Continuous Continuous Probabilistic Genotyping: A differentiable model and modern Bayesian inference techniques for forensic DNA mixtures

DNA samples are a part of the collected physical evidence during the comtemporary crime scene investigation procedure. After processing the samples, a laboratory obtains short tandem repeat electropherograms. In case of mixed DNA profiles, i.e., profiles that contain DNA material from more than one contributor, the laboratory needs to estimate the test statistic (likelihood ratio) that could provide evidence, either inculpatory or exculpatory, against the person of interest. This is automated with probabilistic genotyping (PG) software with (fully-)continuous models: the ones that consider the heights of the observed peaks. In this thesis, we provide understanding of the modern PG methods. We then show how to improve measurable indicators of the algorithm performance, such as precision and inference runtime, that directly correspond to the efficiency and efficacy of work performed in a lab. With quicker algorithms the forensics laboratories can process more samples and provide more comprehensive results by reanalysing the mixtures with different hypotheses and hyperparameterisations. With more precise algorithms, there will be a grater confidence in their results. The precision of the solution would ameliorate the admissibility of the provided evidence and reliability of the results. We achieve improvements over the state-of-the-art by utilising probabilistic programming and modern Bayesian inference methods. We describe a differentiable (and hence continuous) continuous model that can be used with different estimators from both the sampling and variational families of techniques. Finally, as the different PG products output different likelihood ratios, we provide explanation of some of the factors causing this behaviour. This is of high importance because if two solutions are used for the same crime case, the difference must be understood. Otherwise, because of lack of consensus, the results would cause confusion or, in the worst case, would not be admitted by the court

Adaptive particle representation of fluorescence microscopy images

Modern microscopes can generate high volumes of 3D images, driving difficulties in data handling and processing. Here, the authors present a content-adaptive image representation as an alternative to standard pixels that goes beyond data compression to overcome storage, memory, and processing bottlenecks

cheesema/LibAPR: Initial Release v1.1

First release of LibAPR: Basic Python wrappers.Pipeline clean-up and efficiencies. Additional testing.For creation of citable DO

Multiple Reprocessing of Conductive PLA 3D-Printing Filament: Rheology, Morphology, Thermal and Electrochemical Properties Assessment

Additive manufacturing technologies are gaining more and more attention, resulting in the development or modification of 3D printing techniques and dedicated materials. On the other hand, economic and ecological aspects force the industry to develop material recycling strategies. In this work, the multiple reprocessing of a commercially available PLA conductive composite with carbon black filler, dedicated to 3D printing, was investigated. The effects of extrusion temperature (190 °C and 200 °C) and reprocessing steps (1–5 steps) on the rheology, morphology, thermal and electrochemical properties of the conductive PLA 3D-printing filament were evaluated. The results showed deterioration of the thermal stability and material strength, as well as the influence of reprocessing on the melting point, which increases after initial melting. The electronic conduction mechanism of the composite depends on the percolation paths and it is also affected by the multiple processing. The reversibility of the [Fe(CN)6]3−/4− redox process diminishes with a higher degradation level of the conductive PLA. Importantly, the material fluidity was too high after the multiple reprocessing, which should be considered and suitably corrected during CB–PLA application as a 3D-printed electrode material