Five-stage Milstein methods for SDEs

In this paper, we consider the problem of computing numerical solutions for Ito stochastic differential equations (SDEs). The five-stage Milstein (FSM) methods are constructed for solving SDEs driven by an m-dimensional Wiener process. The FSM methods are fully explicit methods. It is proved that the FSM methods are convergent with strong order 1 for SDEs driven by an m-dimensional Wiener process. The analysis of stability (with multidimensional Wiener process) shows that the mean-square stable regions of the FSM methods are unbounded. The analysis of stability shows that the mean-square stable regions of the methods proposed in this paper are larger than the Milstein method and three-stage Milstein methods.

Dual-Stage Power Management Algorithms for Energy Harvesting Sensors

In this paper, we propose power management algorithms for maximizing the utility of energy harvesting sensors (EHS) that operate purely on the basis of energy harvested from the environment. In particular, we consider communication (i.e., transmission and reception) power management issues for EHS under an energy neutrality constraint. We also consider the fixed power loss effects of the circuitry, the battery inefficiency and its storage capacity, in the design of the algorithms. We propose a two-stage structure that exploits the inherent difference in the timescales at which the energy harvesting and channel fading processes evolve, without loss of optimality of the resulting solution. The outer stage schedules the power that can be used by an inner stage algorithm, so as to maximize the long term average utility and at the same time maintain energy neutrality. The inner stage optimizes the communication parameters to achieve maximum utility in the short-term, subject to the power constraint imposed by the outer stage. We optimize the algorithms for different transmission schemes such as the truncated channel inversion and retransmission strategies. The performance of the algorithms is illustrated via simulations using solar irradiance data, and for the case of Rayleigh fading channels. The results demonstrate the significant performance benefits that can be obtained using the proposed power management algorithms compared to the energy efficient (optimum when there is no storage) and the uniform power consumption (optimum when the battery has infinite capacity and is perfectly efficient) approaches.

Performances of single and two-stage pulse tube cryocoolers under different vacuum levels with and without thermal radiation shields

Single and two-stage Pulse Tube Cryocoolers (PTC) have been designed, fabricated and experimentally studied. The single stage PTC reaches a no-load temperature of similar to 29 K at its cold end, the two-stage PTC reaches similar to 2.9 K in its second stage cold end and similar to 60 K in its first stage cold end. The two-stage Pulse Tube Cryocooler provides a cooling power of similar to 250 mW at 4.2 K. The single stage system uses stainless steel meshes along with Pb granules as its regenerator materials, while the two-stage PTC uses combinations of Pb along with Er3Ni/HoCu2 as the second stage regenerator materials. Normally, the above systems are insulated by thermal radiation shields and mounted inside a vacuum chamber which is maintained at high vacuum. To evaluate the performance of these systems in the possible conditions of loss of vacuum with and without radiation shields, experimental studies have been performed. The heat-in-leak under such severe conditions has been estimated from the heat load characteristics of the respective stages. The experimental results are analyzed to obtain surface emissivities and effective thermal conductivities as a function of interspace pressure.

A Single-Stage Water-Gas Shift Reaction over Highly Active and Stable Si- and Al-Substituted Pt/CeO2 Catalysts

Ce0.88Si0.1Pt0.02O2-d and Ce0.88Al0.1Pt0.02O2-d catalysts were synthesized by using a low-temperature sonochemical method and characterized by using XRD, TEM, XPS, FTIR, and BET surface analyzer. The catalytic activities of these compounds were investigated for the watergas shift reaction in the temperature range of 140-440 degrees C. The substitution of Si in Ce0.98Pt0.02O2-d increased the releasing capacity of lattice oxygen, whereas the substitution of Al decreased the reducibility of Ce0.98Pt0.02O2-d, as evidenced by hydrogen temperature-programmed reduction studies. However, both the catalysts showed a considerable improvement in terms of activity and stability compared to Ce0.98Pt0.02O2-d. The combined activity measurement and characterization results suggest that the increase in the oxygen vacancy, which acts as a dissociation center for water, is the primary reason for the improvement in the activity of modified Ce0.98Pt0.02O2-d. Both the catalysts are 100?% selective toward H2 production, and approximately 99?% conversion of CO to CO2 was observed at 260 and 270 degrees C for Ce0.88Si0.1Pt0.02O2-d and Ce0.88Al0.1Pt0.02O2-d, respectively. These catalysts do not deactivate during the daily startup/shutdown operations and are sustainable even after prolonged reaction. Notably, these catalysts do not require any pretreatment or activation during startup/shutdown operations.

A Two Stage Selective Averaging LDPC Decoding

Low density parity-check (LDPC) codes are a class of linear block codes that are decoded by running belief propagation (BP) algorithm or log-likelihood ratio belief propagation (LLR-BP) over the factor graph of the code. One of the disadvantages of LDPC codes is the onset of an error floor at high values of signal to noise ratio caused by trapping sets. In this paper, we propose a two stage decoder to deal with different types of trapping sets. Oscillating trapping sets are taken care by the first stage of the decoder and the elementary trapping sets are handled by the second stage of the decoder. Simulation results on the regular PEG (504,252,3,6) code and the irregular PEG (1024,518,15,8) code shows that the proposed two stage decoder performs significantly better than the standard decoder.

Smoothed functional and Quasi-Newton algorithms for routing in multi-stage queueing network with constraints

We consider the problem of optimal routing in a multi-stage network of queues with constraints on queue lengths. We develop three algorithms for probabilistic routing for this problem using only the total end-to-end delays. These algorithms use the smoothed functional (SF) approach to optimize the routing probabilities. In our model all the queues are assumed to have constraints on the average queue length. We also propose a novel quasi-Newton based SF algorithm. Policies like Join Shortest Queue or Least Work Left work only for unconstrained routing. Besides assuming knowledge of the queue length at all the queues. If the only information available is the expected end-to-end delay as with our case such policies cannot be used. We also give simulation results showing the performance of the SF algorithms for this problem.

Hierarchical artificial immune system for crop stage classification

This paper presents a new hierarchical clustering algorithm for crop stage classification using hyperspectral satellite image. Amongst the multiple benefits and uses of remote sensing, one of the important application is to solve the problem of crop stage classification. Modern commercial imaging satellites, owing to their large volume of satellite imagery, offer greater opportunities for automated image analysis. Hence, we propose a unsupervised algorithm namely Hierarchical Artificial Immune System (HAIS) of two steps: splitting the cluster centers and merging them. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The classification results have been compared with K-means and Artificial Immune System algorithms. From the results obtained, we conclude that the proposed hierarchical clustering algorithm is accurate.

Heat Shock Protein 90 Inhibitors as Broad Spectrum Anti-Infectives

Combating stress is one of the prime requirements for any organism. For parasitic microbes, stress levels are highest during the growth inside the host. Their survival depends on their ability to acclimatize and adapt to new environmental conditions. Robust cellular machinery for stress response is, therefore, both critical and essential especially for pathogenic microorganisms. Microbes have cleverly exploited stress proteins as virulence factors for pathogenesis in their hosts. Owing to its ability to sense and respond to the stress conditions, Heat shock protein 90 (Hsp90) is one of the key stress proteins utilized by parasitic microbes. There are growing evidences for the critical role played by Hsp90 in the growth of pathogenic organisms like Candida, Giardia, Plasmodium, Trypanosoma, and others. This review, therefore, explores potential of exploiting Hsp90 as a target for the treatment of infectious diseases. This molecular chaperone has already gained attention as an effective anti-cancer drug target. As a result, a lot of research has been done at laboratory, preclinical and clinical levels for several Hsp90 inhibitors as potential anti-cancer drugs. In addition, lot of data pertaining to toxicity studies, pharmacokinetics and pharmacodynamics studies, dosage regime, drug related toxicities, dose limiting toxicities as well as adverse drug reactions are available for Hsp90 inhibitors. Therefore, repurposing/repositioning strategies are also being explored for these compounds which have gone through advanced stage clinical trials. This review presents a comprehensive summary of current status of development of Hsp90 as a drug target and its inhibitors as candidate anti-infectives. A particular emphasis is laid on the possibility of repositioning strategies coupled with pharmaceutical solutions required for fulfilling needs for ever growing pharmaceutical infectious disease market.