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The aim of this study was to assess the effect of air pollution on road side fruit plants (Prunus avium L.) palynology. Flower samples were collected from polluted (1-2 m away from the edge of Quetta to Hunna Urak road) and for the comparison from non-polluted sites (250-300 m away from the same collection site). During the investigation different pollen parameters including pollen umbers/production, pollen size, pollen tube growth, pollen viability, pollen regularity and pollen protein contents were used through different methods. Results indicated that pollen grains of Prunus avium L. were very sensitive to automobile air pollution. Consequences showed significant reduction in numbers and sizes of pollen grains, pollen tube length and pollen viability of polluted site with respect to the control site. Maximum irregularity in pollen morphology and low pollen protein contents were also recorded from the polluted site. Moreover, results also designated that vehicular pollution increases the resting period of pollen grains for 1 to 3 h. So the different attributes of pollen grains can be used as sensitive bioindicators of adverse factors in botanical environment and this leads to the idea that reduction in the development and potential of pollen grains in response to various poisonous environmental pollutants can be exploited as a good index of air purity.

The Internet of Things (IoT) is in a "desperate" need for a practical model that would help in differentiating things according to their non-functional properties. Unfortunately, despite IoT growth, such properties either lack or ill-defined resulting into ad-hoc ways of selecting similar functional things. This paper discusses how things' non-functional properties are combined into a Quality-of-Things (QoT) model. This model includes properties that define the performance of things' duties related to sensing, actuating, and communicating. Since the values of QoT properties might not always be available or confirmed, providers of things can tentatively define these values and submit them to an Independent Regulatory Authority (IRA) whose role is to ensure fair competition among all providers. The IRA assesses the values of non-functional properties of things prior to recommending those that could satisfy users' needs. To evaluate the technical doability of the QoT model, a set of comprehensive experiments are conducted using real datasets. The results depict an acceptable level of the QoT estimation accuracy.

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