Predicting sense of community and participation by applying machine learning to open government data

Community capacity is used to monitor socio-economic development. It is composed of a number of dimensions, which can be measured to understand the possible issues in the implementation of a policy or the outcome of a project targeting a community. Measuring community capacity dimensions is usually expensive and time consuming, requiring locally organised surveys. Therefore, we investigate a technique to estimate them by applying the Random Forests algorithm on secondary open government data. Our research focuses on the prediction of measures for two dimensions: sense of community and participation. The most important variables for this prediction were determined. The variables included in the datasets used to train the predictive models complied with two criteria: nationwide availability; sufficiently fine-grained geographic breakdown, i.e. neighbourhood level. The models explained 77% of the sense of community measures and 63% of participation. Due to the low geographic detail of the outcome measures available, further research is required to apply the predictive models to a neighbourhood level. The variables that were found to be more determinant for prediction were only partially in agreement with the factors that, according to the social science literature consulted, are the most influential for sense of community and participation. This finding should be further investigated from a social science perspective, in order to be understood in depth

Detecting Common Longevity Trends by a Multiple Population Approach

Recently the interest in the development of country and longevity risk models has been growing. The investigation of long-run equilibrium relationships could provide valuable information about the factors driving changes in mortality, in particular across ages and across countries. In order to investigate cross-country common longevity trends, tools to quantify, compare, and model the strength of dependence become essential. On one hand, it is necessary to take into account either the dependence for adjacent age groups or the dependence structure across time in a single population setting-a sort of intradependence structure. On the other hand, the dependence across multiple populations, which we describe as interdependence, can be explored for capturing common long-run relationships between countries. The objective of our work is to produce longevity projections by taking into account the presence of various forms of cross-sectional and temporal dependencies in the error processes of multiple populations, considering mortality data from different countries. The algorithm that we propose combines model-based predictions in the Lee-Carter (LC) framework with a bootstrap procedure for dependent data, and so both the historical parametric structure and the intragroup error correlation structure are preserved. We introduce a model which applies a sieve bootstrap to the residuals of the LC model and is able to reproduce, in the sampling, the dependence structure of the data under consideration. In the current article, the algorithm that we build is applied to a pool of populations by using ideas from panel data; we refer to this new algorithm as the Multiple Lee-Carter Panel Sieve (MLCPS). We are interested in estimating the relationship between populations of similar socioeconomic conditions. The empirical results show that the MLCPS approach works well in the presence of dependence

Reproducing Hierarchies at the APSA Annual Meeting: Patterns of Panel Attendance by Gender, Race, and Ethnicity

Research on the political science profession has shown that homophilous research networks—that is, those organized along the lines of gender and race/ethnicity—reproduce hierarchies. Research networks composed of white men experience the most prestige and lead to the most opportunities. This study documents homophilous networks in a setting where they likely are nurtured: academic conferences. Drawing data from the 2019 Annual Meeting of the American Political Science Association, we examine the correspondence between the gender and the racial/ethnic composition of section members, panelists, and audience members for four research sections: Political Methodology; Political Psychology; Race, Ethnicity, and Politics; and Women and Politics. We find that attendees’ and panelists’ gender and racial/ethnic identity largely mirror the dominant gender and racial/ethnic group in their section. These findings indicate that homophily manifests at academic conferences and that efforts to diversify research networks should consider who listens to whom in these settings

Similarities between skin culturable bacterial species of pool frogs (Pelophylax lessonae) and their habitat

The aim of the present study was to investigate the culturable microflora of pool frogs (Pelophylax lessonae) and their belonging aquatic environment. A total of 60 samples (56 frog cutaneous swabs, 4 water samples) were inoculated onto different selective and differential agar plates to isolate Grampositive and Gram-negative bacteria or yeasts. Microbial investigation of the water hosting frogs was also performed. Isolates were identified by API system and their antibiotic resistance profiles were evaluated by disk diffusion method on Mueller Hinton agar plates. Aeromonas hydrophila and Enterococcus durans were detected in almost all collected samples. Many of the bacterial isolates showed multidrug-resistant profiles. Importantly, this study highlights that skin frog microbiota is correlated to the belonging environment, and, moreover, some isolated bacterial strains resulted to be of interest in animal and public health, since the park was frequented by visitors of all ages

Build orientation effect on Ti6Al4V thin-wall topography by electron beam powder bed fusion

Additive Manufacturing is a key enabling technology for Industry 4.0 and the Green Deal, allowing more efficient resources exploitation while providing innovative design to critical components. Electron Beam Powder Bed Fusion (EB-PBF) is an edge technology for many sectors, i.e. aerospace, medical, and automotive. The control of the surface finish by surface topography measurements is essential to engineer surface functional properties, whose specifications are application specific. This works investigates the effect of thin-wall orientation and surface inclination on the topography, described by areal field and feature parameters, to provide designers with a useful tool in the early stage of product development and tolerance specification and verificatio

Silicon detectors for the n-TOF neutron beams monitoring

During 2014 the second experimental area EAR2 was completed at the n-TOF neutron beam facility at CERN. As the neutrons are produced via spallation, by means of a high-intensity 20 GeV pulsed proton beam impinging on a thick target, the resulting neutron beam covers an enormous energy range, from thermal to several GeV. In this paper we describe two beam diagnostic devices, designed and built at INFN-LNS, both exploiting silicon detectors coupled with neutron converter foils containing 6Li. The first one is based on four silicon pads and allows to monitor the neutron beam flux as a function of the neutron energy. The second one, based on position sensitive silicon detectors, is intended for the reconstruction of the beam profile, again as a function of the neutron energy. Several electronic setups have been explored in order to overcome the issues related to the gamma flash, namely a huge pulse present at the start of each neutron bunch which may blind the detectors for some time. The two devices have been characterized with radioactive sources at INFN-LNS and then tested at n-TOF. The wide energy and intensity range they proved capable of sustaining, made them quite attractive and suitable to be used in both EAR1 and EAR2 n-TOF experimental areas, where they became immediately operational.Comment: submitted to Review of Scientific Instrument

Sars-cov-2 detection in fecal sample from a patient with typical findings of covid-19 pneumonia on ct but negative to multiple sars-cov-2 rt-pcr tests on oropharyngeal and nasopharyngeal swab samples

Reverse transcriptase polymerase chain reaction (RT-PCR) negative results in the upper respiratory tract represent a major concern for the clinical management of coronavirus disease 2019 (COVID-19) patients. Herein, we report the case of a 43-years-old man with a strong clinical suspicion of COVID-19, who resulted in being negative to multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RT-PCR tests performed on different oropharyngeal and nasopharyngeal swabs, despite serology having confirmed the presence of SARS-CoV-2 IgM. The patient underwent a chest computed tomography (CT) that showed typical imaging findings of COVID-19 pneumonia. The presence of viral SARS-CoV-2 was confirmed only by performing a SARS-CoV-2 RT-PCR test on stool. Performing of SARS-CoV-2 RT-PCR test on fecal samples can be a rapid and useful approach to confirm COVID-19 diagnosis in cases where there is an apparent discrepancy between COVID-19 clinical symptoms coupled with chest CT and SARS-CoV-2 RT-PCR tests’ results on samples from the upper respiratory tract

Use of biodegradable materials as alternative packaging of typical Calabrian Provola cheese

Calabrian Provola cheese is typically manufactured in the Southern Italy. The request of a more suitable expansion in the national market has promoted this research, based on the evaluation of biodegradable packaging on its qualitative characteristics as alternative of the conventional plastic multilayer film. The tested materials were: Polyethylene/Ethylene vinyl alcohol/Polyamide/Polyethylene (PE/EVOH/PA/PE), Polylactic acid (PLA), coated with a silicon oxide barrier, and Cellophane, coated with resins. The results of this study evidenced that the material based on PLA can be considered a valid alternative packaging because of the quality maintenance of Calabrian Provola cheese and its sustainable characteristics

A Robotic arm for optical and gamma radwaste inspection

We propose Radibot, a simple and cheap robotic arm for remote inspection, which interacts with the radwaste environment by means of a scintillation gamma detector and a video camera representing its light (< 1 kg) payload. It moves vertically thanks to a crane, while the other three degrees of freedom are obtained by means of revolute joints. A dedicated algorithm allows to automatically choose the best kinematics in order to reach a graphically selected position, while still allowing to fully drive the arm by means of a standard videogame joypad