidity. For the milk solutions, scattering is the dominant process, while the coffee solutions have a high level of absorption. Measurements of the extinction coefficient are performed at both $\lambda =450\mathrm{nm}$ and $\lambda =638\mathrm{nm}$ and the ratio of their values has been extracted. We show that the turbidity limit of valid transmission measurements is reached at an optical depth of $\mathrm{OD}\sim 2.4$, corresponding here to an extinction coefficient of ${\mu }_e=0.60{\mathrm{mm}}^{-1}$ when using a modern absorption spectrometer having a spatial Fourier filter prior to detection. Above this value, errors are induced due to the contribution of scattered and multiply scattered photons reaching the detector. On the contrary, the SLIPI measurements were found to be very reliable, even for an extinction coefficient three times as high, where ${\mu }_e=1.80{\mathrm{mm}}^{-1}$. This improvement is due to the capability of the technique in efficiently suppressing the contribution from multiple light scattering.

We report an accurate optical differentiation technique between healthy and malaria-infected erythrocytes by quasi-simultaneous measurements of transmittance, reflectance, and scattering properties of unstained blood smears using a multispectral and multimode light-emitting diode microscope. We propose a technique for automated imaging, identification, and counting of malaria-infected erythrocytes for real-time and cost-effective parasitaemia diagnosis as an effective alternative to the manual screening of stained blood smears, now considered to be the gold standard in malaria diagnosis. We evaluate the performance of our algorithm against manual estimations of an expert and show a spectrally resolved increased scattering from malaria-infected blood cells.

Spectral imaging and lidar methods for the characterization of vegetation are vital for understanding plants and, in turn, food security, biodiversity, and vegetation health in a changing climate. While novel hyperspectral imaging, canopy lidar,and solar-induced fluorescence provide details on species, state, structure, and plant physiology, such data come from different instruments. Thus, post-processing and data fusion struggles with synchronization, spatial overlap, and resolution issues. Especially in the tropical regions of sub-Saharan Africa, these complex, expensive, and bulky instruments remain inaccessible. Here, in Ghana, we have built a low-cost, lightweight, and realistic instrument for simultaneously acquiring hyperspectral data of vegetation fluorescence and canopy structure with perfect spatial overlap. In this paper, we demonstrate the application of the hyperspectral fluorescence lidar for diagnostics and species specificity of locally significant crops. We demonstrate simultaneous range and fluorescence measurements of forest canopy, conducted in full sunlight. Our results indicate that the upper side of the leaves shows a more substantial deviation for stressed plants, whilethe lower side shows greater contrast for plant species. This new and simple tool provides a combined method for hyperspectral classification and assessment of the physiological state while also reporting the vegetation height over ground and its diversity.