Sub-diffraction error mapping for localisation microscopy images

Assessing the quality of localisation microscopy images is highly challenging due to the difficulty in reliably detecting errors in experimental data. The most common failure modes are the biases and errors produced by the localisation algorithm when there is emitter overlap. Also known as the high density or crowded field condition, significant emitter overlap is normally unavoidable in live cell imaging. Here we use Haar wavelet kernel analysis (HAWK), a localisation microscopy data analysis method which is known to produce results without bias, to generate a reference image. This enables mapping and quantification of reconstruction bias and artefacts common in all but low emitter density data. By avoiding comparisons involving intensity information, we can map structural artefacts in a way that is not adversely influenced by nonlinearity in the localisation algorithm. The HAWK Method for the Assessment of Nanoscopy (HAWKMAN) is a general approach which allows for the reliability of localisation information to be assessed.

Validation and Application of a Low-Cost Sorting Device for Fumonisin Reduction in Maize

Fumonisin mycotoxins are a persistent challenge to human and livestock health in tropical and sub-tropical maize cropping systems, and more efficient methods are needed to reduce their presence in food systems. We constructed a novel, low-cost device for sorting grain, the “DropSort”, and tested its effectiveness on both plastic kernel models and fumonisin-contaminated maize. Sorting plastic kernels of known size and shape enabled us to optimize the sorting performance of the DropSort. The device sorted maize into three distinct fractions as measured by bulk density and 100-kernel weight. The level of fumonisin was lower in the heaviest fractions of maize compared to the unsorted samples. Based on correlations among fumonisin and bulk characteristics of each fraction, we found that light fraction 100-kernel weight could be an inexpensive proxy for unsorted fumonisin concentration. Single kernel analysis revealed significant relationships among kernel fumonisin content and physical characteristics that could prove useful for future sorting efforts. The availability of a low-cost device (materials~USD 300) that can be used to reduce fumonisin in maize could improve food safety in resource-limited contexts in which fumonisin contamination remains a pressing challenge.

Sub-diffraction error mapping for localization microscopy images

Assessing the quality of localization microscopy images is highly challenging due to difficulty in reliably detecting errors in experimental data, with artificial sharpening being a particularly common failure mode of the technique. Here we use Haar wavelet kernel analysis (HAWK), a localization microscopy data analysis method which is known to give results without artificial sharpening, to generate a reference image. This enables the mapping and quantification of this common artefact. By suppressing intensity information, we are able to map sharpening errors in a way which is not influenced by nonlinearity in the localisation imaging process. The HAWK Method for the Assessment of Nanoscopy (HAWKMAN) is a general approach which allows the reliability of localization information to be assessed.

GIS-Based Kernel Analysis for Tourism Flow Mapping

The variation of tourism flow and its spatial representation are indispensable for transport companies, accommodation facilities and future estimations regarding the international arrivals. The major implication for tourism flow mapping is related to the country of origin of tourists, their liquid assets, and tourism statistical database. The approach of tourism flow mapping representation, at least using lines and density, should be based on the spatial characteristics of the objects. In this study, the database consisting of international arrivals in different cities of Romania was used as an example. Thus, GIS-based Kernel density of the tourists’ flow was proposed. To illustrate the international demand, data on arrivals for 33 countries over the period 2015-2017 were used. ‘XY To Line’ and ‘Kernel Density’ functions served to create the convergence lines between the origin countries and Romania. The very high density was found for the European countries with an increase of 13% and 25% between 2015 and 2016, as well as between 2015 and 2017. Map analysis indicated an increase of the density area by 0.7% for 2016 and 1.7% for 2017. The proposed methods, including lines and density, contribute to the mapping of the flow of the international arrivals in Romania.