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The promontory of Ras il-Pellegrin, located in the northwestern part of Malta, is nowadays an isolated,yet archaeologically rich site. The few archaeological studies on this promontory and in the surrounding area indicate an interesting prehistoric use for two principal activities: procurement of chert from the exposed Middle Globigerina levels and bay access. Through the analysis of the lithic assemblage from the site, this study attempts to provide a glimpse on the movement of raw materials and the exploitation of the local chert through a site-landscape relation. N/A

AbstractExtensive canyons, excavated into the margins of the Levant Basin during the Oligocene–Miocene, are interesting case-studies for canyon fills in carbonate settings. The carbonate Pattish Formation, developed along the margins of the pre-evaporitic Messinian Beer Sheva Canyon in Israel, was investigated using both onshore seismic imaging and field data. The canyon has three main seismic facies of fill (1) Subparallel reflections mimicking the canyon´s morphology; (2) chaotic reflections overlying the subparallel ones, and (3) sigmoidal reflections, locally with sharp edges at the canyon margins. The first seismic facies corresponds to the pelagic marls of the Bet Eshel Formation. The other two seismic facies are, respectively, equivalent to bioclastic calcarenite clinobeds with slumps and channels, and to coral–stromatolite reefs and reef slopes of the Pattish Formation observed at outcrop. There were three phases of canyon development: (1) slope incision and headward erosion due to tectonic uplift and eustatic sea-level fall during the Early Oligocene, and large slope failure during the latest Middle Miocene; (2) platform incision and connection with a fluvial system in the Late Miocene related to falling sea level and tectonic uplift; and (3) canyon filling first by pelagic marls at the centre of the canyon, followed by calcarenite clinobeds at the canyon flanks formed by gravity flows. Finally, carbonate production at the margins of the canyon resulted in reefs and associated slopes prograding towards the canyon axis. The late canyon filling phase ended with the deposition of evaporites during the Messinian Salinity Crisis.

The collective control programmes (CPs) that exist for many infectious diseases of farm animals rely on the application of diagnostic testing at regular time intervals for the identification of infected animals or herds. The diversity of these CPs complicates the trade of animals between regions or countries because the definition of freedom from infection differs from one CP to another. In this paper, we describe a statistical model for the prediction of herd-level probabilities of infection from longitudinal data collected as part of CPs against infectious diseases of cattle. The model was applied to data collected as part of a CP against bovine viral diarrhoea virus (BVDV) infection in Loire-Atlantique, France. The model represents infection as a herd latent status with a monthly dynamics. This latent status determines test results through test sensitivity and test specificity. The probability of becoming status positive between consecutive months is modelled as a function of risk factors (when available) using logistic regression. Modelling is performed in a Bayesian framework, using either Stan or JAGS. Prior distributions need to be provided for the sensitivities and specificities of the different tests used, for the probability of remaining status positive between months as well as for the probability of becoming positive between months. When risk factors are available, prior distributions need to be provided for the coefficients of the logistic regression, replacing the prior for the probability of becoming positive. From these prior distributions and from the longitudinal data, the model returns posterior probability distributions for being status positive for all herds on the current month. Data from the previous months are used for parameter estimation. The impact of using different prior distributions and model implementations on parameter estimation was evaluated. The main advantage of this model is its ability to predict a probability of being status positive in a month from inputs that can vary in terms of nature of test, frequency of testing and risk factor availability/presence. The main challenge in applying the model to the BVDV CP data was in identifying prior distributions, especially for test characteristics, that corresponded to the latent status of interest, i.e. herds with at least one persistently infected (PI) animal. The model is available on Github as an R package (https://github.com/AurMad/STOCfree) and can be used to carry out output-based evaluation of disease CPs. European Food Safety Authority (EFSA)

This paper attempts to give an idea of the sonorous past of prehistoric Malta by presenting possible soundscape scenarios. It validates the importance of sound as auditory experience, because this was crucial in the history of humanity, while it attempts to trace the beginnings of organised sound. This research is to introduce a number of findings that are connected to sound perception and distribution among the inhabitants of Malta. Specific emphasis is given to discussions of whether these sounds were essentially intentional or not. By going through the collected facts about the introduced findings, there are overlaps in functions and sound tools that indicate an early cultivation of music. In protecting the related findings, some of these early attempts can be hopefully reconstructed in the future.

Thirty-three species of Chalcidoidea (Hymenoptera) are newly recorded from the Maltese Islands, of which, 19 include host data. An updated checklist for the 181 chalcidoid species recorded from Malta is also included, which belong to 17 families as follows: Agaonidae (3), Aphelinidae (21, 1 as new record), Azotidae (1), Chalcididae (8 species, 5 as new records), Encyrtidae (24, 1 as new record), Eulophidae (51, 16 are new records), Eupelmidae (9, 2 as new records), Eurytomidae (6, 1 as new record), Leucospidae (4), Megastigmidae (1), Mymaridae (2), Ormyridae (1), Perilampidae (1 new record), Pteromalidae (39, 5 as new records), Signiphoridae (2), Tetracampidae (1) and Torymidae (7, 1 as new record). peer-reviewed

In the framework of H2020, the European Commission recently funded the project ReSHEALience (www.uhdc.eu). The main idea behind the project is that the long-term behaviour of structures under extremely aggressive exposure conditions can highly benefit from the use of high performance materials, in the framework of durability-based design approaches. The project consortium, coordinated by Politecnico di Milano, features 14 partners from 8 different countries, including 6 academic/research institutions and 8 industrial partners, covering the whole value chain from producers of concrete constituents to construction companies to stake-holders and end-users. The main goals of the project are the development (a) of an Ultra High Durability Concrete (UHDC) and (b) a Durability Assessment-based Design (DAD) methodology to improve structure durability and predict long-term performance under Extremely Aggressive Exposures (EAE). The project will tailor the composition of UHDC, by upgrading the UHPC/UHPFRC concept through the incorporation of tailored nanoscale constituents. Trabajo presentado al International Association for Bridge and Structural Engineering (IABSE): Towards a Resilient Built Environment - Risk and Asset Management, celebrado en Guimarães (Portugal) del 27 al 29 de marzo de 2019. The ReSHEALience project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 760824. Peer reviewed

The question of representing emotion computationally remains largely unanswered: popular approaches require annotators to assign a magnitude (or a class) of some emotional dimension, while an alternative is to focus on the relationship between two or more options. Recent evidence in affective computing suggests that following a methodology of ordinal annotations and processing leads to better reliability and validity of the model. This paper compares the generality of classification methods versus preference learning methods in predicting the levels of arousal in two widely used affective datasets. Findings of this initial study further validate the hypothesis that approaching affect labels as ordinal data and building models via preference learning yields models of better validity. peer-reviewed