Seasonal variation and complex analysis of microplastic distribution in different WWTP treatment stages in Lithuania

Industrial wastewater, domestic wastewater, and stormwater are the three entry points for microplastics (MP) in wastewater treatment plants. Extreme weather conditions, such as rising temperatures and heavy rainfall caused by climate change, can alter the rate at which MP enters wastewater treatment plants. In this study, wastewater and sludge samples from different treatment stages were collected during a 12-month sampling campaign (seasonal) to determine the efficiency of a municipal wastewater treatment plant in removing microplastic particles. MP ranging from 20 to 1000 µm were detected and classified by shape, color, size, and chemical composition. All samples contained MP particles, with concentration ranging from 1964 ± 50-2982 ± 54 MP/L in influent to 744 ± 13-1244 ± 21 MP/L in effluent and 91.1 ± 8-61.9 ± 5 MP/g in sludge; 71.6-90.1% identified particles were fragment-type with black, white, and transparent colors. Most of the microplastic particles were removed in the activated sludge tank, while the average removal rate in the wastewater treatment plant was 57%. The total concentration of MP was 27% higher in spring than in other seasons. The most common microplastic particles were polyethylene terephthalate (PET), polystyrene (PS), and polypropylene (PP). These results demonstrate the value of long-term monitoring and MP quantification, which would provide a more accurate estimate of MP pollution from wastewater treatment plants.

Topic based quality indexes assessment through sentiment

This paper proposes a new methodology called TOpic modeling Based Index Assessment through Sentiment (TOBIAS). This method aims at modeling the effects of the topics, moods, and sentiments of the comments describing a phenomenon upon its overall rating. TOBIAS is built combining different techniques and methodologies. Firstly, Sentiment Analysis identifies sentiments, emotions, and moods, and Topic Modeling finds the main relevant topics inside comments. Then, Partial Least Square Path Modeling estimates how they affect an overall rating that summarizes the performance of the analyzed phenomenon. We carried out TOBIAS on a real case study on the university courses' quality evaluated by the University of Cagliari (Italy) students. We found TOBIAS able to provide interpretable results on the impact of discussed topics by students with their expressed sentiments, emotions, and moods and with the overall rating.

Transient analysis of the Erlang A model

We consider the Erlang A model, or [Formula: see text] queue, with Poisson arrivals, exponential service times, and m parallel servers, and the property that waiting customers abandon the queue after an exponential time. The queue length process is in this case a birth-death process, for which we obtain explicit expressions for the Laplace transforms of the time-dependent distribution and the first passage time. These two transient characteristics were generally presumed to be intractable. Solving for the Laplace transforms involves using Green's functions and contour integrals related to hypergeometric functions. Our results are specialized to the [Formula: see text] queue, the M / M / m queue, and the M / M / m / m loss model. We also obtain some corresponding results for diffusion approximations to these models.