Deploying a Sensor Network in an Extreme Environment

A wireless sensor network has been designed and deployed to gather data from nodes on and inside glaciers. This paper describes the solutions to power management, radio communications, management and discusses the performance of the final system. 18 months of data have now been received, which provide an insight not only into the glacier’s behaviour but on the design decisions. The system uses custom PIC-based sensor nodes and an ARM-based base station which controls weather and differential GPS. Different versions have been installed in Norway from 2003-5 and this paper describes the lessons learnt from coping with the extreme conditions found in glaciers

Planar Tc99m – sestamibi scintimammography should be considered cautiously in the axillary evaluation of breast cancer protocols: Results of an international multicenter trial

BACKGROUND: Lymph node status is the most important prognostic indicator in breast cancer in recently diagnosed primary lesion. As a part of an interregional protocol using scintimammography with Tc99m compounds, the value of planar Tc99m sestamibi scanning for axillary lymph node evaluation is presented. Since there is a wide range of reported values, a standardized protocol of planar imaging was performed. METHODS: One hundred and forty-nine female patients were included prospectively from different regions. Their mean age was 55.1 ± 11.9 years. Histological report was obtained from 2.987 excised lymph nodes from 150 axillas. An early planar chest image was obtained at 10 min in all patients and a delayed one in 95 patients, all images performed with 740–925 MBq dose of Tc99m sestamibi. Blind lecture of all axillary regions was interpreted by 2 independent observers considering any well defined focal area of increased uptake as an involved axilla. Diagnostic values, 95% confidence intervals [CI] and also likelihood ratios (LR) were calculated. RESULTS: Node histology demonstrated tumor involvement in 546 out of 2987 lymph nodes. Sestamibi was positive in 30 axillas (25 true-positive) and negative in 120 (only 55 true-negative). The sensitivity corresponded to 27.8% [CI = 18.9–38.2] and specificity to 91.7% [81.6–97.2]. The positive and negative LR were 3.33 and 0.79, respectively. There was no difference between early and delayed images. Sensitivity was higher in patients with palpable lesions. CONCLUSION: This work confirmed that non tomographic Tc99m sestamibi scintimammography had a very low detection rate for axillary lymph node involvement and it should not be applied for clinical assessment of breast cancer

A Biased Random Key Genetic Algorithm Approach for Unit Commitment Problem

A Biased Random Key Genetic Algorithm (BRKGA) is proposed to find solutions for the unit commitment problem. In this problem, one wishes to schedule energy production on a given set of thermal generation units in order to meet energy demands at minimum cost, while satisfying a set of technological and spinning reserve constraints. In the BRKGA, solutions are encoded by using random keys, which are represented as vectors of real numbers in the interval [0, 1]. The GA proposed is a variant of the random key genetic algorithm, since bias is introduced in the parent selection procedure, as well as in the crossover strategy. Tests have been performed on benchmark large-scale power systems of up to 100 units for a 24 hours period. The results obtained have shown the proposed methodology to be an effective and efficient tool for finding solutions to large-scale unit commitment problems. Furthermore, from the comparisons made it can be concluded that the results produced improve upon some of the best known solutions

Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject

A utility-based adaptive sensing and multi-hop communication protocol for wireless sensor networks

This article reports on the development of a utility-based mechanism for managing sensing and communication in cooperative multisensor networks. The specific application on which we illustrate our mechanism is that of GlacsWeb. This is a deployed system that uses battery-powered sensors to collect environmental data related to glaciers which it transmits back to a base station so that it can be made available world-wide to researchers. In this context, we first develop a sensing protocol in which each sensor locally adjusts its sensing rate based on the value of the data it believes it will observe. The sensors employ a Bayesian linear model to decide their sampling rate and exploit the properties of the Kullback-Leibler divergence to place an appropriate value on the data. Then, we detail a communication protocol that finds optimal routes for relaying this data back to the base station based on the cost of communicating it (derived from the opportunity cost of using the battery power for relaying data). Finally, we empirically evaluate our protocol by examining the impact on efficiency of a static network topology, a dynamic network topology, the size of the network, the degree of dynamism of the environment, and the mobility of the nodes. In so doing, we demonstrate that the efficiency gains of our new protocol, over the currently implemented method over a 6 month period, are 78%, 133%, 100%, and 93%, respectively. Furthermore, we show that our system performs at 65%, 70%, 63%, and 70% of the theoretical optimal, respectively, despite being a distributed protocol that operates with incomplete knowledge of the environment

Synthesis and anti-microbial activity of some pyrimidine derivatives

910-9154-Aryl-5-carboethoxy-6-methyl-1 ,2,3,4-tetrahydropyrimidin-2-ones have been synthesized from easily available starting materials. The carboethoxy group at the C5-position of the pyrimidine ring is converted to corresponding hydrazide which in turn is condensed with cycli sing agents such as aromatic aldehydes, CS2 etc. to give fused heterocycles. The fused heterocycles are then subjected to phenacylation to give N3-phenacylpyrimido-heterocycles in excellent yield. In a slightly modified way, uracil derivatives are condensed with ethyl bromoacetate to give N3-β-ethoxycarbonyl derivatives. The hydrazide derivatives of these N3-β-ethoxycarbonyl derivatives subsequently react with 1,2-diketones to give corresponding pyrimido pyridazine derivatives

Synthesis and Antimicrobial Activity of Some Pyrimidine Derivatives.

910-9154-Aryl-5-carboethoxy-6-methyl-1 ,2,3,4-tetrahydropyrimidin-2-ones have been synthesized from easily available starting materials. The carboethoxy group at the C5-position of the pyrimidine ring is converted to corresponding hydrazide which in turn is condensed with cycli sing agents such as aromatic aldehydes, CS2 etc. to give fused heterocycles. The fused heterocycles are then subjected to phenacylation to give N3-phenacylpyrimido-heterocycles in excellent yield. In a slightly modified way, uracil derivatives are condensed with ethyl bromoacetate to give N3-β-ethoxycarbonyl derivatives. The hydrazide derivatives of these N3-β-ethoxycarbonyl derivatives subsequently react with 1,2-diketones to give corresponding pyrimido pyridazine derivatives