Thermodynamic Modeling of Alkali Metal Oxide-Silica Binary Melts

The evaluation of the thermodynamic properties as well as the phase diagrams for the binary Na₂O–SiO₂, K₂O–SiO₂, and Li₂O–SiO₂ systems are carried out with a structural model for silicate melts and glasses. This thermodynamic model is based on the assumption that each metallic oxide produces the depolymerization reaction of silica network with a characteristic free-energy change. A least squares optimization program permits all available thermodynamic and phase diagram data to be optimized simultaneously. In this manner, data for these binary systems have been analyzed and represented with a small number of parameters. The resulting equations represent the thermodynamic and phase diagram data for these alkali metal oxide–silica systems within experimental error limits. In particular, the measured limiting liquidus slope at     is well reproduced.     

CO2‐assisted polymer processing: A new alternative for intractable polymers

CO₂‐assisted polymer processing is proposed as an alternative route for intractable and high molecular weight polymers based on the plasticization effects of CO₂ and its direct effect on the melting behavior of semicrystalline polymers. A modified processing system was used to process a variety of polymers in the presence of high‐pressure CO₂. The system includes an extruder that was modified to allow for high pressures created by the injection of CO₂. The new design includes a modified feed section that allows a given mass of polymer to interact with CO₂ before and during the extrusion process. The inherent shear mixing and the presence of CO₂ allow for a specific control over the extrudate morphology. Results suggest that this alternative design provides a new and easy route to melt process high melt viscosity polymers of commercial importance, such as polytetrafluoroethylene (PTFE), fluorinated ethylene propylene copolymer (FEP), and syndiotactic polystyrene (s‐PS). The increased processability of these systems in CO₂ is related to the plasticization effect of CO₂ that was quantified through a depression in the glass‐transition temperature according to the Chow model. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 93: 1501–1511, 2004     

Mit zweierlei Maß: Die mangelnde Verbindlichkeit von Patientenverfügungen bei untergebrachten Personen mit psychischen Störungen in der Schweiz

Definition of the problem

Full age patients with mental disorders and preserved decision-making capacity are increasingly interested in drafting advance directives. Whereas in Switzerland (as well as in Germany) advance directives are binding in principle, an advance directive is not binding and has only to be considered in case of involuntary admission due to a mental disorder. Thereby, the virtual aim of an advance directive – the anticipated self-determination – is questioned.

Arguments

From an ethical perspective, patients with mental disorders have the same rights as patients with somatic diseases. Therefore, the question arises if there are good reasons for this unequal treatment. In the present contribution, four possible reasons are analyzed: (1) persons with mental disorders are “different”; (2) protection from self-harm; (3) often not present end-of-life context; (4) reduced bindingness as the more appropriate standard in general.

Conclusion

The authors come to the conclusion that patients with mental disorders are often capable of composing a valid advance directive, and just as any other human being, they have a principal and binding right for self-determination, even though they are particularly vulnerable in crisis situations.

     

A customised approach to determining the geomorphic effectiveness of small flood events in a regulated river

The construction of dams significantly alters flow and sediment regimes with subsequent deleterious effects on the morphological and ecological character of rivers. Effective experimental floods can ameliorate the downstream geomorphic impacts of dams. The traditional view is that large floods are required to perform effective geomorphic work, and the geomorphic outcomes of small floods are often overlooked. Many river restoration frameworks do not consider small floods. Yet, there is evidence that the hydrological characteristics that ameliorate specific geomorphic impacts in a river are unique to each river, and a customised approach to setting the right mix of floods (including small experimental floods) is needed. In this study, we modify an existing flood effectiveness model developed for large floods, for determining the geomorphic effectiveness of small floods in a highly regulated Australian river. Two flood classes were added to the model (medium peak stream power and moderate total energy expenditure), and the flood power characteristics were rescaled to reflect the relative difference in the magnitude of the small floods and the magnitude of the geomorphic work performed. Using a step‐wise approach, this customised model determined the geomorphic effectiveness of small floods. The best flood for ameliorating the geomorphic impacts of flow regulation had medium to long duration (10 to 51 days), high peak unit stream power (77 to 123 Wm^?2) and moderate to large total energy expenditure (78,600 to 342,320 × 10³ J). This approach to determining flood effectiveness for small floods is applicable to other geomorphically impacted river channels downstream of dams and can be used to inform experimental flood releases for geomorphic outcomes.     

Extended Reflexive Ontologies for the Generation of Clinical Recommendations

Decision recommendations are a set of alternative options for clinical decisions (e.g., diagnosis, prognosis, treatment selection, follow-up, and prevention) that are provided to decision makers by knowledge-based Clinical Decision Support Systems (k-CDSS) as aids. We propose to follow a “reasoning over domain” approach for the generation of decision recommendations by gathering and inferring conclusions from production rules. In order to rationalize our approach, we present a specification that will sustain the logic models supported in the knowledge bases we use for persistence. We introduce first the underlying knowledge model and then the necessary extensions that will convey toward the solution of the reported needs. The starting point of our approach is the proposition of Reflexive Ontologies (RO). Here, we go a step further, proposing an extension of RO that includes the handling and reasoning that production rules provide. Our approach speeds up the recommendation generation process.     

Reliable Communication Networks for Smart Grid Transmission Systems

In this paper, we discuss the communications reliability requirements posed by the smart power grid with a focus on communications in support of wide area situational awareness. Implementation of wide area situational awareness relies on both transmission substation networks and wide area optical networks. We study the reliability of a sample communications network of the California Power Grid and find that its reliability falls short of proposed requirements. To overcome this issue, we consider the problem of designing the substation network and the wide area network to meet the reliability requirements while minimizing the network cost. For the wide area network design problem, we propose two alternate design approaches, namely: (1) following the power lines and (2) a mesh based design interconnecting the nodes. For the first approach we develop two greedy iterative heuristics and a heuristic integer linear programming (H-ILP) model using minimum cut-sets for network reliability optimization. The greedy iterative algorithms outperform the H-ILP approach in terms of cost, but require a larger amount of computing resources. Both proposed models are in fact complementary and thus provide a framework to optimize the reliability of smart grid communications networks restricted to following the power lines. In the second approach a greenfield mesh network method is proposed based on starting with a minimum spanning tree which is then augmented through a greedy heuristic into a mesh. Comparative numerical results show that the reliable mesh design has advantages in terms of the number of links and total link distance needed.     

Real time motion estimation using a neural architecture implemented on GPUs

This work describes a neural network based architecture that represents and estimates object motion in videos. This architecture addresses multiple computer vision tasks such as image segmentation, object representation or characterization, motion analysis and tracking. The use of a neural network architecture allows for the simultaneous estimation of global and local motion and the representation of deformable objects. This architecture also avoids the problem of finding corresponding features while tracking moving objects. Due to the parallel nature of neural networks, the architecture has been implemented on GPUs that allows the system to meet a set of requirements such as: time constraints management, robustness, high processing speed and re-configurability. Experiments are presented that demonstrate the validity of our architecture to solve problems of mobile agents tracking and motion analysis.     

Improving the Control Energy in Model Reference Adaptive Controllers Using Fractional Adaptive Laws

This paper presents the analysis of the control energy consumed in model reference adaptive control (MRAC) schemes using fractional adaptive laws, through simulation studies. The analysis is focused on the energy spent in the control signal represented by means of the integral of the squared control input (ISI). Also, the behavior of the integral of the squared control error (ISE) is included in the analysis. The orders of the adaptive laws were selected by particle swarm optimization (PSO), using an objective function including the ISI and the ISE, with different weighting factors. The results show that, when ISI index is taken into account in the optimization process to determine the orders of adaptive laws, the resulting values are fractional, indicating that control energy of the scheme might be better managed if fractional adaptive laws are used.