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Founded in 1959, the Italian Society of Parasitology (SoIPa) includes nearly 200 researchers and professionals in the fields of medicine, veterinary medicine, biotechnology, epidemiology and environmental sciences. The diversity of its members, in a historical and continuous collaboration with other international scientific societies, embodies a broad and multidisciplinary field such as parasitology. Since 1959, SoIPa has organized a biennial congress, covering all aspects of general parasitology with participants from all over Italy, Europe and beyond, involved in a dynamic and multi-faceted scientific framework of contributions and symposia. The present Special Issue (SI) contains 6 review papers and 1 research article, focussed on emerging topics presented and discussed during some of the symposia organized within the XXXII SoIPa Congress, held in Naples from 27th June to 30th June 2022. These review papers reflect several emerging subjects (i.e. 'Italian network on Neglected Tropical Diseases', 'Wildlife parasites and citizen science', 'Comparing approaches to parasitological issues', 'Unusual perspectives on the role of parasites') with the aim to explore the new role that parasitologists can play in the future society, working together to promote dialogue on science-informed decisions to support the so-called 'twin green and digital transition'. [ABSTRACT FROM AUTHOR]

Purpose: The introduction in Italy in July 2021 of the "COVID-19 Green Certification", known as the "Green Pass", was a particularly important moment in the political and social history of the country. While its use for health reasons is debatable both logically and scientifically, its effects should be measured at the general sociological level. The "Green Pass" allowed Italian social life to be shaped according to a social and political profile that can be traced back to a "society of control". This paper aims to discuss the aforementioned issue. Design/methodology/approach: This paper, of a theoretical nature, intends to verify such an interpretation through a critical survey of Gilles Deleuze's well-known Post-scriptum sur les sociétés de contrôle (1990) and relating the theories to it from cybernetic science, sociology of social systems and the continental philosophy, specifically Michel Foucault. After a short introduction on the history of the instrument's introduction, the paper, divided into parts reflecting the set-up of Deleuze's text, examines the systemic social effects of the "Green Pass" with regard to its logic, and concludes with a reflection on the program of the instrument's future developments. Findings: The "Green Pass" put into practice a model of a society of control as anticipated by Deleuze, verified with particular reference to some instances of Luhmann's theory of social systems, and in the perspective of a Foucault's "normalizing society" in the process of definition and affirmation. Social implications: The "Green Pass" has been a controversial tool that has caused forms of social discrimination and exclusion and has seriously questioned the architecture of the rule of law. The conceptual paper tries to reflect on the premises and implications of this instrument. Originality/value: The approach to the problem both in a critical key and according to concepts and theories of the sociology of social systems, cybernetics and continental philosophy. [ABSTRACT FROM AUTHOR]

The Late Pliocene-Quaternary Outer Thrust System of the Apennine-Maghrebides fold-and-thrust belt extends ~2000 km from northern Italy to Sicily. Its northernmost arc is seismically active and represents a test case to study geometries and seismogenesis of slowly deforming megathrusts developed within the continental lithosphere. Two distinct SW- dipping reverse shear zones (T1 and T2) in the Outer Thrust System of eastern Central Italy have been recently unveiled thanks to geological and integrated seismological information. These shear zones penetrate the Adria continental lithosphere to a maximum depth of ~60 km, with an outward convex shape associated with an outwarddiverging radial pattern. This paper presents new constraints on the megathrusts' geometry in light of a novel microseismic catalog (from 2009-2022) specifically focused on the compressional volume. Further details in the reconstruction of T1 and T2 are derived from a recent compressional seismic sequence (November 2022, MW 5.5) located in the Adriatic offshore. It activated the outermost T1 upper crustal segment with pure compressional kinematics and illuminated T2 at lower crustal depths. We integrate geological sections, seismic lines, serial hypocentral cross sections, and focal mechanisms to build a detailed nonplanar 3-D model of the thrusts involved. In addition, we build Coulomb stress scenarios for analyzing the possibility of the static interplay between the upper crust T1 segment activated by the 2022 sequence and the underlying T2 crust segment. The overall results may be relevant for assessing seismic hazards in areas with multi-depth active structures and for gaining insights into plate tectonic dynamics. [ABSTRACT FROM AUTHOR]

The article offers information on the MIAC Tissue Exhibition and Conference 2015, a traditional autumn tissue industry fair held in Lucca, Italy.

In Italy, computer science is still far from playing a relevant role within an overall cultural vision: on the one hand, public discourse superimposes informatics as such on digital world in a broad sense; on the other hand, there is a tendency to conceive computer science exclusively as a knowledge useful for specialised job placement. However, this is an evolving situation, in the wake of countries that have already started a real debate on these issues for some time. In the present paper, a comparison between different educational systems is made, while carrying out an analysis about the role of informatics in a globalised society; of course, it is not possible to ignore the importance of an epistemological reflection on its core concepts and on Ict ethical implications, especially in the light of pedagogical issues and digital education need for everyone [ABSTRACT FROM AUTHOR]

This paper aims to provide a general overview of sensory disabilities, focusing on the importance of teacher training in digital technologies from an inclusive perspective. In Italy, students with sensory disabilities represent 3.6 percent of the total number of students with disabilities. It becomes clear how crucial it is to direct educational attention to the strategies and ways that teachers and educators can put in place in order to be able to promote inclusive learning. In this, ICT can contribute in responding to what are the individual needs of students with sensory disabilities, enabling them to express their full potential both cognitively and in terms of their autonomy [ABSTRACT FROM AUTHOR]

Textbooks determine the way school is experienced and learning realised. Their centrality, however, differs according to the various pedagogical cultures in which they are used. This paper shows how mother-tongue and literature textbooks are used in secondary education in Romania and the way in which they reflect an adequate pedagogy for the cognitive development of students. The Romanian case can stimulate a reflection also on the teaching of language and literature in Italy. [ABSTRACT FROM AUTHOR]

The theme of inclusion in the school environment is increasingly defined in the name of a conquest of civilization. The paper aims to summarize the main phases that led to Italy on a regulatory and methodological level from the Deamicisian School to that of Inclusion, through literaries references such as Cuore by Edmondo De Amicis and The appeal by Alessandro D'Avenia. [ABSTRACT FROM AUTHOR]

Purpose: The paper aims to disentangle the factors behind territorial disparities in the coronavirus disease 2019 (COVID-19) case fatality ratio, focusing on the pressure put by the pandemic on healthcare services and adopting a spatial perspective. Design/methodology/approach: Multiscale geographically weighted regression (MGWR) models have been used for uncovering the spatial variability in the impact of healthcare services on COVID-19 case fatality ratio, allowing authors to better capture the real spatial patterns at local level. The authors proved that this approach yields better results, and the MGWR model outperforms traditional regression methods. The selected case studies are two of the biggest UE countries, among the first affected by a high incidence of COVID-19 cases, namely Italy and Germany. Findings: The authors found sizeable regional differences in COVID-19 mortality rates within each of the analysed countries, and the stress borne by local healthcare systems seems to be the most powerful factor in explaining them. In line with other studies, the authors found additional factors of influence, such as age distribution, gender ratio, population density and regional development. Originality/value: This research clearly indicated that COVID-19 related deaths are strongly associated with the degree of resilience of the local healthcare systems. The authors supply localized results on the factors of influence, useful for assisting the decision-makers in prioritizing limited healthcare resources. The authors provide a scientific argument in favour of the decentralization of the pandemic management towards local authorities not neglecting, however, the necessary regional or national coordination. [ABSTRACT FROM AUTHOR]

Different laws, including the recent Law no.227 / 2021 "Delega al Governo in materia di disabilità", underline the importance of building educational projects for pupils, especially in a condition of disability, according to the Life Design’s perspective: alongside the pedagogical tension that characterizes the daily educational experience it is essential that the learning contexts know how to systematize organizational strategies to manage the various school life’s transitions: from the entering school phase, to internships experience rather than in outgoing educational guidance, assuming a systemic and unitary vision introduced thirty years ago with the law 104/1992. This paper documents the quantitative outcomes relating to the first phase of a survey involving a network of Vocational Training Centers (VTC) in Italy. The main goal is to know and understand the complexity of the practices implemented, the VTCs ability to give coherence to the educational guidance, even linking themselves to different stakeholders in the territory. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this study is to investigate contemporary changes in the education system. In particular, an analysis of the mechanisms of coordination and communication involved in the process can show how different geographical factors with different relational mechanisms may contribute to the creation of a new academic entrepreneurship. Design/methodology/approach: The authors propose a methodology with two-step approach. In the first part of the paper, they use a theoretical approach to carry out a longitudinal study of academic literature on the topics of "entrepreneurial university," "academic entrepreneurship" and "spin-off organizations." In the second part, they use cross-database analysis to theorize the main aspects of recent developments in higher education in Italy. To this end, the authors use three public and open-access databases on spin-offs, universities and higher education institutions and incubators in Italy. Findings: First, issues relating to the formation and best practices of entrepreneurial universities are discussed, based on the works of researchers from 25 countries. Second, a hypothesis is put forward to suggest that the organizational model of entrepreneurial university affects microeconomic competitiveness. Third, a case study of Italian spin-off organizations suggests that the number of incubators and spin-offs, and the type of academic knowledge, all directly affect the entrepreneurial university. Originality/value: This paper aims to examine the role of the university in the modern economic system. The originality of this investigation lies in its ability to offer a picture and first analysis of the main actors and of the entrepreneurial university system. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to explore the sharing economy in Italy, focusing on key socioeconomic characteristics. Design/methodology/approach: Adopting an exploratory approach, it analyzes the answers of a questionnaire, created using Google Forms and administered via social networks and e-mails. To analyze the answers statistical tests and descriptive statistics were used. The survey reveals potential behavioral factors, which influence the participation propensity to share economic practices. Findings: Results exhibit that the age of the consumer is an impactful participating factor of sharing economy, and therefore, it seems to be a discriminant. On the contrary, gender and annual income are insignificant determinants. Research limitations/implications: The sample is unbalanced, the majority of the answers were provided by young people. Social implications: The paper can give a picture of the role and the importance of the sharing economy in Italy. Motivated by its global economic growth that could reach in 2025 the value of €570bn, it contextualizes what drives people to collaborate and share tangible and intangible assets. Originality/value: It aims to discover how this digital trend shapes the social fabric of the global economy, providing a broader reflection in terms of future sustainability developments. Ongoing dynamic changes on digital consumer preferences toward sharing products and services provide valuable evidence on their future commercial behavior. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to identify the key factors for successful creation of social value using the social business model (SBM) as an explanatory framework. Design/methodology/approach: This study follows the Krippendorff and Gioia's methodology seeking the rigor while examining the selected case study – a social cooperative named La Paranza, in the city of Naples in the south of Italy. In doing so, the SBM canvas is used to present the research's results in a systematic way. Findings: The existence of a strong "identity" with the local context, the "enthusiasm and the wish to change things", the presence of a "visionary", acting as an orchestrator and the ability to provide for responses to the local needs were identified as key factors in the successful creation of social value in the examined case. Research limitations/implications: The main research limits stem from the single case study methodology approach, which embodies the researchers' subjectivity. A comparative study based on the collection of multiple successful case studies is therefore suggested to develop a generalization of the key drivers underlying the process of social value creation. Originality/value: The study's originality results from its use of the SBM framework in presenting a successful example of social value creation. The examined empirical evidence is also original in itself, mainly because of its inner uniqueness as a new and innovative formula: this allows an in-depth investigation and the inspiration for new ideas in the ground of SBM and, in a broader sense, in the field of social innovation and social value creation. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to analyse the independence of regulatory authorities (RAs) under Italian law. In this paper, reflecting a widespread opinion in Italy, we will address the idea of the inadequacy on the part of the Italian legal framework in ensuring the independence of RAs. The structure of the paper is as follows. After a brief presentation of Italian RAs, independence from politics and independence from stakeholders are both separately considered in light of Italian law. Before concluding, we also offer some insights concerning judicial review of RAs' acts.A part of the debate regards how to ensure and to improve their independence. [ABSTRACT FROM AUTHOR]

This paper explores a real-world fundamental theme under a data science perspective. It specifically discusses whether fraud or manipulation can be observed in and from municipality income tax size distributions, through their aggregation from citizen fiscal reports. The study case pertains to official data obtained from the Italian Ministry of Economics and Finance over the period 2007–2011. All Italian (20) regions are considered. The considered data science approach concretizes in the adoption of the Benford first digit law as quantitative tool. Marked disparities are found, - for several regions, leading to unexpected “conclusions”. The most eye browsing regions are not the expected ones according to classical imagination about Italy financial shadow matters. [ABSTRACT FROM AUTHOR]

The objective of the paper is to evaluate the potential of tank-based rainwater harvesting systems in free standing houses as the source control method to mitigate peak roof runoff due to rainfall in urban areas. To this aim, the water balance simulation of the rainwater tank was carried out using both high resolution rainfall series and toilet water demand data extracted from the database of results built in a previous field campaign involving six experimental households in southern Italy. Simulations show that significant potential for runoff peak reduction exists, basically depending on the rainwater tank size and on the characteristics of the water demand in the house. [ABSTRACT FROM AUTHOR]

Owing to the growing importance of efficient water management, it has become crucial to understand water utilities' characteristics and the environmental factors affecting water pricing, so as to provide guidance to policy-makers. The analysis of factors influencing water tariffs is a challenging task in a context in which companies providing the service are characterized by different ownership features. Moreover, environmental factors and companies' characteristics may simultaneously influence both the decision to privatize the service and the water tariff level. Using a treatment effects model, where privatization is considered as an endogenous binary treatment variable, this paper analyzes whether and how certain relevant variables affect the tariffs levied by water utilities in Italy. The results show that higher tariffs are set in order to cover a greater amount of investments; furthermore, abundant water availability, measured by the average annual rainfall, significantly reduces prices. The data surprisingly show that tariffs are higher where the income level is lower. Significantly, after accounting for the endogeneity due to the fact that water firms are not randomly distributed between totally publicly or not totally publicly owned, our results seem to suggest that ownership does not influence the tariffs levied by water utilities. [ABSTRACT FROM AUTHOR]

This special issue is a collection of selected papers presented at the IEEE International Symposium on Circuits and Systems (ISCAS) 2018 that was held in Florence, Italy, on 27-30 May 2018. As the flagship conference of the IEEE Circuits and Systems Society (CASS), ISCAS attracts researchers across all the main themes associated with the circuits and systems domain. ISCAS 2018 was attended by more than a thousand delegates presenting their papers on analog, mixed signal and digital circuits, communication systems, signal processing, power circuits and systems, and many other relevant and timely topics. [ABSTRACT FROM AUTHOR]

• New COVID-19 mathematical model with lock-down effect. • New fractal-fractional differentiation. • New fractal-fractional integration. • Numerical scheme based on Newton polynomial. Countries around the world are implementing lock-down measures in a bid to flatten the curve of the new deadly COVID-19 disease. Our paper does not claim to have found the cure for COVID-19, neither does it claim that the suggested model have taken into account all the complexities around the spread of the disease. Nonetheless, the fundamental question asked in this paper is to know if within the conditions taken into account in this suggested model, the integral lock-down is effective in saving human lives. To answer this question, a mathematical model was suggested taking into account the possibility of transmission of COVID-19 from dead bodies to humans and the effect of lock-down. Three cases were considered. The first case suggested that there is transmission from dead to the living (medical staffs as they perform postmortem procedures on corpses, and direct contacts with during burial ceremonies). This case has no equilibrium points except for disease free equilibrium, a clear indication that care must be taken when dealing with corpses due to corona-19. In the second case we removed the transmission rate from dead bodies. This case showed an equilibrium point, although the number of deaths, carriers and infected grew exponentially up to a certain stability level. In the last case, we incorporated a lock-down and social distancing effect, using the next generation matrix. We could achieve a zero reproduction number, with number of deaths, infected and carriers decaying very rapidly. This is a clear indication that if lock-down recommendations are observed the threat of COVID-19 can be reduced to zero in few months.While our mathematical model agrees with the effectiveness of the lock-down, it is important to mention damaging effects of inadequate testing. The long waiting period of few days before confirmation of status, can only lead to more infections. The asymptomatic tested person could be positive and spread the infection, or could contact the virus in days after testing and will spread the disease further, after being given a false result. Testing kit that with immediate results are needed for more efficient measures. We used Italy's Data to guide the construction of the mathematical model. To include non-locality into mathematical formulas, differential and integral operators were suggested. Properties and numerical approximations were presented in details. Finally, the suggested differential and integral operators were applied to the model. [ABSTRACT FROM AUTHOR]

This paper presents a comprehensive geoneutrino measurement using the Borexino detector, located at Laboratori Nazionali del Gran Sasso (LNGS) in Italy. The analysis is the result of 3262.74 days of data between December 2007 and April 2019. The paper describes improved analysis techniques and optimized data selection, which includes enlarged fiducial volume and sophisticated cosmogenic veto. The reported exposure of (1.29 ± 0.05) × 1032 protons × year represents an increase by a factor of two over a previous Borexino analysis reported in 2015. By observing 52.6+9.4-8.6 (stat)+2.7-2.1 (sys) geoneutrinos (68% interval) from 238U and 232Th, a geoneutrino signal of 47.0+8.4-7.7 (stat)+2.4-1.9 (sys) TNU with +18.3-17.2% total precision was obtained. This result assumes the same Th/U mass ratio as found in chondritic CI meteorites but compatible results were found when contributions from 238U and 232Th were both fit as free parameters. Antineutrino background from reactors is fit unconstrained and found compatible with the expectations. The null-hypothesis of observing a geoneutrino signal from the mantle is excluded at a 99.0% C.L. when exploiting detailed knowledge of the local crust near the experimental site. Measured mantle signal of 21.2+ 9.5-9.0 (stat)+1.1-0.9 (sys) TNU corresponds to the production of a radiogenic heat of 24.6+11.1-10.4 TW (68% interval) from 238U and 232Th in the mantle. Assuming 18% contribution of 40K in the mantle and 8.1+1.9-1.4 TW of total radiogenic heat of the lithosphere, the Borexino estimate of the total radiogenic heat of the Earth is 38.2 +13.6-12.7 TW, which corresponds to the convective Urey ratio of 0.78+0.41-0.28. These values are compatible with different geological predictions, however there is a 2.4 σ tension with those Earth models which predict the lowest concentration of heat-producing elements in the mantle. In addition, by constraining the number of expected reactor antineutrino events, the existence of a hypothetical georeactor at the center of the Earth having power greater than 2.4 TW is excluded at 95% C.L. Particular attention is given to the description of all analysis details which should be of interest for the next generation of geoneutrino measurements using liquid scintillator detectors. [ABSTRACT FROM AUTHOR]

• Z-control approach is applied on a SEIR model with an overexposure mechanism. • Awareness is considered as an indirect control on the class of infective individuals. • Z-control is used to detect what trend must awareness display to eradicate the disease. • The Z-procedure is generalized to treat high-dimensional uncontrolled models. • The awareness variable is qualitatively compared to Google Trends data on Covid19. In this paper, we use the Z-control approach to get further insight on the role of awareness in the management of epidemics that, just like Covid-19, display a high rate of overexposure because of the large number of asymptomatic people. We focus on a SEIR model including a overexposure mechanism and consider awareness as a time-dependent variable whose dynamics is not assigned a priori. Exploiting the potential of awareness to produce social distancing and self-isolation among susceptibles, we use it as an indirect control on the class of infective individuals and apply the Z-control approach to detect what trend must awareness display over time in order to eradicate the disease. To this aim, we generalize the Z-control procedure to appropriately treat an uncontrolled model with more than two governing equations. Analytical and numerical investigations on the resulting Z-controlled system show its capability in controlling some representative dynamics within both the backward and the forward scenarios. The awareness variable is qualitatively compared to Google Trends data on Covid-19 that are discussed in the perspective of the Z-control approach, inferring qualitative indications in view of the disease control. The cases of Italy and New Zealand in the first phase of the pandemic are analyzed in detail. The theoretical framework of the Z-control approach can hence offer the chance to reflect on the use of Google Trends as a possible indicator of good management of the epidemic. [ABSTRACT FROM AUTHOR]

• A model for the expansion of COVID-19 in Italy, Spain and the USA is considered. • Predictions on cumulative deaths due to COVID-19 are provided. • The effect of favourable seasonal conditions is assessed in the expansion of COVID-19 in different countries. • The effect of the relaxation of lockdown is assessed in the expansion of COVID- 19 in different countries. It is well-known that the classical SIR model is unable to make accurate predictions on the course of illnesses such as COVID-19. In this paper, we show that the official data released by the authorities of several countries (Italy, Spain and The USA) regarding the expansion of COVID-19 are compatible with a non-autonomous SIR type model with vital dynamics and non-constant population, calibrated according to exponentially decaying infection and death rates. Using this calibration we construct a model whose outcomes for most relevant epidemiological paramenters, such as the number of active cases, cumulative deaths, daily new deaths and daily new cases (among others) fit available real data about the first and successive waves of COVID-19. In addition to this, we also provide predictions on the evolution of this pandemic in Italy and the USA in several plausible scenarios. [ABSTRACT FROM AUTHOR]

• A novel grey Richards model GERM(1,1, e a t) is proposed. • The optimal nonlinear terms and background value of the novel model are determined by Genetic algorithm. • The comparative study shows that the new model is superior to the other seven benchmark models. • The predict the daily number of new confirmed cases of COVID-19 of four regions are projected. In 2020, a new type of coronavirus is in the global pandemic. Now, the number of infected patients is increasing. The trend of the epidemic has attracted global attention. Based on the traditional Richards model and the differential information principle in grey prediction model, this paper uses the modified grey action quantity to propose a new grey prediction model for infectious diseases. This model weakens the dependence of the Richards model on single-peak and saturated S-shaped data, making Richards model more applicable, and uses genetic algorithm to optimize the nonlinear terms and the background value. To illustrate the effectiveness of the model, groups of slowly growing small-sample and large-sample data are selected for simulation experiments. Results of eight evaluation indexes show that the new model is better than the traditional GM(1,1) and grey Richards model. Finally, this model is applied to China, Italy, Britain and Russia. The results show that the new model is better than the other 7 models. Therefore, this model can effectively predict the number of daily new confirmed cases of COVID-19, and provide important prediction information for the formulation of epidemic prevention policies. [ABSTRACT FROM AUTHOR]

• Developed deep learning methods to forecast the COVID19 spread. • Five deep learning models have been compared for COVID-19 forecasting. • Time-series COVID19 data from Italy, Spain, France, China, the USA, and Australia are used. • Results demonstrate the potential of deep learning models to forecast COVID19 data. • Results show the superior performance of the Variational AutoEncoder model. The novel coronavirus (COVID-19) has significantly spread over the world and comes up with new challenges to the research community. Although governments imposing numerous containment and social distancing measures, the need for the healthcare systems has dramatically increased and the effective management of infected patients becomes a challenging problem for hospitals. Thus, accurate short-term forecasting of the number of new contaminated and recovered cases is crucial for optimizing the available resources and arresting or slowing down the progression of such diseases. Recently, deep learning models demonstrated important improvements when handling time-series data in different applications. This paper presents a comparative study of five deep learning methods to forecast the number of new cases and recovered cases. Specifically, simple Recurrent Neural Network (RNN), Long short-term memory (LSTM), Bidirectional LSTM (BiLSTM), Gated recurrent units (GRUs) and Variational AutoEncoder (VAE) algorithms have been applied for global forecasting of COVID-19 cases based on a small volume of data. This study is based on daily confirmed and recovered cases collected from six countries namely Italy, Spain, France, China, USA, and Australia. Results demonstrate the promising potential of the deep learning model in forecasting COVID-19 cases and highlight the superior performance of the VAE compared to the other algorithms. [ABSTRACT FROM AUTHOR]

• Two contrasting models are presented to understand and predict the spreading of COVID-19. • Estimation of turnaround (peak active cases) day is performed using a mathematical model for India, Italy and USA. • Trend and variability are extracted from the data for daily reported cases using DCT-based Fourier decomposition method. • Bi-modal Gaussian mixture model is fitted to the trend to predict the cases in near future. • End-dates for COVID-19 are predicted with 95% confidence interval in various parts of the world. COVID-19 is caused by a novel coronavirus and has played havoc on many countries across the globe. A majority of the world population is now living in a restricted environment for more than a month with minimal economic activities, to prevent exposure to this highly infectious disease. Medical professionals are going through a stressful period while trying to save the larger population. In this paper, we develop two different models to capture the trend of a number of cases and also predict the cases in the days to come, so that appropriate preparations can be made to fight this disease. The first one is a mathematical model accounting for various parameters relating to the spread of the virus, while the second one is a non-parametric model based on the Fourier decomposition method (FDM), fitted on the available data. The study is performed for various countries, but detailed results are provided for the India, Italy, and United States of America (USA). The turnaround dates for the trend of infected cases are estimated. The end-dates are also predicted and are found to agree well with a very popular study based on the classic susceptible-infected-recovered (SIR) model. Worldwide, the total number of expected cases and deaths are 12.7 × 106 and 5.27 × 105, respectively, predicted with data as of 06-06-2020 and 95% confidence intervals. The proposed study produces promising results with the potential to serve as a good complement to existing methods for continuous predictive monitoring of the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

a mathematical model depicting the spread of covid-19 epidemic and implementation of population covid-19 intervention in Italy. The model has 8 components leading to system of 8 ordinary differential equations. In this paper, we investigate the model using the concept of fractional differential operator. A numerical method based on the Lagrange polynomial was used to solve the system equations depicting the spread of COVID-19. A detailed investigation of stability including reproductive number using the next generation matrix, and the Lyapunov were presented in detail. Numerical simulations are depicted for various fractional orders. [ABSTRACT FROM AUTHOR]

• The very first model to predict the minimum optimal time of the lockdown. • Deliberates salient features like silent carriers, sociability of newly infected person and unregistered deaths of coronavirus infectious people along with SIR model. • Based on the awareness and sustainability of disease, the number of suspected person varies with respect to time of spreading of virus. Hence, three phases are formed to define the suspected rate as it will not grow exponentially all the time. • At first Phase, when the awareness of newly discovered virus is at initial phases, the suspecting rate will grow exponentially. Suspected rate depends on sociability of infected person. • Second Phase is during lockdown when the social distancing is followed. In this phase, death cases are more as number of current infected person are at peak. Simultaneously, the number of recovered person per day will increase. • Third Phase is when there is reduction in number of active cases. Number of suspected cases will reduce depending upon the testing speed of medical team. • In order to calculate the optimal lockdown time T opt , the approach of proposed model is to find a situation when the number suspected people starts to reduce w.r.t. time, number of infected people increases for a while but start reducing with respect to time, and also the number of recovered people rises w.r.t. time. • The model is tested on China data and is efficient enough to propose a model very close to their actual figures of infected people, recovered people, died and active cases. The model predicts the optimal lockdown period as 73 days for China which is very close to their actual lockdown period (77 days). • Also, the model is implemented to predict the optimal lockdown period of India and Italy. • The programming part is done in C++ language with Linux OS. This paper proposes a three-phase Susceptible-Infected-Recovered-Dead (3P-SIRD) model to calculate an optimal lockdown period for some specific geographical regions that will be favorable to break not only the transmission chain but also will help country's economy to recover and support infrastructure in a fight against COVID-19. Proposed model is novel since it additionally includes parameters i.e. silent carriers, sociability of newly infected person and unregistered died coronavirus infected people along with the infection rate, suspected rate and death rate. These parameters contribute a lot to figure out the more clear model, along with essential parameters. The model takes the testing rate of suspected people into consideration and this rate varies with respect to phase of the epidemic growth. Proposed 3P-SIRD model is divided into three-phases based on the awareness and sustainability of disease. Time is divided into different periods as rate of infection and recovery fluctuates region to region. The model is tested on China data and is efficient enough to propose a model very close to their actual figures of infected people, recovered people, died and active cases. The model predicts the optimal lockdown period as 73 days for China which is very close to their actual lockdown period (77 days). Further, the model is implemented to predict the optimal lockdown period of India and Italy. [ABSTRACT FROM AUTHOR]

The article discusses a study on science selection processes at Italian and Spanish universities in science subjects and its potential effect on gender-mixed committees for appointments as a way to improve male-female balance. The paper analyzed the influence of gender discrimination on underrepresentation, hiring and promotion of women in academia and examined whether evaluators fall back on stereotypes when assessing candidates in different research areas.