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As the most common causes of seasonal allergies, pollen affects approximately 30% of the world population. The proper information on the number of airborne allergens can significantly reduce its negative health and economic impact. For this reason, there is a growing network of automatic airborne particle monitors deployed. However, the calibration of such devices is a tedious task. Developing a deep learning classifier may allow model transferability between the devices. To investigate this approach, we employed data from two Rapid-E particle identifier devices, in a multi-class pollen identification task. We aim to improve the performance of models trained with data from one device and tested on another device. To our knowledge, this is the first attempt to apply any domain adaptation technique with unlabeled data between automatic airborne particle identifiers. Convolutional Neural Networks were constructed with two outputs to simultaneously perform pollen identification and domain adaptation. A simple gradient reversal layer between the domain classifier and the feature extractor promotes the emergence of not just discriminative features related to the classification task but also features invariant to the domain shifts in data. The development of a method for model transferability has a huge practical value for pollen monitoring since it reduces the costs of collecting labeled data

Interaction of a TEA CO2laser, operating at 10.6 μm wavelength and pulse length of 100 ns, with titanium target (implant), in nitrogen and carbon-dioxide gas ambience was studied. The Ti-surface modifications were studied at moderate fluence (~17J/cm2) and intensity (~60MW/cm2) regime.The energy absorbed from the laser beam was partially convertedto thermal energy, which generated a series of effects, such as melting, vaporization of the molten material, shock waves, etc. The following Ti-surface changes and phenomena were observed: (i) superficial damages in both atmospheres; (ii) creation of cone-and hill-like structures in atmosphere of N2and CO2, respectively; (iii) possible formation of TiN, Ti-oxide(s) and, Ti-carbide layers, in N2and CO2gas, respectively and, (iv) occurrence of plasma inboth gas ambiences. It can be concluded that the applied laser fluence was high enough to produce effective modification of the Ti-implant target in nitrogen as well as in carbon-dioxide gas. Creation of plasma may provide sterilization effect. Physical chemistry 2016 : 13th international conference on fundamental and applied aspects of physical chemistry; Belgrade (Serbia); 26-30 September 2016