Predicting stock market returns and volatility with investor sentiment : evidence from eight developed countries

We test the predictive ability of investor sentiment on the return and volatility at the aggregate market level in the U.S., four largest European countries and three Asia-Pacific countries. We find that in the U.S., France and Italy periods of high consumer confidence levels are followed by low market returns. In Japan both the level and the change in consumer confidence boost the market return in the next month. Further, shifts in sentiment significantly move conditional volatility in most of the countries, and in Italy such impacts lead to an increase in returns by 4.7% in the next month.

Diffusivity of adatoms on plasma-exposed surfaces determined from the ionization energy approximation and ionic polarizability

Microscopic surface diffusivity theory based on atomic ionization energy concept is developed to explain the variations of the atomic and displacement polarizations with respect to the surface diffusion activation energy of adatoms in the process of self-assembly of quantum dots on plasma-exposed surfaces. These polarizations are derived classically, while the atomic polarization is quantized to obtain the microscopic atomic polarizability. The surface diffusivity equation is derived as a function of the ionization energy. The results of this work can be used to fine-tune the delivery rates of different adatoms onto nanostructure growth surfaces and optimize the low-temperature plasma based nanoscale synthesis processes.

Electron/ion energy loss to discharge walls revised : a case study in low-temperature, thermally nonequilibrium plasmas

Reliable calculations of the electron/ion energy losses in low-pressure thermally nonequilibrium low-temperature plasmas are indispensable for predictive modeling related to numerous applications of such discharges. The commonly used simplified approaches to calculation of electron/ion energy losses to the chamber walls use a number of simplifying assumptions that often do not account for the details of the prevailing electron energy distribution function (EEDF) and overestimate the contributions of the electron losses to the walls. By direct measurements of the EEDF and careful calculation of contributions of the plasma electrons in low-pressure inductively coupled plasmas, it is shown that the actual losses of kinetic energy of the electrons and ions strongly depend on the EEDF. It is revealed that the overestimates of the total electron/ion energy losses to the walls caused by improper assumptions about the prevailing EEDF and about the ability of the electrons to pass through the repulsive potential of the wall may lead to significant overestimates that are typically in the range between 9 and 32%. These results are particularly important for the development of power-saving strategies for operation of low-temperature, low-pressure gas discharges in diverse applications that require reasonably low power densities. © 2008 American Institute of Physics.

Spatially averaged model of complex-plasma discharge with self-consistent electron energy distribution

A global, or averaged, model for complex low-pressure argon discharge plasmas containing dust grains is presented. The model consists of particle and power balance equations taking into account power loss on the dust grains and the discharge wall. The electron energy distribution is determined by a Boltzmann equation. The effects of the dust and the external conditions, such as the input power and neutral gas pressure, on the electron energy distribution, the electron temperature, the electron and ion number densities, and the dust charge are investigated. It is found that the dust subsystem can strongly affect the stationary state of the discharge by dynamically modifying the electron energy distribution, the electron temperature, the creation and loss of the plasma particles, as well as the power deposition. In particular, the power loss to the dust grains can take up a significant portion of the input power, often even exceeding the loss to the wall.

Electron energy distribution function in low-pressure complex plasmas

The effect of density and size of dust grains on the electron energy distribution function (EEDF) in low-temperature complex plasmas is studied. It is found that the EEDF depends strongly on the dust density and size. The behavior of the electron temperature can differ significantly from that of a pristine plasma. For low-pressure argon glow discharge, the Druyvesteyn-like EEDF often found in pristine plasmas can become nearly Maxwellian if the dust density and/or sizes are large. One can thus control the plasma parameters by the dust grains.

Determination of battery storage capacity in energy buffer for wind farm

Design of a battery energy storage system (BESS) in a buffer scheme is examined for the purpose of attenuating the effects of unsteady input power from wind farms. The design problem is formulated as maximization of an objective function that measures the economic benefit obtainable from the dispatched power from the wind farm against the cost of the BESS. Solution to the problem results in the determination of the capacity of the BESS to ensure constant dispatched power to the connected grid, while the voltage level across the dc-link of the buffer is kept within preset limits. A computational procedure to determine the BESS capacity and the evaluation of the dc voltage is shown. Illustrative examples using the proposed design method are included.

Buffer scheme with battery energy storage capability for enhancement of network transient stability and load ride-through

This paper examines a buffer scheme to mitigate the negative impacts of power-conditioned loads on network voltage and transient stabilities. The scheme is based on the use of battery energy-storage systems in the buffers. The storage systems ensure that protected loads downstream of the buffers can ride through upstream voltage sags and swells. Also, by controlling the buffers to operate in either constant impedance or constant power modes, power is absorbed or injected by the storage systems. The scheme thereby regulates the rotor-angle deviations of generators and enhances network transient stability. A computational method is described in which the capacity of the storage systems is determined to achieve simultaneously the above dual objectives of load ride-through and stability enhancement. The efficacy of the resulting scheme is demonstrated through numerical examples.

Lower partial moment and information entropy-based dynamic electricity purchasing strategy

In the electricity market environment, load-serving entities (LSEs) will inevitably face risks in purchasing electricity because there are a plethora of uncertainties involved. To maximize profits and minimize risks, LSEs need to develop an optimal strategy to reasonably allocate the purchased electricity amount in different electricity markets such as the spot market, bilateral contract market, and options market. Because risks originate from uncertainties, an approach is presented to address the risk evaluation problem by the combined use of the lower partial moment and information entropy (LPME). The lower partial moment is used to measure the amount and probability of the loss, whereas the information entropy is used to represent the uncertainty of the loss. Electricity purchasing is a repeated procedure; therefore, the model presented represents a dynamic strategy. Under the chance-constrained programming framework, the developed optimization model minimizes the risk of the electricity purchasing portfolio in different markets because the actual profit of the LSE concerned is not less than the specified target under a required confidence level. Then, the particle swarm optimization (PSO) algorithm is employed to solve the optimization model. Finally, a sample example is used to illustrate the basic features of the developed model and method.

Strategic entry deterrence : does it constitute a misuse of market power?

A challenge for regulators and the courts has been establishing the boundary between behaviour is exclusionary and should be condemned under s 46 of the then Trade Practices Act 1974 (Cth) (TPA), now s 46 of the Competition and Consumer Act 2010 (Cth) (CCA), and behaviour that is not exclusionary and might even be pro-competitive. This boundary can be especially difficult to draw in the case of entry deterring strategies. Section 46(1) prohibits corporations with a substantial degree of market power from taking advantage of that market power for one of the statutorily proscribed purposes which include preventing the entry of a person into that or any other market. Section 45(2) separately prohibits corporations from making and giving effect to contracts arrangements and understandings that have the purpose, effect or likely effect of substantially lessening competition in a market. The latest case in which the ACCC has failed to satisfy the s 46 criteria is the decision of Greenwood J in ACCC v Cement Australia Pty Ltd [2013] FCA 909 (Cement Australia case). Final orders were published in a separate judgment, in ACCC v Cement Australia Pty Ltd [2014] FCA 148 (28 February 2014). The case concerned an entry deterring strategy, namely the pre-emptive buying of input factors in an upstream market to protect an incumbent with substantial market power in a downstream market and to prevent new entry in the downstream market. Greenwood J found that while Cement Australia Pty Ltd, formerly known as Queensland Cement Ltd (QCL), had substantial market power, its conduct in entering into the pre-emptive contracts was not a contravention of s 46, because Cement Australia had not “taken advantage” of its market power. However, since Cement Australia’s purpose in entering into the pre-emptive contracts was anti-competitive, they were held to contravene s 45(2) of the TPA. The purpose of this Note is to consider only the reasons for judgment in the Cement Australia case in relation to the “taking advantage” element. The judgment was handed down on 10 September 2013. The final hearing date was 15 July 2011, so it was long-awaited. At 714 pages, it is carefully drafted.

Long-term exploration and tours for energy constrained robots with online proprioceptive traversability estimation

This paper is concerned with how a localised and energy-constrained robot can maximise its time in the field by taking paths and tours that minimise its energy expenditure. A significant component of a robot's energy is expended on mobility and is a function of terrain traversability. We estimate traversability online from data sensed by the robot as it moves, and use this to generate maps, explore and ultimately converge on minimum energy tours of the environment. We provide results of detailed simulations and parameter studies that show the efficacy of this approach for a robot moving over terrain with unknown traversability as well as a number of a priori unknown hard obstacles.

Systems modelling of mine water and energy tradeoffs

In the coming decades, the mining industry faces the dual challenge of lowering both its water and energy use. This presents a difficulty since technological advances that decrease the use of one can increase the use of the other. Historically, energy and water use have been modelled independently, making it difficult to evaluate the true costs and benefits from water and energy improvements. This paper presents a hierarchical systems model that is able to represent interconnected water and energy use at a whole of site scale. In order to explore the links between water and energy four technologies advancements have been modelled: use of dust suppression additives, the adoption of thickened tailings, the transition to dry processing and the incorporation of a treatment plant. The results show a synergy between decreased water and energy use for dust suppression additives, but a trade-off for the others.

Development of gas sensing technology for ground and airborne applications powered by solar energy : methodology and experimental results

Monitoring gases for environmental, industrial and agricultural fields is a demanding task that requires long periods of observation, large quantity of sensors, data management, high temporal and spatial resolution, long term stability, recalibration procedures, computational resources, and energy availability. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) are currently representing the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialised gas sensing systems, and offer the possibility of geo-located and time stamp samples. However, these technologies are not fully functional for scientific and commercial applications as their development and availability is limited by a number of factors: the cost of sensors required to cover large areas, their stability over long periods, their power consumption, and the weight of the system to be used on small UAVs. Energy availability is a serious challenge when WSN are deployed in remote areas with difficult access to the grid, while small UAVs are limited by the energy in their reservoir tank or batteries. Another important challenge is the management of data produced by the sensor nodes, requiring large amount of resources to be stored, analysed and displayed after long periods of operation. In response to these challenges, this research proposes the following solutions aiming to improve the availability and development of these technologies for gas sensing monitoring: first, the integration of WSNs and UAVs for environmental gas sensing in order to monitor large volumes at ground and aerial levels with a minimum of sensor nodes for an effective 3D monitoring; second, the use of solar energy as a main power source to allow continuous monitoring; and lastly, the creation of a data management platform to store, analyse and share the information with operators and external users. The principal outcomes of this research are the creation of a gas sensing system suitable for monitoring any kind of gas, which has been installed and tested on CH4 and CO2 in a sensor network (WSN) and on a UAV. The use of the same gas sensing system in a WSN and a UAV reduces significantly the complexity and cost of the application as it allows: a) the standardisation of the signal acquisition and data processing, thereby reducing the required computational resources; b) the standardisation of calibration and operational procedures, reducing systematic errors and complexity; c) the reduction of the weight and energy consumption, leading to an improved power management and weight balance in the case of UAVs; d) the simplification of the sensor node architecture, which is easily replicated in all the nodes. I evaluated two different sensor modules by laboratory, bench, and field tests: a non-dispersive infrared module (NDIR) and a metal-oxide resistive nano-sensor module (MOX nano-sensor). The tests revealed advantages and disadvantages of the two modules when used for static nodes at the ground level and mobile nodes on-board a UAV. Commercial NDIR modules for CO2 have been successfully tested and evaluated in the WSN and on board of the UAV. Their advantage is the precision and stability, but their application is limited to a few gases. The advantages of the MOX nano-sensors are the small size, low weight, low power consumption and their sensitivity to a broad range of gases. However, selectivity is still a concern that needs to be addressed with further studies. An electronic board to interface sensors in a large range of resistivity was successfully designed, created and adapted to operate on ground nodes and on-board UAV. The WSN and UAV created were powered with solar energy in order to facilitate outdoor deployment, data collection and continuous monitoring over large and remote volumes. The gas sensing, solar power, transmission and data management systems of the WSN and UAV were fully evaluated by laboratory, bench and field testing. The methodology created to design, developed, integrate and test these systems was extensively described and experimentally validated. The sampling and transmission capabilities of the WSN and UAV were successfully tested in an emulated mission involving the detection and measurement of CO2 concentrations in a field coming from a contaminant source; the data collected during the mission was transmitted in real time to a central node for data analysis and 3D mapping of the target gas. The major outcome of this research is the accomplishment of the first flight mission, never reported before in the literature, of a solar powered UAV equipped with a CO2 sensing system in conjunction with a network of ground sensor nodes for an effective 3D monitoring of the target gas. A data management platform was created using an external internet server, which manages, stores, and shares the data collected in two web pages, showing statistics and static graph images for internal and external users as requested. The system was bench tested with real data produced by the sensor nodes and the architecture of the platform was widely described and illustrated in order to provide guidance and support on how to replicate the system. In conclusion, the overall results of the project provide guidance on how to create a gas sensing system integrating WSNs and UAVs, how to power the system with solar energy and manage the data produced by the sensor nodes. This system can be used in a wide range of outdoor applications, especially in agriculture, bushfires, mining studies, zoology, and botanical studies opening the way to an ubiquitous low cost environmental monitoring, which may help to decrease our carbon footprint and to improve the health of the planet.

Defect healing and enhanced nucleation of carbon nanotubes by low-energy ion bombardment

Structural defects inevitably appear during the nucleation event that determines the structure and properties of single-walled carbon nanotubes. By combining ion bombardment experiments with atomistic simulations we reveal that ion bombardment in a suitable energy range allows these defects to be healed resulting in an enhanced nucleation of the carbon nanotube cap. The enhanced growth of the nanotube cap is explained by a nonthermal ion-induced graphene network restructuring mechanism.

Electric breakdown in liquids : faster ignition using less energy

The formation of vapor layers around an electrode immersed in a conducting liquid prior to generation of a plasma discharge is studied using numerical simulations. This study quantifies and explains the effects of the electrode geometry and applied voltage pulses, as well as the electrical and thermal properties of the liquids on the temporal dynamics of the pre-breakdown conditions in the vapor layer. This model agrees well with experimental data, in particular, the time needed to reach the electrical breakdown threshold. Because the time needed for discharge ignition can be accurately predicted from the model, the parameters such as the pulse shape, voltage, and electrode configuration can be optimized under different liquid conditions, which facilitates a faster and more energy-efficient plasma generation.

Controlling electronic and adiabatic isolation of quantum dots from the substrate : an ionization-energy theoretic study

Recent controversy on the quantum dots dephasing mechanisms (between pure and inelastic) is re-examined by isolating the quantum dots from their substrate by using the appropriate limits of the ionization energy theory and the quantum adiabatic theorem. When the phonons in the quantum dots are isolated adiabatically from the phonons in the substrate, the elastic or pure dephasing becomes the dominant mechanism. On the other hand, for the case where the phonons from the substrate are non-adiabatically coupled to the quantum dots, the inelastic dephasing process takes over. This switch-over is due to different elemental composition in quantum dots as compared to its substrate. We also provide unambiguous analysis as to understand why GaAs/AlGaAs quantum dots may only have pure dephasing while InAs/GaAs quantum dots give rise to the inelastic dephasing as the dominant mechanism. It is shown that the elemental composition plays an important role (of both quantum dots and substrate) in evaluating the dephasing mechanisms of quantum dots.