Design and analysis of an antenna for wireless energy harvesting in head-mountable DBS device

This paper presents design and simulation of a circular meander dipole antenna at the industrial, scientific, and medical band of 915 MHz for energy scavenging in a passive head-mountable deep brain stimulation device. The interaction of the proposed antenna with a rat body is modeled and discussed. In the antenna, the radiating layer is meandered, and a FR-4 substrate is used to limit the radius and height of the antenna to 14 mm and 1.60 mm, respectively. The resonance frequency of the designed antenna is 915 MHz and the bandwidth of 15 MHz at a return loss of -10 dB in free space. To model the interaction of the antenna with a rat body, two aspects including functional and biological are considered. The functional aspect includes input impedance, resonance frequency, gain pattern, radiation efficiency of the antenna, and the biological aspect involves electric field distribution, and SAR value. A complete rat model is used in the finite difference time domain based EM simulation software XFdtd. The simulated results demonstrate that the specific absorption rate distributions occur within the skull in the rat model, and their values are higher than the standard regulated values for the antenna receiving power of 1W.

Sustainability analysis and resource management for wireless mesh networks with renewable energy supplies

 There is a growing interest in the use of renewable energy sources to power wireless networks in order to mitigate the detrimental effects of conventional energy production or to enable deployment in off-grid locations. However, renewable energy sources, such as solar and wind, are by nature unstable in their availability and capacity. The dynamics of energy supply hence impose new challenges for network planning and resource management. In this paper, the sustainable performance of a wireless mesh network powered by renewable energy sources is studied. To address the intermittently available capacity of the energy supply, adaptive resource management and admission control schemes are proposed. Specifically, the goal is to maximize the energy sustainability of the network, or equivalently, to minimize the failure probability that the mesh access points (APs) deplete their energy and go out of service due to the unreliable energy supply. To this end, the energy buffer of a mesh AP is modeled as a G/G/1(/N) queue with arbitrary patterns of energy charging and discharging. Diffusion approximation is applied to analyze the transient evolution of the queue length and the energy depletion duration. Based on the analysis, an adaptive resource management scheme is proposed to balance traffic loads across the mesh network according to the energy adequacy at different mesh APs. A distributed admission control strategy to guarantee high resource utilization and to improve energy sustainability is presented. By considering the first and second order statistics of the energy charging and discharging processes at each mesh AP, it is demonstrated that the proposed schemes outperform some existing state-of-the-art solutions.

Analysis of lightning current characteristics to investigate lightning strike damages to energy pipeline

Australia is one of the most lightning prone area on earth. Lightning strikes have been identified as one of the most common cause of energy pipeline damage in Australia. Therefore, a suitable protection schemes and mitigation strategies against lighting strike damage is very important for Australian pipeline industry. There are a number of research on lighting protection of establishment such as, power systems, buildings, and telecommunications systems, however, very few publications could be found which discuss about protection of pipeline from lightning strike. Assessment of effects in buried pipeline, due to lighting strikes is important. Existing models do not account adequately the effect of the characteristics of soil breakdown channels intercepted by the buried object. This paper aims to investigate the characteristics of lightning current on metal object under the soil of strike point so that lighting attachment to energy pipeline could be understand and a protection technique could be developed. Along with lightning current characteristics, lightning attachment process, distribution method, soil resistivity, propagation of lightning current in soil with a buried pipeline, pipeline electrical properties and other related areas and technologies is explored. The study shows that though there are some research on characteristics of induced on simple buried structures like narrow telephone cable or residential gas pipe, but no substantial research have been done on large comparatively complex structures like buried energy pipelines. Also dynamic behavior of soil and the object to be protected not been considered in protections schemes and experiments.

Different thermal analysis technique application in determination of fold surface-free energy

In this work, the crystallization rates and spherulitic growth rate of miscible blends of poly(vinylidene fluoride) (PVDF) and acrylic rubber (ACM) were determined using differential scanning calorimetry (DSC), real-time FTIR, and optical microscopy. FTIR results suggest that blending does not induce the creation of polymorphic crystalline forms of PVDF. SAXS data demonstrate the formation of interlamellar structure after blending. The fold surface-free energy (σ e) was analyzed and compared using different thermal analysis techniques. The isothermal crystallization curves obtained using real-time FTIR and DSC explored in two different methods: t 1/2 or Avrami equation. While the Avrami equation is more widespread and precise, both analytical methods gave similar free energy of folding values. However, it was found that the direct optical method of measuring spherulitic growth rate yields σ e values 30-50 % lower than those obtained from the overall crystallization rate data. Conversely, the σ e values were found to increase with increasing amorphous ACM phase content regardless of the analytical methods.

Energy consumption and income in six Asian developing countries: a multivariate cointegration analysis

 This article examines the short- and long-run causal relationship between energy consumption and GDP of six emerging economies of Asia. Based on cointegration and vector error correction modeling the empirical results show that there exists unidirectional short- and long-run causality running from energy consumption to GDP for China, uni-directional short-run causality from output to energy consumption for India, whilst bi-directional short-run causality for Thailand. Neutrality between energy consumption and income is found for Indonesia, Malaysia and Philippines. Both the generalized variance decompositions and impulse response functions confirm the direction of causality. These findings have important policy implications for the countries concerned. The results suggest that while India may directly initiate energy conservation measures, China and Thailand may opt for a balanced combination of alternative polices.

Automated analysis of performance and energy consumption for cloud applications

In cloud environments, IT solutions are delivered to users via shared infrastructure. One consequence of this model is that large cloud data centres consume large amounts of energy and produce significant carbon footprints. A key objective of cloud providers is thus to develop resource provisioning and management solutions at minimum energy consumption while still guaranteeing Service Level Agreements (SLAs). However, a thorough understanding of both system performance and energy consumption patterns in complex cloud systems is imperative to achieve a balance of energy efficiency and acceptable performance. In this paper, we present StressCloud, a performance and energy consumption analysis tool for cloud systems. StressCloud can automatically generate load tests and profile system performance and energy consumption data. Using StressCloud, we have conducted extensive experiments to profile and analyse system performance and energy consumption with different types and mixes of runtime tasks. We collected finegrained energy consumption and performance data with different resource allocation strategies, system configurations and workloads. The experimental results show the correlation coefficients of energy consumption, system resource allocation strategies and workload, as well as the performance of the cloud applications. Our results can be used to guide the design and deployment of cloud applications to balance energy and performance requirements.

Associations between FTO genotype and total energy and macronutrient intake in adults: a systematic review and meta-analysis

Risk variants of fat mass and obesity-associated (FTO) gene have been associated with increased obesity. However, the evidence for associations between FTO genotype and macronutrient intake has not been reviewed systematically. Our aim was to evaluate the potential associations between FTO genotype and intakes of total energy, fat, carbohydrate and protein. We undertook a systematic literature search in OVID MEDLINE, Scopus, EMBASE and Cochrane of associations between macronutrient intake and FTO genotype in adults. Beta coefficients and confidence intervals (CIs) were used for per allele comparisons. Random-effect models assessed the pooled effect sizes. We identified 56 eligible studies reporting on 213,173 adults. For each copy of the FTO risk allele, individuals reported 6.46 kcal day(-1) (95% CI: 10.76, 2.16) lower total energy intake (P = 0.003). Total fat (P = 0.028) and protein (P = 0.006), but not carbohydrate intakes, were higher in those carrying the FTO risk allele. After adjustment for body weight, total energy intakes remained significantly lower in individuals with the FTO risk genotype (P = 0.028). The FTO risk allele is associated with a lower reported total energy intake and with altered patterns of macronutrient intake. Although significant, these differences are small and further research is needed to determine whether the associations are independent of dietary misreporting.

Energy-efficiency analysis of cluster-based routing protocols in wireless sensor network

This paper extends the conditions of the cluster-based routing protocols in terms of general algorithm complexity of data fusion, general compressing ratio of data fusion, and network area with long distance. Corresponding three general evaluation methods to evaluate the energy efficiency of the cluster-based routing protocols such as LEACH, PEGASIS, and BCDCP are provided. Moreover, three facts are found in them: (1) High-level software energy macro model is used to compute the energy dissipation of general data fusion software and make the constant value of energy dissipation of 1-bit data fusion an especial instance. (2) Multi-hop energy efficiency is related to the radio hardware parameters and the dynamic topology of network and the above protocols do not exploit the best use of the energy efficiency of multi-hop scheme. (3) High-energy dissipation non-cluster-head nodes, whose number changes with the density of the sensor nodes in clusters, worsen the death of nodes. The numerical results of experiments reprove these discoveries. Furthermore, they provide helpful guide for improving the above routing protocols to extent their application ranges.

Analysis of different scenarios for residential energy management under existing retail market structure

This paper presents an analysis of a residential energy management scheme under existing retail market structure with the integration of solar photovoltaic (PV) and battery energy storage systems. In this paper, different scenarios are analyzed with an aim of achieving the most cost-effective solutions for the integration of solar PV and battery energy storage systems. The main idea behind these analyses is to obtain a grid independent residential energy management system through the reduction of purchasing energy from the existing power grid. The results from the analysis of different scenarios for a typical Australian house demonstrate that the shortage of energy during the high loads and excess of energy during the higher output of solar PV system can be reduced with the design of a proper energy management scheme employing a transactive energy management framework.

Automating performance and energy consumption analysis for cloud applications

In cloud environments, IT solutions are delivered to users via shared infrastructure, enabling cloud service providers to deploy applications as services according to user QoS (Quality of Service) requirements. One consequence of this cloud model is the huge amount of energy consumption and significant carbon footprints caused by large cloud infrastructures. A key and common objective of cloud service providers is thus to develop cloud application deployment and management solutions with minimum energy consumption while guaranteeing performance and other QoS specified in Service Level Agreements (SLAs). However, finding the best deployment configuration that maximises energy efficiency while guaranteeing system performance is an extremely challenging task, which requires the evaluation of system performance and energy consumption under various workloads and deployment configurations. In order to simplify this process we have developed Stress Cloud, an automatic performance and energy consumption analysis tool for cloud applications in real-world cloud environments. Stress Cloud supports the modelling of realistic cloud application workloads, the automatic generation of load tests, and the profiling of system performance and energy consumption. We demonstrate the utility of Stress Cloud by analysing the performance and energy consumption of a cloud application under a broad range of different deployment configurations.