Bond Modelling of prestressed concrete during the prestressing force release

This paper presents an analytical model for simulating the bond between steel and concrete, in precast prestressed concrete elements, during the prestressing force release. The model establishes a relationship between bond stress, steel and concrete stress and slip in such concrete structures. This relationship allows us to evaluate the bond stress in the transmission zone, where bond stress is not constant, along the whole prestressing force release process. The model is validated with the results of a series of tests and is extended to evaluate the transmission length. This capability has been checked by comparing the transmission length predicted by the model and one measured experimentally in a series of tests.

Bond modelling of prestressed concrete during the prestressing force release

This paper presents an analytical model for simulating the bond between steel and concrete, in precast prestressed concrete elements, during the prestressing force release. The model establishes a relationship between bond stress, steel and concrete stress and slip in such concrete structures. This relationship allows us to evaluate the bond stress in the transmission zone, where bond stress is not constant, along the whole prestressing force release process. The model is validated with the results of a series of tests, considering different steel indentation depths and concrete covers and is extended to evaluate the transmission length. This capability has been checked by comparing the transmission length predicted by the model and one measured experimentally in two series of tests.

Human midbrain precursors activate the expected developmental genetic program and differentiate long-term to functional A9 dopamine neurons in vitro. Enhancement by Bcl-XL

Understanding the molecular programs of the generation of human dopaminergic neurons (DAn) from their ventral mesencephalic (VM) precursors is of key importance for basic studies, progress in cell therapy, drug screening and pharmacology in the context of Parkinson's disease. The nature of human DAn precursors in vitro is poorly understood, their properties unstable, and their availability highly limited. Here we present positive evidence that human VM precursors retaining their genuine properties and long-term capacity to generate A9 type Substantia nigra human DAn (hVM1 model cell line) can be propagated in culture. During a one month differentiation, these cells activate all key genes needed to progress from pro-neural and prodopaminergic precursors to mature and functional DAn. For the first time, we demonstrate that gene cascades are correctly activated during differentiation, resulting in the generation of mature DAn. These DAn have morphological and functional properties undistinguishable from those generated by VM primary neuronal cultures. In addition, we have found that the forced expression of Bcl-XL induces an increase in the expression of key developmental genes (MSX1, NGN2), maintenance of PITX3 expression temporal profile, and also enhances genes involved in DAn long-term function, maintenance and survival (EN1, LMX1B, NURR1 and PITX3). As a result, Bcl-XL anticipates and enhances DAn generation.

An analytical model for simulating the bond of prestressed concrete during the prestressed force release

A bond analytical model is proposed in this paper. The model is capable of reproducing the bond stress developed between the steel and concrete, in precast prestressed elements, during the entire process of prestressing force release. The bond stress developed in the transmission zone, where the bond stress is not constant, is also obtained. The steel and concrete stresses as well as the slip between both materials can be also estimated by means of the relation established in the model between these parameters and the bond stress. The model is validated with the results of a series of tests, considering different steel indentation depths and concrete covers and it is extended to evaluate the transmission length. This has been checked by comparing the transmission length predicted by the model and one measured experimentally in two series of tests.

An analytical model for simulating the bond of prestressed concrete during the prestressed force release

A bond analytical model is proposed in this paper. The model is capable of reproducing the bond stress developed between the steel and concrete, in precast prestressed elements, during the entire process of prestressing force release. The bond stress developed in the transmission zone, where the bond stress is not constant, is also obtained. The steel and concrete stresses as well as the slip between both materials can be also estimated by means of the relation established in the model between these parameters and the bond stress. The model is validated with the results of a series of tests, considering different steel indentation depths and concrete covers and it is extended to evaluate the transmission length. This has been checked by comparing the transmission length predicted by the model and one measured experimentally in two series of tests.

Dopamine receptor 4 promoter polymorphism modulates memory and neuronal responses to salience

Animal models and human functional imaging data implicate the dopamine system in mediating enhanced encoding of novel stimuli into human memory. A separate line of investigation suggests an association between a functional polymorphism in the promoter region for the human dopamine 4 receptor gene (DRD4) and sensitivity to novelty. We demonstrate, in two independent samples, that the -521Cmayor queT DRD4 promoter polymorphism determines the magnitude of human memory enhancement for contextually novel, perceptual oddball stimuli in an allele dose-dependent manner. The genotype-dependent memory enhancement conferred by the C allele is associated with increased neuronal responses during successful encoding of perceptual oddballs in the ventral striatum, an effect which is again allele dose-dependent. Furthermore, with repeated presentations of oddball stimuli, this memory advantage decreases, an effect mirrored by adaptation of activation in the hippocampus and substantia nigra/ventral tegmental area in C carriers only. Thus, a dynamic modulation of human memory enhancement for perceptually salient stimuli is associated with activation of a dopaminergic-hippocampal system, which is critically dependent on a functional polymorphism in the DRD4 promoter region.

Use of the energy-release rate in a 2 scale damage analysis of a bonded joint

Stress singularities appear at the extremities of an adhesive bond. They can produce a damage mechanism that we assimilate in this Note to a crack. The energy release rate permits to characterize its evolution. But a very refined mesh would be necessary for a real structure. Using an asymptotic method based on the small thickness of the bond a limit model with a different local behaviour is suggested. It leads to an approximation of the energy release rate

Mining mobile apps reviews to support release planning

The mobile apps market is a tremendous success, with millions of apps downloaded and used every day by users spread all around the world. For apps’ developers, having their apps published on one of the major app stores (e.g. Google Play market) is just the beginning of the apps lifecycle. Indeed, in order to successfully compete with the other apps in the market, an app has to be updated frequently by adding new attractive features and by fixing existing bugs. Clearly, any developer interested in increasing the success of her app should try to implement features desired by the app’s users and to fix bugs affecting the user experience of many of them. A precious source of information to decide how to collect users’ opinions and wishes is represented by the reviews left by users on the store from which they downloaded the app. However, to exploit such information the app’s developer should manually read each user review and verify if it contains useful information (e.g. suggestions for new features). This is something not doable if the app receives hundreds of reviews per day, as happens for the very popular apps on the market. In this work, our aim is to provide support to mobile apps developers by proposing a novel approach exploiting data mining, natural language processing, machine learning, and clustering techniques in order to classify the user reviews on the basis of the information they contain (e.g. useless, suggestion for new features, bugs reporting). Such an approach has been empirically evaluated and made available in a web-­‐based tool publicly available to all apps’ developers. The achieved results showed that the developed tool: (i) is able to correctly categorise user reviews on the basis of their content (e.g. isolating those reporting bugs) with 78% of accuracy, (ii) produces clusters of reviews (e.g. groups together reviews indicating exactly the same bug to be fixed) that are meaningful from a developer’s point-­‐of-­‐view, and (iii) is considered useful by a software company working in the mobile apps’ development market.