Determining the enthalpy and specific heat of magnesia spinels in the range 1400–2200°K

Conclusions Temperature functions were obtained for H(T) and C_p(T) which can be used for calculating the thermodynamic functions of the spinels MgAl₂O₄ and MgCr₂O₄ in the temperature regions of their service (up to 2200°K), to supplement the existing relationships (up to 1800°K).Translated from Ogneupory, No. 6, pp. 9–12, June, 1979.     

Thermal conductivity of magnesite refractories in the range 500–1800°C

Conclusions An experimental setup was developed for studying the thermal conductivity of refractories up to 2300°C on the hot face of the specimen.In the average temperature range of 500–1800°C a study was made of the thermal conductivity of magnesite refractories of different porosity. The experimental data obtained satisfactorily agree with well-known literature and calculated values for the thermal conductivity coefficients.Translated from Ogneupory, No. 1, pp. 17–21, January, 1972.     

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.     

Simulations of Self-Expanding Braided Stent Using Macroscopic Model of NiTi Shape Memory Alloys Covering R-Phase

Self-expanding stents or stentgrafts made from Nitinol superelastic alloy are widely used for a less invasive treatment of disease-induced localized flow constriction in the cardiovascular system. The therapy is based on insertion of a stent into a blood vessel to maintain the inner diameter of the vessel; it provides highly effective results at minimal cost and with reduced hospital stays. However, since stent is an external mechanical healing tool implemented into human body for quite a long time, information on the mechanical performance of it is of fundamental importance with respect to patient’s safety and comfort. Advantageously, computational structural analysis can provide valuable information on the response of the product in an environment where in vivo experimentation is extremely expensive or impossible. With this motivation, a numerical model of a particular braided self-expanding stent was developed. As a reasonable approximation substantially reducing computational demands, the stent was considered to be composed of a set of helical springs with specific constrains reflecting geometry of the structure. An advanced constitutive model for NiTi-based shape memory alloys including R-phase transition was employed in analysis. Comparison to measurements shows a very good match between the numerical solution and experimental results. Relation between diameter of the stent and uniform radial pressure on its surface is estimated. Information about internal phase and stress state of the material during compression loading provided by the model is used to estimate fatigue properties of the stent during cyclic loading.     

The effect of flow on the physical properties of polyurethane/carbon nanotubes nanocomposites: Repercussions on their use as electrically conductive Hot‐Melt adhesives

The properties of multiwall carbon nanotubes (MWCNT)/polyurethane (PUR) nanocomposites after being submitted to flow, i.e., in conditions similar to their application as electrically conductive adhesives (ECA), are investigated. A decrease of the elastic modulus is observed after flow is stopped, compatible with a rearrangement of the MWCNT/PUR network during flow. The implications of the viscoelastic results on probe‐tack data are elucidated and a slightly higher energy of adhesion is observed for sheared samples. Dynamic viscoelastic measurements reveal that crystallization of PUR is fastened with MWCNTs, shortening the solidification process for samples submitted to flow or not. Electrical conductivity results show that the 4 wt% MWCNT/PUR nanocomposite can be submitted to flow and give, on cooling to room temperature, values of the electrical conductivity between 10⁻² and 10⁻¹ Siemens /m. 2 wt% MWCNT/PUR sample presents a shear induced semiconductor to insulator transition and a temperature‐induced isolator to semiconductor transition. We conclude that MWCNT/PUR nanocomposites are good candidates to develop Hot Melt ECAs, since they display satisfactory viscosity, tack, crystallization (linked to permanent adhesion), and electrical conductivity. POLYM. COMPOS., 36:704–712, 2015. © 2014 Society of Plastics Engineers     

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