Thiophene–tetrafluorophenyl–thiophene : a promising building block for ambipolar organic field effect transistors

A thiophene–tetrafluorophenyl–thiophene donor–acceptor–donor building block was used in combination with a furan-substituted diketopyrrolopyrrole for synthesizing the polymer semiconductor, PDPPF-TFPT. Due to the balance of tetrafluorophenylene/diketopyrrolopyrrole electron-withdrawing and furan/thiophene electron-donating moieties in the backbone, PDPPF-TFPT exhibits ambipolar behaviour in organic thin-film transistors, with hole and electron mobilities as high as 0.40 cm2 V−1 s−1 and 0.12 cm2 V−1 s−1.

Clinical use of diodes and micro-chambers to obtain accurate small field output factor measurements

There have been substantial advances in small field dosimetry techniques and technologies, over the last decade, which have dramatically improved the achievable accuracy of small field dose measurements. This educational note aims to help radiation oncology medical physicists to apply some of these advances in clinical practice. The evaluation of a set of small field output factors (total scatter factors) is used to exemplify a detailed measurement and simulation procedure and as a basis for discussing the possible effects of simplifying that procedure. Field output factors were measured with an unshielded diode and a micro-ionisation chamber, at the centre of a set of square fields defined by a micro-multileaf collimator. Nominal field sizes investigated ranged from 6×6 to 98×98 mm2. Diode measurements in fields smaller than 30 mm across were corrected using response factors calculated using Monte Carlo simulations of the full diode geometry and daisy-chained to match micro-chamber measurements at intermediate field sizes. Diode measurements in fields smaller than 15 mm across were repeated twelve times over three separate measurement sessions, to evaluate the to evaluate the reproducibility of the radiation field size and its correspondence with the nominal field size. The five readings that contributed to each measurement on each day varied by up to 0.26%, for the “very small” fields smaller than 15 mm, and 0.18% for the fields larger than 15 mm. The diode response factors calculated for the unshielded diode agreed with previously published results, within 1.6%. The measured dimensions of the very small fields differed by up to 0.3 mm, across the different measurement sessions, contributing an uncertainty of up to 1.2% to the very small field output factors. The overall uncertainties in the field output factors were 1.8% for the very small fields and 1.1% for the fields larger than 15 mm across. Recommended steps for acquiring small field output factor measurements for use in radiotherapy treatment planning system beam configuration data are provided.

An external field prior for the hidden Potts model with application to cone-beam computed tomography

In images with low contrast-to-noise ratio (CNR), the information gain from the observed pixel values can be insufficient to distinguish foreground objects. A Bayesian approach to this problem is to incorporate prior information about the objects into a statistical model. A method for representing spatial prior information as an external field in a hidden Potts model is introduced. This prior distribution over the latent pixel labels is a mixture of Gaussian fields, centred on the positions of the objects at a previous point in time. It is particularly applicable in longitudinal imaging studies, where the manual segmentation of one image can be used as a prior for automatic segmentation of subsequent images. The method is demonstrated by application to cone-beam computed tomography (CT), an imaging modality that exhibits distortions in pixel values due to X-ray scatter. The external field prior results in a substantial improvement in segmentation accuracy, reducing the mean pixel misclassification rate for an electron density phantom from 87% to 6%. The method is also applied to radiotherapy patient data, demonstrating how to derive the external field prior in a clinical context.

Application of anomaly technique in wind turbine bearing fault detection

Bearing faults are the most common cause of wind turbine failures. Unavailability and maintenance cost of wind turbines are becoming critically important, with their fast growing in electric networks. Early fault detection can reduce outage time and costs. This paper proposes Anomaly Detection (AD) machine learning algorithms for fault diagnosis of wind turbine bearings. The application of this method on a real data set was conducted and is presented in this paper. For validation and comparison purposes, a set of baseline results are produced using the popular one-class SVM methods to examine the ability of the proposed technique in detecting incipient faults.

An improved robust field weakening algorithm for direct torque controlled synchronous reluctance motor drives

This paper presents an improved field weakening algorithm for synchronous reluctance motor (RSMs) drives. The proposed algorithm is robust to the variations in the machine d- and q-axes inductances. The transition between the maximum torque per ampere (MTPA), current and voltage limits as well as the maximum torque per flux (MTPF) trajectories is smooth. The proposed technique is combined with the direct torque control method to attain a high performance drive in the field weakening region. Simulation and experimental results are supplemented to verify the effectiveness of the proposed approach.

Herds of methane chambers grazing bubbles

Water to air methane emissions from freshwater reservoirs can be dominated by sediment bubbling (ebullitive) events. Previous work to quantify methane bubbling from a number of Australian sub-tropical reservoirs has shown that this can contribute as much as 95% of total emissions. These bubbling events are controlled by a variety of different factors including water depth, surface and internal waves, wind seiching, atmospheric pressure changes and water levels changes. Key to quantifying the magnitude of this emission pathway is estimating both the bubbling rate as well as the areal extent of bubbling. Both bubbling rate and areal extent are seldom constant and require persistent monitoring over extended time periods before true estimates can be generated. In this paper we present a novel system for persistent monitoring of both bubbling rate and areal extent using multiple robotic surface chambers and adaptive sampling (grazing) algorithms to automate the quantification process. Individual chambers are self-propelled and guided and communicate between each other without the need for supervised control. They can maintain station at a sampling site for a desired incubation period and continuously monitor, record and report fluxes during the incubation. To exploit the methane sensor detection capabilities, the chamber can be automatically lowered to decrease the head-space and increase concentration. The grazing algorithms assign a hierarchical order to chambers within a preselected zone. Chambers then converge on the individual recording the highest 15 minute bubbling rate. Individuals maintain a specified distance apart from each other during each sampling period before all individuals are then required to move to different locations based on a sampling algorithm (systematic or adaptive) exploiting prior measurements. This system has been field tested on a large-scale subtropical reservoir, Little Nerang Dam, and over monthly timescales. Using this technique, localised bubbling zones on the water storage were found to produce over 50,000 mg m-2 d-1 and the areal extent ranged from 1.8 to 7% of the total reservoir area. The drivers behind these changes as well as lessons learnt from the system implementation are presented. This system exploits relatively cheap materials, sensing and computing and can be applied to a wide variety of aquatic and terrestrial systems.

WIL-power: Developing journalism students' intercultural communications and international reporting skills on field trips to Vietnam

This article examines journalism students' learning experience that is intercultural, immersive and intensive. Accounts of 'intercultural' experience date back to Herodotus of Halicarnassus; 'immersion' is integral to contemporary practice in language learning; and 'intensive' delivery has been refined to an art by postgraduate business education. Together they can be grouped under the broader pedagogical concept of work-integrated learning (WIL). This article examines two WIL projects that involved field trips by journalism students to Vietnam in 2012 and 2014, and their implications for future WIL initiatives.

Robust sensing for a 3,500 tonne field robot

The mining industry is highly suitable for the application of robotics and automation technology since the work is arduous, dangerous and often repetitive. This paper discusses a robust sensing system developed to find and trade the position of the hoist ropes of a dragline. Draglines are large `walking cranes' used in open-pit coal mining to remove the material covering the coal seam. The rope sensing system developed uses two time-of-flight laser scanners. The finding algorithm uses a novel data association and tracking strategy based on pairing rope data.

Perspectives on global nursing leadership: International experiences from the field

AIM Nursing leaders from six countries engaged in a year-long discussion on global leadership development. The purpose of these dialogues was to strengthen individual and collective capacity as nursing leaders in a global society. Field experiences in practice and education were shared. Perspectives on global leadership can strengthen nurses' contributions to practice, workplace and policy issues worldwide. BACKGROUND Transformational leadership empowers nurses' increasing confidence. Mentoring is needed to stimulate leadership development but this is lacking in many settings where nurses practice, teach and influence policy. Organizations with global mission provide opportunity for nurses' professional growth in leadership through international dialogues. PROCEDURES Dialogues among participants were held monthly by conference calls or videoconferences. Example stories from each participant illustrated nursing leadership in action. From these exemplars, concepts were chosen to create a framework. Emerging perspectives and leadership themes represented all contexts of practice, education, research and policy. The cultural context of each country was reflected in the examples. RESULTS Themes emerged that crossed global regions and countries. Themes were creativity, change, collaboration, community, context and courage. IMPLICATIONS FOR NURSING AND HEALTH POLICY Relationships initially formed in professional organizations can be extended to intentionally facilitate global nursing leadership development. Exemplars from the dialogues demonstrated nursing leadership in health policy development within each cultural context. Recommendations are given for infrastructure development in organizations to enhance future collaborations.

A new constraint handling method for wind farm layout optimization with lands owned by different owners

For wind farm optimizations with lands belonging to different owners, the traditional penalty method is highly dependent on the type of wind farm land division. The application of the traditional method can be cumbersome if the divisions are complex. To overcome this disadvantage, a new method is proposed in this paper for the first time. Unlike the penalty method which requires the addition of penalizing term when evaluating the fitness function, it is achieved through repairing the infeasible solutions before fitness evaluation. To assess the effectiveness of the proposed method on the optimization of wind farm, the optimizing results of different methods are compared for three different types of wind farm division. Different wind scenarios are also incorporated during optimization which includes (i) constant wind speed and wind direction; (ii) various wind speed and wind direction, and; (iii) the more realisticWeibull distribution. Results show that the performance of the new method varies for different land plots in the tested cases. Nevertheless, it is found that optimum or at least close to optimum results can be obtained with sequential land plot study using the new method for all cases. It is concluded that satisfactory results can be achieved using the proposed method. In addition, it has the advantage of flexibility in managing the wind farm design, which not only frees users to define the penalty parameter but without limitations on the wind farm division.

Field and Service Robotics: Results of the 9th International Conference

The Field and Service Robotics (FSR) conference is a single track conference with a specific focus on field and service applications of robotics technology. The goal of FSR is to report and encourage the development of field and service robotics. These are non-factory robots, typically mobile, that must operate in complex and dynamic environments. Typical field robotics applications include mining, agriculture, building and construction, forestry, cargo handling and so on. Field robots may operate on the ground (of Earth or planets), under the ground, underwater, in the air or in space. Service robots are those that work closely with humans, importantly the elderly and sick, to help them with their lives. The first FSR conference was held in Canberra, Australia, in 1997. Since then the meeting has been held every 2 years in Asia, America, Europe and Australia. It has been held in Canberra, Australia (1997), Pittsburgh, USA (1999), Helsinki, Finland (2001), Mount Fuji, Japan (2003), Port Douglas, Australia (2005), Chamonix, France (2007), Cambridge, USA (2009), Sendai, Japan (2012) and most recently in Brisbane, Australia (2013). This year we had 54 submissions of which 36 were selected for oral presentation. The organisers would like to thank the international committee for their invaluable contribution in the review process ensuring the overall quality of contributions. The organising committee would also like to thank Ben Upcroft, Felipe Gonzalez and Aaron McFadyen for helping with the organisation and proceedings. and proceedings. The conference was sponsored by the Australian Robotics and Automation Association (ARAA), CSIRO, Queensland University of Technology (QUT), Defence Science and Technology Organisation Australia (DSTO) and the Rio Tinto Centre for Mine Automation, University of Sydney.

Fault detection of wind turbine drivetrain utilizing power-speed characteristics

Wind energy, being the fastest growing renewable energy source in the present world, requires a large number of wind turbines to transform wind energy into electricity. One factor driving the cost of this energy is the reliable operation of these turbines. Therefore, it is a growing requirement within the wind farm community, to monitor the operation of the wind turbines on a continuous basis so that a possible fault can be detected ahead of time. As the wind turbine operates in an environment of constantly changing wind speed, it is a challenging task to design a fault detection technique which can accommodate the stochastic operational behavior of the turbines. Addressing this issue, this paper proposes a novel fault detection criterion which is robust against operational uncertainty, as well as having the ability to quantify severity level specifically of the drivetrain abnormality within an operating wind turbine. A benchmark model of wind turbine has been utilized to simulate drivetrain fault condition and effectiveness of the proposed technique has been tested accordingly. From the simulation result it can be concluded that the proposed criterion exhibits consistent performance for drivetrain faults for varying wind speed and has linear relationship with the fault severity level.

Fuzzy-logic based frequency controller for wind farms augmented with energy storage systems

Displacement of conventional synchronous generators by non-inertial units such as wind or solar generators will result in reduced-system inertia affecting under-frequency response. Frequency control is important to avoid equipment damage, load shedding, and possible blackouts. Wind generators along with energy storage systems can be used to improve the frequency response of low-inertia power system. This paper proposes a fuzzy-logic based frequency controller (FFC) for wind farms augmented with energy storage systems (wind-storage system) to improve the primary frequency response in future low-inertia hybrid power system. The proposed controller provides bidirectional real power injection using system frequency deviations and rate of change of frequency (RoCoF). Moreover, FFC ensures optimal use of energy from wind farms and storage units by eliminating the inflexible de-loading of wind energy and minimizing the required storage capacity. The efficacy of the proposed FFC is verified on the low-inertia hybrid power system.

Fast unscented transformation-based transient stability margin estimation incorporating uncertainty of wind generation

Intermittent generation from wind farms leads to fluctuating power system operating conditions pushing the stability margin to its limits. The traditional way of determining the worst case generation dispatch for a system with several semi-scheduled wind generators yields a conservative solution. This paper proposes a fast estimation of the transient stability margin (TSM) incorporating the uncertainty of wind generation. First, the Kalman filter (KF) is used to provide linear estimation of system angle and then unscented transformation (UT) is used to estimate the distribution of the TSM. The proposed method is compared with the traditional Monte Carlo (MC) method and the effectiveness of the proposed approach is verified using Single Machine Infinite Bus (SMIB) and IEEE 14 generator Australian dynamic system. This method will aid grid operators to perform fast online calculations to estimate TSM distribution of a power system with high levels of intermittent wind generation.

Field size consistency of nominally matched linacs

Given that there is increasing recognition of the effect that submillimetre changes in collimator position can have on radiotherapy beam dosimetry, this study aimed to evaluate the potential variability in small field collimation that may exist between otherwise matched linacs. Field sizes and field output factors were measured using radiochromic film and an electron diode, for jaw- and MLC-collimated fields produced by eight dosimetrically matched Varian iX linacs (Varian Medical Systems, Palo Alto, USA). This study used nominal sizes from 0.6×0.6 to 10×10 cm215 , for jaw-collimated fields,and from 1×1 to 10×10 cm216 , for MLC-collimated fields, delivered from a zero (head up, beam directed vertically downward) gantry angle. Differences between the field sizes measured for the eight linacs exceeded the uncertainty of the film measurements and the repositioning uncertainty of the jaws and MLCs on one linac. The dimensions of fields defined by MLC leaves were more consistent between linacs, while also differing more from their nominal values than fields defined by orthogonal jaws. The field output factors measured for the different linacs generally increased with increasing measured field size for the nominal 0.6×0.6 and 1×1 cm2 fields, and became consistent between linacs for nominal field sizes of 2×2 cm2 25 and larger. The inclusion in radiotherapy treatment planning system beam data of small field output factors acquired in fields collimated by jaws (rather than the more-reproducible MLCs), associated with either the nominal or the measured field sizes, should be viewed with caution. The size and reproducibility of the fields (especially the small fields) used to acquire treatment planning data should be investigated thoroughly as part of the linac or planning system commissioning process. Further investigation of these issues, using different linac models, collimation systems and beam orientations, is recommended.