Incorporation of fused tetrathiafulvalenes (TTFs) into polythiophene architectures : varying the electroactive dominance of the TTF species in hybrid systems

A novel polythienylenevinylene (PTV) and two new polythiophenes (PTs), featuring fused tetrathiafulvalene (TTF) units, have been prepared and characterized by ultraviolet−visible (UV−vis) and electron paramagnetic resonance (EPR) spectroelectrochemistry. All polymers undergo two sequential, reversible oxidation processes in solution. Structures in which the TTF species is directly linked to the polymer backbone (2 and 4) display redox behavior which is dictated by the fulvalene system. Once the TTF is spatially removed from the polymer chain by a nonconjugated link (polymer 3), the electroactivity of both TTF and polythiophene moieties can be detected. Computational studies confirm the delocalization of charge over both electroactive centers (TTF and PT) and the existence of a triplet dication intermediate. PTV 4 has a low band gap (1.44 eV), is soluble in common organic solvents, and is stable under ambient conditions. Organic solar cells of polymer 4:[6,6]-phenyl-C₆₁ butyric acid methyl ester (PCBM) have been fabricated. Under illumination, a photovoltaic effect is observed with a power conversion efficiency of 0.13% under AM1.5 solar simulated light. The onset of photocurrent at 850 nm is consistent with the onset of the π−π absorption band of the polymer. Remarkably, UV−vis spectroelectrochemistry of polymer 4 reveals that the conjugated polymer chain remains unchanged during the oxidation of the polymer.

A marginalised Markov Chain Monte Carlo approach for model based analysis of EEG data

The work presented in this paper focuses on fitting of a neural mass model to EEG data. Neurophysiology inspired mathematical models were developed for simulating brain's electrical activity imaged through Electroencephalography (EEG) more than three decades ago. At the present well informative models which even describe the functional integration of cortical regions also exists. However, a very limited amount of work is reported in literature on the subject of model fitting to actual EEG data. Here, we present a Bayesian approach for parameter estimation of the EEG model via a marginalized Markov Chain Monte Carlo (MCMC) approach.

Come play with me : an argument to link autism spectrum disorders and anorexia nervosa through early childhood pretend play

This article builds on the argument of a link between behaviours observed in persons with autism spectrum disorders and persons with anorexia nervosa. In describing these behaviours, a link is made between deficits in social cognition, lack of flexible and creative thinking, theory of mind, and deficits in early pretend play ability. Early pretend play ability is a strong avenue to the development and strengthening of social cognition, problem solving, language, logical sequential thought, and understanding social situations. Currently, there is no literature on the pretend play ability of persons who develop anorexia nervosa. This article argues for research into this area which may potentially contribute to developments in new intervention strategies for these persons.

Trust evaluation for indirectly connected nodes using link community information

Inspired by recent empirical research on link communities, we borrow some important ideas and concepts for our own research to provide a more reasonable computation model of transitive trust. The key advantages of using link community methodology is to reflect on the nature of the social network features of Hierarchy and Overlap. Our research mainly resolves the computation of trust transitivity in which two nodes do not have any direct links to any link community. In this research, we discover a new direction analyzing trust transitivity. By using a social network game, we found that the link community methodology is a natural way to analyze trust in social networks. We also discovered, even in a small social network, trust has certain community features.

Corporate entrepreneurship and innovation part 1 : the missing link

Purpose – To examine the literature on corporate entrepreneurship and innovation and to develop a combined definition of these two terms. Moreover, the literature is used to construct a holistic model that seeks to explain the links between corporate entrepreneurial activity and the innovation process. Design/methodology/approach – A number of published works on entrepreneurship and innovation are critiqued. The findings from this literature review are used to develop a framework illustrating the relationships between the corporate entrepreneur and the innovation process. Findings – The paper presents a combined definition of corporate entrepreneurship and innovation and, from the literature review, concludes that previous models on entrepreneurship and innovation are fragmented because there is little exploration on the relationships and dynamics between these two factors. A framework of corporate entrepreneurship and innovation is constructed by synthesising the information gathered from previous literature. This model shows that there are missing links between the entrepreneur and the innovation process. The paper discusses three factors that may explain both the dynamics and the relationships between the entrepreneur and the innovation process. These are entrepreneurial attitudes, vision and actions. Originality/value – This paper fulfils an identified gap in the literature, namely the lack of investigation into the links between the corporate entrepreneur and the innovation process, and suggests three factors that could be used to explain this gap. Part 2 of this paper will present a new holistic model of corporate entrepreneurship and innovation that illustrates the relationships between these two areas in more detail.

Family support and ease of access link socio-economic status and sports club membership in adolescent girls : a mediation study

Background Much research has been conducted into the determinants of physical activity (PA) participation among adolescent girls. However, the more specific question of what are the determinants of particular forms of PA participation, such as the link between participation through a sports club, has not been investigated. Accordingly, the aim of this study was to investigate the relationships between participation in a sports club and socio-economic status (SES), access to facilities, and family and peer support, for female adolescents.

Methods A survey of 732 female adolescent school students (521 metropolitan, 211 non-metropolitan; 489 Year 7, 243 Year 11) was conducted. The survey included demographic information (living arrangements, ethnicity indicators, and indicators of SES such as parental education and employment status and locality); access to facilities; and family and peer support (travel, encouragement, watching, praise, joint participation). For each characteristic, sports club participants and non-participants were compared using chi-square tests. Multiple mediation analyses were used to investigate the role of access, family and peer support in the link between SES and sport participation.

Results There were significant associations (p<0.05) between sports club participation and: all demographic characteristics; all measures of family and peer support; and access to sport-related facilities. Highest levels of participation were associated with monolingual Australian-born families, with two parents, at least one of whom was well-educated, with both parents employed, and high levels of parental assistance, engagement and support. Participation in club sport among both younger and older adolescent girls was significantly positively associated with the SES of both their neighbourhoods and their households, particularly in metropolitan areas. These associations were most strongly mediated by family support and by access to facilities.

Conclusions To facilitate and promote greater participation in club sport among adolescent girls from low SES neighbourhoods and households, strategies should target modifiable determinants such as facility access and parental support. This will involve improving access to sports facilities and promoting, encouraging and assisting parents to provide support for their daughters’ participation in sport clubs.

Uplink power control via adaptive Hidden-Markov-Model-Based pathloss estimation

Dynamic variations in channel behavior is considered in transmission power control design for cellular radio systems. It is well known that power control increases system capacity, improves Quality of Service (QoS), and reduces multiuser interference. In this paper, an adaptive power control design based on the identification of the underlying pathloss dynamics of the fading channel is presented. Formulating power control decisions based on the measured received power levels allows modeling the fading channel pathloss dynamics in terms of a Hidden Markov Model (HMM). Applying the online HMM identification algorithm enables accurate estimation of the real pathloss ensuring efficient performance of the suggested power control scheme.

Inferring activity budgets in wild animals to estimate the consequences of disturbances

Activity budgets can provide a direct link to an animal's bioenergetic budget and is thus a valuable unit of measure when assessing human-induced nonlethal effects on wildlife conservation status. However, activity budget inference can be challenging for species that are difficult to observe and require multiple observational variables. Here, we assessed whether whalewatching boat interactions could affect the activity budgets of minke whales (Balaenoptera acutorostrata). We used a stepwise modeling approach to quantitatively record, identify, and assign activity states to continuous behavioral time series data, to estimate activity budgets. First, we used multiple behavioral variables, recorded from continuous visual observations of individual animals, to quantitatively identify and define behavioral types. Activity states were then assigned to each sampling unit, using a combination of hidden and observed states. Three activity states were identified: nonfeeding, foraging, and surface feeding (SF). From the resulting time series of activity states, transition probability matrices were estimated using first-order Markov chains. We then simulated time series of activity states, using Monte Carlo methods based on the transition probability matrices, to obtain activity budgets, accounting for heterogeneity in state duration. Whalewatching interactions reduced the time whales spend foraging and SF, potentially resulting in an overall decrease in energy intake of 42%. This modeling approach thus provides a means to link short-term behavioral changes resulting from human disturbance to potential long-term bioenergetic consequences in animals. It also provides an analytical framework applicable to other species when direct observations of activity states are not possible.