Microscopes offer a limited depth of focus which precludes the observation of a complete image of a three-dimensional (3D) object in a single view. Investigations, by a variety of researchers, have led to the development of extended depth of focus algorithms for serial optical slices of microscopic 3D objects in recent years. However, to date, no quantitative comparison of the different algorithms has been performed, generally leaving the evaluation to the subjective qualitative appreciation of the observer. In this paper we use three different tests for extended depth of focus algorithm evaluation and test 10 different algorithms, some of them have been adapted (by us) for a series of optical slices. However, the main contribution of the paper is a new improved algorithm for computing the extended depth of focus. q

The identification of organisms is a time-consuming task even for highly specialized researchers. Many ways to accelerate the identification process have been devised -from pictorial keys to automatic, machine identification -with different degrees of success. This paper explores landmark configurations as an aid to taxonomic identification. The basic hypothesis rests on the analogy between human fingerprints and organism landmark configuration. Translated into biological terms, it asks whether individual landmark configurations can be used as diagnostic characteristics for species identification. Water mites of the genus Torrenticola were used as test organisms. The results show that identification can be made simpler through the use of landmark configurations.

Means of transport should be able to fulfil their main function safely and comfortably for travellers and drivers. The effects of vibrations on ride comfort are in the frequency range of 0.5 to 80 Hz and can be analysed using the UNE-2631 standard. This type of analysis has been conducted for several means of transport (bicycles, motorcycles, cars, trucks, etc.), but the literature on e-scooter comfort is very scarce. Existing research describes methodologies, simulation models, and a few measurements related to e-scooter comfort. This paper presents, for the first time, a comfort analysis using an Arduino-based data acquisition system at a sampling frequency of 200 Hz (higher than that in previous studies). Acceleration and speed measurements were obtained by sensorising an e-scooter with inflated wheels without any additional damping systems, which is one of the commonly used e-scooter types. In this study, the comfort for two different speeds (20 and 28 km/h), two types of pavements (pavers and asphalt), and two drivers with different weights was investigated. The results indicate the lowest comfort values for higher velocities and paver pavement. Furthermore, the comfort values were extremely low for all scenarios. In addition, the results demonstrate the necessity of using a sampling rate of at least 80 Hz for this e-scooter model.

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