Montane lakes (lagoons) of the New England Tablelands Bioregion

The vegetation of montane lagoons of the New England Tablelands Bioregion, New South Wales is examined using flexible UPGMA analysis of frequency scores on all vascular plant taxa, charophytes and one liverworts. Seven communities are described: 1. Hydrocotyle tripartita – Isotoma fluviatilis – Ranunculus inundatus – Lilaeopsis polyantha herbfield; 2. Eleocharis sphacelata – Potamogeton tricarinatus sedgeland; 3. Eleocharis sphacelata – Utricularia australis – Isolepis fluitans, herbfield; 4. Utricularia australis – Nitella sonderi herbfield; 5. Eleocharis sphacelata – Utricularia australis – Ricciocarpus natans sedgeland; 6. Carex gaudichaudiana – Holcus lanatus – Stellaria angustifolia sedgeland; 7. Cyperus sphaeroides – Eleocharis gracilis – Schoenus apogon – Carex gaudichaudiana sedgeland. 58 lagoons were located and identified, only 28% of which are considered to be intact and in good condition. Two threatened species (Aldovandra vesiculosa and Arthaxon hispidus) and three RoTAP-listed taxa were encountered during the survey

Financial signal processing: a self calibrating model

Previous work on multifactor term structure models has proposed that the short rate process is a function of some unobserved diffusion process. We consider a model in which the short rate process is a function of a Markov chain which represents the 'state of the world'. This enables us to obtain explicit expressions for the prices of zero-coupon bonds and other securities. Discretizing our model allows the use of signal processing techniques from Hidden Markov Models. This means we can estimate not only the unobserved Markov chain but also the parameters of the model, so the model is self-calibrating. The estimation procedure is tested on a selection of U.S. Treasury bills and bonds.Bonds

Untargeted Lipidomics of Non-Small Cell Lung Carcinoma Demonstrates Differentially Abundant Lipid Classes in Cancer vs. Non-Cancer Tissue

Lung cancer remains the leading cause of cancer death worldwide and non-small cell lung carcinoma (NSCLC) represents 85% of newly diagnosed lung cancers. In this study, we utilized our untargeted assignment tool Small Molecule Isotope Resolved Formula Enumerator (SMIRFE) and ultra-high-resolution Fourier transform mass spectrometry to examine lipid profile differences between paired cancerous and non-cancerous lung tissue samples from 86 patients with suspected stage I or IIA primary NSCLC. Correlation and co-occurrence analysis revealed significant lipid profile differences between cancer and non-cancer samples. Further analysis of machine-learned lipid categories for the differentially abundant molecular formulas identified a high abundance sterol, high abundance and high m/z sphingolipid, and low abundance glycerophospholipid metabolic phenotype across the NSCLC samples. At the class level, high abundances of sterol esters and cardiolipins were observed suggesting altered stearoyl-CoA desaturase 1 (SCD1) or acetyl-CoA acetyltransferase (ACAT1) activity and altered human cardiolipin synthase 1 or lysocardiolipin acyltransferase activity respectively, the latter of which is known to confer apoptotic resistance. The presence of a shared metabolic phenotype across a variety of genetically distinct NSCLC subtypes suggests that this phenotype is necessary for NSCLC development and may result from multiple distinct genetic lesions. Thus, targeting the shared affected pathways may be beneficial for a variety of genetically distinct NSCLC subtype