Open-air direct current plasma jet : scaling up, uniformity, and cellular control

Atmospheric-pressure plasma jets are commonly used in many fields from medicine to nanotechnology, yet the issue of scaling the discharges up to larger areas without compromising the plasma uniformity remains a major challenge. In this paper, we demonstrate a homogenous cold air plasmaglow with a large cross-section generated by a direct current power supply. There is no risk of glow-to-arc transitions, and the plasmaglow appears uniform regardless of the gap between the nozzle and the surface being processed. Detailed studies show that both the position of the quartz tube and the gas flow rate can be used to control the plasma properties. Further investigation indicates that the residual charges trapped on the inner surface of the quartz tube may be responsible for the generation of the air plasma plume with a large cross-section. The spatially resolved optical emission spectroscopy reveals that the air plasma plume is uniform as it propagates out of the nozzle. The remarkable improvement of the plasma uniformity is used to improve the bio-compatibility of a glass coverslip over a reasonably large area. This improvement is demonstrated by a much more uniform and effective attachment and proliferation of human embryonic kidney 293 (HEK 293) cells on the plasma-treated surface.

Furan substituted diketopyrrolopyrrole and thienylenevinylene based low band gap copolymer for high mobility organic thin film transistors

A novel solution processable donor-acceptor (D-A) based low band gap polymer semiconductor poly{3,6-difuran-2-yl-2,5-di(2-octyldodecyl)-pyrrolo[3,4- c]pyrrole-1,4-dione-alt-thienylenevinylene} (PDPPF-TVT), was designed and synthesized by a Pd-catalyzed Stille coupling route. An electron deficient furan based diketopyrrolopyrrole (DPP) block and electron rich thienylenevinylene (TVT) donor moiety were attached alternately in the polymer backbone. The polymer exhibited good solubility, film forming ability and thermal stability. The polymer exhibits wide absorption bands from 400 nm to 950 nm (UV-vis-NIR region) with absorption maximum centered at 782 nm in thin film. The optical band gap (Eoptg) calculated from the polymer film absorption onset is around 1.37 eV. The π-energy band level (ionization potential) calculated by photoelectron spectroscopy in air (PESA) for PDPPF-TVT is around 5.22 eV. AFM and TEM analyses of the polymer reveal nodular terrace morphology with optimized crystallinity after 200 °C thermal annealing. This polymer exhibits p-channel charge transport characteristics when used as the active semiconductor in organic thin-film transistor (OTFT) devices. The highest hole mobility of 0.13 cm 2 V -1 s -1 is achieved in bottom gate and top-contact OTFT devices with on/off ratios in the range of 10 6-10 7. This work reveals that the replacement of thiophene by furan in DPP copolymers exhibits such a high mobility, which makes DPP furan a promising block for making a wide range of promising polymer semiconductors for broad applications in organic electronics.

A national satellite-based land-use regression model for air pollution exposure assessment in Australia

Land-use regression (LUR) is a technique that can improve the accuracy of air pollution exposure assessment in epidemiological studies. Most LUR models are developed for single cities, which places limitations on their applicability to other locations. We sought to develop a model to predict nitrogen dioxide (NO2) concentrations with national coverage of Australia by using satellite observations of tropospheric NO2 columns combined with other predictor variables. We used a generalised estimating equation (GEE) model to predict annual and monthly average ambient NO2 concentrations measured by a national monitoring network from 2006 through 2011. The best annual model explained 81% of spatial variation in NO2 (absolute RMS error=1.4 ppb), while the best monthly model explained 76% (absolute RMS error=1.9 ppb). We applied our models to predict NO2 concentrations at the ~350,000 census mesh blocks across the country (a mesh block is the smallest spatial unit in the Australian census). National population-weighted average concentrations ranged from 7.3 ppb (2006) to 6.3 ppb (2011). We found that a simple approach using tropospheric NO2 column data yielded models with slightly better predictive ability than those produced using a more involved approach that required simulation of surface-to-column ratios. The models were capable of capturing within-urban variability in NO2, and offer the ability to estimate ambient NO2 concentrations at monthly and annual time scales across Australia from 2006–2011. We are making our model predictions freely available for research.

Estimating the burden of disease attributable to urban outdoor air pollution in South Africa in 2000

Objectives To quantify the mortality burden attributed to urban outdoor air pollution in South Africa in 2000. Design The study followed comparative risk assessment (CRA) methodology developed by the World Heath Organization (WHO). In most urban areas, annual mean concentrations of particulate matter (PM) with diameters less than 10 μum (PM10) from monitoring network data and PM with diameters less than 2.5 μm (PM2.5) derived using a ratio method were weighted according to population size. PM10 and PM2.5 data from air-quality assessment studies in areas not covered by the network were also included. Population-attributable fractions calculated using risk coefficients presented in the WHO study were weighted by the proportion of the total population (33%) in urban environments, and applied to revised estimates of deaths and years of life lost (YLLs) for South Africa in 2000. Setting South Africa. Subjects Children under 5 years and adults 30 years and older. Outcome measures Mortality and YLLs from lung cancer and cardiopulmonary disease in adults (30 years and older), and from acute respiratory infections (ARIs) in children aged 0 - 4 years. Results Outdoor air pollution in urban areas in South Africa was estimated to cause 3.7% of the national mortality from cardiopulmonary disease and 5.1% of mortality attributable to cancers of the trachea, bronchus and lung in adults aged 30 years and older, and 1.1% of mortality from ARIs in children under 5 years of age. This amounts to 4 637 or 0.9% (95% uncertainty interval 0.3 - 1.5%) of all deaths and about 42 000 YLLs, or 0.4% (95% uncertainty interval 0.1 - 0.7%) of all YLLs in persons in South Africa in 2000. Conclusion Urban air pollution has under-recognised public health impacts in South Africa. Fossil fuel combustion emissions and traffic-related air pollution remain key targets for public health in South Africa.

Development and integration of a solar powered unmanned aerial vehicle and a wireless sensor network to monitor greenhouse gases

Measuring gases for environmental monitoring is a demanding task that requires long periods of observation and large numbers of sensors. Wireless Sensor Networks (WSNs) and Unmanned Aerial Vehicles (UAVs) currently represent the best alternative to monitor large, remote, and difficult access areas, as these technologies have the possibility of carrying specialized gas sensing systems. This paper presents the development and integration of a WSN and an UAV powered by solar energy in order to enhance their functionality and broader their applications. A gas sensing system implementing nanostructured metal oxide (MOX) and non-dispersive infrared sensors was developed to measure concentrations of CH4 and CO2. Laboratory, bench and field testing results demonstrate the capability of UAV to capture, analyze and geo-locate a gas sample during flight operations. The field testing integrated ground sensor nodes and the UAV to measure CO2 concentration at ground and low aerial altitudes, simultaneously. Data collected during the mission was transmitted in real time to a central node for analysis and 3D mapping of the target gas. The results highlights the accomplishment of the first flight mission of a solar powered UAV equipped with a CO2 sensing system integrated with a WSN. The system provides an effective 3D monitoring and can be used in a wide range of environmental applications such as agriculture, bushfires, mining studies, zoology and botanical studies using a ubiquitous low cost technology.

Autonomous helicopter hover using an artificial neural network

Details the developments to date of an unmanned air vehicle (UAV) based on a standard size 60 model helicopter. The design goal is to have the helicopter achieve stable hover with the aid of an INS and stereo vision. The focus of the paper is on the development of an artificial neural network (ANN) that makes use of only the INS data to generate hover commands, which are used to directly manipulate the flight servos. Current results show that networks incorporating some form of recurrency (state history) offer little advantage over those without. At this stage, the ANN has partially maintained periods of hover even with misaligned sensors.

Remote Sensing and Data Collection from Solar Powered Wireless Sensor Network using an Unmanned Aerial Vehicle System

Sensor networks for environmental monitoring present enormous benefits to the community and society as a whole. Currently there is a need for low cost, compact, solar powered sensors suitable for deployment in rural areas. The purpose of this research is to develop both a ground based wireless sensor network and data collection using unmanned aerial vehicles. The ground based sensor system is capable of measuring environmental data such as temperature or air quality using cost effective low power sensors. The sensor will be configured such that its data is stored on an ATMega16 microcontroller which will have the capability of communicating with a UAV flying overhead using UAV communication protocols. The data is then either sent to the ground in real time or stored on the UAV using a microcontroller until it lands or is close enough to enable the transmission of data to the ground station.

LiDAR Augmented Optimal Path Planning for Unmanned Aerial Vehicle during Remote Sensing at Low Altitude and Network Sensor Data Acquisition

This technical report describes a Light Detection and Ranging (LiDAR) augmented optimal path planning at low level flight methodology for remote sensing and sampling Unmanned Aerial Vehicles (UAV). The UAV is used to perform remote air sampling and data acquisition from a network of sensors on the ground. The data that contains information on the terrain is in the form of a 3D point clouds maps is processed by the algorithms to find an optimal path. The results show that the method and algorithm are able to use the LiDAR data to avoid obstacles when planning a path from a start to a target point. The report compares the performance of the method as the resolution of the LIDAR map is increased and when a Digital Elevation Model (DEM) is included. From a practical point of view, the optimal path plan is loaded and works seemingly with the UAV ground station and also shows the UAV ground station software augmented with more accurate LIDAR data.

Formative time lags in nitrogen, oxygen and dry air In crossed electric and magnetic fields

Formative time lags in nitrogen, oxygen, and dry air are measured with and without a magnetic field over a range of gas pressures (0.05 ' p ' 20.2 torr 5 kPa to 2 MPa, electric field strengths (1.8xO14 EEs 60xlO V m l) and magnetic field strengths (85xl0-4 < B ' 16x10-2 Tesla). For experiments below the Paschen minimum, the electrodes are designed to ensure that breakdown occurs over longer gaps and for experiments above the Paschen minimum, a coaxial cylindrical system is employed. The experimental technique consists of applying pulse voltages to the gap at various constant values of E/p and B/p and measuring the time lags from which the formative time lags are separated. In the gases studed, formative time lags decrease on application of a magnetic field at a given pressure for conditions below the Paschen minimum. The voltages at which the formative time lags remain the same without and with magnetic fields are determined, and electron molecule collision frequencies (v/p) are determined using the Effective Reduced Electric Field [EREF] concept. With increasing ratio of E/p in crossed fields, v/p decreases in all the three gases. Measurements above the Paschen minimum yield formative time lags which increase on application of a magnetic field. Formative time lags in nitrogen in ExB fields are calculated assuming an average collision frequency of 8.5x109 sec-1 torr 1. It is concluded that the EREF concept can be applied to explain formative time lags in ExB fields.

Indoor air quality and energy management through real–time sensing in commercial buildings

Rapid growth in the global population requires expansion of building stock, which in turn calls for increased energy demand. This demand varies in time and also between different buildings, yet, conventional methods are only able to provide mean energy levels per zone and are unable to capture this inhomogeneity, which is important to conserve energy. An additional challenge is that some of the attempts to conserve energy, through for example lowering of ventilation rates, have been shown to exacerbate another problem, which is unacceptable indoor air quality (IAQ). The rise of sensing technology over the past decade has shown potential to address both these issues simultaneously by providing high–resolution tempo–spatial data to systematically analyse the energy demand and its consumption as well as the impacts of measures taken to control energy consumption on IAQ. However, challenges remain in the development of affordable services for data analysis, deployment of large–scale real–time sensing network and responding through Building Energy Management Systems. This article presents the fundamental drivers behind the rise of sensing technology for the management of energy and IAQ in urban built environments, highlights major challenges for their large–scale deployment and identifies the research gaps that should be closed by future investigations.

Phase Diagram for the System RuO2-TiO2 in Air

There are conflicting reports in the literature regarding solid solubility in the system RuO2-TiO2. To resolve this issue a few experiments were conducted in air at 1673, 1723, and 1773 K. The results show limited terminal solid solubility. There is an extended solid-state miscibility gap that intersects the decomposition curve for the RuO2-rich solid solution generating a peritectoid reaction at 1698 K. The measured equilibrium compositions of the solid solutions are used to develop a thermodynamic description of the oxide solid solution with rutile structure. Using the subregular solution model, the enthalpy of mixing can be represented by the expression, Delta H-M/J center dot mol(-1) = XTiO2XRuO2 ( 34,100X(TiO2) + 30,750X(RuO2)). The binodal and spinodal curves and T-X phase diagram in air are computed using this datum and Gibbs energy of formation of RuO2 available in the literature. The computed results suggest that equilibrium was not attained during solubility measurements at lower temperatures reported in the literature.

Adaptation in a Business Network Cooperation Context (summary section only)

In today’s business one can say that competition does not take place inside the network, but between networks. Change and dynamics are central issues in network studies, and a company, due its changing environment, can identify opportunities and threats and respond to them accordingly. These opportunities are vital, but also complex and demanding for the management. Earlier research has identified a shortcoming in explanations of how the micro-level interactions to macro-level patterns are connected. The IMP-group has been trying to fill this research gap with research on interactions within business networks. In this area of research lies the focus of research on relationships between organizations. Adaptation in cooperation is a central concept within business network research. Adaptation has been dealt with in previous literature, but the focus of the studies has mainly been outside this phenomenon, and it has mostly had a supporting role. Most literature has also described the buyers' point of view in studied supply networks, whereas much less attention has been paid to the suppliers' view on them. This study focuses on this research gap. The results of the study stress that adaptation should be included to a greater extent in the strategy work of companies. The adaptations should be carefully planned and, as far as possible, made consciously. Conscious, well-planned adaptations can be seen as investments into present and future relationships, and resources should be invested into something that does not increase the company’s dependence, but divides the power in the relationship between the companies. Adaptations should be planned so that they result in a more offensive way of responding to the demands that are placed upon the companies. In this way, the actions can be viewed and analyzed in accordance with whether the actions make the company weaker or stronger.

GAP-RBF based NR image quality measurement for JPEG coded images

In this paper, we present a growing and pruning radial basis function based no-reference (NR) image quality model for JPEG-coded images. The quality of the images are estimated without referring to their original images. The features for predicting the perceived image quality are extracted by considering key human visual sensitivity factors such as edge amplitude, edge length, background activity and background luminance. Image quality estimation involves computation of functional relationship between HVS features and subjective test scores. Here, the problem of quality estimation is transformed to a function approximation problem and solved using GAP-RBF network. GAP-RBF network uses sequential learning algorithm to approximate the functional relationship. The computational complexity and memory requirement are less in GAP-RBF algorithm compared to other batch learning algorithms. Also, the GAP-RBF algorithm finds a compact image quality model and does not require retraining when the new image samples are presented. Experimental results prove that the GAP-RBF image quality model does emulate the mean opinion score (MOS). The subjective test results of the proposed metric are compared with JPEG no-reference image quality index as well as full-reference structural similarity image quality index and it is observed to outperform both.

Analytical Evaluation of Squeeze Film Forces in a CMUT With Sealed Air-Filled Cavity

The presence of vacuum inside the cavity of a capacitive micromachined ultrasonic transducer (CMUT) causes the membrane of the device (which is the main vibrating structural component) to deflect towards the substrate, thereby causing a reduction in the effective gap height. This reduction causes a drastic decrease in the pull-in voltage of the device limiting the DC bias at which the device can be operated for maximum efficiency. In addition, this initial deflection of the membrane due to atmospheric pressure, causes significant stress stiffening of the the membrane, changing the natural frequency of the device significantly from the design value. To circumvent the deleterious effects of vacuum in the sealed cavity, we investigate the possibility of using sealed CMUT cavities with air inside at ambient pressure. In order to estimate the transducer loss due to the presence of air in the sealed cavity, we evaluate the resulting damping and determine the forces acting on the vibrating membrane resulting from the compression of the trapped air film. We take into account the flexure of the top vibrating membrane instead of assuming the motion to be parallel-plate like. Towards this end, we solve the linearized Reynolds equation using the appropriate boundary conditions and show that, for a sealed CMUT cavity, the presence of air does not cause any squeeze film damping.