Soft computing in investment appraisal

Standard financial techniques neglect extreme situations and regards large market shifts as too unlikely to matter. Such approach accounts for what occurs most of the time in the market, but does not reflect the reality, as major events happen in the rest of the time and investors are ‘surprised’ by ‘unexpected’ market movements. An alternative fuzzy approach permits fluctuations well beyond the probability type of uncertainty and allows one to make fewer assumptions about the data distribution and market behaviour. Fuzzifying the present value criteria, we suggest a measure of the risk associated with each investment opportunity and estimate the project’s robustness towards market uncertainty. The procedure is applied to thirty-five UK companies traded on the London Stock Exchange and a neural network solution to the fuzzy criterion is provided to facilitate the decision-making process. Finally, we suggest a specific evolutionary algorithm to train a fuzzy neural net - the bidirectional incremental evolution will automatically identify the complexity of the problem and correspondingly adapt the parameters of the fuzzy network

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

Better estimates from binned income data: Interpolated CDFs and mean-matching

Researchers often estimate income statistics from summaries that report the number of incomes in bins such as \$0-10,000, \$10,001-20,000,...,\$200,000+. Some analysts assign incomes to bin midpoints, but this treats income as discrete. Other analysts fit a continuous parametric distribution, but the distribution may not fit well. We fit nonparametric continuous distributions that reproduce the bin counts perfectly by interpolating the cumulative distribution function (CDF). We also show how both midpoints and interpolated CDFs can be constrained to reproduce the mean of income when it is known. We compare the methods' accuracy in estimating the Gini coefficients of all 3,221 US counties. Fitting parametric distributions is very slow. Fitting interpolated CDFs is much faster and slightly more accurate. Both interpolated CDFs and midpoints give dramatically better estimates if constrained to match a known mean. We have implemented interpolated CDFs in the binsmooth package for R. We have implemented the midpoint method in the rpme command for Stata. Both implementations can be constrained to match a known mean.Comment: 20 pages (including Appendix), 3 tables, 2 figures (+2 in Appendix

Cluster phases of membrane proteins

A physical scenario accounting for the existence of size-limited submicrometric domains in cell membranes is proposed. It is based on the numerical investigation of the counterpart, in lipidic membranes where proteins are diffusing, of the recently discovered cluster phases in colloidal suspensions. I demonstrate that the interactions between proteins, namely short-range attraction and longer-range repulsion, make possible the existence of stable small clusters. The consequences are explored in terms of membrane organization and diffusion properties. The connection with lipid rafts is discussed and the apparent protein diffusion coefficient as a function of their concentration is analyzed.Comment: 5 pages - enhanced versio

Different forms of the bovine PrP gene have five or six copies of a short, G-C-rich element within the protein-coding exon

Current models of the virus-like agents of scrapie and bovine spongiform encephalopathy (BSE) have to take into account that structural changes in a host-encoded protein (PrP protein) exhibit an effect on the time course of these diseases and the survival time of any man or animal exposed to these pathogens. We report here the sequence of different forms of the bovine PrP gene which contain either five or six copies of a short, G-C-rich element which encodes the octapeptide Pro-His-Gly-Gly-Gly-Trp-Gly-Gln or its longer variants Pro-Gln/His-Gly-Gly-Gly-Gly-Trp-Gly-Gln. Out of 12 cattle, we found eight animals homozygous for genes with six copies of the Gly-rich peptide (6:6), while four were heterozygous (6:5). Two confirmed cases of BSE occurred in (6: 6) homozygous animals. Bovine spongiform encephalopathy (BSE) is a transmissible disease (Fraser et al., 1988; Dawson et al., 1990; Barlow & Middleton, 1990) which produces neuropathological lesions in cattle similar to those seen in ovine scrapie (Wells et al., 1987) and the rare human dementias Creutzfeldt-Jakob disease (CJD) and Gerstmann-Str/iussler syndrome (GSS) (Beck & Daniel, 1987). A cellular membrane protein (PrP) has a key role in the transmission and development of these diseases. This protein accumulates in the brain and other tissues during the protracted time course of these diseases and, in a disease-specific, protease-resistant isoform (SAF-PrP), has been purified by subcellular fractionation of scrapie

Label-free proteomics identifies Calreticulin and GRP75/Mortalin as peripherally accessible protein biomarkers for spinal muscular atrophy

BACKGROUND: Spinal muscular atrophy (SMA) is a neuromuscular disease resulting from mutations in the survival motor neuron 1 (SMN1) gene. Recent breakthroughs in preclinical research have highlighted several potential novel therapies for SMA, increasing the need for robust and sensitive clinical trial platforms for evaluating their effectiveness in human patient cohorts. Given that most clinical trials for SMA are likely to involve young children, there is a need for validated molecular biomarkers to assist with monitoring disease progression and establishing the effectiveness of therapies being tested. Proteomics technologies have recently been highlighted as a potentially powerful tool for such biomarker discovery. METHODS: We utilized label-free proteomics to identify individual proteins in pathologically-affected skeletal muscle from SMA mice that report directly on disease status. Quantitative fluorescent western blotting was then used to assess whether protein biomarkers were robustly changed in muscle, skin and blood from another mouse model of SMA, as well as in a small cohort of human SMA patient muscle biopsies. RESULTS: By comparing the protein composition of skeletal muscle in SMA mice at a pre-symptomatic time-point with the muscle proteome at a late-symptomatic time-point we identified increased expression of both Calreticulin and GRP75/Mortalin as robust indicators of disease progression in SMA mice. We report that these protein biomarkers were consistently modified in different mouse models of SMA, as well as across multiple skeletal muscles, and were also measurable in skin biopsies. Furthermore, Calreticulin and GRP75/Mortalin were measurable in muscle biopsy samples from human SMA patients. CONCLUSIONS: We conclude that label-free proteomics technology provides a powerful platform for biomarker identification in SMA, revealing Calreticulin and GRP75/Mortalin as peripherally accessible protein biomarkers capable of reporting on disease progression in samples of muscle and skin

Stabilizing the surface morphology of Si1–x–yGexCy/Si heterostructures grown by molecular beam epitaxy through the use of a silicon-carbide source

Si1–x–yGexCy/Si superlattices were grown by solid-source molecular beam epitaxy using silicon carbide as a source of C. Samples consisting of alternating layers of nominally 25 nm Si1–x–yGexCy and 35 nm Si for 10 periods were characterized by high-resolution x-ray diffraction, transmission electron microscopy (TEM), and Rutherford backscattering spectrometry to determine strain, thickness, and composition. C resonance backscattering and secondary ion mass spectrometries were used to measure the total C concentration in the Si1–x–yGexCy layers, allowing for an accurate determination of the substitutional C fraction to be made as a function of growth rate for fixed Ge and substitutional C compositions. For C concentrations close to 1%, high-quality layers were obtained without the use of Sb-surfactant mediation. These samples were found to be structurally perfect to a level consistent with cross-sectional TEM (< 10^7 defects/cm^2) and showed considerably improved homogeneity as compared with similar structures grown using graphite as the source for C. For higher Ge and C concentrations, Sb-surfactant mediation was found to be required to stabilize the surface morphology. The maximum value of substitutional C concentration, above which excessive generation of stacking fault defects caused polycrystalline and/or amorphous growth, was found to be approximately 2.4% in samples containing between 25 and 30% Ge. The fraction of substitutional C was found to decrease from roughly 60% by a factor of 0.86 as the Si1–x–yGexCy growth rate increased from 0.1 to 1.0 nm/s

STEAM games are good for learning: A study of teachers professional development in the Philippines

In a study on digital game-based learning in five high-poverty elementary schools in the Philippines, the teachers’ professional development experiences were investigated. Research conducted for the study was part of a university-industry partnership with the developer of a new platform designed to give teachers and students experience of integrated Science, Technology, Engineering, Arts and Mathematics (STEAM) curriculum in an innovative digital game-based format with elements of coding, robotics and project-based learning. Findings suggest that teachers found it highly effective for engaging students more in learning, with fewer student absentees recorded across the five-week intervention. While noteworthy satisfaction with the program was expressed by teachers about the in-class effectiveness of digital game-based learning, and with the professional learning provided to up-skill themselves in the platform prior to implementation of the program, it was found that significant contextual and language improvements could enhance the overarching aims of this digital game-based resource for STEAM teaching and learning