Confucius Institutes and the network communication approach to public diplomacy

Discussions of public diplomacy in recent years have paid a growing amount of attention to networks. This network perspective is understood to provide insights into various issues of public diplomacy, such as its effects, credibility, reputation, identity and narratives. This paper applies the network idea to analyse China’s Confucius Institutes initiative. It understands Confucius Institutes as a global network and argues that this network structure has potential implications for the operation of public and cultural diplomacy that are perhaps underestimated in existing accounts of Chinese cultural diplomacy. In particular, it is noted that the specific setup of Confucius Institutes requires the engagement of local stakeholders, in a way that is less centralised and more networked than comparable cultural diplomacy institutions. At the same time, the development of a more networked for of public cultural diplomacy is challenged in practice by both practical issues and the configuration of China’s state-centric public diplomacy system informed by the political constitution of the Chinese state.

The brain-specific microRNA miR-128b regulates the formation of fear-extinction memory

MicroRNAs are small non-coding RNAs that mediate post-transcriptional gene silencing. Fear-extinction learning in C57/Bl6J mice led to increased expression of the brain-specific microRNA miR-128b, which disrupted stability of several plasticity-related target genes and regulated formation of fear-extinction memory. Increased miR-128b activity may therefore facilitate the transition from retrieval of the original fear memory toward the formation of a new fear-extinction memory.

Exploring the properties of macroscopic fundamental diagram : analysing Brisbane urban network

This thesis explored traffic characteristics at the aggregate level for area-wide traffic monitoring of large urban area. It focused on three aspects: understanding a macroscopic network performance under real-time traffic information provision, measuring traffic performance of a signalised arterial network using available data sets, and discussing network zoning for monitoring purposes in the case of Brisbane, Australia. This work presented the use of probe vehicle data for estimating traffic state variables, and illustrated dynamic features of regional traffic performance of Brisbane. The results confirmed the viability and effectiveness of area-wide traffic monitoring.

Antisocial behaviour orders : Unanticipated directions in social network site development

Abstract: Social network technologies, as we know them today have become a popular feature of everyday life for many people. As their name suggests, their underlying premise is to enable people to connect with each other for a variety of purposes. These purposes however, are generally thought of in a positive fashion. Based on a multi-method study of two online environments, Habbo Hotel and Second Life, which incorporate social networking functionality, we she light on forms of what can be conceptualized as antisocial behaviours and the rationales for these. Such behaviours included: scamming, racist/homophobic attacks, sim attacks, avatar attacks, non-conformance to contextual norms, counterfeiting and unneighbourly behaviour. The rationales for sub behaviours included: profit, fun, status building, network disruption, accidental acts and prejudice. Through our analysis we are able to comment upon the difficulties of defining antisocial behaviour in such environments, particularly when such environments are subject to interpretation vis their use and expected norms. We also point to the problems we face in conducting our public and private lives given the role ICTs are playing in the convergence of these two spaces and also the convergence of ICTs themselves.

Automated diagnosis of Age-related Macular Degeneration using greyscale features from digital fundus images

Age-related Macular Degeneration (AMD) is one of the major causes of vision loss and blindness in ageing population. Currently, there is no cure for AMD, however early detection and subsequent treatment may prevent the severe vision loss or slow the progression of the disease. AMD can be classified into two types: dry and wet AMDs. The people with macular degeneration are mostly affected by dry AMD. Early symptoms of AMD are formation of drusen and yellow pigmentation. These lesions are identified by manual inspection of fundus images by the ophthalmologists. It is a time consuming, tiresome process, and hence an automated diagnosis of AMD screening tool can aid clinicians in their diagnosis significantly. This study proposes an automated dry AMD detection system using various entropies (Shannon, Kapur, Renyi and Yager), Higher Order Spectra (HOS) bispectra features, Fractional Dimension (FD), and Gabor wavelet features extracted from greyscale fundus images. The features are ranked using t-test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance (CBBD), Receiver Operating Characteristics (ROC) curve-based and Wilcoxon ranking methods in order to select optimum features and classified into normal and AMD classes using Naive Bayes (NB), k-Nearest Neighbour (k-NN), Probabilistic Neural Network (PNN), Decision Tree (DT) and Support Vector Machine (SVM) classifiers. The performance of the proposed system is evaluated using private (Kasturba Medical Hospital, Manipal, India), Automated Retinal Image Analysis (ARIA) and STructured Analysis of the Retina (STARE) datasets. The proposed system yielded the highest average classification accuracies of 90.19%, 95.07% and 95% with 42, 54 and 38 optimal ranked features using SVM classifier for private, ARIA and STARE datasets respectively. This automated AMD detection system can be used for mass fundus image screening and aid clinicians by making better use of their expertise on selected images that require further examination.

Pipeline renewal decision support : a case study using LinEAR in a water pipeline network

This paper presents a case study for the application of a Linear Engineering Asset Renewal decision support software tool (LinEAR) at a water distribution network in Australia. This case study examines how the LinEAR can assist water utilities to minimise their total pipeline management cost, to make a long-term budget based on mathematically predicted expenditure, and to present calculated evidence for supporting their expenditure requirements. The outcomes from the study on pipeline renewal decision support demonstrate that LinEAR can help water utilities to improve the decision process and save renewal costs over a long-term by providing an optimum renewal schedules. This software can help organisation to accumulate technical knowledge and prediction future impact of the decision using what-if analysis.

Demand Response for Residential Appliances in a Smart Electricity Distribution Network: Utility and Customer Perspectives

This thesis introduces advanced Demand Response algorithms for residential appliances to provide benefits for both utility and customers. The algorithms are engaged in scheduling appliances appropriately in a critical peak day to alleviate network peak, adverse voltage conditions and wholesale price spikes also reducing the cost of residential energy consumption. Initially, a demand response technique via customer reward is proposed, where the utility controls appliances to achieve network improvement. Then, an improved real-time pricing scheme is introduced and customers are supported by energy management schedulers to actively participate in it. Finally, the demand response algorithm is improved to provide frequency regulation services.

Muramidases found in the foregut microbiome of the Tammar wallaby can direct cell aggregation and biofilm formation

We describe here the role of muramidases present in clones of metagenomic DNA that result in cell aggregation and biofilm formation by Escherichia coli. The metagenomic clones were obtained from uncultured Lachnospiraceae-affiliated bacteria resident in the foregut microbiome of the Tammar wallaby. One of these fosmid clones (p49C2) was chosen for more detailed studies and a variety of genetic methods were used to delimit the region responsible for the phenotype to an open reading frame of 1425 bp. Comparative sequence analysis with other fosmid clones giving rise to the same phenotype revealed the presence of muramidase homologues with the same modular composition. Phylogenetic analysis of the fosmid sequence data assigned these fosmid inserts to recently identified, but uncultured, phylogroups of Lachnospiraceae believed to be numerically dominant in the foregut microbiome of the Tammar wallaby. The muramidase is a modular protein containing putative N-acetylmuramoyl--alanine amidase and an endo-β-N-acetylglucosaminidase catalytic module, with a similar organization and functional properties to some Staphylococcal autolysins that also confer adhesive properties and biofilm formation. We also show here that the cloned muramidases result in the production of extracellular DNA, which appears to be the key for biofilm formation and autoaggregation. Collectively, these findings suggest that biofilm formation and cell aggregation in gut microbiomes might occur via the concerted action of carbohydrate-active enzymes and the production of extracellular DNA to serve as a biofilm scaffold.

UpaH Is a newly identified autotransporter protein That contributes to biofilm formation and bladder colonization by Uropathogenic Escherichia coli CFT073

Escherichia coli is the primary cause of urinary tract infection (UTI) in the developed world. The major factors associated with virulence of uropathogenic E. coli (UPEC) are fimbrial adhesins, which mediate specific attachment to host receptors and trigger innate host responses. Another group of adhesins is represented by the autotransporter (AT) subgroup of proteins. In this study, we identified a new AT-encoding gene, termed upaH, present in a 6.5-kb unannotated intergenic region in the genome of the prototypic UPEC strain CFT073. Cloning and sequencing of the upaH gene from CFT073 revealed an intact 8.535-kb coding region, contrary to the published genome sequence. The upaH gene was widely distributed among a large collection of UPEC isolates as well as the E. coli Reference (ECOR) strain collection. Bioinformatic analyses suggest β-helix as the predominant structure in the large N-terminal passenger (α) domain and a 12-strand β-barrel for the C-terminal β-domain of UpaH. We demonstrated that UpaH is expressed at the cell surface of CFT073 and promotes biofilm formation. In the mouse UTI model, deletion of the upaH gene in CFT073 and in two other UPEC strains did not significantly affect colonization of the bladder in single-challenge experiments. However, in competitive colonization experiments, CFT073 significantly outcompeted its upaH isogenic mutant strain in urine and the bladder.

Disturbed microtubule function and induction of micronuclei by chelate complexes of mercury(II)

Interactions of mercury(II) with the microtubule network of cells may lead to genotoxicity. Complexation of mercury(II) with EDTA is currently being discussed for its employment in detoxification processes of polluted sites. This prompted us to re-evaluate the effects of such complexing agents on certain aspects of mercury toxicity, by examining the influences of mercury(II) complexes on tubulin assembly and kinesin-driven motility of microtubules. The genotoxic effects were studied using the micronucleus assay in V79 Chinese hamster fibroblasts. Mercury(II) complexes with EDTA and related chelators interfered dose-dependently with tubulin assembly and microtubule motility in vitro. The no-effect-concentration for assembly inhibition was 1 μM of complexed Hg(II), and for inhibition of motility it was 0.05 μM, respectively. These findings are supported on the genotoxicity level by the results of the micronucleus assay, with micronuclei being induced dose-dependently starting at concentrations of about 0.05 μM of complexed Hg(II). Generally, the no-effect-concentrations for complexed mercury(II) found in the cell-free systems and in cellular assays (including the micronucleus test) were identical with or similar to results for mercury tested in the absence of chelators. This indicates that mercury(II) has a much higher affinity to sulfhydryls of cytoskeletal proteins than to this type of complexing agents. Therefore, the suitability of EDTA and related compounds for remediation of environmental mercury contamination or for other detoxification purposes involving mercury has to be questioned.

Determination of glutathione transferase (GSTT1-1) activities in different tissues based on formation of radioactive metabolites using 35S-glutathione

A new system has been developed to determine enzyme activities of glutathione transferase θ (GSTT1-1) based on radiometric product detection resulting from the enzymic reaction of methyl chloride with 35S-labelled glutathione. In principle, the method is universally applicable for determination of glutathione transferase activities towards a multiplicity of substrates. The method distinguishes between erythrocyte GSTT1-1 activities of human 'non-conjugators', 'low conjugators' and 'high conjugators'. Application to cytosol preparations of livers and kidneys of male and female Fischer 344 and B6C3F1 mice reveals differential GSTT1-1 activities in hepatic and renal tissues. These ought to be considered in species-specific modellings of organ toxicities of chlorinated hydrocarbons.

A convolutional neural network for automatic analysis of aerial imagery

This paper introduces a new method to automate the detection of marine species in aerial imagery using a Machine Learning approach. Our proposed system has at its core, a convolutional neural network. We compare this trainable classifier to a handcrafted classifier based on color features, entropy and shape analysis. Experiments demonstrate that the convolutional neural network outperforms the handcrafted solution. We also introduce a negative training example-selection method for situations where the original training set consists of a collection of labeled images in which the objects of interest (positive examples) have been marked by a bounding box. We show that picking random rectangles from the background is not necessarily the best way to generate useful negative examples with respect to learning.