Optimal energy management policies for energy harvesting sensor nodes

We study a sensor node with an energy harvesting source. The generated energy can be stored in a buffer. The sensor node periodically senses a random field and generates a packet. These packets are stored in a queue and transmitted using the energy available at that time. We obtain energy management policies that are throughput optimal, i.e., the data queue stays stable for the largest possible data rate. Next we obtain energy management policies which minimize the mean delay in the queue. We also compare performance of several easily implementable sub-optimal energy management policies. A greedy policy is identified which, in low SNR regime, is throughput optimal and also minimizes mean delay.

Real-time monitoring of critical nodes with minimal number of Phasor Measurement Units

This paper presents a method for placement of Phasor Measurement Units, ensuring the monitoring of vulnerable buses which are obtained based on transient stability analysis of the overall system. Real-time monitoring of phase angles across different nodes, which indicates the proximity to instability, the very purpose will be well defined if the PMUs are placed at buses which are more vulnerable. The issue is to identify the key buses where the PMUs should be placed when the transient stability prediction is taken into account considering various disturbances. Integer Linear Programming technique with equality and inequality constraints is used to find out the optimal placement set with key buses identified from transient stability analysis. Results on IEEE-14 bus system are presented to illustrate the proposed approach.

State Dependent Attempt Rate modeling of single cell IEEE 802.11 WLANs with homogeneous nodes and Poisson packet arrivals

We study a State Dependent Attempt Rate (SDAR) approximation to model M queues (one queue per node) served by the Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) protocol as standardized in the IEEE 802.11 Distributed Coordination Function (DCF). The approximation is that, when n of the M queues are non-empty, the (transmission) attempt probability of each of the n non-empty nodes is given by the long-term (transmission) attempt probability of n saturated nodes. With the arrival of packets into the M queues according to independent Poisson processes, the SDAR approximation reduces a single cell with non-saturated nodes to a Markovian coupled queueing system. We provide a sufficient condition under which the joint queue length Markov chain is positive recurrent. For the symmetric case of equal arrival rates and finite and equal buffers, we develop an iterative method which leads to accurate predictions for important performance measures such as collision probability, throughput and mean packet delay. We replace the MAC layer with the SDAR model of contention by modifying the NS-2 source code pertaining to the MAC layer, keeping all other layers unchanged. By this model-based simulation technique at the MAC layer, we achieve speed-ups (w.r.t. MAC layer operations) up to 5.4. Through extensive model-based simulations and numerical results, we show that the SDAR model is an accurate model for the DCF MAC protocol in single cells. (C) 2012 Elsevier B.V. All rights reserved.

Queuing theoretic and information theoretic capacity of energy harvesting sensor nodes

Energy harvesting sensor networks provide near perpetual operation and reduce carbon emissions thereby supporting `green communication'. We study such a sensor node powered with an energy harvesting source. We obtain energy management policies that are throughput optimal. We also obtain delay-optimal policies. Next we obtain the Shannon capacity of such a system. Further we combine the information theoretic and queuing theoretic approaches to obtain the Shannon capacity of an energy harvesting sensor node with a data queue. Then we generalize these results to models with fading and energy consumption in activities other than transmission.

Information capacity of energy harvesting sensor nodes

Sensor nodes with energy harvesting sources are gaining popularity due to their ability to improve the network life time and are becoming a preferred choice supporting `green communication'. We study such a sensor node with an energy harvesting source and compare various architectures by which the harvested energy is used. We find its Shannon capacity when it is transmitting its observations over an AWGN channel and show that the capacity achieving energy management policies are related to the throughput optimal policies. We also obtain the capacity when energy conserving sleep-wake modes are supported and an achievable rate for the system with inefficiencies in energy storage.

Optimal design of timer-based, distributed selection with unknown number of nodes

The timer-based selection scheme is a popular, simple, and distributed scheme that is used to select the best node from a set of available nodes. In it, each node sets a timer as a function of a local preference number called a metric, and transmits a packet when its timer expires. The scheme ensures that the timer of the best node, which has the highest metric, expires first. However, it fails to select the best node if another node transmits a packet within Delta s of the transmission by the best node. We derive the optimal timer mapping that maximizes the average success probability for the practical scenario in which the number of nodes in the system is unknown but only its probability distribution is known. We show that it has a special discrete structure, and present a recursive characterization to determine it. We benchmark its performance with ad hoc approaches proposed in the literature, and show that it delivers significant gains. New insights about the optimality of some ad hoc approaches are also developed.

Regulation of protumorigenic pathways by Insulin like growth factor binding protein2 and its association along with beta-catenin in breast cancer lymph node metastasis

Background: Insulin like growth factor binding proteins modulate the mitogenic and pro survival effects of IGF. Elevated expression of IGFBP2 is associated with progression of tumors that include prostate, ovarian, glioma among others. Though implicated in the progression of breast cancer, the molecular mechanisms involved in IGFBP2 actions are not well defined. This study investigates the molecular targets and biological pathways targeted by IGFBP2 in breast cancer. Methods: Transcriptome analysis of breast tumor cells (BT474) with stable knockdown of IGFBP2 and breast tumors having differential expression of IGFBP2 by immunohistochemistry was performed using microarray. Differential gene expression was established using R-Bioconductor package. For validation, gene expression was determined by qPCR. Inhibitors of IGF1R and integrin pathway were utilized to study the mechanism of regulation of beta-catenin. Immunohistochemical and immunocytochemical staining was performed on breast tumors and experimental cells, respectively for beta-catenin and IGFBP2 expression. Results: Knockdown of IGFBP2 resulted in differential expression of 2067 up regulated and 2002 down regulated genes in breast cancer cells. Down regulated genes principally belong to cell cycle, DNA replication, repair, p53 signaling, oxidative phosphorylation, Wnt signaling. Whole genome expression analysis of breast tumors with or without IGFBP2 expression indicated changes in genes belonging to Focal adhesion, Map kinase and Wnt signaling pathways. Interestingly, IGFBP2 knockdown clones showed reduced expression of beta-catenin compared to control cells which was restored upon IGFBP2 re-expression. The regulation of beta-catenin by IGFBP2 was found to be IGF1R and integrin pathway dependent. Furthermore, IGFBP2 and beta-catenin are co-ordinately overexpressed in breast tumors and correlate with lymph node metastasis. Conclusion: This study highlights regulation of beta-catenin by IGFBP2 in breast cancer cells and most importantly, combined expression of IGFBP2 and beta-catenin is associated with lymph node metastasis of breast tumors.

Solvent-templated supramolecular isomerism in 2D coordination polymer constructed by (Ni2CoII)-Co-II nodes and dicyanamido spacers: drastic change in magnetic behaviours

Two heterometallic coordination polymers (CPs) have been prepared using (NiL)-L-II](2)Co-II (where H2L = N,N'-bis(salicylidene)-1,3-propanediamine) as nodes and dicyanamido spacers by varying the solvent for synthesis. Structural characterizations revealed that methanol assisted the formation of a two-dimensional (4,4) connected rhombic grid network of (NiL)(2)Co(NCNCN)2](infinity) (1a) whereas relatively less polar acetonitrile afforded a different superstructure {(NiL)(2)Co(NCNCN)(2)]center dot CH3CN}(infinity) (1b) with a two-dimensional (4,4) connected square grid network. The presence of acetonitrile molecules in the structure of 1b seems to change the spatial orientation of the terminal metalloligands NiL] from pseudo-eclipsed in 1a to staggered-like in 1b around the central Co(II). These structural changes in the nodes together with the conformationally flexible dicyanamido spacers, which are cis coordinated to the Co(II) in both trinuclear units, led to the differences in the final 2D network. Variable-temperature magnetic susceptibility measurements revealed that this supramolecular isomerism led to a drastic transition from spin-frustrated antiferromagnetism for 1a to a dominant ferromagnetic behaviour for 1b. The geometrical differences in Ni2Co coordination clusters (CCs) which are scalene triangular in 1a but nearly linear in 1b, are held responsible for the changes of the magnetic properties. The DFT calculations of exchange interactions between metal centres provide a clear evidence of the role played by the fundamental geometrical factors on the nature and magnitude of the magnetic coupling in these pseudo-polymorphic CPs.

Monte Carlo simulation of light transport in tissue for optimizing light delivery in photoacoustic imaging of the sentinel lymph node

Noninvasive or minimally invasive identification of sentinel lymph node (SLN) is essential to reduce the surgical effects of SLN biopsy. Photoacoustic (PA) imaging of SLN in animal models has shown its promise for clinical use in the future. Here, we present a Monte Carlo simulation for light transport in the SLN for various light delivery configurations with a clinical ultrasound probe. Our simulation assumes a realistic tissue layer model and also can handle the transmission/reflectance at SLN-tissue boundary due to the mismatch of refractive index. Various light incidence angles show that for deeply situated SLNs the maximum absorption of light in the SLN is for normal incidence. We also show that if a part of the diffused reflected photons is reflected back into the skin using a reflector, the absorption of light in the SLN can be increased significantly to enhance the PA signal. (C) 2013 Society of Photo-Optical Instrumentation Engineers (SPIE)

Network, nodes and nexus: systems approach to multitarget therapeutics

Systems biology is revealing multiple layers of regulatory networks that manifest spatiotemporal variations. Since genes and environment also influence the emergent property of a cell, the biological output requires dynamic understanding of various molecular circuitries. The metabolic networks continually adapt and evolve to cope with the changing milieu of the system, which could also include infection by another organism. Such perturbations of the functional networks can result in disease phenotypes, for instance tuberculosis and cancer. In order to develop effective therapeutics, it is important to determine the disease progression profiles of complex disorders that can reveal dynamic aspects and to develop mutitarget systemic therapies that can help overcome pathway adaptations and redundancy.

Capacity of a Gaussian MAC with energy harvesting transmit nodes

We consider a Gaussian multiple access channel (GMAC) where the users are sensor nodes powered by energy harvesters. The energy harvesters may have finite or infinite buffer to store the harvested energy. First, we find the capacity region of a GMAC powered by transmit nodes with an infinite energy buffer. Next, we consider a GMAC with the transmitting nodes equipped with a finite energy buffer. Initially we assume perfect knowledge of the buffer state information at both the encoders and the decoder. We provide an achievable region for this case. We also generalize the achievable region when only partial information about buffer state is available at both the encoders and the decoder.

Optimal Timer-Based Best Node Selection for Wireless Systems with Unknown Number of Nodes

The distributed, low-feedback, timer scheme is used in several wireless systems to select the best node from the available nodes. In it, each node sets a timer as a function of a local preference number called a metric, and transmits a packet when its timer expires. The scheme ensures that the timer of the best node, which has the highest metric, expires first. However, it fails to select the best node if another node transmits a packet within Delta s of the transmission by the best node. We derive the optimal metric-to-timer mappings for the practical scenario where the number of nodes is unknown. We consider two cases in which the probability distribution of the number of nodes is either known a priori or is unknown. In the first case, the optimal mapping maximizes the success probability averaged over the probability distribution. In the second case, a robust mapping maximizes the worst case average success probability over all possible probability distributions on the number of nodes. Results reveal that the proposed mappings deliver significant gains compared to the mappings considered in the literature.

Energy Sharing for Multiple Sensor Nodes With Finite Buffers

We consider the problem of finding optimal energy sharing policies that maximize the network performance of a system comprising of multiple sensor nodes and a single energy harvesting (EH) source. Sensor nodes periodically sense the random field and generate data, which is stored in the corresponding data queues. The EH source harnesses energy from ambient energy sources and the generated energy is stored in an energy buffer. Sensor nodes receive energy for data transmission from the EH source. The EH source has to efficiently share the stored energy among the nodes to minimize the long-run average delay in data transmission. We formulate the problem of energy sharing between the nodes in the framework of average cost infinite-horizon Markov decision processes (MDPs). We develop efficient energy sharing algorithms, namely Q-learning algorithm with exploration mechanisms based on the epsilon-greedy method as well as upper confidence bound (UCB). We extend these algorithms by incorporating state and action space aggregation to tackle state-action space explosion in the MDP. We also develop a cross entropy based method that incorporates policy parameterization to find near optimal energy sharing policies. Through simulations, we show that our algorithms yield energy sharing policies that outperform the heuristic greedy method.

A novel index for identification of weak nodes for reactive compensation to improve voltage stability

In this study, a new reactive power loss index (RPLI) is proposed for identification of weak buses in the system. This index is further used for determining the optimal locations for placement of reactive compensation devices in the power system for additional voltage support. The new index is computed from the reactive power support and loss allocation algorithm using Y-bus method for the system under intact condition and as well as critical/severe network contingencies cases. Fuzzy logic approach is used to select the important and critical/severe line contingencies from the contingency list. The inherent characteristics of the reactive power in system operation is properly addressed while determining the reactive power loss allocation to load buses. The proposed index is tested on sample 10-bus equivalent system and 72-bus practical equivalent system of Indian southern region power grid. The validation of the weak buses identification from the proposed index with that from other existing methods in the literature is carried out to demonstrate the effectiveness of the proposed index. Simulation results show that the identification of weak buses in the system from the new RPLI is completely non-iterative, thus requires minimal computational efforts as compared with other existing methods in the literature.

Sobrevida e fatores prognósticos para o câncer de mama em Juiz de Fora, Minas Gerais, na coorte diagnosticada entre 1998 e 2000

Este estudo teve como objetivo analisar a sobrevida e fatores prognósticos para o câncer de mama feminino, com ênfase no papel de variáveis relacionadas aos serviços de saúde. Foram analisadas 782 mulheres com câncer invasivo da mama e submetidas à cirurgia curativa, que realizaram tratamento cirúrgico e/ou terapia complementar no município de Juiz de Fora, Minas Gerais, com diagnóstico da doença entre 1998 e 2000. O recrutamento dos casos foi efetuado a partir de busca ativa nos registros médicos de todos os serviços de saúde que prestam atendimento em oncologia na cidade. O seguimento foi realizado mediante retorno aos prontuários e complementado por busca no banco do Sistema de Informação sobre Mortalidade (SIM), contato telefônico e consulta de situação cadastral no Cadastro de Pessoas Físicas (CPF). As principais variáveis analisadas foram: cor da pele, idade ao diagnóstico, tamanho do tumor, comprometimento de linfonodos, estadiamento, cidade de residência e variáveis relativas aos serviços de saúde, entre outras. As funções de sobrevida foram calculadas por meio do método de Kaplan-Meier. Foi utilizado o modelo de riscos proporcionais de Cox para avaliação dos fatores prognósticos. No primeiro artigo, foi observada taxa de sobrevida específica em cinco anos de 80,9%, sendo identificados tamanho tumoral e comprometimento de linfonodos axilares como importantes fatores prognósticos associados de forma independente à sobrevida pela doença na população de estudo (HR=1,99, IC95%: 1,27-3,10 e HR=3,92, IC95%: 2,49-6,16, respectivamente). No segundo artigo, quando consideradas as variáveis relativas aos serviços de saúde, foi verificada pior sobrevida para as mulheres assistidas no serviço público, embora com significância limítrofe (p=0,05), e para aquelas que não tinham plano privado de saúde, apesar de não significativa (p=0,1). As funções de sobrevida não ajustadas e estratificadas por natureza do serviço de saúde exibiram sobrevida mais desfavorável para as mulheres não brancas e para os casos com nenhum ou menos de 10 linfonodos isolados somente no serviço público, embora com significâncias estatísticas apenas marginais (p=0,09 e p=0,07, respectivamente). Na análise multivariada, foi observado maior risco de óbito nas mulheres que não fizeram uso de hormonioterapia apenas para os casos assistidos no serviço público (HR=1,56; IC95%: 1,01-2,41), independentemente do tamanho tumoral e do status ganglionar axilar. Tais achados sugerem desigualdades sociais e disparidades na prevenção primária e secundária da doença na região estudada, com desvantagem para o serviço público de saúde, enfatizando a maior necessidade de esclarecimento sobre a doença, assim como de diagnóstico e tratamento dos casos em estádios mais precoces. Destacou-se, ainda, o valor de se trabalhar com informações produzidas pelos serviços de saúde responsáveis pela assistência oncológica no país, possibilitando a caracterização do perfil e da sobrevida das pacientes assistidas e fornecendo subsídios aos órgãos competentes do setor saúde local para nortear a adoção de estratégias de prevenção direcionadas ao controle da doença na população avaliada.