Size Control and Magnetic Property Trends in Cobalt Ferrite Nanoparticles Synthesized Using an Aqueous Chemical Route

Cobalt ferrite (CoFe2O4) is an engineering material which is used for applications such as magnetic cores, magnetic switches, hyperthermia based tumor treatment, and as contrast agents for magnetic resonance imaging. Utility of ferrites nanoparticles hinges on its size, dispersibility in solutions, and synthetic control over its coercivity. In this work, we establish correlations between room temperature co-precipitation conditions, and these crucial materials parameters. Furthermore, post-synthesis annealing conditions are correlated with morphology, changes in crystal structure and magnetic properties. We disclose the synthesis and process conditions helpful in obtaining easily sinterable CoFe2O4 nanoparticles with coercive magnetic flux density (H-c) in the range 5.5-31.9 kA/m and M-s in the range 47.9-84.9 A.m(2)Kg(-1). At a grain size of similar to 54 +/- 2 nm (corresponding to 1073 K sintering temperature), multi-domain behavior sets in, which is indicated by a decrease in H-c. In addition, we observe an increase in lattice constant with respect to grain size, which is the inverse of what is expected of in ferrites. Our results suggest that oxygen deficiency plays a crucial role in explaining this inverse trend. We expect the method disclosed here to be a viable and scalable alternative to thermal decomposition based CoFe2O4 synthesis. The magnetic trends reported will aid in the optimization of functional CoFe2O4 nanoparticles

Moment-Matched Lognormal Modeling of Uplink Interference with Power Control and Cell Selection

We develop an alternate characterization of the statistical distribution of the inter-cell interference power observed in the uplink of CDMA systems. We show that the lognormal distribution better matches the cumulative distribution and complementary cumulative distribution functions of the uplink interference than the conventionally assumed Gaussian distribution and variants based on it. This is in spite of the fact that many users together contribute to uplink interference, with the number of users and their locations both being random. Our observations hold even in the presence of power control and cell selection, which have hitherto been used to justify the Gaussian distribution approximation. The parameters of the lognormal are obtained by matching moments, for which detailed analytical expressions that incorporate wireless propagation, cellular layout, power control, and cell selection parameters are developed. The moment-matched lognormal model, while not perfect, is an order of magnitude better in modeling the interference power distribution.

Functional Mimics of Glutathione Peroxidase: Bioinspired Synthetic Antioxidants

Oxidative stress is caused by an imbalance between the production of reactive oxygen species (ROS) and the biological system's ability to detoxify these reactive intermediates. Mammalian cells have elaborate antioxidant defense mechanisms to control the damaging effects of ROS. Glutathione peroxidase (GPx), a selenoenzyme, plays a key role in protecting the organism from oxidative damage by catalyzing the reduction of harmful hydroperoxides with thiol a ``catalytic triad'' with tryptophan and glutamine, which cofactors. The selenocysteine residue at the active site forms activates the selenium moiety for an efficient reduction of peroxides. After the discovery that ebselen, a synthetic organoselenium compound, mimics the catalytic activity of GPx both in vitro and in vivo, several research groups developed a number of small-molecule selenium compounds as functional mimics of GPx, either by modifying the basic structure of ebselen or by incorporating some structural features of the native enzyme. The synthetic mimics reported in the literature can be classified in three major categories: (i) cyclic selenenyl amides having a Se-N bond, (ii) diaryl diselenides, and (iii) aromatic or aliphatic monoselenides. Recent studies show that ebselen exhibits very poor GPx activity when aryl or benzylic thiols such as PhSH or BnSH are used as cosubstrates. Because the catalytic activity of each GPx mimic largely depends on the thiol cosubstrates used, the difference in the thiols causes the discrepancies observed in different studies. In this Account, we demonstrate the effect of amide and amine substituents on the GPx activity of various organoselenium compounds. The existence of strong Se ... O/N interactions in the selenenyl sulfide intermediates significantly reduces the GPx activity. These interactions facilitate an attack of thiol at selenium rather than at sulfur, leading to thiol exchange reactions that hamper the formation of catalytically active selenol. Therefore, any substituent capable of enhancing the nucleophilic attack of thiol at sulfur in the selenenyl sulfide state would enhance the antioxidant potency of organoselenium compounds. Interestingly, replacement of the sec-amide substituent by a tert-amide group leads to a weakening of Se ... 0 interactions in the selenenyl sulfide intermediates. This modification results in 10- to 20-fold enhancements in the catalytic activities. Another strategy involving the replacement of tert-amide moieties by tert-amino substituents further increases the activity by 3- to 4-fold. The most effective modification so far in benzylamine-based GPx mimics appears to be either the replacement of a tert-amino substituent by a sec-amino group or the introduction of an additional 6-methoxy group in the phenyl ring. These strategies can contribute to a remarkable enhancement in the GPx activity. In addition to enhancing catalytic activity, a change in the substituents near the selenium moiety alters the catalytic mechanisms. The mechanistic investigations of functional mimics are useful not only for understanding the complex chemistry at the active site of GPx but also for designing and synthesizing novel antioxidants and anti-inflammatory agents.

Adaptive Sleep-Wake Control using Reinforcement Learning in Sensor Networks

The aim in this paper is to allocate the `sleep time' of the individual sensors in an intrusion detection application so that the energy consumption from the sensors is reduced, while keeping the tracking error to a minimum. We propose two novel reinforcement learning (RL) based algorithms that attempt to minimize a certain long-run average cost objective. Both our algorithms incorporate feature-based representations to handle the curse of dimensionality associated with the underlying partially-observable Markov decision process (POMDP). Further, the feature selection scheme used in our algorithms intelligently manages the energy cost and tracking cost factors, which in turn assists the search for the optimal sleeping policy. We also extend these algorithms to a setting where the intruder's mobility model is not known by incorporating a stochastic iterative scheme for estimating the mobility model. The simulation results on a synthetic 2-d network setting are encouraging.

Synthetic image super resolution using FeatureMatch

In this paper, we propose a super resolution (SR) method for synthetic images using FeatureMatch. Existing state-of-the-art super resolution methods are learning based methods, where a pair of low-resolution and high-resolution dictionary pair are trained, and this trained pair is used to replace patches in low-resolution image with appropriate matching patches from the high-resolution dictionary. In this paper, we show that by using Approximate Nearest Neighbour Fields (ANNF), and a common source image, we can by-pass the learning phase, and use a single image for dictionary. Thus, reducing the dictionary from a collection obtained from hundreds of training images, to a single image. We show that by modifying the latest developments in ANNF computation, to suit super resolution, we can perform much faster and more accurate SR than existing techniques. To establish this claim we will compare our algorithm against various state-of-the-art algorithms, and show that we are able to achieve better and faster reconstruction without any training phase.