Determination of joint efforts in the human body during maximum ramp pushing efforts.

Determining with accuracy, the internal efforts in the human body is a great challenge in Biomechanics, particularly in Physical Therapy and Ergonomics. In this context, the present study develops a human body model that permits a non-invasive determination of the joint efforts produced by a seated subject performing maximum ramp pushing efforts. The joint interactions during these experiments are provided by a dynamic inverse model of the human body, using a symbolically generated recursive Newton-Euler formalism. The theoretical investigation is presented in two steps, with increasing complexity and relevance:The dynamic model confirms some previous studies of the effects of biomechanical factors on the performance of the task and is proposed as an accurate method for determining the joint efforts in dynamic contexts. Finally, this application is a preliminary benchmark case that will be extended to: *physical therapy, in order to analyse the joint and muscle efforts in various motion contexts, particularly for patients with fibromyalgia and patients with lumbar diseases; *accidentology, in order to analyse and simulate car occupant dynamics before a crash

3D deep convolutional neural network segmentation model for precipitate and porosity identification in synchrotron X-ray tomograms

New developments at synchrotron beamlines and the ongoing upgrades of synchrotron facilities allow the possibility to study complex structures with a much better spatial and temporal resolution than ever before. However, the downside is that the data collected are also significantly larger (more than several terabytes) than ever before, and post-processing and analyzing these data is very challenging to perform manually. This issue can be solved by employing automated methods such as machine learning, which show significantly improved performance in data processing and image segmentation than manual methods. In this work, a 3D U-net deep convolutional neural network (DCNN) model with four layers and base-8 characteristic features has been developed to segment precipitates and porosities in synchrotron transmission X-ray micrograms. Transmission X-ray microscopy experiments were conducted on micropillars prepared from additively manufactured 316L steel to evaluate precipitate information. After training the 3D U-net DCNN model, it was used on unseen data and the prediction was compared with manual segmentation. A good agreement was found between both segmentations. An ablation study was performed and revealed that the proposed model showed better statistics than other models with lower numbers of layers and/or characteristic features. The proposed model is able to segment several hundreds of gigabytes of data in a few minutes and could be applied to other materials and tomography techniques. The code and the fitted weights are made available with this paper for any interested researcher to use for their needs (https://github.com/manasvupadhyay/erc-gamma-3D-DCNN)

A synchrotron transmission X-ray microscopy study on precipitate evolution during solid-state thermal cycling of a stainless steel

International audienceDuring additive manufacturing of stainless steels, sub-micron sized oxide (i.e., MnSiO3 , SiO2 , and CrMn2O4) and non-oxide (i.e., sulfide, in particular MnS, and possibly carbides, phosphides and nitrides) precipitates form during solidification. But do they evolve during the subsequent solid-state thermal cycling (SSTC) until the end of the printing process? A recent study on subjecting thin-film lamellae extracted from an additively manufactured stainless steel to heating-cooling treatments inside a transmission electron microscope (TEM) confirmed that precipitate composition can indeed evolve during SSTC. However, that study could not provide any conclusive evidence on precipitate volume fraction, density, and size evolution. In this work, we have quantified these changes using a novel experimental procedure combining (i) micropillar extraction from an additively manufactured stainless steel, (ii) subjecting them to different SSTC (including annealing) inside a TEM, (iii) performing synchrotron transmission X-ray microscopy to identify precipitates, and (iv) using a machine learning model to segment precipitates and quantify precipitate volume fraction, density, and size. Comparing these quantities before and after each SSTC/annealing sequence reveals that new oxides nucleated during rapid SSTC with high maximum temperature. However, during slow SSTC with high maximum temperature and annealing, precipitates dissolve because of oxygen evaporation during SSTC inside the TEM. A new empirical relationship correlating precipitate sizes and cooling rates is proposed. It is in good agreement with data collected from conventional casting, directed energy deposition, and powder bed fusion processes

Norms, Interests and Institutional Change

This paper provides a norms-based account of institutional change. It compares two cases of attempted change, one successful and one unsuccessful. The argument advanced is that norm-based change occurs when the norms are congruent with the perceived interests of the actors who have the power to take on the decision. Norms affect the process of institutional change not only by providing legitimacy to some forms of political action, but also by shaping the actors’ perception of their interests as well their strategies. It is argued that norms, in that sense, help political actors combine Max Weber's zweckrational (goal-orientated) and wertrational (value-orientated) categories of behaviour. Empirical evidence drawn from the context of the evolving European Union supports this argument

Numerical investigations of the effects of substitutional elements on the interface conditions during partitioning in quenching and partitioning steels

International audienceIn quenched and partitioned steels, carbon partitioning is considered to be driven by a constraint para-equilibrium at the martensite/austenite interface. Using Thermo-Calc calculations, we investigated the effect of non-partitioned elements on the resulting interface condition. Among all tested elements, only aluminum and chromium have significant effects. From this numerical study, a practical composition- and temperature-dependent relationship describing interface tie lines was derived and calibrated for Fe-C-2.5Mn-1.5Si-X wt pct alloys (X = Cr or Al)

Indications for islet or pancreatic transplantation: Statement of the TREPID working group on behalf of the Societe francophone du diabete (SFD), Societe francaise d'endocrinologie (SFE), Societe francophone de transplantation (SFT) and Societe francaise de nephrologie - dialyse - transplantation (SFNDT)

While either pancreas or pancreatic islet transplantation can restore endogenous insulin secretion in patients with diabetes, no beta-cell replacement strategies are recommended in the literature. For this reason, the aim of this national expert panel statement is to provide information on the different kinds of beta-cell replacement, their benefit-risk ratios and indications for each type of transplantation, according to type of diabetes, its control and association with end-stage renal disease. Allotransplantation requires immunosuppression, a risk that should be weighed against the risks of poor glycaemic control, diabetic lability and severe hypoglycaemia, especially in cases of unawareness. Pancreas transplantation is associated with improvement in diabetic micro- and macro-angiopathy, but has the associated morbidity of major surgery. Islet transplantation is a minimally invasive radiological or mini-surgical procedure involving infusion of purified islets via the hepatic portal vein, but needs to be repeated two or three times to achieve insulin independence and long-term functionality. Simultaneous pancreas-kidney and pancreas after kidney transplantations should be proposed for kidney recipients with type 1 diabetes with no surgical, especially cardiovascular, contraindications. In cases of high surgical risk, islet after or simultaneously with kidney transplantation may be proposed. Pancreas, or more often islet, transplantation alone is appropriate for non-uraemic patients with labile diabetes. Various factors influencing the therapeutic strategy are also detailed in this report. (C) 2018 Published by Elsevier Masson SAS