Geoarcheologicalprospection of megalithic structures using Ground Penetrating Radar (Almendralejo, Spain)

In 1980, in Almendralejo, Spain, it was discovered the Tomb of Huerta Montero, a megalithic funerary monument, the best preserved in the Iberian Peninsula, dating from the Chalcolithic (Copper Age, about 4650 BC). According to the opinion of archaeologists, it is quite probable that there are similar buried monuments in the vicinity of the known tomb. This suspicion led to the geophysical study, carried out with the aim of identifying new structures in the vicinity of the necropolis discovered. The choice of geophysical method it was the GPR, because it is a non-invasive technique, accurate and rapid in its implementation. The results obtained allow us to conclude that there may be a structure of circular shape, with a diameter of about 7 m which may to correspond to a funeral monument as there are a few meters, with a temporal thickness ranging between 13 and 21 ns deep. In the northern part of the structure there are two protrusions that may match an entry in the building or even the rest of the tunnel entrance

Addressing preference heterogeneity in public health policy by combining Cluster Analysis and Multi-Criteria Decision Analysis: Proof of Method.

The use of subgroups based on biological-clinical and socio-demographic variables to deal with population heterogeneity is well-established in public policy. The use of subgroups based on preferences is rare, except when religion based, and controversial. If it were decided to treat subgroup preferences as valid determinants of public policy, a transparent analytical procedure is needed. In this proof of method study we show how public preferences could be incorporated into policy decisions in a way that respects both the multi-criterial nature of those decisions, and the heterogeneity of the population in relation to the importance assigned to relevant criteria. It involves combining Cluster Analysis (CA), to generate the subgroup sets of preferences, with Multi-Criteria Decision Analysis (MCDA), to provide the policy framework into which the clustered preferences are entered. We employ three techniques of CA to demonstrate that not only do different techniques produce different clusters, but that choosing among techniques (as well as developing the MCDA structure) is an important task to be undertaken in implementing the approach outlined in any specific policy context. Data for the illustrative, not substantive, application are from a Randomized Controlled Trial of online decision aids for Australian men aged 40-69 years considering Prostate-specific Antigen testing for prostate cancer. We show that such analyses can provide policy-makers with insights into the criterion-specific needs of different subgroups. Implementing CA and MCDA in combination to assist in the development of policies on important health and community issues such as drug coverage, reimbursement, and screening programs, poses major challenges -conceptual, methodological, ethical-political, and practical - but most are exposed by the techniques, not created by them