This study reports the pico- and femtosecond laser-induced photocrosslinking of protein microstructures. The capabilities of a picosecond Nd:YAG laser to promote multiphoton excited crosslinking of proteins were evaluated by fabricating 2D and 3D microstructures of avidin, bovine serum albumin (BSA) and biotinylated bovine serum albumin (bBSA). The multiphoton absorption-induced photocrosslinking of proteins was demonstrated here for the first time with a non-toxic biomolecule flavin mononucleotide (FMN) as the photosensitizer. Sub-micrometer and micrometer scale structures were fabricated from several different compositions of protein and photosensitizer by varying the average laser power and scanning speed in order to determine the optimal process parameters for efficient photocrosslinking. In addition, the retention of ligand-binding ability of the crosslinked protein structures was shown by fluorescence imaging of immobilized biotin or streptavidin conjugated fluorescence labels. The surface topography and the resolution of the protein patterns fabricated with the Nd:YAG laser were compared to the results obtained with a femtosecond Ti:Sapphire laser. Quite similar grain characteristics and comparable feature sizes were achieved with both laser sources, which demonstrates the utility of the low-cost Nd:YAG microlaser for direct laser writing of protein microstructures.

No abstract

An easy to use and inexpensive green filter seems to reduce the stress caused by light during the IVP procedures without affecting either the accuracy of embryo monitoring or the need to increase the light intensity.

This article focuses on monitoring a driver's cognitive impairment due to talking to passengers or on a mobile phone, daydreaming, or just thinking about other than driving-related matters. This paper describes an investigation of cognitive distraction, firstly, giving an overall idea of its effects on the driver and, secondly, discussing the practical implementation of an algorithm for detection of cognitive distraction using a support vector machine (SVM) classifier. The evaluation data have been gathered by recruiting 12 professional drivers to drive for approximately 45 min in various environments and inducing cognitive tasks, i.e. arithmetic calculations. According to the prior knowledge and the experimental analysis, gaze, head and lane-keeping variances over a 15 s time window were selected indicative features. The SVM classifier's performance was optimized through exhaustive parameter tuning. The executed tests show that the cognitive workload can be detected with approximately 65-80 per cent confidence despite the fact that the test material represented medium-difficulty cognitive tasks (i.e. the induced workload was not very high). Thus, it could be assumed that a more challenging cognitive task would yield better detection results.

This paper presents a novel automatic scrap metal sorting system which employs a colour vision based optical sensing system and an inductive sensor array. The operation of the system is verified in a real metal recycling plant. The long period test results indicate that 80 % purity can be achieved when the feeding conveyor speed is limited below 1,5 m/s. The described system is not designed for any particular metal. However, the above separation result can only be achieved when reddish (brass, copper) and bright metals (stainless steel) are separated. The properties of aluminium, zinc, and magnesium are too similar for the current sensing principle. The results do not only depend on the sensing system, but also optimal work flow, lighting, dust and vibrations have to be considered in a practical sorting machine. The achieved purity and capacity is sufficient for industrial use. Efficient use of sensor fusion provides good performance despite the diversity of the scrap metals.