Genetic architecture of parallel armor plate reduction in threespine sticklebacks

Journal ArticleHow many genetic changes control the evolution of new traits in natural populations? Are the same genetic changes seen in cases of parallel evolution? Despite long-standing interest in these questions, they have been difficult to address, particularly in vertebrates. We have analyzed the genetic basis of natural variation in three different aspects of the skeletal armor of threespine sticklebacks (Gasterosteus aculeatus): the pattern, number, and size of the bony lateral plates. A few chromosomal regions can account for variation in all three aspects of the lateral plates, with one major locus contributing to most of the variation in lateral plate pattern and number. Genetic mapping and allelic complementation experiments show that the same major locus is responsible for the parallel evolution of armor plate reduction in two widely separated populations. These results suggest that a small number of genetic changes can produce major skeletal alterations in natural populations and that the same major locus is used repeatedly when similar traits evolve in different locations

Spatio-temporal Analysis of Thermal Profiles in Extrusion-based Additive Manufacturing

Extrusion-based Additive Manufacturing (AM) processes have recently gained increasing attention in the scientific and industrial communities because of the wide range of processible materials (from thermoplastics to composite and biomaterials), printable volumes, and industrial applications. As for many other AM processes, the actual problems with process stability and repeatability are still limiting the industrial process adoption, as these problems can significantly impact on the final part quality. In this framework, a latest research trend aims at developing in-situ monitoring solutions for inline defect detection, in a zero-waste production perspective. Among the existing in-situ sensing techniques, many studies showed that in-situ thermography represents a viable solution to describe the temperature dynamic and validate the thermal models but very few approaches have been proposed to quantitively study the temperature evolution to quickly detect process instabilities. This paper presents a new approach to quickly analyse the temporal dynamic of temperature in the printed layer while providing a spatial mapping of the temperature homogeneities. Compared with previous methods, the current one has the main novelty feature of combining both the spatial and temporal signature in a synthetic mapping that allows to detect unstable or unusual problems. In order to show the effectiveness of the proposed solution, a real case study of Big Area Additive Manufacturing (BAAM) for composite materials is considered. The study shows that the provided method can clearly enhance defect detection and represents a new solution for detecting anomalous areas where thermal profiles behave differently with respect to the surrounding areas. The same methodology underlined the thermal evolution complexity in the BAAM case study and enabled the detection of local flaws, i.e., hot and cold spots

Robust in-line qualification of lattice structures manufactured via laser powder bed fusion

The shape complexity enabled by AM would impose new part inspection systems (e.g., x-ray computed tomography), which translate into qualification time and costs that may be not affordable. However, the layerwise nature of the process potentially allows anticipating qualification tasks in-line and in-process, leading to a quick detection of defects since their onset stage. This opportunity is particularly attractive in the presence of lattice structures, whose industrial adoption has considerably increased thanks to AM. This paper presents a novel methodology to model the quality of lattice structures at unit cell level while the part is being built, using high resolutions images of the powder bed for in-line geometry reconstruction and identification of deviations from the nominal shape. The methodology is designed to translate complex 3D shapes into 1D deviation profiles that capture the “geometrical signature” of the cell together with the reconstruction uncertainty

Design Performance Analysis of a Self-Organizing Map for Statistical Monitoring of Distribution-free Data Streams

In industrial applications, the continuously growing development of multi-sensor approaches, together with the trend of creating data-rich environments, are straining the effectiveness of the traditional Statistical Process Control (SPC) tools. Industrial data streams frequently violate the statistical assumptions on which SPC tools are based, presenting non-normal or even mixture distributions, strong autocorrelation and complex noise patterns. To tackle these challenges, novel nonparametric approaches are required. Machine learning techniques are suitable to deal with distributional assumption violations and to cope with complex data patterns. Recent studies showed that those methods can be used in quality control problems by exploiting only in-control data for training (such a learning paradigm is also known as “one-class-classification”). In recent studies, the use of distribution-free multivariate SPC methods was proposed, based on unsupervised statistical learning tools, pointing out the difficulty of defining suitable control regions for non-normal data. In this paper, a Self-Organizing Map (SOM) based monitoring approach is presented. The SOM is an automatic data-analysis method, widely applied in recent works to clustering and data exploration problems. A very interesting feature of this method consists of its capability of providing a computationally efficient way to estimate a data-adaptive control region, even in the presence of high dimensional problems. Nevertheless, very few authors adopted the SOM in an SPC monitoring strategy. The aim of this work is to exploit the SOM network architecture, and proposing a network design approach that suites the SPC needs. A comparison study is presented, in which the process monitoring performances are compared against literature benchmark methods. The comparison framework is based on both simulated data and real data from a roll grinding application

Forensic textile damage analysis: Practical issues and methodological perspectives

Clothing damage analysis is an important tool for forensic investigations and, even it is a niche field, it is gaining interest. Moreover, the attention is shifting from evaluating just the “biological” traces found on the clothes to the modifications that clothes themselves undergo in the context of a specific traumatic dynamic. The Authors analyze a case of the investigation on a hole in the jacket worn by the victim when he was attacked, performed through optical microscope and morphological and elemental SEM/EDX analysis, to determine the origin of this texture damage to verify a witness story

Determination of the CNGS global geodesy

This paper describes the activities carried out in order to estimate the distance traveled by the neutrinos beam between CERN and LNGS with an accuracy better than 1 meter. In particular, the distance between two fundamental points has been estimated: the start point at CERN (de ned as T-40-S-CERN) and the OPERA detector point (de ned as A1-9999). The measurements campaings, at CERN and at LNGS, were performed using both terrestrial and Global Positioning System (GPS) based geodetic techniques. The positions of the two fundamental points were estimated in a common reference frame through the processing of the collected observations. The resulting distance (730534.610 m) was estimated with an accuracy at the level of 20 cm, remarkably better than the stated limit

Avaliação antropométrica longitudinal de lactentes nascidos de mães infectadas pelo HIV-1

OBJETIVO: Evaluar los parámetros de crecimiento en lactantes nacidos de madres infectadas con el VIH-1. MÉTODOS: Evaluación longitudinal de los z-escores peso-edad (PI), estatura-edad (EI), peso-estatura (PE) fue realizada en una cohorte. Fueran estudiados 97 lactantes no infectados y 33 lactantes infectados nacidos de madres infectadas con el VIH-1 en Belo Horizonte, Sureste de Brasil, de 1995 a 2003. El tiempo medio de seguimiento para los lactantes infectados y no infectados fue de 15,8 meses (variación: 6,8 a 18,0 meses) y 14,3 meses (variación: 6,3 a 18,6 meses), respectivamente. Se utilizó el modelo de regresión linear de efectos mixtos ajustado por máxima verosimilitud restringida para construir las curvas de crecimiento. RESULTADOS: Los z-escores PI, EI y PE de los lactantes infectados con el VIH-1 presentaron decrecimiento. A los seis meses, la diferencia promedio en los z-escores PI, EI y PE entre lactantes infectados y no infectados con el VIH era, respectivamente, 1,02, 0,59 y 0,63 desviaciones-estándares. A los 12 meses, la diferencia promedio en los z-escores PI, EI y PE entre lactantes infectados y no infectados era, respectivamente, 1,15, 1,01 y 0,87 desviaciones-estándares. CONCLUSIONES: El comprometimiento precoz y creciente de los indicadores antropométricos de niños infectados con el VIH-1 muestra la importancia de identificar precozmente niños infectados con el VIH que están en riesgo nutricional y la necesidad de evaluarse continuamente las intervenciones nutricionales adoptadas.OBJECTIVE: To evaluate the growth parameters in infants who were born to HIV-1-infected mothers. METHODS: The study was a longitudinal evaluation of the z-scores for the weight-for-age (WAZ), weight-for-length (WLZ) and length-for-age (LAZ) data collected from a cohort. A total of 97 non-infected and 33 HIV-infected infants born to HIV-1-infected mothers in Belo Horizonte, Southeastern Brazil, between 1995 and 2003 was studied. The average follow-up period for the infected and non-infected children was 15.8 months (variation: 6.8 to 18.0 months) and 14.3 months (variation: 6.3 to 18.6 months), respectively. A mixed-effects linear regression model was used and was fitted using a restricted maximum likelihood. RESULTS: There was an observed decrease over time in the WAZ, LAZ and WLZ among the infected infants. At six months of age, the mean differences in the WAZ, LAZ and WLZ between the HIV-infected and non-infected infants were 1.02, 0.59, and 0.63 standard deviations, respectively. At 12 months, the mean differences in the WAZ, LAZ and WLZ between the HIV-infected and non-infected infants were 1.15, 1.01, and 0.87 standard deviations, respectively. CONCLUSIONS: The precocious and increasing deterioration of the HIV-infected infants' anthropometric indicators demonstrates the importance of the early identification of HIV-infected infants who are at nutritional risk and the importance of the continuous assessment of nutritional interventions for these infants.OBJETIVO: Avaliar os parâmetros de crescimento em lactentes nascidos de mães infectadas com o HIV-1. MÉTODOS: Avaliação longitudinal dos z-escores peso-idade (PI), estatura-idade (EI), peso-estatura (PE) foi realizada em uma coorte. Foram estudados 97 lactentes não-infectados e 33 lactentes infectados nascidos de mães infectadas com o HIV-1 em Belo Horizonte, MG, de 1995 a 2003. O tempo mediano de seguimento para os lactentes infectados e não-infectados foi de 15,8 meses (variação: 6,8 a 18,0 meses) e 14,3 meses (variação: 6,3 a 18,6 meses), respectivamente. Utilizou-se o modelo de regressão linear de efeitos mistos ajustado por máxima verossimilhança restrita para construir as curvas de crescimento. RESULTADOS: Os z-escores PI, EI e PE dos lactentes infectados com o HIV-1 apresentaram decréscimo. Aos seis meses, a diferença média nos z-escores PI, EI e PE entre lactentes infectados e não-infectados com o HIV era, respectivamente, 1,02, 0,59 e 0,63 desvios-padrão. Aos 12 meses, a diferença média nos z-escores PI, EI e PE entre lactentes infectados e não-infectados era, respectivamente, 1,15, 1,01 e 0,87 desvios-padrão. CONCLUSÕES: O comprometimento precoce e crescente dos indicadores antropométricos de crianças infectadas com o HIV-1 mostra a importância de identificar precocemente crianças infectadas com o HIV que estão em risco nutricional e a necessidade de se avaliarem continuamente as intervenções nutricionais adotadas

An innovative agro-forestry supply chain for residual biomass : physicochemical characterisation of biochar from olive and hazelnut pellets

Concerns about climate change and food productivity have spurred interest in biochar, a form of charred organic material typically used in agriculture to improve soil productivity and as a means of carbon sequestration. An innovative approach in agriculture is the use of agro-forestry waste for the production of soil fertilisers for agricultural purposes and as a source of energy. A common agricultural practice is to burn crop residues in the field to produce ashes that can be used as soil fertilisers. This approach is able to supply plants with certain nutrients, such as Ca, K, Mg, Na, B, S, and Mo. However, the low concentration of N and P in the ashes, together with the occasional presence of heavy metals (Ni, Pb, Cd, Se, Al, etc.), has a negative effect on soil and, therefore, crop productivity. This work describes the opportunity to create an innovative supply chain from agricultural waste biomass. Olive (Olea europaea) and hazelnut (Corylus avellana) pruning residues represent a major component of biomass waste in the area of Viterbo (Italy). In this study, we evaluated the production of biochar from these residues. Furthermore, a physicochemical characterisation of the produced biochar was performed to assess the quality of the two biochars according to the standards of the European Biochar Certificate (EBC). The results of this study indicate the cost-effective production of high-quality biochar from olive and hazelnut biomass residues