Investigating the effect of solution pH on speciation of La(4OH-cin)3 with correlation to electrochemical behaviour and corrosion efficiency

The nature of the species in solution plays a major role on the effectiveness of the corrosion inhibitor on a steel substrate. The speciation of lanthanum 4-hydroxy cinnamate (La(4OHCin) ₃) in solution has been evaluated using experimental techniques composed of potentiodynamic polarisation, immersion tests, nuclear magnetic spectroscopy and mass spectroscopy. It is evident that the species in solution are dependent on pH and this impacts the corrosion inhibition mechanism and the efficiency. It was found that at a neutral pH of 5.5 the La(4OH-Cin)₃ behaves as a strong anodic inhibitor. Whereas, when the pH shifts to low (pH2.5) and/or high (pH8) the corrosion mechanism changes.

Histological health indices : linking complex pollutant exposure with tissue alteration in sand flathead Platycephalus bassensis

Port Phillip Bay, Victoria, is a pollutant-impacted environment that is extensively fished both professionally and recreationally. Consumption of contaminated fish represents a potential threat to human health, and fish exposed to environmental contaminants may themselves be affected in a similar fashion. This study describes a fish health index based on histological alterations identified in multiple organs of the sand flathead Platycephalus bassensis. Alterations were evident in tissues from all individuals assessed, with common pathologies observed in the gills, skin, kidney, liver and spleen. Alterations commonly present included necrosis, melanomacrophage centres, inflammation and multiple alterations of the gill epithelium (e.g. hyperplasia and hypertrophy). Fish health, calculated using severity of histological alterations, differed significantly across Port Phillip Bay, with heavily industrialized regions of Altona and St. Helens showing greatest alteration prevalence across multiple organs. This study indicates that the health of P.bassensis from Altona, St. Helens, and Mornington to a lesser extent, are currently compromised, potentially due to complex pollutant exposures which require further investigation

Two-dimensional correlation localized surface plasmon resonance spectroscopy for analysis of the interaction between metal nanoparticles and bovine serum albumin

Time-resolved extinction spectra assisted with two-dimensional correlation spectroscopy (2DCOS) analysis and principal component analysis (PCA) were employed to investigate the interaction between bovine serum albumin (BSA) and metal nanoparticles (NPs). A series of localized surface plasmon resonance (LSPR) spectra of metal NPs were measured just after a small amount of BSA was added into metal colloids. Through 2DCOS analysis, remarkable changes in the intensities of the LSPR were observed. The interaction process was totally divided into three periods according to the PCA. Transmission electron microscopy, dynamic light scattering, and ζ-potential measurements were also employed to characterize the interaction between BSA and metal NPs. The addition of BSA brings silver NPs to aggregate through the electrostatic interaction between them, but it has less effect on gold NPs. In a gold and silver mixed system, gold NPs can affect the interaction of silver NPs and BSA, leading it to weaken. The combination of 2DCOS analysis and LSPR spectroscopy is powerful for exploring the LSPR spectra of the metal NP involved systems. This combined technique holds great potential in LSPR sensing through analysis of slight, slim spectral changes of metal colloids

Application of rank correlation, clustering and classification in information security

This article is devoted to experimental investigation of a novel application of a clustering technique introduced by the authors recently in order to use robust and stable consensus functions in information security, where it is often necessary to process large data sets and monitor outcomes in real time, as it is required, for example, for intrusion detection. Here we concentrate on a particular case of application to profiling of phishing websites. First, we apply several independent clustering algorithms to a randomized sample of data to obtain independent initial clusterings. Silhouette index is used to determine the number of clusters. Second, rank correlation is used to select a subset of features for dimensionality reduction. We investigate the effectiveness of the Pearson Linear Correlation Coefficient, the Spearman Rank Correlation Coefficient and the Goodman--Kruskal Correlation Coefficient in this application. Third, we use a consensus function to combine independent initial clusterings into one consensus clustering. Fourth, we train fast supervised classification algorithms on the resulting consensus clustering in order to enable them to process the whole large data set as well as new data. The precision and recall of classifiers at the final stage of this scheme are critical for the effectiveness of the whole procedure. We investigated various combinations of several correlation coefficients, consensus functions, and a variety of supervised classification algorithms.

Discriminating DDoS attacks from flash crowds using flow correlation coefficient

Distributed Denial of Service (DDoS) attack is a critical threat to the Internet, and botnets are usually the engines behind them. Sophisticated botmasters attempt to disable detectors by mimicking the traffic patterns of flash crowds. This poses a critical challenge to those who defend against DDoS attacks. In our deep study of the size and organization of current botnets, we found that the current attack flows are usually more similar to each other compared to the flows of flash crowds. Based on this, we proposed a discrimination algorithm using the flow correlation coefficient as a similarity metric among suspicious flows. We formulated the problem, and presented theoretical proofs for the feasibility of the proposed discrimination method in theory. Our extensive experiments confirmed the theoretical analysis and demonstrated the effectiveness of the proposed method in practice.

Event extraction using behaviors of sentiment signals and burst structure in social media

Significant world events often cause the behavioral convergence of the expression of shared sentiment. This paper examines the use of the blogosphere as a framework to study user psychological behaviors, using their sentiment responses as a form of ‘sensor’ to infer real-world events of importance automatically. We formulate a novel temporal sentiment index function using quantitative measure of the valence value of bearing words in blog posts in which the set of affective bearing words is inspired from psychological research in emotion structure. The annual local minimum and maximum of the proposed sentiment signal function are utilized to extract significant events of the year and corresponding blog posts are further analyzed using topic modeling tools to understand their content. The paper then examines the correlation of topics discovered in relation to world news events reported by the mainstream news service provider, Cable News Network, and by using the Google search engine. Next, aiming at understanding sentiment at a finer granularity over time, we propose a stochastic burst detection model, extended from the work of Kleinberg, to work incrementally with stream data. The proposed model is then used to extract sentimental bursts occurring within a specific mood label (for example, a burst of observing ‘shocked’). The blog posts at those time indices are analyzed to extract topics, and these are compared to real-world news events. Our comprehensive set of experiments conducted on a large-scale set of 12 million posts from Livejournal shows that the proposed sentiment index function coincides well with significant world events while bursts in sentiment allow us to locate finer-grain external world events.

Document clustering in correlation similarity measure space

This paper presents a new spectral clustering method called correlation preserving indexing (CPI), which is performed in the correlation similarity measure space. In this framework, the documents are projected into a low-dimensional semantic space in which the correlations between the documents in the local patches are maximized while the correlations between the documents outside these patches are minimized simultaneously. Since the intrinsic geometrical structure of the document space is often embedded in the similarities between the documents, correlation as a similarity measure is more suitable for detecting the intrinsic geometrical structure of the document space than euclidean distance. Consequently, the proposed CPI method can effectively discover the intrinsic structures embedded in high-dimensional document space. The effectiveness of the new method is demonstrated by extensive experiments conducted on various data sets and by comparison with existing document clustering methods.

lnvestigating spatial linkages of construction prices in Australia's regions

Linkages among different construction markets have attracted great of attention from the construction economist. With notable exceptions, most of this infestation has carried out by using input-output analysis. Interactions among regional construction markets have been discussed in few studies and none of them investigate spatial effects on the regional construction markets. This study employed spatial econometric techniques, spatial autocorrelation and convergence tests, to analysis interactions and linkages among construction price indices in Australian six states and two territories. The empirical results indicate the presence of significant positive spatial correlation between the construction prices in Australian eight construction markets and the degree of dependence decrease sufficiently quickly as the space between units increase. The results of convergence test further present evidence on "ripple effect" in the construction prices in Australian regional markets and the changes in regional construction price would positively influence neighboring states first, and then spread out into others, and then the regional prices converge and reach a long-run equilibrium in the following quarters. Urban development policymakers and construction developers could benefit from the analysis of spatial linkages in regional construction markets.

Implications of Kungurian (Early Permian) conodonts from Hatahoko, Japan, for correlation between the Tethyan and international timescales

The correlation between the fusulinid-based Tethyan and the conodont-based international timescales of the Permian System has become one of themost disputed issues among the Permian community during the past two decades. In this paper,we document a conodont fauna consisting of four species including Sweetognathus guizhouensis, Pseudohindeodus augustus, Hindeodus permicus and a new genus Meiognathus pustulus from the lower part of a large exotic limestone block at Hatahoko in the Nyukawa area, Gifu Prefecture, central Japan, which all suggest aKungurian age. The Kungurian age indicated by the conodonts is consistent with the age of the associated brachiopods, but conflicts with the Murgabian age indicated by the associated fusulinids including Cancellina nipponica, Neoschwagerina simplex, Neofusulinella praecursor etc. This co-occurrence of Kungurian conodonts and Murgabian fusulinids in central Japan suggests that previously unrecognized temporal distributions of some key fusulinid or conodont elements need to be clarified and that the intensively-disputed correlation problem between theKungurian containing theMurgabian fusulinids at the Luodian section in Guizhou, South China with the strata containing the ammonoid Waagenoceras in Oman and Sicily was caused by artificial conodont taxonomic discrepancies. The Luodian section in South China could serve as a key reference section for the correlation of the Kungurian Stage (late Early Permian) between the Tethyan and international timescales.