A fluorenone based low band gap solution processable copolymer for air stable and high mobility organic field effect transistors

A fluorenone based alternating copolymer (PFN-DPPF) with a furan based fused aromatic moiety has been designed and synthesized. PFN-DPPF exhibits a small band gap with a lower HOMO value. Testing this polymer semiconductor as the active layer in organic thin-film transistors results in hole mobilities as high as 0.15 cm2 V-1 s-1 in air.

Solution processable low bandgap diketopyrrolopyrrole (DPP) based derivatives : novel acceptors for organic solar cells

Novel low bandgap solution processable diketopyrrolopyrrole (DPP) based derivatives functionalized with electron withdrawing end capping groups (trifluoromethylphenyl and trifluorophenyl) were synthesized, and their photophysical, electrochemical and photovoltaic properties were investigated. These compounds showed optical bandgaps ranging from 1.81 to 1.94 eV and intense absorption bands that cover a wide range from 300 to 700 nm, attributed to charge transfer transition between electron rich phenylene-thienylene moieties and the electron withdrawing diketopyrrolopyrrole core. All of the compounds were found to be fluorescent in solution with an emission wavelength ranging from 600 to 800 nm. Cyclic voltammetry indicated reversible oxidation and reduction processes with tuning of HOMO-LUMO energy levels. Bulk heterojunction (BHJ) solar cells using poly(3-hexylthiophene) (P3HT) as the electron donor with these new acceptors were used for fabrication. The best power conversion efficiencies (PCE) using 1:2 donor-acceptor by weight mixture were 1% under simulated AM 1.5 solar irradiation of 100 mW cm-2. These findings suggested that a DPP core functionalized with electron accepting end-capping groups were a promising new class of solution processable low bandgap n-type organic semiconductors for organic solar cell applications.

License scheme : an optimal waste management policy under asymmetric information

A system requiring a waste management license from an enforcement agency has been introduced in many countries. A license system is usually coupled with fines, a manifest, and a disposal tax. However, these policy devices have not been integrated into an optimal policy. In this paper we derive an optimal waste management policy by using those policy devices. Waste management policies are met with three difficult problems: asymmetric information, the heterogeneity of waste management firms, and non-compliance by waste management firms and waste disposers. The optimal policy in this paper overcomes all three problems.

Mission path planning of aerial survey tasks using hybrid game evolutionary algorithm

The work presented in this report is aimed to implement a cost-effective offline mission path planner for aerial inspection tasks of large linear infrastructures. Like most real-world optimisation problems, mission path planning involves a number of objectives which ideally should be minimised simultaneously. Understandably, the objectives of a practical optimisation problem are conflicting each other and the minimisation of one of them necessarily implies the impossibility to minimise the other ones. This leads to the need to find a set of optimal solutions for the problem; once such a set of available options is produced, the mission planning problem is reduced to a decision making problem for the mission specialists, who will choose the solution which best fit the requirements of the mission. The goal of this work is then to develop a Multi-Objective optimisation tool able to provide the mission specialists a set of optimal solutions for the inspection task amongst which the final trajectory will be chosen, given the environment data, the mission requirements and the definition of the objectives to minimise. All the possible optimal solutions of a Multi-Objective optimisation problem are said to form the Pareto-optimal front of the problem. For any of the Pareto-optimal solutions, it is impossible to improve one objective without worsening at least another one. Amongst a set of Pareto-optimal solutions, no solution is absolutely better than another and the final choice must be a trade-off of the objectives of the problem. Multi-Objective Evolutionary Algorithms (MOEAs) are recognised to be a convenient method for exploring the Pareto-optimal front of Multi-Objective optimization problems. Their efficiency is due to their parallelism architecture which allows to find several optimal solutions at each time

Preventing infections following caesarean section

Surgical site infections following caesarean section are a serious and costly adverse event for Australian hospitals. In the United Kingdom, 9% of women are diagnosed with a surgical site infection following caesarean section either in hospital or post-discharge (Wloch et al 2012, Ward et al 2008). Additional staff time, pharmaceuticals and health supplies, and increased length of stay or readmission to hospital are often required (Henman et al 2012). Part of my PhD investigated the economics of preventing post-caesarean infection. This paper summarises a review of relevant infection prevention strategies. Administering antibiotic prophylaxis 15 to 60 minutes pre-incision, rather than post cordclamping, is probably the most important infection prevention strategy for caesarean section (Smaill and Gyte2010, Liu et al 2013, Dahlke et al 2013). However the timing of antibiotic administration is reportedly inconsistent in Australian hospitals. Clinicians may be taking advice from the influential, but out-dated RANZCOG and United States Centers for Disease Control and Prevention guidelines (Royal Australian and New Zealand College of Obstetricians and Gynaecologists 2011, Mangram et al 1999). A number of other important international clinical guidelines, including Australia's NHMRC guidelines, recommend universal prophylactic antibiotics pre-incision for caesarean section (National Health and Medical Research Council 2010, National Collaborating Centre for Women's and Children's Health 2008, Anderson et al 2008, National Collaborating Centre for Women's and Children's Health 2011, Bratzler et al 2013, American College of Obstetricians and Gynecologists 2011a, Antibiotic Expert Group 2010). We need to ensure women receive preincision antibiotic prophylaxis, particularly as nurses and midwives play a significant role in managing an infection that may result from sub-optimal practice. It is acknowledged more explicitly now that nurses and midwives can influence prescribing and administration of antibiotics through informal approaches (Edwards et al 2011). Methods such as surgical safety checklists are a more formal way for nurses and midwives to ensure that antibiotics are administered pre-incision (American College of Obstetricians and Gynecologists 2011 b). Nurses and midwives can also be directly responsible for other infection prevention strategies such as instructing women to not remove pubic hair in the month before the expected date of delivery and wound management education (Ng et al 2013). Potentially more costly but effective strategies include using a Chlorhexidine-gluconate (CHG) sponge preoperatively (in addition to the usual operating room skin preparation) and vaginal cleansing with a povidone-iodine solution (Riley et al 2012, Rauk 2010, Haas, Morgan, and Contreras 2013).

A non-aqueous solution synthesis of boron carbide by control of in-situ carbon

Synthesis of high quality boron carbide (B4C) powder is achieved by carbothermal reduction of boron oxide (B2O3) from a condensed boric acid (H3BO3) / polyvinyl acetate (PVAc) product. Precursor solutions are prepared via polymerisation of vinyl acetate (VA) in methanol in the presence of dissolved H3BO3. With excess VA monomer being removed during evaporation of the solvent, the polymerisation time is then used to manage availability of carbon for reaction.

Making optimal and justifiable asset maintenance decisions

Maintenance decisions for large-scale asset systems are often beyond an asset manager's capacity to handle. The presence of a number of possibly conflicting decision criteria, the large number of possible maintenance policies, and the reality of budget constraints often produce complex problems, where the underlying trade-offs are not apparent to the asset manager. This paper presents the decision support tool "JOB" (Justification and Optimisation of Budgets), which has been designed to help asset managers of large systems assess, select, interpret and optimise the effects of their maintenance policies in the presence of limited budgets. This decision support capability is realized through an efficient, scalable backtracking- based algorithm for the optimisation of maintenance policies, while enabling the user to view a number of solutions near this optimum and explore tradeoffs with other decision criteria. To assist the asset manager in selecting between various policies, JOB also provides the capability of Multiple Criteria Decision Making. In this paper, the JOB tool is presented and its applicability for the maintenance of a complex power plant system.

1,3,6,8-Tetrasubstituted Pyrenes: Solution-Processable Materials for Application in Organic Electronics

(Equation Presented). A series of star-shaped organic semiconductors have been synthesized from 1,3,6,8-tetrabromopyrene. The materials are soluble in common organic solvents allowing for solution processing of devices such as light-emitting diodes (OLEDs). One of the materials, 1,3,6,8-tetrakis(4- butoxyphenyl)pyrene, has been used as the active emitting layer in simple solution-processed OLEDs with deep blue emission (CIE = 0.15, 0.18) and maximum efficiencies and brightness levels of 2.56 cd/A and >5000 cd/m2, respectively.

A frontier functions approach to optimal scales of sustainable production

This paper translates the concepts of sustainable production to three dimensions of economic, environmental and ecological sustainability to analyze optimal production scales by solving optimizing problems. Economic optimization seeks input-output combinations to maximize profits. Environmental optimization searches for input-output combinations that minimize the polluting effects of materials balance on the surrounding environment. Ecological optimization looks for input-output combinations that minimize the cumulative destruction of the entire ecosystem. Using an aggregate space, the framework illustrates that these optimal scales are often not identical because markets fail to account for all negative externalities. Profit-maximizing firms normally operate at the scales which are larger than optimal scales from the viewpoints of environmental and ecological sustainability; hence policy interventions are favoured. The framework offers a useful tool for efficiency studies and policy implication analysis. The paper provides an empirical investigation using a data set of rice farms in South Korea.

Optimal HMM processing of differentially phase modulated communication systems

This paper investigates demodulation of differentially phase modulated signals DPMS using optimal HMM filters. The optimal HMM filter presented in the paper is computationally of order N3 per time instant, where N is the number of message symbols. Previously, optimal HMM filters have been of computational order N4 per time instant. Also, suboptimal HMM filters have be proposed of computation order N2 per time instant. The approach presented in this paper uses two coupled HMM filters and exploits knowledge of ...

Optimal HMM filtering and decision feedback equalisation for differential encoded transmission systems

In this paper conditional hidden Markov model (HMM) filters and conditional Kalman filters (KF) are coupled together to improve demodulation of differential encoded signals in noisy fading channels. We present an indicator matrix representation for differential encoded signals and the optimal HMM filter for demodulation. The filter requires O(N3) calculations per time iteration, where N is the number of message symbols. Decision feedback equalisation is investigated via coupling the optimal HMM filter for estimating the message, conditioned on estimates of the channel parameters, and a KF for estimating the channel states, conditioned on soft information message estimates. The particular differential encoding scheme examined in this paper is differential phase shift keying. However, the techniques developed can be extended to other forms of differential modulation. The channel model we use allows for multiplicative channel distortions and additive white Gaussian noise. Simulation studies are also presented.

Methods for extracting genomic DNA from whole blood samples : current perspectives

Deoxyribonucleic acid (DNA) extraction has considerably evolved since it was initially performed back in 1869. It is the first step required for many of the available downstream applications used in the field of molecular biology. Whole blood samples are one of the main sources used to obtain DNA, and there are many different protocols available to perform nucleic acid extraction on such samples. These methods vary from very basic manual protocols to more sophisticated methods included in automated DNA extraction protocols. Based on the wide range of available options, it would be ideal to determine the ones that perform best in terms of cost-effectiveness and time efficiency. We have reviewed DNA extraction history and the most commonly used methods for DNA extraction from whole blood samples, highlighting their individual advantages and disadvantages. We also searched current scientific literature to find studies comparing different nucleic acid extraction methods, to determine the best available choice. Based on our research, we have determined that there is not enough scientific evidence to support one particular DNA extraction method from whole blood samples. Choosing a suitable method is still a process that requires consideration of many different factors, and more research is needed to validate choices made at facilities around the world.

A non-fullerene electron acceptor based on fluorene and diketopyrrolopyrrole building blocks for solution-processable organic solar cells with an impressive open-circuit voltage

A novel solution-processable non-fullerene electron acceptor 6,6′-(5,5′-(9,9-dioctyl-9H-fluorene-2,7-diyl)bis(thiophene-5,2-diyl))bis(2,5-bis(2-ethylhexyl)-3-(thiophen-2-yl)pyrrolo[3,4-c]pyrrole-1,4(2H,5H)-dione) (DPP1) based on fluorene and diketopyrrolopyrrole conjugated moieties was designed, synthesized and fully characterized. DPP1 exhibited excellent solubility and high thermal stability which are essential for easy processing. Upon using DPP1 as an acceptor with the classical electron donor poly(3-hexylthiophene), solution processable bulk-heterojunction solar cells afforded a power conversion efficiency of 1.2% with a high open-circuit voltage (1.1 V). As per our knowledge, this value of open circuit voltage is one of the highest values reported so far for a bulk-heterojunction device using DPP1 as a non-fullerene acceptor.

A model predictive approach for community battery energy storage system optimization

This paper presents an efficient algorithm for optimizing the operation of battery storage in a low voltage distribution network with a high penetration of PV generation. A predictive control solution is presented that uses wavelet neural networks to predict the load and PV generation at hourly intervals for twelve hours into the future. The load and generation forecast, and the previous twelve hours of load and generation history, is used to assemble load profile. A diurnal charging profile can be compactly represented by a vector of Fourier coefficients allowing a direct search optimization algorithm to be applied. The optimal profile is updated hourly allowing the state of charge profile to respond to changing forecasts in load.