Synthesis, characterization and comparative study of thiophene- benzothiadiazole based donor-acceptor-donor (D-A-D) materials

The synthesis and characterization of solution processable donor-acceptor-donor (D-A-D) based conjugated molecules with varying ratios of thiophene as donor (D) and benzothiadiazole as acceptor (A) are reported. Optical, electrochemical, thermal, morphological and organic thin film transistor (OTFT) device properties of these materials were investigated. The thermal and polarized optical microscope analysis indicates that the materials having higher D/A ratios exhibit both liquid crystalline (LC) and OTFT behavior. AFM analysis of the materials having D/A ratios of 3 and 4 (3T1B and 4T1B) show well ordered structures, resulting from strong π-π interchain interactions compared to the other molecules in this study. A XRD patterns for 3T1B and 4T1B thin films also shows high crystalline ordering. Solution processed OTFTs of 3T1B and 4T1B have shown un-optimized charge carrier mobilities of 2 × 10 -2 cm 2 V -1 s -1 and 4 × 10 -3 cm 2 V -1 s -1, respectively on bare Si/SiO 2 substrate.

Water-based nanoparticulate solar cells using a diketopyrrolopyrrole donor polymer

Organic photovoltaic devices with either bulk heterojunction (BHJ) or nanoparticulate (NP) active layers have been prepared from a 1:2 blend of (poly{3,6-dithiophene-2-yl-2,5-di(2-octyldodecyl)-pyrrolo[3,4-c]pyrrole-1, 4-dione-alt-naphthalene}) (PDPP-TNT) and the fullerene acceptor, ([6,6]-phenyl C71-butyric acid methyl ester) (PC70BM). Atomic force microscopy (AFM) and scanning electron microscopy (SEM) have been used to investigate the morphology of the active layers of the two approaches. Mild thermal treatment of the NP film is required to promote initial joining of the NPs in order for the devices to function, however the NP structure is retained. Consequently, whereas gross phase segregation of the active layer occurs in the BHJ device spin cast from chloroform, the nanoparticulate approach retains control of the material domain sizes on the length scale of exciton diffusion in the materials. As a result, NP devices are found to generate more than twice the current density of BHJ devices and have a substantially greater overall efficiency. The use of aqueous nanoparticulate dispersions offers a promising approach to control the donor acceptor morphology on the nanoscale with the benefit of environmentally- friendly, solution-based fabrication. © 2014 the Owner Societies.

School based youth health nurses and attrition : the reasons for moving on

Like the UK, Australia has a number of school nursing models and programmes. The School Based Youth Health Nurse Program (SBYHNP) is a new and unique model of school nursing in Queensland, Australia. The SBYHNP represents a philosophical and structural shift from traditional school nursing programmes. The purpose of this qualitative case study is to explore the reasons School Based Youth Health Nurses (SBYHN) leave school nursing. Sixteen in-depth interviews were conducted with participants who practiced as SBYHN and left the SBYHNP. This case study reveals six themes: The politics’: Navigating the organisational divide, 'Unconditional positive regard’: Surviving without team cohesion, 'Absolutely exhausted’: Maintaining physical and emotional strength, ‘Definitely geographical’: Managing the tyranny of time and distance, ‘If things fell into place’: Thinking about what could have been, and ‘A stepping stone’: Moving on to the next nursing position. This case study suggests nurses considering school nursing as a specialty should seek opportunity to understand this complex role, ensure realistic expectations and ndertake relevant qualifications. This approach may secure the investment made by nurses and schools and create demand for a highly sort after position.

How does Nepal Television (NTV) frame natural disasters? A qualitative content analysis of news scripts using news frames and PPRR cycle

Introduction- This study investigates the prevailing status of Nepalese media portrayal of natural disasters. It is contributing to the development of a disaster management model to improve the effectiveness and efficiency of news production throughout the continuum of prevention, preparedness, response and recovery (PPRR) phases of disaster management. Theoretical framework- Studies of media content often rely on framing as the theoretical underpinning of the study, as it describes how the press crafts the message. However there are additional theoretical perspectives that underline an understanding of the role of the media. This article outlines a conceptual understanding of the role of the media in modern society, the way that this conceptual understanding is used in the crafting of media messages and how those theoretical considerations are applied to the concepts that underpin effective disaster management. (R.M. Entman, 2003; Liu, 2007; Meng & Berger, 2008). Methodology- A qualitative descriptive design is used to analyse the disaster news of Nepal Television (NTV). However, this paper presents the preliminary findings of Nepal Television (a government owned Television station) using qualitative content analysis of 105 natural disaster related news scripts (June 2012-March 2013) based on the framing theory and PPRR cycle. Results- The preliminary results indicate that the media focus while framing natural disasters is dominated by human interest frame followed by responsibility frame. News about response phase was found to be most prominent in terms of PPRR cycle. Limited disaster reporting by NTV has impacted the national disaster management programs and strategies. The findings describe natural disasters are being reported within the limited understanding of the important principles of disaster management and PPRR cycle. Conclusion- This paper describes the current status of the coverage of natural disasters by Nepal Television to identify the frames used in the news content. It contributes to determining the characteristics of effective media reporting of natural disasters in the government owned media outlets, and also leads to including communities and agencies involved in disasters. It suggests the frames which are best suited for news making and how media responds to the different phases of the disaster cycle.

Industry based rehabilitation and closure knowledge management system : scoping study

The Central Queensland Mine Rehabilitation Group (CQMRG) has hosted mine site rehabilitation inspections combined with technical workshops for more than 20 years. It was recognised at CQMRG's anniversary meeting in April 2013 that the vast body of knowledge held by rehabilitation and closure planning practitioners was being lost as senior rehabilitation experts retire from the industry. It was noted that even more knowledge could be readily lost unless a knowledge management platform was developed to capture, store and enable retrieval of this information. This loss of knowledge results in a significant cost to industry. This project was therefore undertaken to review tools which have the capability to gather the less formal knowledge as well as to make links to existing resources and bibliographic material. This scoping study evaluated eight alternative knowledge management systems to provide guidance on the best method of providing the industry with an up-to-date, good practice, knowledge management system for rehabilitation and closure practices, with capability for information sharing via a portal and discussion forum. This project provides guidance for a larger project which will implement the knowledge management system to meet the requirements of the CQMRG and be transferrable to other regions if applicable. It will also provide the opportunity to identify missing links between existing tools and their application. That is, users may not be aware of how these existing tools can be used to assist with mine rehabilitation planning and implementation and the development of a new platform will help to create those linkages. The outcomes of this project are directed toward providing access to a live repository of rehabilitation practice information which is Central Queensland coal mine-specific, namely: highlighting best practice activities, results of trials and innovative practices; updated legislative requirements; links to practices elsewhere; and informal anecdotal information relevant to particular sites which may be of assistance in the development of rehabilitation of new areas. Solutions to the rehabilitation of challenging spoils/soils will also be provided. The project will also develop a process which can be applied more broadly within the mining sector to other regions and other commodities. Providing a platform for uploading information and holding discussion forums which can be managed by a regional practitioner network enables the new system to be kept alive, driven by users and information needs as they evolve over time. Similar internet-based platforms exist and are managed successfully. The preferred knowledge management system will capture the less formal and more difficult to access knowledge from rehabilitation and mine closure practitioners and stakeholders through the CQMRG and other contributors. It will also provide direct links, and greater accessibility, to more formal sources of knowledge with anticipated cost savings to the industry and improved rehabilitation practices with successful transitioning to closure and post-mining land use.

A normal-distribution based reputation model

Rating systems are used by many websites, which allow customers to rate available items according to their own experience. Subsequently, reputation models are used to aggregate available ratings in order to generate reputation scores for items. A problem with current reputation models is that they provide solutions to enhance accuracy of sparse datasets not thinking of their models performance over dense datasets. In this paper, we propose a novel reputation model to generate more accurate reputation scores for items using any dataset; whether it is dense or sparse. Our proposed model is described as a weighted average method, where the weights are generated using the normal distribution. Experiments show promising results for the proposed model over state-of-the-art ones on sparse and dense datasets.

Acceptability-based QoE management for user-centric mobile video delivery : a field study evaluation

Effective Quality of Experience (QoE) management for mobile video delivery – to optimize overall user experience while adapting to heterogeneous use contexts – is still a big challenge to date. This paper proposes a mobile video delivery system to emphasize the use of acceptability as the main indicator of QoE to manage the end-to-end factors in delivering mobile video services. The first contribution is a novel framework for user-centric mobile video system that is based on acceptability-based QoE (A-QoE) prediction models, which were derived from comprehensive subjective studies. The second contribution is results from a field study that evaluates the user experience of the proposed system during realistic usage circumstances, addressing the impacts of perceived video quality, loading speed, interest in content, viewing locations, network bandwidth, display devices, and different video coding approaches, including region-of-interest (ROI) enhancement and center zooming

An alternative approach to setting a mill

The conventional approach to setting a milling unit is essentially based on the desire to achieve a particular bagasse moisture content or fibre fill in each nip of the mill. This approach relies on the selection of the speed at which the mill will operate for the selected fibre rate. There is rarely any checking that the selected speed or the selected fibre fill is achieved and the same set of assumptions is generally carried over to use again in the next year. The conventional approach largely ignores the fact that the selection of mill settings actually determines the speed at which the mill will operate. Making an adjustment with the intent of changing the performance of the mill often also changes the speed of the mill as an unintended consequence. This paper presents an alternative approach to mill setting. The approach discussed makes use of mill feeding theory to define the relationship between fibre rate, mill speed and mill settings and uses that theory to provide an alternative means of determining the settings in some nips of the mill. Mill feeding theory shows that, as the feed work opening reduces, roll speed increases. The theory also shows that there is an optimal underfeed opening and Donnelly chute exit opening that will minimise roll speed and that the current South African guidelines appear to be well away from those optimal values.

Developing a transdisciplinary approach to improve urban traffic congestion based on Product Ecosystem theory

Product Ecosystem theory is an emerging theory that shows that disruptive “game changing” innovation is only possible when the entire ecosystem is considered. When environmental variables change faster than products or services can adapt, disruptive innovation is required to keep pace. This has many parallels with natural ecosystems where species that cannot keep up with changes to the environment will struggle or become extinct. In this case the environment is the city, the environmental pressures are pollution and congestion, the product is the car and the product ecosystem is comprised of roads, bridges, traffic lights, legislation, refuelling facilities etc. Each one of these components is the responsibility of a different organisation and so any change that affects the whole ecosystem requires a transdisciplinary approach. As a simple example, cars that communicate wirelessly with traffic lights are only of value if wireless-enabled traffic lights exist and vice versa. Cars that drive themselves are technically possible but legislation in most places doesn’t allow their use. According to innovation theory, incremental innovation tends to chase ever diminishing returns and becomes increasingly unable to tackle the “big issues.” Eventually “game changing” disruptive innovation comes along and solves the “big issues” and/or provides new opportunities. Seen through this lens, the environmental pressures of urban traffic congestion and pollution are the “big issues.” It can be argued that the design of cars and the other components of the product ecosystem follow an incremental innovation approach. That is why the “big issues” remain unresolved. This paper explores the problems of pollution and congestion in urban environments from a Product Ecosystem perspective. From this a strategy will be proposed for a transdisciplinary approach to develop and implement solutions.

A tag-based personalized item recommendation system using tensor modeling and topic model approaches

This research falls in the area of enhancing the quality of tag-based item recommendation systems. It aims to achieve this by employing a multi-dimensional user profile approach and by analyzing the semantic aspects of tags. Tag-based recommender systems have two characteristics that need to be carefully studied in order to build a reliable system. Firstly, the multi-dimensional correlation, called as tag assignment , should be appropriately modelled in order to create the user profiles [1]. Secondly, the semantics behind the tags should be considered properly as the flexibility with their design can cause semantic problems such as synonymy and polysemy [2]. This research proposes to address these two challenges for building a tag-based item recommendation system by employing tensor modeling as the multi-dimensional user profile approach, and the topic model as the semantic analysis approach. The first objective is to optimize the tensor model reconstruction and to improve the model performance in generating quality rec-ommendation. A novel Tensor-based Recommendation using Probabilistic Ranking (TRPR) method [3] has been developed. Results show this method to be scalable for large datasets and outperforming the benchmarking methods in terms of accuracy. The memory efficient loop implements the n-mode block-striped (matrix) product for tensor reconstruction as an approximation of the initial tensor. The probabilistic ranking calculates the probabil-ity of users to select candidate items using their tag preference list based on the entries generated from the reconstructed tensor. The second objective is to analyse the tag semantics and utilize the outcome in building the tensor model. This research proposes to investigate the problem using topic model approach to keep the tags nature as the “social vocabulary” [4]. For the tag assignment data, topics can be generated from the occurrences of tags given for an item. However there is only limited amount of tags availa-ble to represent items as collection of topics, since an item might have only been tagged by using several tags. Consequently, the generated topics might not able to represent the items appropriately. Furthermore, given that each tag can belong to any topics with various probability scores, the occurrence of tags cannot simply be mapped by the topics to build the tensor model. A standard weighting technique will not appropriately calculate the value of tagging activity since it will define the context of an item using a tag instead of a topic.

Learning-based Relevance Feedback for Web-based Relation Completion

In a pilot application based on web search engine calledWeb-based Relation Completion (WebRC), we propose to join two columns of entities linked by a predefined relation by mining knowledge from the web through a web search engine. To achieve this, a novel retrieval task Relation Query Expansion (RelQE) is modelled: given an entity (query), the task is to retrieve documents containing entities in predefined relation to the given one. Solving this problem entails expanding the query before submitting it to a web search engine to ensure that mostly documents containing the linked entity are returned in the top K search results. In this paper, we propose a novel Learning-based Relevance Feedback (LRF) approach to solve this retrieval task. Expansion terms are learned from training pairs of entities linked by the predefined relation and applied to new entity-queries to find entities linked by the same relation. After describing the approach, we present experimental results on real-world web data collections, which show that the LRF approach always improves the precision of top-ranked search results to up to 8.6 times the baseline. Using LRF, WebRC also shows performances way above the baseline.

Ranking based clustering for social event detection

The problem of clustering a large document collection is not only challenged by the number of documents and the number of dimensions, but it is also affected by the number and sizes of the clusters. Traditional clustering methods fail to scale when they need to generate a large number of clusters. Furthermore, when the clusters size in the solution is heterogeneous, i.e. some of the clusters are large in size, the similarity measures tend to degrade. A ranking based clustering method is proposed to deal with these issues in the context of the Social Event Detection task. Ranking scores are used to select a small number of most relevant clusters in order to compare and place a document. Additionally,instead of conventional cluster centroids, cluster patches are proposed to represent clusters, that are hubs-like set of documents. Text, temporal, spatial and visual content information collected from the social event images is utilized in calculating similarity. Results show that these strategies allow us to have a balance between performance and accuracy of the clustering solution gained by the clustering method.

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.

Pyrene based conjugated materials: synthesis, characterization and electroluminescent properties

In this work, three novel pyrene cored small conjugated molecules, namely 1,3,6,8-tetrakis(6-(octyloxy)naphthalene-2-yl)pyrene (PY-1), 1,3,6,8-tetrakis((E)-2-(6-(n-octyloxy)naphthalene-2-yl)vinyl)pyrene (PY-2) and 1,3,6,8-tetrakis((6-(n-octyloxy)naphthalene-2-yl)ethynyl)pyrene (PY-3) have been synthesized by Suzuki, heck and Sonogashira organometallic coupling reactions, respectively. The effects of single, double and triple bonds on their optical, electrochemical, and thermal properties are studied in detail. These are all materials fluorescent and they have been used in organic light-emitting diodes (OLEDs) and their electroluminescent properties have been studied.

Best practice in peer-led curriculum content : informing an interactive program to improve passenger safety among high school seniors

Despite ongoing improvements in behaviour change strategies, licensing models and road law enforcement measures young drivers remain significantly over-represented in fatal and non-fatal road related crashes. This paper focuses on the safety of those approaching driving age and identifies both high priority road safety messages and relevant peer-led strategies to guide the development school programs. It summarises the review in a program logic model built around the messages and identified curriculum elements, as they may be best operationalised within the licensing and school contexts in Victoria. This paper summarises a review of common deliberate risk-taking and non-deliberate unsafe driving behaviours among novice drivers, highlighting risks associated with speeding, driving while fatigued, driving while impaired and carrying passengers. Common beliefs of young people that predict risky driving were reviewed, particularly with consideration of those beliefs that can be operationalised in a behaviour change school program. Key components of adolescent risk behaviour change programs were also reviewed, which identified a number of strategies for incorporation in a school based behaviour change program, including: a well-structured theoretical design and delivery, thoughtfully considered peer-selected processes, adequate training and supervision of peer facilitators, a process for monitoring and sustainability, and interactive delivery and participant discussions. The research base is then summarised in a program logic model with further discussion about the quality of the current state of knowledge of evaluation of behaviour change programs and the need for considerable development in program evaluation.