Using sentiment analysis to evaluate the impact of the COVID-19 outbreak on Italy’s country reputation and stock market performance

During the recent Coronavirus disease 2019 (COVID-19) outbreak, the microblogging service Twitter has been widely used to share opinions and reactions to events. Italy was one of the frst European countries to be severely afected by the outbreak and to establish lockdown and stay-at-home orders, potentially leading to country reputation damage. We resort to sentiment analysis to investigate changes in opinions about Italy reported on Twitter before and after the COVID-19 outbreak. Using diferent lexicons-based methods, we fnd a breakpoint corresponding to the date of the frst established case of COVID-19 in Italy that causes a relevant change in sentiment scores used as a proxy of the country’s reputation. Next, we demonstrate that sentiment scores about Italy are associated with the values of the FTSE-MIB index, the Italian Stock Exchange main index, as they serve as early detection signals of changes in the values of FTSE-MIB. Lastly, we evaluate whether diferent machine learning classifers were able to determine the polarity of tweets posted before and after the outbreak with a diferent level of accuracy

Threshold-based Naïve Bayes classifier

The Threshold-based Naive Bayes (Tb-NB) classifier is introduced as a (simple) improved version of the original Naive Bayes classifier. Tb-NB extracts the sentiment from a Natural Language text corpus and allows the user not only to predict how much a sentence is positive (negative) but also to quantify a sentiment with a numeric value. It is based on the estimation of a single threshold value that concurs to define a decision rule that classifies a text into a positive (negative) opinion based on its content. One of the main advantage deriving from Tb-NB is the possibility to utilize its results as the input of post-hoc analysis aimed at observing how the quality associated to the different dimensions of a product or a service or, in a mirrored fashion, the different dimensions of customer satisfaction evolve in time or change with respect to different locations. The effectiveness of Tb-NB is evaluated analyzing data concerning the tourism industry and, specifically, hotel guests' reviews from all hotels located in the Sardinian region and available on Booking.com. Moreover, Tb-NB is compared with other popular classifiers used in sentiment analysis in terms of model accuracy, resistance to noise and computational efficiency

An integrated reconstruction of the multiannual wave pattern in the gulf of naples (South-Eastern Tyrrhenian Sea, Western Mediterranean Sea)

Surface gravity waves retrieved by a network of HF (High Frequency) radars and measured in situ by an ADCP (Acoustic Doppler Current Profiler) current meter connected to an elastic beacon were used to carry out a multiple-year characterization of the wave field of the Gulf of Naples (south-eastern Tyrrhenian Sea, western Mediterranean). The aim of the work was to create a climatology of the study area and to demonstrate the potential of an integrated platform for coastal studies. The patterns recorded by the different instruments were in agreement with the wave climatology of the southern Tyrrhenian Sea as well as with previous scores for the same area. The results presented in this work also highlight seasonal and interannual consistency in the wave patterns for each site. In a wider context, this study demonstrates the potential of HF radars as long-term monitoring tools of the wave field in coastal basins, and supports the development of integrated observatories to address large-scale scientific challenges such as coastal ocean dynamics and the impact of global change on the local dynamics

MODELING AND DESIGNING A FULL BEAMFORMER FOR ACOUSTIC SENSING AND MEASUREMENT

Acoustic sensing is a viable approach for solving issues related to many applications, namely, biomedical, distance measurements, mechanical, health infrastructure monitoring, etc. It is generally sustainable and of no negative impact on the object under test. The use of acoustic sensing under beamforming technique is an important asset to be exploited, especially for the aforementioned applications. This paper illustrates a generalized approach of modeling and designing a full beamfomer using two specific classes: LCMP (Linear Constrained Minimum Power) beamformers that are used to overcome robustness limitations and MVDR (Minimum Variance Distortionless Response) beamformers. Any aspect of modeling and designing is always related to the DOA (Direction of Arrival). The obtained results are based on assumptions extracted from an actual case of constructed system

Host-cell dependent role of phosphorylated keratin 8 during influenza A/NWS/33 virus (H1N1) infection in mammalian cells

In this study, we investigated the involvement of keratin 8 during human influenza A/NWS/33 virus (H1N1) infection in semi-permissive rhesus monkey-kidney (LLC-MK2) and permissive human type II alveolar epithelial (A549) cells. In A549 cells, keratin 8 showed major expression and phosphorylation levels. Influenza A/NWS/33 virus was able to subvert keratin 8 structural organization at late stages of infection in both cell models, promoting keratin 8 phosphorylation in A549 cells at early phases of infection. Accordingly, partial colocalizations of the viral nucleoprotein with keratin 8 and its phosphorylated form were assessed by confocal microscopy at early stages of infection in A549 cells. The employment of chemical activators of phosphorylation resulted in structural changes as well as increased phosphorylation of keratin 8 in both cell models, favoring the influenza A/NWS/33 virus's replicative efficiency in A549 but not in LLC-MK2 cells. In A549 and human larynx epidermoid carcinoma (HEp-2) cells inoculated with respiratory secretions from pediatric patients positive for, respectively, influenza A virus or respiratory syncytial virus, the keratin 8 phosphorylation level had increased only in the case of influenza A virus infection. The results obtained suggest that in A549 cells the influenza virus is able to induce keratin 8 phosphorylation thereby enhancing its replicative efficiency

The role of noise on the steady state distributions of phytoplankton populations

The spatio-temporal behaviour of total chlorophyll concentration is investigated in the middle of the Tyrrhenian Sea by using a stochastic approach. The study is based on a reaction-diffusion-taxis model, which is used to analyse the dynamics of five phytoplankton groups, responsible for about 80% of the total chlorophyll a inside the euphotic zone of the water column. The analysis is performed by considering: (i) the intraspecific competition of the phytoplanktonic groups for limiting factors, i.e. light intensity and nutrient concentration, (ii) the seasonal changes of environmental variables, and (iii) the random fluctuations of the components of the velocity field and temperature. Specifically, we investigate the effects of external perturbations, both deterministic and random, on the dynamics of phytoplankton populations, by inserting a term of multiplicative noise into the differential equation of the nutrient dynamics. The theoretical results of the phytoplankton abundances obtained by the stochastic model are converted in chlorophyll a concentrations, and compared with the experimental findings. The statistical checks, based on the chi-square test, show that the vertical distributions of total chlorophyll concentration are in a good agreement with the experimental data. Finally, we observe that the high intensity of environmental noise strongly modifies the steady spatial distributions of two phytoplankton groups usually localized in deeper layers, causing algal blooms in surface water

Executive function abnormalities in pathological gamblers

Background: Pathological gambling (PG) is an impulse control disorder characterized by persistent and maladaptive gambling behaviors with disruptive consequences for familial, occupational and social functions. The pathophysiology of PG is still unclear, but it is hypothesized that it might include environmental factors coupled with a genetic vulnerability and dysfunctions of different neurotransmitters and selected brain areas. Our study aimed to evaluate a group of patients suffering from PG by means of some neuropsychological tests in order to explore the brain areas related to the disorder. Methods: Twenty outpatients (15 men, 5 women), with a diagnosis of PG according to DSM-IV criteria, were included in the study and evaluated with a battery of neuropsychological tests: the Wisconsin Card Sorting Test (WCST), the Wechsler Memory Scale revised (WMS-R) and the Verbal Associative Fluency Test (FAS). The results obtained in the patients were compared with normative values of matched healthy control subjects. Results: The PG patients showed alterations at the WCST only, in particular they had a great difficulty in finding alternative methods of problem-solving and showed a decrease, rather than an increase, in efficiency, as they progressed through the consecutive phases of the test. The mean scores of the other tests were within the normal range. Conclusion: Our findings showed that patients affected by PG, in spite of normal intellectual, linguistic and visual-spatial abilities, had abnormalities emerging from the WCST, in particular they could not learn from their mistakes and look for alternative solutions. Our results would seem to confirm an altered functioning of the prefrontal areas which might provoke a sort of cognitive "rigidity" that might predispose to the development of impulsive and/or compulsive behaviors, such as those typical of PG. © 2008 Marazziti et al; licensee BioMed Central Ltd

CO2 hydrogenation to methanol with an innovative Cu/Zn/Al/Zr catalyst: Experimental tests and process modeling

In this study, an innovative Cu/Zn/Al/Zr catalyst for the conversion of CO2 and H2 into methanol is tested at laboratory scale (0.5 g of catalyst into a cylindrical fixed bed reactor, with 9.1 mm internal diameter). Fourteen experimental tests are performed under isothermal conditions (T = 250 °C), covering a range of pressure (3.0–7.0 MPa), Gas Hourly Space Velocity (4000–13,000 h-1) and H2/CO2 molar ratio (between 3 and 6) relevant to industrial applications, with or without CO in the feed mixture, with flow-rates ranging between 200 and 650 NmL min-1. Based on the established Graaf’s kinetic model, new kinetic parameters are calibrated and a plug-flow model of the isothermal reactor is implemented and simulated in Aspen Plus. A reasonable agreement between experimental data and calibrated model is achieved, with deviations lower than 10% of the measured flow rates for each species in the product stream. CO2 conversion up to 26% and methanol yields up to 13% are obtained during the test campaign (test run #12). The model represents a valid tool for future research or engineering studies targeting the design and performance assessment of demo/full-scale CO2-to-methanol synthesis processes based on the Cu/Zn/Al/Zr catalyst introduced in this paper

Stochastic models for phytoplankton dynamics in Mediterranean Sea

In this paper, we review some results obtained from three one-dimensional stochastic models, which were used to analyze picophytoplankton dynamics in two sites of the Mediterranean Sea. Firstly, we present a stochastic advection\u2013reaction\u2013diffusion model to describe the vertical spatial distribution of picoeukaryotes in a site of the Sicily Channel. The second model, which is an extended version of the first one, is used to obtain the vertical stationary profiles of two groups of picophytoplankton, i.e. Pelagophytes and Prochlorococcus, in the same marine site as in the previous case. Here, we include intraspecific competition of picophytoplanktonic groups for limiting factors, i.e. light intensity and nutrient concentration. Finally, we analyze the spatio-temporal behaviour of five picophytoplankton populations in a site of the Tyrrhenian Sea by using a reaction\u2013diffusion\u2013taxis model. The study is performed, taking into account the seasonal changes of environmental variables, obtained starting from experimental findings. The multiplicative noise source, present in all three models, mimics the random fluctuations of temperature and velocity field. The vertical profiles of chlorophyll concentration obtained from the stochastic models show a good agreement with experimental data sampled in the two marine sites considered. The results could be useful to devise a new class of models based on a stochastic approach and able to predict future changes in biomass primary production