Nouveau manuel complet du tisserand, ou Description des procédés et machines employés pour les divers tissages des matières organiques filamenteuses ; suivi d'une Histoire de la filature et du tissage, depuis les temps les plus reculés jusqu'à nos jours / par E. Lorentz et C.-E. Jullien,...

Collection : Manuels Roret

Comparison of Setting Time Measured Using Ultrasonic Wave Propagation with Saw-Cutting Times on Pavements, TR-675, 2015

At present, there is little fundamental guidance available to assist contractors in choosing when to schedule saw cuts on joints. To conduct pavement finishing and sawing activities effectively, however, contractors need to know when a concrete mixture is going to reach initial set, or when the sawing window will open. Previous research investigated the use of the ultrasonic pulse velocity (UPV) method to predict the saw-cutting window for early entry sawing. The results indicated that the method has the potential to provide effective guidance to contractors as to when to conduct early entry sawing. The aim of this project was to conduct similar work to observe the correlation between initial setting and conventional sawing time. Sixteen construction sites were visited in Minnesota and Missouri over a two-year period. At each site, initial set was determined using a p-wave propagation technique with a commercial device. Calorimetric data were collected using a commercial semi-adiabatic device at a majority of the sites. Concrete samples were collected in front of the paver and tested using both methods with equipment that was set up next to the pavement during paving. The data collected revealed that the UPV method looks promising for early entry and conventional sawing in the field, both early entry and conventional sawing times can be predicted for the range of mixtures tested.

Growth and recruitment after mountain forest selective cutting in irregular spruce forest : a case study in northern Norway

Abstract

Robust Nonlinear Mapping of Soil Contamination Using Support Regression

Spatial data analysis mapping and visualization is of great importance in various fields: environment, pollution, natural hazards and risks, epidemiology, spatial econometrics, etc. A basic task of spatial mapping is to make predictions based on some empirical data (measurements). A number of state-of-the-art methods can be used for the task: deterministic interpolations, methods of geostatistics: the family of kriging estimators (Deutsch and Journel, 1997), machine learning algorithms such as artificial neural networks (ANN) of different architectures, hybrid ANN-geostatistics models (Kanevski and Maignan, 2004; Kanevski et al., 1996), etc. All the methods mentioned above can be used for solving the problem of spatial data mapping. Environmental empirical data are always contaminated/corrupted by noise, and often with noise of unknown nature. That's one of the reasons why deterministic models can be inconsistent, since they treat the measurements as values of some unknown function that should be interpolated. Kriging estimators treat the measurements as the realization of some spatial randomn process. To obtain the estimation with kriging one has to model the spatial structure of the data: spatial correlation function or (semi-)variogram. This task can be complicated if there is not sufficient number of measurements and variogram is sensitive to outliers and extremes. ANN is a powerful tool, but it also suffers from the number of reasons. of a special type ? multiplayer perceptrons ? are often used as a detrending tool in hybrid (ANN+geostatistics) models (Kanevski and Maignank, 2004). Therefore, development and adaptation of the method that would be nonlinear and robust to noise in measurements, would deal with the small empirical datasets and which has solid mathematical background is of great importance. The present paper deals with such model, based on Statistical Learning Theory (SLT) - Support Vector Regression. SLT is a general mathematical framework devoted to the problem of estimation of the dependencies from empirical data (Hastie et al, 2004; Vapnik, 1998). SLT models for classification - Support Vector Machines - have shown good results on different machine learning tasks. The results of SVM classification of spatial data are also promising (Kanevski et al, 2002). The properties of SVM for regression - Support Vector Regression (SVR) are less studied. First results of the application of SVR for spatial mapping of physical quantities were obtained by the authorsin for mapping of medium porosity (Kanevski et al, 1999), and for mapping of radioactively contaminated territories (Kanevski and Canu, 2000). The present paper is devoted to further understanding of the properties of SVR model for spatial data analysis and mapping. Detailed description of the SVR theory can be found in (Cristianini and Shawe-Taylor, 2000; Smola, 1996) and basic equations for the nonlinear modeling are given in section 2. Section 3 discusses the application of SVR for spatial data mapping on the real case study - soil pollution by Cs137 radionuclide. Section 4 discusses the properties of the modelapplied to noised data or data with outliers.

Growth rate and wood properties of Norway spruce cutting clones on different sites

[Abstract]

Clypeal patterning in the paper wasp Polistes dominulus: no evidence of adaptive value in the wild

Status signals function in a number of species to communicate competitive ability to conspecific rivals during competition for resources. In the paper wasp Polistes dominulus, variable black clypeal patterns are thought to be important in mediating competition among females. Results of previous behavioral experiments in the lab indicate that P dominulus clypeal patterns provide information about an individual's competitive ability to rivals during agonistic interactions. To date, however, there has been no detailed examination of the adaptive value of clypeal patterns in the wild. To address this, we looked for correlations between clypeal patterning and various fitness measures, including reproductive success, hierarchical rank, and survival, in a large, free-living population of P. dominulus in southern Spain. Reproductive success over the nesting season was not correlated with clypeal patterning. Furthermore, there was no relationship between a female's clypeal patterning and the rank she achieved within the hierarchy or her survival during nest founding. Overall, we found no evidence that P dominulus clypeal patterns are related to competitive ability or other aspects of quality in our population. This result is consistent with geographical variation in the adaptive value of clypeal patterns between P. dominulus populations; however, data on the relationship between patterning and fitness from other populations are required to test this hypothesis.

A study of the effects of PVAC on works of art on paper and wood: pH and colour change

This paper presents the preliminary findings of pH and colour measurements carried out on artworks on paperand on wood that had been treated with a poly(vinyl acetate) (PVAC) based adhesive in the 1980s. In both cases, areas treated with PVAC proved to be less acidic than untreated areas. Contrary to expectations, the conservation treatments have not, as yet, increased acidity levels in the objects under study. Colour measurements of the works on paper showed that those that had been backed with a cotton fabric using a mixture of methylcellulose and PVAC were less yellow than those from the same print run that had not been backed. This finding suggests that the backing somehow prevented the natural degradation of the support. In view of these preliminary results, further research is clearly needed. This study forms part of a broader ongoing project to assess the role of PVAC in the conservation of a range of cultural assets.

A study of the effects of PVAC on works of art on paper and wood: pH and colour change

This paper presents the preliminary findings of pH and colour measurements carried out on artworks on paperand on wood that had been treated with a poly(vinyl acetate) (PVAC) based adhesive in the 1980s. In both cases, areas treated with PVAC proved to be less acidic than untreated areas. Contrary to expectations, the conservation treatments have not, as yet, increased acidity levels in the objects under study. Colour measurements of the works on paper showed that those that had been backed with a cotton fabric using a mixture of methylcellulose and PVAC were less yellow than those from the same print run that had not been backed. This finding suggests that the backing somehow prevented the natural degradation of the support. In view of these preliminary results, further research is clearly needed. This study forms part of a broader ongoing project to assess the role of PVAC in the conservation of a range of cultural assets.

Appendix: expert paper

Nanotechnology has been heralded as a "revolution" in science, for two reasons: first, because of its revolutionary view of the way in which chemicals and elements, such as gold and silver, behave, compared to traditional scientific understanding of their properties. Second, the impact of these new discoveries, as applied to commerce, can transform the daily life of consumer products ranging from sun tan lotions and cosmetics, food packaging and paints and coatings for cars, housing and fabrics, medicine and thousands of industrial processes.9 Beneficial consumer use of nanotechnologies, already in the stream of commerce, improves coatings on inks and paints in everything from food packaging to cars. Additionally, "Nanomedicine" offers the promise of diagnosis and treatment at the molecular level in order to detect and treat presymptomatic disease,10 or to rebuild neurons in Alzheimer's and Parkinson's disease. There is a possibility that severe complications such as stroke or heart attack may be avoided by means of prophylactic treatment of people at risk, and bone regeneration may keep many people active who never expected rehabilitation. Miniaturisation of diagnostic equipment can also reduce the amount of sampling materials required for testing and medical surveillance. Miraculous developments, that sound like science fiction to those people who eagerly anticipate these medical products, combined with the emerging commercial impact of nanotechnology applications to consumer products will reshape civil society - permanently. Thus, everyone within the jurisdiction of the Council of Europe is an end-user of nanotechnology, even without realising that nanotechnology has touched daily life.

Detection and chemical profiling of medicine counterfeits by Raman spectroscopy and chemometrics

Raman spectroscopy combined with chemometrics has recently become a widespread technique for the analysis of pharmaceutical solid forms. The application presented in this paper is the investigation of counterfeit medicines. This increasingly serious issue involves networks that are an integral part of industrialized organized crime. Efficient analytical tools are consequently required to fight against it. Quick and reliable authentication means are needed to allow the deployment of measures from the company and the authorities. For this purpose a method in two steps has been implemented here. The first step enables the identification of pharmaceutical tablets and capsules and the detection of their counterfeits. A nonlinear classification method, the Support Vector Machines (SVM), is computed together with a correlation with the database and the detection of Active Pharmaceutical Ingredient (API) peaks in the suspect product. If a counterfeit is detected, the second step allows its chemical profiling among former counterfeits in a forensic intelligence perspective. For this second step a classification based on Principal Component Analysis (PCA) and correlation distance measurements is applied to the Raman spectra of the counterfeits.