Neutron diffraction study of Bronze Age tools from second millennium BC dwellings in Italy

Neutron diffraction was utilized to characterise XX to XIII century BC bronze axes (Ancient to Late Bronze Age) from "Terramare" and other Bronze Age settlements near Modena, Italy. Archaeometric metallurgy issues have been addressed by means of phase and texture analysis from measurements carried out at the ROTAX and GEM beam lines of the neutron spallation source ISIS of the Rutherford Appleton Laboratory (UK), Neutron data provide accurate composition and structural information from the bulk of the alloy, with good grain statistics, without limitations due to surface alterations and with few limitations as to sample size. Bronze composition results are in good agreement with data obtained by micro-sampling and traditional analytical techniques thus confirming the validity of the method used for a totally non-destructive determination of the alloy composition from precise lattice parameter measurements. Phase analysis from diffraction profiles provides identification and quantification of surface alteration and corrosion products, free of interference with the analysis of the bulk alloy. Furthermore, texture analysis techniques may yield information on the ancient production methods of the artefacts. © Società Italians di Fisica

Neutron diffraction study of Bronze Age tools from second millennium BC dwellings in Italy

Neutron diffraction was utilized to characterise XX to XIII century BC bronze axes (Ancient to Late Bronze Age from “Terramare” and other Bronze Age settlements near Modena, Italy. Archaeometric metallurgy issues have been addressed by means of phase and texture analysis from measurements carried out at the ROTAX and GEM beam lines of the neutron spallation source ISIS of the Rutherford Appleton Laboratory (UK). Neutron data provide accurate composition and structural information from the bulk of the alloy, with good grain statistics, without limitations due to surface alterations and with few limitations as to sample size. Bronze composition results are in good agreement with data obtained by micro-sampling and traditional analytical techniques thus confirming the validity of the method used for a totally non-destructive determination of the alloy composition from precise lattice parameter measurements. Phase analysis from diffraction profiles provides identification and quantification of surface alteration and corrosion products, free of interference with the analysis of the bulk alloy. Furthermore, texture analysis techniques may yield information on the ancient production methods of the artefacts

Archaeometric studies at the GILDA beamline at the European Synchrotron Radiation Facility

In the latest years archaeometry scientists have directed a growing interest to synchrotron radiation techniques. The Italian CRG beamline GILDA at the European Synchrotron Radiation Facility provides to the users the access to experimental techniques like X-ray absorption spectroscopy and diffraction that are of great potential usefulness in this field. Here we give a technical overview of the instrumentation available as well as some examples among the archaeometry studies presently in progress on the beamline

Study Projectile Motion With Different Initial Conditions Using Digital Image

The aim of this research is building algorithms to study projectile motion in tow dimension  and tracking the object in sequence frames of digital image . Computer program has written in visual basic language (version 6) depend on mathematical models to detect a motion of object in two–dimensions (2-D)with different initial conditions like initial velocity, the height of object from the earth and the angle of motion, to calculate important variables in motion such as distance, displacement, velocity, speed and the energy (kinetic and potential). Color digital images of type (bmp) and (RGB) color model were used in the study for easy handling them, after determining the center of the image on the x-axis, and y-axis and tracking movement on the basis of the center, and the results were expected to conform to the movement of the body. Key words: Projectile, Motion, Digital Image

Ancient encaustic: An experimental exploration of technology, ageing behaviour and approaches to analytical investigation

The composition of the ancient wax-based painting technique known as encaustic has long been the subject of debate. Ancient sources provide few details of the technology, and modern understanding of the medium is restricted to theoretical interpretation and experimental observation. In this multi-analytical collaborative study, a number of analytical approaches were used to investigate the physical and molecular properties of a range of experimentally prepared encaustic paints before and after ageing. Analysis using gas chromatography mass spectrometry, Fourier transform infrared spectroscopy (invasive and non-invasive), X-ray diffraction and thermogravimetric analysis demonstrated how differences in the technology of production alter the properties and composition of the medium and showed how these are modified by the addition of pigment and the effects of ageing. Comparison of results from the different analytical techniques highlights the benefit of an integrated analytical approach to the analysis of ancient encaustic paints and the fundamental importance of insights from invasive study to evaluating the results of non-invasive analysis

Manejo do dossel vegetativo e seu efeito nos componentes de produção da videira Merlot.

A poda verde é uma prática cultural utilizada para melhorar as condições do dossel vegetativo dos vinhedos, visando a favorecer a qualidade da uva e do vinho. Nesse sentido, realizou-se este experimento entre as safras de 1993/1994 e 1996/1997, com diferentes modalidades de poda verde, num vinhedo do cv. Merlot conduzido em latada. Houve 12 tratamentos e três repetições, sendo o delineamento experimental em blocos casualizados. Os tratamentos constituíram-se da testemunha e de 11 diferentes modalidades de poda verde, ou seja, desbrota, desponta e desfolha, algumas delas em diferentes épocas do ciclo vegetativo da videira. O componente principal 1, da análise de componentes principais (ACP) feita em cada ano, separadamente, mostra que o tratamento 10 (desbrota + desponta + desfolha realizada no início da floração, eliminando-se as folhas abaixo dos cachos) discriminou-se nos quatro anos, e os tratamentos 7 (desfolha realizada 21 dias antes da colheita, eliminando-se metade das folhas abaixo dos cachos) e 6 (desfolha realizada 21 dias antes da colheita, eliminando-se as folhas abaixo dos cachos), em três deles; a ACP da média dos quatro anos também evidencia essa discriminação entre eles. Constata-se que o tratamento 10 foi um dos que tiveram intensidade de poda verde mais intensa, caracterizando-se por variáveis indicativas de plantas com vigor e produtividade mais baixos que os demais

Longitudinal machine learning modeling of MS patient trajectories improves predictions of disability progression

Background and Objectives: Research in Multiple Sclerosis (MS) has recently focused on extracting knowledge from real-world clinical data sources. This type of data is more abundant than data produced during clinical trials and potentially more informative about real-world clinical practice. However, this comes at the cost of less curated and controlled data sets. In this work we aim to predict disability progression by optimally extracting information from longitudinal patient data in the real-world setting, with a special focus on the sporadic sampling problem. Methods: We use machine learning methods suited for patient trajectories modeling, such as recurrent neural networks and tensor factorization. A subset of 6682 patients from the MSBase registry is used. Results: We can predict disability progression of patients in a two-year horizon with an ROC-AUC of 0.85, which represents a 32% decrease in the ranking pair error (1-AUC) compared to reference methods using static clinical features. Conclusions: Compared to the models available in the literature, this work uses the most complete patient history for MS disease progression prediction and represents a step forward towards AI-assisted precision medicine in MS