PMMA‐modified divinylester/styrene resins: Phase diagrams and morphologies

Binary and ternary experimental cloud‐point curves (CPCs) for systems formulated with a low molar mass synthesized divinylester (DVE) resin, styrene (St), and poly(methyl methacrylate) (PMMA) were determined. The CPCs results were analyzed with the Flory–Huggins (F‐H) thermodynamic model taking into account the polydispersity of the DVE and PMMA components, to calculate the different binary interaction parameters and their temperature dependences. The St‐DVE system is miscible in all the composition range and down to the crystallization temperature of the St; therefore, the interaction parameter expression reported for a higher molar mass DVE was adapted. The interaction parameters obtained were used to calculate the phase diagrams of the St‐PMMA and the DVE‐PMMA binary systems and that of the St‐DVE‐PMMA ternary system at three different temperatures. Quasiternary phase diagrams show liquid–liquid partial miscibility of the St‐PMMA and DVE‐PMMA pairs. At room temperature, the St‐DVE‐PMMA system is miscible at all compositions. Final morphologies of PMMA‐modified cured St‐DVE materials were generated by polymerization‐induced phase separation (PIPS) mechanism from initial homogeneous mixtures. SEM and TEM micrographs were obtained to analyze the generated final morphologies, which showed a direct correlation with the initial miscibility of the system. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 4539–4549, 2006     

A hybrid dynamic motion prediction method for multibody digital human models based on a motion database and motion knowledge

In this paper, we present a novel method to predict human motion, seeking to combine the advantages of both data-based and knowledge-based motion prediction methods. Our method relies on a database of captured motions for reference and introduces knowledge in the prediction in the form of a motion control law, which is followed while resembling the actually performed reference motion. The prediction is carried out by solving an optimization problem in which the following conditions are imposed to the motion: must fulfill the goals of the task; resemble the reference motion selected from the database; follow a knowledge-based dynamic motion control law; and ensure the dynamic equilibrium of the human model, considering its interactions with the environment. In this work, we apply the proposed method to a database of clutch pedal depression motions, and we present the results for three predictions. The method is validated by comparing the results of the prediction to motions actually performed in similar conditions. The predicted motions closely resemble the motions in the validation database and no significant differences have been noted either in the motion’s kinematics or in the motion’s dynamics.     

Imhotep: an approach to user and device conscious mobile applications

As the dependence on mobile devices increases, the need for supporting a wider range of users and devices becomes crucial. Elders and people with disabilities adopt new technologies reluctantly, a tendency caused by the lack of adaptation of these technologies to their needs. To address this challenge, this paper describes a framework, Imhotep, whose aim is to aid developers in the accessible application creation process, making the creation of user-centered applications easier and faster. Our framework allows to easily adapt the applications to the constraints imposed by the user capabilities (sensorial, cognitive, and physical capabilities) and device capabilities by providing a repository that will manage the compilation and deployment of applications that include a set of preprocessor directives in the source code. These directives are enhanced with concepts that are automatically adjusted to the current trends of mobile devices by using a Fuzzy Knowledge-Eliciting Reasoner. Our final goal is to increase the number of applications targeted to elders and people with disabilities providing tools that facilitate their development. The paper also describes the evaluation of both the accuracy of the fuzzy terms generated for mobile devices and the usability of the proposed platform.     

Advances and Perspectives in Dental Pulp Stem Cell Based Neuroregeneration Therapies

Human dental pulp stem cells (hDPSCs) are some of the most promising stem cell types for regenerative therapies given their ability to grow in the absence of serum and their realistic possibility to be used in autologous grafts. In this review, we describe the particular advantages of hDPSCs for neuroregenerative cell therapies. We thoroughly discuss the knowledge about their embryonic origin and characteristics of their postnatal niche, as well as the current status of cell culture protocols to maximize their multilineage differentiation potential, highlighting some common issues when assessing neuronal differentiation fates of hDPSCs. We also review the recent progress on neuroprotective and immunomodulatory capacity of hDPSCs and their secreted extracellular vesicles, as well as their combination with scaffold materials to improve their functional integration on the injured central nervous system (CNS) and peripheral nervous system (PNS). Finally, we offer some perspectives on the current and possible future applications of hDPSCs in neuroregenerative cell therapies.     

Study of Complete Thermoelectric Generator Behavior Including Water-to-Ambient Heat Dissipation on the Cold Side

Reduction of the thermal resistances of the heat exchangers of a thermoelectric generation (TEG) system leads to a significant increase in TEG efficiency. For the cold side of a thermoelectric module (TEM), a wide range of heat exchangers have been studied, from simple finned dissipators to more complex water (water–glycol) heat exchangers. As the Nusselt number is much higher in water heat exchangers than in conventional air finned dissipators, the convective thermal resistances are better. However, to conclude which heat exchanger leads to higher efficiencies, it is necessary to include the whole system involved in the heat dissipation, i.e., the TEM-to-water heat exchanger, the water-to-ambient heat exchanger, as well as the required pumps and fans. This paper presents a dynamic computational model able to simulate the complete behavior of a TEG, including both heat exchangers. The model uses the heat transfer and hydraulic equations to compute the TEM-to-water and water-to-ambient thermal resistances, along with the resistance of the hot-side heat exchanger at different operating conditions. Likewise, the model includes all the thermoelectric effects with temperature-dependent properties. The model calculates the net power generation for different configurations, providing a methodology to design and optimize the heat exchange in order to maximize the net power generation for a wide variety of TEGs.     

Polyaniline‐modified cellulose nanofibrils as reinforcement of a smart polyurethane

Segmented polyurethanes exhibiting shape memory properties were modified by the addition of polyaniline (PANI)‐coated cellulose nanofibrils (CNFs). The two‐phase structure of the polymer is responsible for the material's ability to ‘remember’ and autonomously recover its original shape after being deformed in response to an external thermal stimulus. PANI was grown on the surface of the CNFs via in situ polymerization. Modified nanocrystals were added to the segmented polyurethane in concentrations ranging from 0 to 15 wt%. The changes in the material properties associated with the percolation of the coated fibrils appear at higher concentrations than previously observed for non‐modified CNFs, which suggests that fibril agglomeration is occurring due to the PANI coating. The shape memory behavior of the composites is maintained at about the same level as that of the unfilled polyurethane only up to 4 wt% of fibrils. At higher concentrations, the rigidity of the nanofibrils as well as their interaction with the hard‐segment phase and the increasing difficulty of dispersing them in the polymer collaborate to produce early breakage of the specimens when stretched at temperatures above the melting point of the soft segments. Copyright © 2010 Society of Chemical Industry     

Cooperative Distributed MIMO Channels in Wireless Sensor Networks

The large number of network nodes and the energy constraints make Wireless Sensor Networks (WSN) one of the most important application fields for Cooperative Diversity. Node cooperation increases the spatial diversity of wireless channels and, thus, reduces the transmitted power. In this paper, we propose a multi-hop WSN with nodes grouped in cooperative clusters that exploits transmit and receive cooperation among cluster nodes. Multi-hop transmission is carried out by concatenating single cluster-to-cluster hops, where every cluster-to-cluster link is defined as a cooperative distributed multiple-input-multiple-output (MIMO) channel. Transmit diversity is exploited through a time-division, decoder-and-forward, relaying scheme based upon two time slots: the Intracluster Slot, used for data sharing within the cluster, and the Intercluster Slot, used for transmission between clusters. At the receiver side, a distributed reception protocol is devised based upon a Selection Diversity algorithm. The proposed multi-hop cooperative WSN is optimally designed for minimum end-to-end outage probability by deriving the optimum time and power allocated on the intracluster and intercluster slots of every single hop, given a per-link energy constraint. A simplified suboptimum resource allocation is also proposed, which performs close to the optimal policy. Results show that the proposed scheme achieves diversity equal to the equivalent MIMO system and significantly reduces energy consumption with respect to. the non-cooperative channel