Peptide-mediated constructs of quantum dot nanocomposites for enzymatic control of nonradiative energy transfer

A bottom-up approach for constructing colloidal semiconductor quantum dot (QDot) nanocomposites that facilitate nonradiative Fo?rster-type resonance energy transfer (FRET) using polyelectrolyte peptides was proposed and realized. The electrostatic interaction of these polypeptides with altering chain lengths was probed for thermodynamic, structural, and morphological aspects. The resulting nanocomposite film was successfully cut with the protease by digesting the biomimetic peptide layer upon which the QDot assembly was constructed. The ability to control photoluminescence decay lifetime was demonstrated by proteolytic enzyme activity, opening up new possibilities for biosensor applications.     

Workload Distribution Framework for the Parallel Solution of Large Structural Models on Heterogeneous PC Clusters

One of the main problems of substructure-based parallel solution methods is the imbalances in the condensation times of substructures when direct solvers are used. Such imbalances usually decrease the performance of the parallel solution. Thus, in this study, a workload distribution framework for such methods at heterogeneous computing environment is presented. The main idea behind this framework is to iteratively adjust the shapes of substructures so that the imbalance in their condensation times is minimized. Both generated and actual structural models were solved to illustrate the applicability and the efficiency of this approach. In these examples, a PC cluster having eight different computers was used.     

Pricing strategies for differentiated services content delivery networks

In order to reduce the user latency, the web sites disseminate some of their information to surrogate caches located closer to the users. We discuss a simple differentiated service type architecture for content delivery networks. A pricing scheme is next proposed to complement this architecture and provide fair service to the subscribed publishers. Then, we show that the suggested pricing scheme is also the optimal (revenue maximizing) pricing scheme for a monopolistic surrogate. We investigate the performance of the pricing scheme in a duopoly and show that under certain conditions the competition results in peering of the surrogates. Finally, we suggest methods to determine the optimal number of service classes offered to the users.     

Renal afferent impulses, the posterior hypothalamus, and hypertension in rats with chronic renal failure

Hypertension in 5/6 nephrectomized (CRF) rats is partly related to increased activity of the sympathetic nervous system. We have previously shown a greater norepinephrine turnover rate in the posterior hypothalamic nuclei and locus coeruleus of CRF than control rats. Dorsal rhizotomy prevented the rise in blood pressure and the increase in NE turnover rate in the posterior hypothalamus and the locus coeruleus. The studies suggest that afferent impulses from the kidney to central integrative structures in the brain may be responsible for hypertension in CRF rats. To further evaluate the role of renal afferent nerves in the regulation of blood pressure, and whether renal afferent pathways integrate with the posterior hypothalamus, we studied the effects of an intrarenal injection of 50 microliters of 10% phenol on blood pressure and NE secretion from the posterior hypothalamus of Sprague-Dawley rats. Mean arterial pressure increased from 89 +/- 4.0 to 114 +/- 4.3 mm Hg in rats which received intrarenal injection of phenol, but it did not change in rats that received vehicle (95 +/- 4.3 and 89 +/- 3.6 mm Hg, respectively). Renal denervation totally prevented the increase in blood pressure caused by intrarenal injection of phenol. The secretion of NE from the posterior hypothalamus increased from 139 +/- 4.8 to 250 +/- 9.9 pg/ml (P < 0.01) in rats that received intrarenal phenol, but it did not change in rats which received vehicle or in those with renal denervation. In CRF rats NE secretion from the posterior hypothalamus was greater than in control and CRF rats subjected to dorsal rhizotomy. These studies show that afferent impulses from an injured kidney increase NE secretion from the posterior hypothalamus and raise blood pressure. NE secretion is higher in the posterior hypothalamus of CRF than control rats. The posterior hypothalamus appears to be an important integrative structure of the sympathetic regulation of blood pressure.     

Active and reactive power sharing and frequency restoration in a distributed power system consisting of two UPS units

A distributed power system consisting of two uninterrupted power supplies (UPS) is investigated in this paper. Parallel operation of the two sources increases the established power rating of the system. One of the sources can supply the system even when the other system is disconnected due to some faults, and this is an important feature. The control algorithm makes sure that the total load is shared between the supplies in accordance with their rated power levels, and the frequency of the supplies are restored to the rated values after the transitions. As the UPSs operate at an optimum power level, losses and faults due to overloading are prevented. The units safely operate without any means of communication between each other. The focus of the work is on the inverter stages of the UPSs. Simulations performed in Matlab Simulink environment have been verified with experimental work via DS1103 controller card.     

Intermittent Streamflow Forecasting by Using Several Data Driven Techniques

Forecasting intermittent streamflows is an important issue for water quality management, water supplies, hydropower and irrigation systems. This paper compares the accuracy of several data driven techniques, that is, adaptive neuro fuzzy inference system (ANFIS), artificial neural networks (ANNs) and support vector machine (SVM) for forecasting daily intermittent streamflows. The results are also compared with those of the local linear regression (LLR) and the dynamic local linear regression (DLLR). Intermittent streamflow data from two stations, Uzunkopru and Babaeski, in Thrace region located in north-western Turkey are used in the study. The root mean square error and correlation coefficient were used as comparison criteria. The comparison results indicated that the ANFIS, ANN and SVM models performed better than the LLR and DLLR models in forecasting daily intermittent streamflows. The ANN and ANFIS gave the best forecasts for the Uzunkopru and Babaeski stations, respectively.     

Hierarchical Cooperation Achieves Optimal Capacity Scaling in Ad Hoc Networks

n source and destination pairs randomly located in an area want to communicate with each other. Signals transmitted from one user to another at distance r apart are subject to a power loss of r^-alpha as well as a random phase. We identify the scaling laws of the information-theoretic capacity of the network when nodes can relay information for each other. In the case of dense networks, where the area is fixed and the density of nodes increasing, we show that the total capacity of the network scales linearly with n. This improves on the best known achievability result of n^2/3 of Aeron and Saligrama. In the case of extended networks, where the density of nodes is fixed and the area increasing linearly with n, we show that this capacity scales as n^2-alpha/2 for 2lesalpha<3 and radicn for a alphages3. The best known earlier result of Xie and Kumar identified the scaling law for alpha > 4. Thus, much better scaling than multihop can be achieved in dense networks, as well as in extended networks with low attenuation. The performance gain is achieved by intelligent node cooperation and distributed multiple-input multiple-output (MIMO) communication. The key ingredient is a hierarchical and digital architecture for nodal exchange of information for realizing the cooperation.