Measuring the amount of crystallinity in solutions using DSC

The amount of solid that forms in a solution at temperatures below the cloud point, is an important quantity in the design of crystallisation processes. A new method using differential scanning calorimetry (DSC) to measure the fraction of crystallised solution, α ' is proposed. A very good agreement is obtained between the data measured by the new calorimetric method and using alternative techniques. A simple graphic version of the calculation procedure is also presented. It is shown to produce quick and fair estimates for the solid fraction by a simple analysis of a plot of enthalpy variation with temperature.     

Effect of wind stress forcing on ocean dynamics at air-sea interface

We evidence and study the differences in turbulence statistics in ocean dynamics carried by wind forcing at the air-sea interface. Surface currents at the air-sea interaction are of crucial importance because they transport heat from low to high latitudes. At first order, oceanic currents are generated by the balance of the Coriolis and pressure gradient forces (geostrophic current) and the balance of the Coriolis and the frictional forces dominated by wind stress (Ekman current) in the surface ocean layers. The study was conducted by computing statistical moments on the shapes of spectra computed within the framework of microcanonical multi-fractal formalism. Remotely sensed daily datasets derived from one year of altimetry and wind data were used in this study, allowing for the computation of two kinds of vector fields: geostrophy with and geostrophy without wind stress forcing. We explore the statistical properties of singularity spectra computed from velocity norms and vorticity data, notably in relation with kurtosis information to underline the differences in the turbulent regimes associated with both kinds of velocity fields.     

Design and integration of a spatio-temporal memory with emotional influences to categorize and recall the experiences of an autonomous mobile robot

Autonomous robots cohabiting with humans will have to achieve recurring tasks while adapting to the changing conditions of the world. A spatio-temporal memory categorizes the experiences of a robot to improve its ability to adapt to its environment. In this paper, we present a spatio-temporal (ST) memory model consisting of a cascade of two adaptive resonance theory (ART) networks: one to categorize spatial events and the other to extract temporal episodes from the robot’s experiences. Artificial emotions are used to dynamically modulate learning and recall of the ART networks based on how the robot is able to carry its task, using a simple model of artificial emotions. Once an episode is recalled, future events can be predicted and used to influence the intentions of the robot. Evaluation of our ST model is done using an autonomous robotic platform that has to deliver objects to people within an office area. Results demonstrate that our model can memorize and recall the experiences of a robot, and that emotional episodes are recalled more often, allowing the robot to use its memory of past experiences early on when repeating a task.     

Thermoresponsive crosslinked isocyanate‐free polyurethanes by Diels‐Alder polymerization

This new study is a continuation of our previous work on thermocleavable nonisocyanate polyurethanes (NIPUs), but it is focused on crosslinked networks. Two systems are studied: the first system involves a dicyclocarbonate adduct with a PPO‐bicyclocarbonate and a triamine as crosslinker. The second system involves a tetracyclocarbonate DA adduct as crosslinker with the same PPO‐bicyclocarbonate and a difunctional amine. Firstly, Diels‐Alder adducts are synthesized and characterized. Then they are copolymerized to yield two types of cleavable polymer networks. The thermal behavior of synthesized polymers is fully characterized. Finally, by SEC, it was demonstrated that the obtained NIPU polymer chains are sliced up by rDA reaction. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017 , 134, 44408.     

Deploying solar energy with community choice aggregation: A carbon fee model

This article investigates solar photovoltaic deployment through community choice aggregation programs. A case study of a solar energy program facilitated through a public energy council in Southeastern Ohio is highlighted, which used a ‘carbon fee’ model to collect a 0.2 cents per kilowatt hour incremental fee above the standard aggregation rate. This premium funds the development of behind-the-meter solar installations, and may serve as an exemplary approach for other aggregation programs to deploy solar.     

The ManyEars open framework

ManyEars is an open framework for microphone array-based audio processing. It consists of a sound source localization, tracking and separation system that can provide an enhanced speaker signal for improved speech and sound recognition in real-world settings. ManyEars software framework is composed of a portable and modular C library, along with a graphical user interface for tuning the parameters and for real-time monitoring. This paper presents the integration of the ManyEars Library with Willow Garage’s Robot Operating System. To facilitate the use of ManyEars on various robotic platforms, the paper also introduces the customized microphone board and sound card distributed as an open hardware solution for implementation of robotic audition systems.     

Experimental Study of Wear Behaviour of Hot Forging Tool Steels Under Dry Conditions: 40CrMoV13 Against C35E

The dimensions and quality of forged-steel components are significantly affected by the action of friction and wear. The thermal and mechanical operating conditions of hot forging tools provoke serious degradation, such as oxidative wear, thermal fatigue, plastic damage and mechanical cracking. This slowly causes the tools to lose their original geometry and thus they must be either reformed or discarded [1]. The knowledge and control of this damage is essential and must be taken into consideration, both in die design and in the choice of tool material and the type of surface conditioning. The degradation has direct effects on the lifespan of the tools, and consequently on the cost of the components. This paper deals with the sliding wear behaviour of 40CrMoV13 Steel against C35E in the 700 to 850 °C temperature range under ambient conditions. This steel is used frequently as hot forging die material. This study focuses on the effect of the test temperature and the role of the oxide scales. The purpose of these experiments was to obtain tribological data (friction coefficient, wear rate, etc.), in order to include it in numerical simulations of damage to hot forging tools for the purpose of optimizing the tools' lifespan.     

Development of a numerical simulation model for predicting the curing of ceramic systems in the stereolithography process

The control of ceramic green parts dimensions produced by stereolithography is a central concern of the ceramic additive manufacturing industry. The presence of ceramic particles within the photopolymerizable system induces UV-laser beam scattering phenomenon, disrupting the polymerization process. This study focuses on the development of a numerical simulation model of the curing process, considering the scattering phenomenon. This paper presents each stages of the development of the numerical simulation model, supported and finally validated by experimentation on a commercial photopolymerizable alumina paste. Firstly, the numerical simulation model is presented. Then, a Greco-Latin square design of experiments is conducted to reduce the number of experiments. Subsequently, material-dependent parameters are identified through simulations and experimental measurements, and a scattering law is proposed. Finally, the simulation model enables to simulate easily and with accuracy the cure widths and the cure depth. It also provides visualization of the exposure distribution and the scattering phenomenon.     

Economic incentives to use fertilizer on maize under differing agro-ecological conditions in Burkina Faso

Increasing agricultural productivity while protecting natural resources depends on proper understanding of farmers’ incentives to use intensification strategies, including fertilizer. Using a large-scale household dataset collected in rural Burkina Faso, we examined how the response of maize yield to fertilizer, and thus the economic incentives for its use, varied according to agro-ecological conditions. We employed a Control Function Approach with Correlated Random Effects in order to test and control for endogeneity of fertilizer use, measuring agro-ecological conditions at several scales. We investigated the profitability of fertilizer use with value-cost ratios. We found that productivity and marginal effects of fertilizer differ significantly according to agro-ecological conditions. Micro-variation appeared to be more critical than the definition of agro-ecological zone. Burkinabe soils are severely degraded and would benefit from greater application of fertilizer. However, at full market prices, fertilizer use was unprofitable. Though it was profitable with subsidized prices, transaction costs diminish the benefits of the subsidy. Profitability of fertilizer use with maize varied across agro-ecological conditions, even for field plots located in the same agro-ecological zone. Our results confirm that policy makers need to be cautious when generalizing across regions or drawing policy recommendations from a single agro-ecological zone because crop responses and economic incentives vary widely.     

A human-like visual-attention-based artificial vision system for wildland firefighting assistance

In this work we contribute to development of a “Human-like Visual-Attention-based Artificial Vision” system for boosting firefighters’ awareness about the hostile environment in which they are supposed to move along. Taking advantage from artificial visual-attention, the investigated system’s conduct may be adapted to firefighter’s way of gazing by acquiring some kind of human-like artificial visual neatness supporting firefighters in interventional conditions’ evaluation or in their appraisal of the rescue conditions of people in distress dying out within the disaster. We achieve such a challenging goal by combining a statistically-founded bio-inspired saliency detection model with a Machine-Learning-based human-eye-fixation model. Hybridization of the two above-mentioned models leads to a system able to tune its parameters in order to fit human-like gazing of the inspected environment. It opens appealing perspectives in computer-aided firefighters’ assistance boosting their awareness about the hostile environment in which they are supposed to evolve. Using as well various available wildland fires images’ databases as an implementation of the investigated concept on a 6-wheeled mobile robot equipped with communication facilities, we provide experimental results showing the plausibility as well as the efficiency of the proposed system.