Hydrothermal synthesis of zirconium oxide nanoparticles and its characterization

The paper presents the preparation and investigations of zirconium oxide (ZrO₂) nanoparticles that were synthesized by hydrothermal method. The products were characterized by means of powder X-ray diffraction, scanning electron microscopy (SEM), transmission electron microscopy (TEM), UV-absorption spectroscopy and photoluminescence (PL) spectroscopy. The crystal structure was determined using X-ray diffraction. The morphology and the particle size were studied using (SEM) and (TEM). The spherical shaped particles were confirmed through the SEM analysis. The transmission electron microscopic analysis confirmed the formation of the nanoparticles with the particle size. The FT-IR and Raman spectrum ascertained the strong presence of ZrO₂ nanoparticles. The optical properties were obtained from UV–visible absorption spectrum and also PL emission spectrum. The dielectric constant and the dielectric loss were measured as a function of frequency and temperature.     

Life cycle energy and carbon footprint analysis of photovoltaic battery microgrid system in India

Electricity supply in India is from a centralized grid. Many parts of the country experience grid interruptions. Life cycle energy and environmental analysis has been done for a 27 kWp photovoltaic system which acts as grid backup for 3 h outage in an Indian urban residential scenario. This paper discusses energy requirements and carbon emission for a PV storage system for five different battery technologies in Indian context. This can be used as a metric for comparative analysis for new batteries, with an undeveloped market. The energy requirements for the components are quantified and are compared in terms of energy payback time (EPBT) and Net Energy Ratio (NER). All the calculations are done for Indian context. EPBT is found to be in the range of 2–4.5 years for all the systems, while NER is in the range of 6.6–2.52. NaS has the highest emission factor of 0.67 kgCO₂/kWh and the least for NiCd (0.091 kgCO₂/kWh). These factors can be used to select a PV battery option and to target selection of materials and systems based on the reported values.     

The role of protein kinase in C ischemic/reperfused preconditioned isolated rat hearts

Protein kinase C (PKC) has been implicated in the preconditioning-induced cardiac protection in ischemic/reperfused myocardium. We studied the effect of PKC inhibition with calphostin C (25, 50, 100, 200, 400, and 800 nM), a potent and specific inhibitor of PKC, in isolated working nonpreconditioned and preconditioned ischemic/reperfused hearts. In the nonpreconditioned groups, all hearts underwent 30 min of normothermic global ischemia followed by 30 min of reperfusion. In the preconditioned groups, hearts were subjected to four cycles of ischemic preconditioning by using 5 min of ischemia followed by 10 min reperfusion, before the induction of 30 min ischemia and reperfusion. At low concentrations of calphostin C (25, 50, and 100 nM), the PKC inhibitor had no effect on the incidence or arrhythmias or postischemic cardiac function in the nonpreconditioned ischemic/reperfused groups. With 200 and 400 nM of calphostin C, a significant increase in postischemic function and a reduction in the incidence of arrhythmias were observed in the nonpreconditioned ischemic/reperfused groups. Increasing the concentration of calphostin C to 800 NM, the recovery of postischemic cardiac function was similar to that of the drug-free control group. In preconditioned hearts, lower concentrations (< 100 nM) of calphostin C did not change the response of the myocardium to ischemia and reperfusion in comparison to the preconditioned drug-free myocardium. Two hundred and 400 nM of the PKC inhibitor further reduced the incidence of ventricular fibrillation (VF) from the preconditioned drug-free value of 50% to 0 (p < 0.05) and 0 (p < 0.05), respectively, indicating that the combination of the two, preconditioning and calphostin C, affords significant additional protection. Increasing the concentration of calphostin C to 800 nM blocked the cardioprotective effect of preconditioning (100% incidence of VF). The recovery of cardiac function was similarly improved at calphostin C doses of 200 and 400 nM and was reduced at 800 nM (p < 0.05). With 200 and 400 nM of calphostin C, both cytosolic and particulate PKC activity were reduced by approximately 40 and 60%, respectively, in both preconditioned and preconditioned/ischemic/reperfused hearts. The highest concentration of calphostin C (800 nM) resulted in almost a complete inhibition of cytosolic (100%) and particulate (85%) PKC activity correlated with the abolition of preconditioning-induced cardiac protection. In conclusion, calphostin C protects the ischemic myocardium obtained from intact animals, provides significant additional protection to preconditioning at moderate doses, and blocks the protective effect of preconditioning at high concentrations. The dual effects of calphostin C appear to be strictly dose and "enzyme inhibition" related.     

Computing delay resistant railway timetables

In the past, much research has been dedicated to compute optimum railway timetables. A typical objective has been the minimization of passenger waiting times. But only the planned nominal waiting times have been addressed, whereas delays as they occur in daily operations have been neglected. Delays have been rather treated mainly in an online context and solved as a separate optimization problem, called delay management.We provide the first computational study which aims at computing delay resistant periodic timetables. In particular we assess the delay resistance of a timetable by evaluating it subject to several delay scenarios to which optimum delay management will be applied.We arrive at computing delay resistant timetables by selecting a new objective function which we design to be somehow in the middle of the traditional simple timetabling objective and the sophisticated delay management objective. This is a slight extension of the concept of “light robustness” (LR) as it has been proposed by Fischetti and Monaci [2006. Robust optimization through branch-and-price. In: Proceedings of AIRO]. Moreover, in our application we are able to provide accurate interpretations for the ingredients of LR. We apply this new technique to real-world data of a part of the German railway network of Deutsche Bahn AG. Our computational results suggest that a significant decrease of passenger delays can be obtained at a relatively small price of robustness, i.e. by increasing the nominal travel times of the passengers.     

Dynamic control mechanisms for revenue management with flexible products

Revenue management with flexible products has experienced a growing interest in the academic literature within the last few years. Flexible products allow supply-side substitution between resources and can therefore help to maximize overall revenue as well as capacity utilization in markets with highly uncertain demand. This paper addresses the question of how the mathematical models which have been developed for capacity control with flexible products should be used over time to exploit the substitution opportunities, while keeping practical applicability in mind. Several dynamic control mechanisms are proposed, each of which makes use of the flexibility to a different extent. A comprehensive computational study shows the potential of the different approaches by revealing their strengths and weaknesses.     

Affine-based registration of CT and MR modality images of human brain using multiresolution approaches: comparative study on genetic algorithm and particle swarm optimization

We present a non-linear 2-D/2-D affine registration technique for MR and CT modality images of section of human brain. Automatic registration is achieved by maximization of a similarity metric, which is the correlation function of two images. The proposed method has been implemented by choosing a realistic, practical transformation and optimization techniques. Correlation-based similarity metric should be maximal when two images are perfectly aligned. Since similarity metric is a non-convex function and contains many local optima, choice of search strategy for optimization is important in registration problem. Many optimization schemes are existing, most of which are local and require a starting point. In present study we have implemented genetic algorithm and particle swarm optimization technique to overcome this problem. A comparative study shows the superiority and robustness of swarm methodology over genetic approach.     

Discovering implicit intention-level knowledge from natural-language texts

In this paper, we propose a new approach to automatic discovery of implicit rhetorical information from texts based on evolutionary computation methods. In order to guide the search for rhetorical connections from natural-language texts, the model uses previously obtained training information which involves semantic and structural criteria. The main features of the model and new designed operators and evaluation functions are discussed, and the different experiments assessing the robustness and accuracy of the approach are described. Experimental results show the promise of evolutionary methods for rhetorical role discovery.     

Hadamard quantum broadcast channels

We consider three different communication tasks for quantum broadcast channels, and we determine the capacity region of a Hadamard broadcast channel for these various tasks. We define a Hadamard broadcast channel to be such that the channel from the sender to one of the receivers is entanglement-breaking and the channel from the sender to the other receiver is complementary to this one. As such, this channel is a quantum generalization of a degraded broadcast channel, which is well known in classical information theory. The first communication task we consider is classical communication to both receivers, the second is quantum communication to the stronger receiver and classical communication to other, and the third is entanglement-assisted classical communication to the stronger receiver and unassisted classical communication to the other. The structure of a Hadamard broadcast channel plays a critical role in our analysis: The channel to the weaker receiver can be simulated by performing a measurement channel on the stronger receiver’s system, followed by a preparation channel. As such, we can incorporate the classical output of the measurement channel as an auxiliary variable and solve all three of the above capacities for Hadamard broadcast channels, in this way avoiding known difficulties associated with quantum auxiliary variables.