Radio Frequency Energy Harvesting and Management for Wireless Sensor Networks

Radio Frequency (RF) Energy Harvesting holds a promising future for generating a small amount of electrical power to drive partial circuits in wirelessly communicating electronics devices. Reducing power consumption has become a major challenge in wireless sensor networks. As a vital factor affecting system cost and lifetime, energy consumption in wireless sensor networks is an emerging and active research area. This chapter presents a practical approach for RF Energy harvesting and management of the harvested and available energy for wireless sensor networks using the Improved Energy Efficient Ant Based Routing Algorithm (IEEABR) as our proposed algorithm. The chapter looks at measurement of the RF power density, calculation of the received power, storage of the harvested power, and management of the power in wireless sensor networks. The routing uses IEEABR technique for energy management. Practical and real-time implementations of the RF Energy using Powercast harvesters and simulations using the energy model of our Libelium Waspmote to verify the approach were performed. The chapter concludes with performance analysis of the harvested energy, comparison of IEEABR and other traditional energy management techniques, while also looking at open research areas of energy harvesting and management for wireless sensor networks.Comment: 40 pages, 9 figures, 5 tables, Book chapte

An Adaptive Lossless Data Compression Scheme for Wireless Sensor Networks

Energy is an important consideration in the design and deployment of wireless sensor networks (WSNs) since sensor nodes are typically powered by batteries with limited capacity. Since the communication unit on a wireless sensor node is the major power consumer, data compression is one of possible techniques that can help reduce the amount of data exchanged between wireless sensor nodes resulting in power saving. However, wireless sensor networks possess significant limitations in communication, processing, storage, bandwidth, and power. Thus, any data compression scheme proposed for WSNs must be lightweight. In this paper, we present an adaptive lossless data compression (ALDC) algorithm for wireless sensor networks. Our proposed ALDC scheme performs compression losslessly using multiple code options. Adaptive compression schemes allow compression to dynamically adjust to a changing source. The data sequence to be compressed is partitioned into blocks, and the optimal compression scheme is applied for each block. Using various real-world sensor datasets we demonstrate the merits of our proposed compression algorithm in comparison with other recently proposed lossless compression algorithms for WSNs

FDG–PET. A possible prognostic factor in head and neck cancer

Previous studies have shown that high uptake of 18F-fluoro-2-deoxy-glucose in head and neck cancer, as determined by the standardized uptake value on positron emission tomography scan, was associated with poor survival. The aim of this study was to confirm the association and to establish whether a high standardized uptake value had prognostic significance. Seventy-three consecutive patients with newly diagnosed squamous cell carcinoma of the head and neck underwent a positron emission tomography study before treatment. Age, gender, performance status tumour grade, stage, maximal tumour diameter and standardized uptake value were analyzed for their possible association with survival. The median standardized uptake value for all primary tumours was 7.16 (90% range 2.30 to 18.60). In univariate survival analysis the cumulative survival was decreased as the stage, tumour diameter and standardized uptake value increased. An standardized uptake value of 10 was taken as a cut-off for high and low uptake tumours. When these two groups were compared, an standardized uptake value >10 predicted for significantly worse outcome (P=0.003). Multivariate analysis demonstrated that an standardized uptake value >10 provided prognostic information independent of the tumour stage and diameter (P=0.002). We conclude that high FDG uptake (standardized uptake value>10) on positron emission tomography is an important marker for poor outcome in primary squamous cell carcinoma of the head and neck. Standardized uptake value may be useful in distinguishing those tumours with a more aggressive biological nature and hence identifying patients that require intensive treatment protocols including hyperfractionated radiotherapy and/or chemotherapy

A time-domain control signal detection technique for OFDM

Transmission of system-critical control information plays a key role in efficient management of limited wireless network resources and successful reception of payload data information. This paper uses an orthogonal frequency division multiplexing (OFDM) architecture to investigate the detection performance of a time-domain approach used to detect deterministic control signalling information. It considers a type of control information chosen from a finite set of information, which is known at both transmitting and receiving wireless terminals. Unlike the maximum likelihood (ML) estimation method, which is often used, the time-domain detection technique requires no channel estimation and no pilots as it uses a form of time-domain correlation as the means of detection. Results show that when compared with the ML method, the time-domain approach improves detection performance even in the presence of synchronisation error caused by carrier frequency offset

An in vitro method to select malignant cells from surgical biopsies of breast cancer patients

To date, breast cancer (BC) research is mainly studied with cell lines. These cells were passaged multiple times, acquiring phenotypes, additional mutations and epigenetic changes. These changes make the passaged cell lines different from the original malignancy. Thus cell lines, although useful as models could be improved with additional studies with primary BC. It is difficult to obtain malignant cells from breast tissues without contamination from surrounding healthy cells. Selection and expansion of malignant cells from surgical tissues have proved to be daunting tasks. This study describes a reliable and reproducible method for isolating and expanding malignant cells from surgical breast tissues. The method uses co-cultures with BM stroma to select for the cancer cells while the healthy cells undergo rapid cell death. Studies are described to show the cloning efficiencies and sensitivity of the method using surgical samples of varying sizes, different stages of BC, and samples from needle biopsies

Radiotherapy volume delineation using dynamic [18F]-FDG PET/CT imaging in patients with oropharyngeal cancer: a pilot study

Abstract PURPOSE: Delineation of gross tumour volume in 3D is a critical step in the radiotherapy (RT) treatment planning for oropharyngeal cancer (OPC). Static [Formula: see text]-FDG PET/CT imaging has been suggested as a method to improve the reproducibility of tumour delineation, but it suffers from low specificity. We undertook this pilot study in which dynamic features in time-activity curves (TACs) of [Formula: see text]-FDG PET/CT images were applied to help the discrimination of tumour from inflammation and adjacent normal tissue. METHODS: Five patients with OPC underwent dynamic [Formula: see text]-FDG PET/CT imaging in treatment position. Voxel-by-voxel analysis was performed to evaluate seven dynamic features developed with the knowledge of differences in glucose metabolism in different tissue types and visual inspection of TACs. The Gaussian mixture model and K-means algorithms were used to evaluate the performance of the dynamic features in discriminating tumour voxels compared to the performance of standardized uptake values obtained from static imaging. RESULTS: Some dynamic features showed a trend towards discrimination of different metabolic areas but lack of consistency means that clinical application is not recommended based on these results alone. CONCLUSIONS: Impact of inflammatory tissue remains a problem for volume delineation in RT of OPC, but a simple dynamic imaging protocol proved practicable and enabled simple data analysis techniques that show promise for complementing the information in static uptake values.  </p

HI Narrow Self-Absorption in Dark Clouds: Correlations with Molecular Gas and Implications for Cloud Evolution and Star Formation

We present the results of a comparative study of HI narrow self-absorption (HINSA), OH, 13CO, and C18O in five dark clouds. The HINSA follows the distribution of the emission of the carbon monoxide isotopologues, and has a characteristic size close to that of 13CO. This confirms that the HINSA is produced by cold HI which is well mixed with molecular gas in well-shielded regions. The ratio of the atomic hydrogen density to total proton density for these sources is 5 to 27 x 10^{-4}. Using cloud temperatures and the density of HI, we set an upper limit to the cosmic ray ionization rate of 10^{-16} s^{-1}. Comparison of observed and modeled fractional HI abundances indicates ages for these clouds to be 10^{6.5} to 10^{7} yr. The low values of the HI density we have determined make it certain that the time scale for evolution from an atomic to an almost entirely molecular phase, must be a minimum of several million years. This clearly sets a lower limit to the overall time scale for star formation and the lifetime of molecular clouds