Ionic conductivity and molecular dynamic behavior in supramolecular ionic networks; the effect of lithium salt addition

Supramolecular ionic networks combine singular properties such as self-healing behaviour and ionic conductivity. In this work we present an insight into the ionic conductivity and molecular dynamic behaviour of an amorphous and semicrystalline supramolecular ionic networks (iNets) that were synthesised by self-assembly of difunctional imidazolium dicationic molecules coupled with (trifluoromethane-sulfonyl) imide dianionic molecules. Relatively low ionic conductivity values were obtained for the semicrystalline iNet below its melting point (Tm =101°C) in comparison with the amorphous iNet for which the conductivity significantly increased (~3 orders of magnitude) above 100°C. Upon LiTFSI doping, the semicrystalline iNet reached conductivity values ~ 10-3 Scm-1 due to enhanced mobility of the network which was supported by solid-state static NMR. Furthermore, the overlapping of 19F and 7Li resonance lines from both the semicrystalline network and the LiTFSI suggests fast molecular motions.

Artificial neural network modeling of flow stress in hot rolling

In this study, an artificial neural network model is proposed to predict the flow stress variations during the hot rolling process. Optimization of the proposed neural network with respect to number of neurons within the hidden layer, different training methods and transfer functions of the neural network is performed. The results of the optimal network were compared with those of the conventional analytic method and it is shown that using an optimal neural network the mean calculated error is drastically reduced.

Application of neural network to rock slope stability assessments

It is known that rock masses are inhomogeneous, discontinuous media composed of rock material and naturally occurring discontinuities such as joints, fractures and bedding planes. These features make any analysis very difficult using simple theoretical solutions. Generally speaking, back analysis technique can be used to capture some implicit parameters for geotechnical problems. In order to perform back analyses, the procedure of trial and error is generally required. However, it would be time-consuming. This study aims at applying a neural network to do the back analysis for rock slope failures. The neural network tool will be trained by using the solutions of finite element upper and lower bound limit analysis methods. Therefore, the uncertain parameter can be obtained, particularly for rock mass disturbance.

To shut them up or to clarify: restraining the spread of rumors in online social networks

Restraining the spread of rumors in online social networks (OSNs) has long been an important but difficult problem to be addressed. Currently, there are mainly two types of methods 1) blocking rumors at the most influential users or community bridges, or 2) spreading truths to clarify the rumors. Each method claims the better performance among all the others according to their own considerations and environments. However, there must be one standing out of the rest. In this paper, we focus on this part of work. The difficulty is that there does not exist a universal standard to evaluate them. In order to address this problem, we carry out a series of empirical and theoretical analysis on the basis of the introduced mathematical model. Based on this mathematical platform, each method will be evaluated by using real OSN data.We have done three types of analysis in this work. First, we compare all the measures of locating important users. The results suggest that the degree and betweenness measures outperform all the others in the Facebook network. Second, we analyze the method of the truth clarification method, and find that this method has a long-term performance while the degree measure performs well only in the early stage. Third, in order to leverage these two methods, we further explore the strategy of different methods working together and their equivalence. Given a fixed budget in the real world, our analysis provides a potential solution to find out a better strategy by integrating both types of methods together. From both the academic and technical perspective, the work in this paper is an important step towards the most practical and optimal strategies of restraining rumors in OSNs.

The microstructure and physicochemical properties of probiotic buffalo yoghurt during fermentation and storage: a comparison with bovine yoghurt

The physicochemical and rheological properties of yoghurt made from unstandardised unhomogenised buffalo milk were investigated during fermentation and 28 days of storage and compared to the properties of yoghurt made from homogenised fortified bovine milk. A number of differences observed in the gel network can be linked to differences in milk composition. The microstructure of buffalo yoghurt, as assessed by confocal laser scanning microscopy (CLSM) and cryo scanning electron microscopy (cryo-SEM), was interrupted by large fat globules and featured more serum pores. These fat globules have a lower surface area and bind less protein than the homogenised fat globules in bovine milk. These microstructural differences likely lead to the higher syneresis observed for buffalo yoghurt with an increase from 17.4 % (w/w) to 19.7 % (w/w) in the weight of whey generated at days 1 and 28 of the storage. The higher concentration of total calcium in buffalo milk resulted in the release of more ionic calcium during fermentation. Gelation was also slower but the strength of the two gels was similar due to similar protein and total solids concentrations. Buffalo yoghurt was more viscous, less able to recover from deformation and less Newtonian than bovine yoghurt with a thixotropy of 3,035 Pa.s-1 measured for buffalo yoghurt at the end of the storage, at least four times higher than the thixotropy of bovine yoghurt. While the titratable acidity, lactose consumption and changes in organic acid concentrations were similar, differences were recorded in the viability of probiotic bacteria with a lower viability of Lactobacillus acidophilus of 5.17 log (CFU/g) recorded for buffalo yoghurt at day 28 of the storage. Our results show that factors other than the total solids content and protein concentration of milk affect the structural properties of yoghurt. They also illustrate the physicochemical reasons why buffalo and bovine yoghurt are reported to have different sensory properties and provide insight into how compositional changes can be used to alter the microstructure and properties of dairy products. © 2013 Springer Science+Business Media New York.

A multi-objective ant colony optimization algorithm based on the physarum-inspired mathematical model

Multi-objective traveling salesman problem (MOTSP) is an important field in operations research, which has wide applications in the real world. Multi-objective ant colony optimization (MOACO) as one of the most effective algorithms has gained popularity for solving a MOTSP. However, there exists the problem of premature convergence in most of MOACO algorithms. With this observation in mind, an improved multiobjective network ant colony optimization, denoted as PMMONACO, is proposed, which employs the unique feature of critical tubes reserved in the network evolution process of the Physarum-inspired mathematical model (PMM). By considering both pheromones deposited by ants and flowing in the Physarum network, PM-MONACO uses an optimized pheromone matrix updating strategy. Experimental results in benchmark networks show that PM-MONACO can achieve a better compromise solution than the original MOACO algorithm for solving MOTSPs.

Reflections on doing inclusive research in the 'making life good in the community' study

BACKGROUND: The involvement of people with intellectual disability in research is framed as inclusive, denoting their active participation in its processes. However, questions are raised about ownership and control, genuineness of involvement, and the need for honest accounts to develop practice. Such issues are particularly pressing in Australia, where there is the absence of a strong self-advocacy movement to partner with academics or hold them to account. METHOD: Action research was used to reflect on and progressively refine the support provided by a research mentor to a co-researcher with intellectual disability employed on a large multimethod study. RESULTS AND CONCLUSIONS: Accepting the co-researcher's strengths and designing support on the job rather than teaching them to "pass" before venturing out in the field are important in ceding control. Support required for a co-researcher is more than practical and involves developing a relationship that can actively challenge views and foster reflection. Ownership of questions and disseminating of outcomes are hampered by contextual factors such as tender processes, short-term positions, and a failure to acknowledge the support required to present findings.

Investigating the efficacy of an intelligent operation planning and support tool for acute healthcare contexts

Nurses are the largest group of healthcare professionals in hospitals providing 24-hour care to patients. Hence, nurses are pivotal in coordinating and communicating patient care information in the complex network of healthcare professionals, services and other care processes. Yet, despite nurses' central role in health care delivery, intelligent systems have historically rarely been designed around nurses' operational needs. This could explain the poor integration of technologies into nursing work processes and consequent rejection by nursing professionals. The complex nature of acute care delivery in hospitals and the frequently interrupted patterns of nursing work suggest that nurses require flexible intelligent systems that can support and adapt to their variable workflow patterns. This study is designed to explore nurses' initial reactions to a new intelligent operational planning and support tool (IOPST) for acute healthcare. The following reports on the first stage of a longitudinal project to use an innovative approach involving nurses in the development of the IOPST; from conceptualization to implementation.

RFID translation into Australian hospitals: an exploration through Actor-Network Theoretical(ANT) Lens

Radio Frequency Identification (RFID) is a technology that has been deployed successfully for asset tracking within hospitals aimed at improving the quality of processes. In the Australian hospitals context however, adoption of this technology seem sporadic. This research reports on a long-term investigation to gain a deeper understanding of the socio-technical factors involved in the adoption of RFID in Australian hospitals. The research was conducted using interpretive multiple case methodology and results analyzed through the Actor-Network Theoretical (ANT) Lens. © 2013 Infonomics Society.

Distinct kinetics of molecular gelation in a confined space and its relation to the structure and property of thin gel films

Thin films of molecular gels formed in a confined space have potential applications in transdermal delivery, artificial skin, molecular electronics, etc. The microstructures and properties of thin gel films can be significantly different from those of their bulk counterparts. However, so far a comprehensive understanding of the effects of spatial confinement on the molecular gelation kinetics, fiber network structure and related mechanical properties is still lacking. In this work, using rheological techniques, we investigated the effect of one-dimensional confinement on the formation kinetics of fiber networks in the molecular gelation process. Fractal analyses of the kinetic information in terms of an extended Dickinson model enabled us to describe quantitatively the distinct kinetic signature of molecular gelation. The structural features derived from gelation kinetics support well the fractal patterns of the fiber networks acquired by optical and electron microscopy. With the kinetics-structure correlation, we can gain an in-depth understanding of the confinement-induced differences in the structure and consequently the mechanical properties of a model molecular gelling system. Particularly, the confinement induced structural transition, from a three-dimensional, dense and compact spherulitic network composed of highly branched fibers to a quasi-two-dimensional sparse spherulitic network composed of less branched fibers and entangled fibrils at the boundary areas, renders a gel film to become less stiff but more ductile. Our study suggests here a new strategy of engineering the fiber network microstructure to achieve functional gel films with unusual but useful properties.

Global biodiversity indicators reflect the modeled impacts of protected area policy change

Global biodiversity indicators can be used to measure the status and trends of biodiversity relating to Convention on Biological Diversity (CBD) targets. Whether such indicators can support decision makers by distinguishing among policy options remains poorly evaluated. We tested the ability of two CBD indicators, the Living Planet Index and the Red List Index, to reflect projected changes in mammalian populations in sub-Saharan Africa in response to potential policies related to CBD targets for protected areas (PAs). We compared policy scenarios to expand the PA network, improve management effectiveness of the existing network, and combinations of the two, against business as usual. Both indicators showed that more effective management would provide greater benefits to biodiversity than expanding PAs alone. The indicators were able to communicate outcomes of modeled scenarios in a simple quantitative manner, but behaved differently. This work highlights both the considerable potential of indicators in supporting decisions, and the need to understand how indicators will respond as biodiversity changes.

K-Center: an approach on the multi-source identification of information diffusion

The global diffusion of epidemics, computer viruses, and rumors causes great damage to our society. It is critical to identify the diffusion sources and timely quarantine them. However, most methods proposed so far are unsuitable for diffusion with multiple sources because of the high computational cost and the complex spatiotemporal diffusion processes. In this paper, based on the knowledge of infected nodes and their connections, we propose a novel method to identify multiple diffusion sources, which can address three main issues in this area: 1) how many sources are there? 2) where did the diffusion emerge? and 3) when did the diffusion break out? We first derive an optimization formulation for multi-source identification problem. This is based on altering the original network into a new network concerning two key elements: 1) propagation probability and 2) the number of hops between nodes. Experiments demonstrate that the altered network can accurately reflect the complex diffusion processes with multiple sources. Second, we derive a fast method to optimize the formulation. It has been proved that the proposed method is convergent and the computational complexity is O(mn log α) , where α = α (m,n) is the slowly growing inverse-Ackermann function, n is the number of infected nodes, and m is the number of edges connecting them. Finally, we introduce an efficient algorithm to estimate the spreading time and the number of diffusion sources. To evaluate the proposed method, we compare the proposed method with many competing methods in various real-world network topologies. Our method shows significant advantages in the estimation of multiple sources and the prediction of spreading time.

Real-Time Control Of Floods Along The Demer River, Belgium, By Means Of MPC In Combination With GA And A Fast Conceptual River Model

Climate model projections show that climate change will further increase the risk of flooding in many regions of the world. There is a need for climate adaptation, but building new infrastructure or additional retention basins has its limits, especially in densely populated areas where open spaces are limited. Another solution is the more efficient use of the existing infrastructure. This research investigates a method for real-time flood control by means of existing gated weirs and retention basins. The method was tested for the specific study area of the Demer basin in Belgium but is generally applicable. Today, retention basins along the Demer River are controlled by means of adjustable gated weirs based on fixed logic rules. However, because of the high complexity of the system, only suboptimal results are achieved by these rules. By making use of precipitation forecasts and combined hydrological-hydraulic river models, the state of the river network can be predicted. To fasten the calculation speed, a conceptual river model was used. The conceptual model was combined with a Model Predictive Control (MPC) algorithm and a Genetic Algorithm (GA). The MPC algorithm predicts the state of the river network depending on the positions of the adjustable weirs in the basin. The GA generates these positions in a semi-random way. Cost functions, based on water levels, were introduced to evaluate the efficiency of each generation, based on flood damage minimization. In the final phase of this research the influence of the most important MPC and GA parameters was investigated by means of a sensitivity study. The results show that the MPC-GA algorithm manages to reduce the total flood volume during the historical event of September 1998 by 46% in comparison with the current regulation. Based on the MPC-GA results, some recommendations could be formulated to improve the logic rules.

Income inequality in a job-search model with heterogeneous time preferences

This paper explores the use of an intertemporal job-search model in the investigation of within-cohort and between-cohort income inequality, the latter being generated by the heterogeneity of time preferences among cohorts of homogenous workers and the former by the cross-sectional turnover in the job market. It also offers an alternative explanation for the empirically-documented negative correlation between time preference and labor income. Under some speciÖc distributions regarding wage offers and time preferences, we show how the within-cohort and between-cohort Gini coe¢ cients of income distribution can be calculated, and how they vary as a function of the parameters of the model.