Context‐aware Android applications through transportation mode detection techniques

In this paper, we study the problem of how to detect the current transportation mode of the user from the smartphone sensors data, because this issue is considered crucial for the deployment of a multitude of mobility‐aware systems, ranging from trace collectors to health monitoring and urban sensing systems. Although some feasibility studies have been performed in the literature, most of the proposed systems rely on the utilization of the GPS and on computational expensive algorithms that do not take into account the limited resources of mobile phones. On the opposite, this paper focuses on the design and implementation of a feasible and efficient detection system that takes into account both the issues of accuracy of classification and of energy consumption. To this purpose, we propose the utilization of embedded sensor data (accelerometer/gyroscope) with a novel meta‐classifier based on a cascading technique, and we show that our combined approach can provide similar performance than a GPS‐based classifier, but introducing also the possibility to control the computational load based on requested confidence. We describe the implementation of the proposed system into an Android framework that can be leveraged by third‐part mobile applications to access context‐aware information in a transparent way. Copyright © 2016 John Wiley & Sons, Ltd.     

A speed sensorless control based on a MRAS applied to a double fed induction machine drive

This paper proposes a new MRAS method to estimate the mechanical quantities in a double fed induction machine. In the traditional formulation the integral term, introduced by the PI MRAS regulator, is canceled in the transfer function between the estimated and the real speed. As a novelty, an additional term depending on the reference rotor flux through a constant gain g is introduced in the adjustable model of the MRAS. This innovation restores the integral term in the transfer function. As a consequence, during the closed loop operation, the estimated speed does not exhibit anymore a steady state error. The influence of the inverter non-linearities and of the non-linear rotor brush resistance on the speed estimation is also discussed. Some experimental tests validate the proposed method.     

Potential of different additives to improve performance of potassium carbonate for CO<Subscript>2</Subscript> absorption

The performance of potassium carbonate (K₂CO₃) solution promoted by three amines, potassium alaninate (K-Ala), potassium serinate (K-Ser) and aminoethylethanolamine (AEEA), in terms of heat of absorption, absorption capacity and rate was studied experimentally. The experiments were performed using a batch reactor, and the results were compared to pure monoethanolamine (MEA) and K₂CO₃ solutions. The heat of absorption of K₂CO₃+additive solution was calculated using the Gibbs-Helmholtz equation. In addition, a correlation for prediction of CO₂ loading was presented. The results indicated that absorption heat, absorption rate and loading capacity of CO₂ increase as the concentration of additive increases. The blend solutions have higher CO₂ loading capacity and absorption rate when compared to pure K₂CO₃. The heat of CO₂ absorption for K₂CO₃+additive solutions was found to be lower than that of the pure MEA. Among the additives, AEEA showed the highest CO₂ absorption capacity and absorption rate with K₂CO₃. In conclusion, the K₂CO₃+AEEA solution with high absorption performance can be a potential solvent to replace the existing amines for CO₂ absorption.     

Inflammasome Signaling Regulates the Microbial–Neuroimmune Axis and Visceral Pain in Mice

Interactions between the intestinal microbiota, immune system and nervous system are essential for homeostasis in the gut. Inflammasomes contribute to innate immunity and brain–gut interactions, but their role in microbiota–neuro–immune interactions is not clear. Therefore, we investigated the effect of the inflammasome on visceral pain and local and systemic neuroimmune responses after antibiotic-induced changes to the microbiota. Wild-type (WT) and caspase-1/11 deficient (Casp1 KO) mice were orally treated for 2 weeks with an antibiotic cocktail (Abx, Bacitracin A and Neomycin), followed by quantification of representative fecal commensals (by qPCR), cecal short chain fatty acids (by HPLC), pathways implicated in the gut–neuro-immune axis (by RT-qPCR, immunofluorescence staining, and flow cytometry) in addition to capsaicin-induced visceral pain responses. Abx-treatment in WT-mice resulted in an increase in colonic macrophages, central neuro-immune interactions, colonic inflammasome and nociceptive receptor gene expression and a reduction in capsaicin-induced visceral pain. In contrast, these responses were attenuated in Abx-treated Casp1 KO mice. Collectively, the data indicate an important role for the inflammasome pathway in functional and inflammatory gastrointestinal conditions where pain and alterations in microbiota composition are prominent.     

Experimental study on performance and emissions of a high speed diesel engine fuelled with n-butanol diesel blends under premixed low temperature combustion

In the present paper, results of an experimental investigation carried out in a modern diesel engine running at different operative conditions and fuelled with blends of diesel and n-butanol, are reported. The exploration strategy was focused on the management of the timing and injection pressure to achieve a condition in which the whole amount of fuel was delivered before ignition. The aim of the paper was to evaluate the potential to employ fuel blends having low cetane number and high resistance to auto-ignition to reduce engine out emissions of NOx and smoke without significant penalty on engine performance. Fuel blends were mixed by the baseline diesel (BU00) with 20% and 40% of n-butanol by volume. The n-butanol was taken by commercial production that is largely produced through petrochemical pathways although the molecule is substantially unchanged for butanol produced through biological mechanisms.The experimental activity was performed on a turbocharged, water cooled, DI diesel engine, equipped with a common rail injection system. The engine equipment includes an exhaust gas recirculation system controlled by an external driver, a piezo-quartz pressure transducer to detect the in-cylinder pressure signal and a current probe to acquire the energizing current to the injectors. Engine tests were carried out at 2500 rpm and 0.8 MPa of BMEP exploring the effect of start of injection, O₂ concentration at intake and injection pressure on combustion behavior and engine out emissions. The in-cylinder pressure and rate of heat release were investigated for the neat diesel and the two blends to evaluate engine performance and exhaust emissions both for the conventional diesel and the advanced premixed combustion processes.The management of injection pressure, O₂ concentration at intake and injection timing allowed to realize a partial premixed combustion by extending the ignition delay, particularly for blends. The main results of the investigation made reach smoke and NOx emissions due to the longer ignition delay and a better mixing control before combustion. The joint effect of higher resistance to auto ignition and higher volatility of n-butanol blends improved emissions compared to the neat diesel fuel with a low penalty on fuel consumption.     

Model Predictive Control of Glucose Concentration Based on Signal Temporal Logic Specifications with Unknown-Meals Occurrence

Abstract

The glycemia regulation is a significant challenge in the Artificial Pancreas (AP) scenario. Several control systems have been developed in the last years, many of them requiring meal announcements. Therefore, if the patients skip the meal announcement or make a mistake in the estimation of the amount of carbohydrates, the control performance will be negatively affected. In this extended version of our previous work, we present a Model Predictive Controller (MPC) for the AP in which the meal is treated as a disturbance to be estimated by an Unknown Input Observer (UIO). The MPC constraints are expressed in terms of Signal Temporal Logic (STL) specifications. Indeed, in the AP some requirements result in hard constraints (in particular, absolutely avoid hypoglycemia and absolutely avoid severe hyperglycemia) and some other in soft constraints (avoid a prolonged hyperglycemia) and STL is suitable for expressing such requirements. The achieved results are obtained using the BluSTL toolbox, which allows to synthesize model predictive controllers with STL constraints. We report simulations showing that the proposed approach, avoiding unnecessary restrictions, provides safe trajectories in correspondence of higher unknown disturbance.     

Investigating the contribution of linguistic information to quality estimation

This paper describes a study on the contribution of linguistically-informed features to the task of quality estimation for machine translation at sentence level. A standard regression algorithm is used to build models using a combination of linguistic and non-linguistic features extracted from the input text and its machine translation. Experiments with three English–Spanish translation datasets show that linguistic features on their own are not able to outperform shallower features based on statistics from the input text, its translation and additional corpora. However, further analysis suggests that linguistic information can be useful to produce better results if carefully combined with other features. An in-depth analysis of the results highlights a number of issues related to the use of linguistic features.     

A two-step,fourth-order method with energy preserving properties

We introduce a family of fourth-order two-step methods that preserve the energy function of canonical polynomial Hamiltonian systems. As is the case with linear mutistep and one-leg methods, a prerogative of the new formulae is that the associated nonlinear systems to be solved at each step of the integration procedure have the very same dimension of the underlying continuous problem.The key tools in the new methods are the line integral associated with a conservative vector field (such as the one defined by a Hamiltonian dynamical system) and its discretization obtained by the aid of a quadrature formula. Energy conservation is equivalent to the requirement that the quadrature is exact, which turns out to be always the case in the event that the Hamiltonian function is a polynomial and the degree of precision of the quadrature formula is high enough. The non-polynomial case is also discussed and a number of test problems are finally presented in order to compare the behavior of the new methods to the theoretical results.     

A fast time-domain algorithm for the simulation of switching powerconverters

An efficient algorithm for the simulation of switched-mode power converters is developed. A Chebyshev series expansion is used to effectively solve the differential equations describing the system in each topology. The power of the new simulation technique lies both in the simple, but accurate, polynomial approximation for the state transition matrices and in the ability to explicitly obtain the instants at which the switching of the circuit topology takes place. The simulation technique is illustrated with reference to a simple Buck converter operating at a constant frequency. The derivation of the new algorithm is presented and its performance is analyzed. The case of a rapidly varying input forcing function is analyzed. Examples illustrating the generality and the computational efficiency of the algorithm are presented     

DEM modelling analysis of tree root growth in street pavements

The coexistence of urban green spaces and infrastructure is often difficult. Trees find inhospitable environments in urban areas, whereas tree root systems can damage sidewalk, street and parking lot. The main form of failure concerns the growing of tree roots beneath the pavements, which produce upheavals and displacements on wearing course. The main objective of this study was a distinct element method modelling analysis of the potential interactions between tree root systems and street pavements. This calculation code allowed us to simulate the dynamic behaviour of the ground-pavement system as result of the roots growth. The performed modelling, representative of various planting strategies commonly used in urban contexts, have highlighted the progressive reduction of deformations with the increase of the roots penetration depth. Such displacements were strongly influenced by other factors such as the porosity and the grain-size distribution of the soil and the type of pavement considered.