The absence of abdominal pigmentation in livestock associated culicoides following artificial blood feeding and the epidemiological implication for arbovirus surveillance

Culicoides midges (Diptera: Ceratopogonidae), the vectors of economically important arboviruses such as bluetongue virus and African horse sickness virus, are of global importance. In the absence of transovarial transmission, the parity rate of a Culicoides population provides imperative information regarding the risk of virus dispersal. Abdominal pigmentation, which develops after blood feeding and ovipositioning, is used as an indicator of parity in Culicoides. During oral susceptibility trials over the last three decades, a persistent proportion of blood engorged females did not develop pigment after incubation. The present study, combining a number of feeding trials and different artificial feeding methods, reports on this phenomenon, as observed in various South African and Italian Culicoides species and populations. The absence of pigmentation in artificial blood-fed females was found in at least 23 Culicoides species, including important vectors such as C. imicola, C. bolitinos, C. obsoletus, and C. scoticus. Viruses were repeatedly detected in these unpigmented females after incubation. Blood meal size seems to play a role and this phenomenon could be present in the field and requires consideration, especially regarding the detection of virus in apparent “nulliparous” females and the identification of overwintering mechanisms and seasonally free vector zones.This publication is part of the project “ArtOmic” (Grant number RF-2016-02362851) which has received funding from the Italian Ministry of Health’s Ricerca Finalizzata programme (2016).https://www.mdpi.com/journal/pathogensam2022Veterinary Tropical Disease

The use of artificial intelligence systems in diagnosis of pneumonia via signs and symptoms : a systematic review

Artificial Intelligence (AI) systems using symptoms/signs to detect respiratory diseases may improve diagnosis especially in limited resource settings. Heterogeneity in such AI systems creates an ongoing need to analyse performance to inform future research. This systematic literature review aimed to investigate performance and reporting of diagnostic AI systems using machine learning (ML) for pneumonia detection based on symptoms and signs, and to provide recommendations on best practices for designing and implementing predictive ML algorithms. This article was conducted following the PRISMA protocol, 876 articles were identified by searching PubMed, Scopus, and OvidSP databases (last search 5th May 2021). For inclusion, studies must have differentiated clinically diagnosed pneumonia from controls or other diseases using AI. Risk of Bias was evaluated using The STARD 2015 tool. Information was extracted from 16 included studies regarding study characteristics, ML-model features, reference tests, study population, accuracy measures and ethical aspects. All included studies were highly heterogenous concerning the study design, setting of diagnosis, study population and ML algorithm. Study reporting quality in methodology and results was low. Ethical issues surrounding design and implementation of the AI algorithms were not well explored. Although no single performance measure was used in all studies, most reported an accuracy measure over 90%. There is strong evidence to support further investigations of ML to automatically detect pneumonia based on easily recognisable symptoms and signs. To help improve the efficacy of future research, recommendations for designing and implementing AI tools based on the findings of this study are provided

To build or not to build? Megaprojects, resources, and environment: an emergy synthesis for a systemic evaluation of a major highway expansion

Systems thinking and emergy synthesis are applied to transport studies in order to assess the socio-ecological convenience of a civil infrastructure: they are presented as comprehensive evaluation tools to go beyond conventional approaches like cost-benefit analyses, while geobiophysically including the overall resource consumption and the release of pollutants. Focusing on road systems, the massive expansion works on the mountainous section of Italian major highway A1 are chosen as a case study: such recently completed project is compared with the no- build option, considering alternative scenarios ranging from dedicated mobility policies using the old infrastructure to a partial modal shift to rail transport. Results are expressed in terms of total invested emergy, emergy per passenger-kilometer, and per ton-kilometer; data can be easily read also in terms of environmental, physical, and financial units. The convenience of the expansion works results highly questionable: the annually required emergy is shown to significantly increase: +24% for passengers and +51% for freight averagely (i.e., with or without services besides energy and material inputs). A key role is played by saved travelling time (computed as driving labor), able to mitigate but not to reverse the situation while representing a controversial accounting item. Instead, alternative uses and policies for the old infrastructure would all have yielded significant savings. In light of the above, some conclusions are drawn on societal priorities, including a critical reappraisal of time saving as an often unsustainable driver within a still mostly unquestioned 'more and faster' mantra. The need to support ecologically and strategically sustainable societal decision-making in the transportation sector is therefore framed in wider thoughts on economic planning and resource allocation, while envisaging a transformation towards a prosperous and sustainable future

The Gaia mission

Gaia is a cornerstone mission in the science programme of the EuropeanSpace Agency (ESA). The spacecraft construction was approved in 2006, following a study in which the original interferometric concept was changed to a direct-imaging approach. Both the spacecraft and the payload were built by European industry. The involvement of the scientific community focusses on data processing for which the international Gaia Data Processing and Analysis Consortium (DPAC) was selected in 2007. Gaia was launched on 19 December 2013 and arrived at its operating point, the second Lagrange point of the Sun-Earth-Moon system, a few weeks later. The commissioning of the spacecraft and payload was completed on 19 July 2014. The nominal five-year mission started with four weeks of special, ecliptic-pole scanning and subsequently transferred into full-sky scanning mode. We recall the scientific goals of Gaia and give a description of the as-built spacecraft that is currently (mid-2016) being operated to achieve these goals. We pay special attention to the payload module, the performance of which is closely related to the scientific performance of the mission. We provide a summary of the commissioning activities and findings, followed by a description of the routine operational mode. We summarise scientific performance estimates on the basis of in-orbit operations. Several intermediate Gaia data releases are planned and the data can be retrieved from the Gaia Archive, which is available through the Gaia home page. http://www.cosmos.esa.int/gai

Il problema dello smaltimento in Lo ’stato dell'arte e prospettive in materia di contrasto alle patologie asbesto correlate.‘

Il problema dello smaltiment