Evidence for a first order transition in a plaquette 3d Ising-like action

We investigate a 3d Ising action which corresponds to a a class of models defined by Savvidy and Wegner, originally intended as discrete versions of string theories on cubic lattices. These models have vanishing bare surface tension and the couplings are tuned in such a way that the action depends only on the angles of the discrete surface, i.e. on the way the surface is embedded in ${\bf Z}^3$. Hence the name gonihedric by which they are known. We show that the model displays a rather clear first order phase transition in the limit where self-avoidance is neglected and the action becomes a plaquette one. This transition persists for small values of the self avoidance coupling, but it turns to second order when this latter parameter is further increased. These results exclude the use of this type of action as models of gonihedric random surfaces, at least in the limit where self avoidance is neglected.Comment: 4 pages Latex text, 4 postscript figure

Economic Value of Climate Variability Impacts on Coconut Production in Sri Lanka

This paper assesses the economic value of climate variability, employing a percentile analysis on an array of 31-years national annual coconut production data from 1971 to 2001. Of the production array, 10% and 90% percentiles have been considered respectively as lower and upper production extremes. The 60% of production departures of each year of extremes with respect to the mean production of 10% to 90% percentile were attributed to climate variability because studies show that the 60% of the variation of coconut production is explained by climate. These production deviations were then valued multiplying by free-on-board (FOB) prices of fresh coconuts. Results show that the foregone income from coconuts due to low rainfall varied between US$32 million to US$ 73 million while the incremental coconut income in crop glut extremes due to high rainfall varied between US$42 million and US$ 87 million. Results show that the climate variability causes income losses to the economy estimated at US$32 million to US$ 73 million in years of extreme crop shortage. And in years of extreme crop surplus, the economy realises income gains of US$42 million to US$ 87 million. These indicate the potential for significant economic benefits from investments in adaptations that would reduce variability in nut production which is caused by variations in climate. Further work is however needed to estimate the effectiveness and economic benefits that might be achieved from investments in adaptation

String tension in gonihedric 3D Ising models

For the 3D gonihedric Ising models defined by Savvidy and Wegner the bare string tension is zero and the energy of a spin interface depends only on the number of bends and self-intersections, in antithesis to the standard nearest-neighbour 3D Ising action. When the parameter kappa weighting the self-intersections is small the model has a first order transition and when it is larger the transition is continuous. In this paper we investigate the scaling of the renormalized string tension, which is entirely generated by fluctuations, using Monte Carlo simulations This allows us to obtain an estimate for the critical exponents alpha and nu using both finite-size-scaling and data collapse for the scaling function.Comment: Latex + postscript figures. 8 pages text plus 7 figures, spurious extra figure now removed

Metabolic Modulation Predicts Heart Failure Tests Performance

The metabolic changes that accompany changes in Cardiopulmonary testing (CPET) and heart failure biomarkers (HFbio) are not well known. We undertook metabolomic and lipidomic phenotyping of a cohort of heart failure (HF) patients and utilized Multiple Regression Analysis (MRA) to identify associations to CPET and HFBio test performance (peak oxygen consumption (Peak VO2), oxygen uptake efficiency slope (OUES), exercise duration, and minute ventilation-carbon dioxide production slope (VE/VCO2 slope), as well as the established HF biomarkers of inflammation C-reactive protein (CRP), beta-galactoside-binding protein (galectin-3), and N-terminal prohormone of brain natriuretic peptide (NT-proBNP)). A cohort of 49 patients with a left ventricular ejection fraction \u3c 50%, predominantly males African American, presenting a high frequency of diabetes, hyperlipidemia, and hypertension were used in the study. MRA revealed that metabolic models for VE/VCO2 and Peak VO2 were the most fitted models, and the highest predictors’ coefficients were from Acylcarnitine C18:2, palmitic acid, citric acid, asparagine, and 3-hydroxybutiric acid. Metabolic Pathway Analysis (MetPA) used predictors to identify the most relevant metabolic pathways associated to the study, aminoacyl-tRNA and amino acid biosynthesis, amino acid metabolism, nitrogen metabolism, pantothenate and CoA biosynthesis, sphingolipid and glycerolipid metabolism, fatty acid biosynthesis, glutathione metabolism, and pentose phosphate pathway (PPP). Metabolite Set Enrichment Analysis (MSEA) found associations of our findings with pre-existing biological knowledge from studies of human plasma metabolism as brain dysfunction and enzyme deficiencies associated with lactic acidosis. Our results indicate a profile of oxidative stress, lactic acidosis, and metabolic syndrome coupled with mitochondria dysfunction in patients with HF tests poor performance. The insights resulting from this study coincides with what has previously been discussed in existing literature thereby supporting the validity of our findings while at the same time characterizing the metabolic underpinning of CPET and HFBio

Leveraging Deep Learning Based Object Detection for Localising Autonomous Personal Mobility Devices in Sparse Maps

© 2019 IEEE. This paper presents a low cost, resource efficient localisation approach for autonomous driving in GPS denied environments. One of the most challenging aspects of traditional landmark based localisation in the context of autonomous driving, is the necessity to accurately and frequently detect landmarks. We leverage the state of the art deep learning framework, YOLO (You Only Look Once), to carry out this important perceptual task using data obtained from monocular cameras. Extracted bearing only information from the YOLO framework, and vehicle odometry, is fused using an Extended Kalman Filter (EKF) to generate an estimate of the location of the autonomous vehicle, together with it's associated uncertainty. This approach enables us to achieve real-time sub metre localisation accuracy, using only a sparse map of an outdoor urban environment. The broader motivation of this research is to improve the safety and reliability of Personal Mobility Devices (PMDs) through autonomous technology. Thus, all the ideas presented here are demonstrated using an instrumented mobility scooter platform

IMPACT OF SAND MINING ACTIVITIES ON THE QUALITY OF THE WATER

Out of 103 number of rivers in Sri Lanka the 3n1 largest major river is Kaluganga. It hasthe highest volume of discharge as a percent (%) of precipitation per year out of the SriLankan rivers. It originates 4600m above mean sea level (Sripada), is 118km in lengthand opens to the sea at Kalutara.At the lower reaches of Kaluganga is a densely populated zone where the inhabitants arehighly dependent on sand mining activities which adversely affect the quality of thewater in the river. To assess the extent of mining effects, six sites were selected. Out ofthose sites, water samples were collected for monitoring purpose samples were collectedfrom the Kethhena water intake. In the other five sites heavy sand mining activities areon going. To compare the variation of chemical, physical & biological parameters inwater, samples were collected from each site and analysed weekly for two months.The physical parameters measured include - temperature, turbidity, suspended solids andelectrical conductivity. Chemical parameters assessed include pH, dissolved oxygen,BODs ( biological oxygen demand ), alkalinity, water hardness, [ Mg+2], [ Ca+2),[cr ]and COD. The data were analyzed by TWO WAY ANOVA using GLM procedureof MINITAB. Microscopic identification of biological parameters (phytoplankton's) wasidentified.According to the results obtained, the value of pH, temperature and dissolved oxygen arein the desirable level. But some values like conductivity, suspended solids, turbidity,alkalinity, [Cl], [Fe], phosphates as P20s, COD are higher than the desired range. BODsis within desired which means low organic matter in the river. [Cl'] along the riverindicates the salt-water intrusion directly effected by mining lowering the river bed.[Mg2+], [Ca+2], Nitrogen, water hardness are lower than the desired level. Anabena,Nostoc, Microcystis, Closterium, Cosmarium, Occilatoria, Spirogyra. Spirulina Spps arcfound as biological indicators in the water at mining sites but in lower abundancy. At thesite of water intake few species were identified but abundancy is higher than in othersites. These species include, Occilatoria.Euglina ssp.,Closterium,Cosmarium,SpirogiraAccording to the above results it can be concluded that the sand mining activities hasadversely affected the quality of the water at the lower reaches of Kaluganga

The Information Geometry of the Ising Model on Planar Random Graphs

It has been suggested that an information geometric view of statistical mechanics in which a metric is introduced onto the space of parameters provides an interesting alternative characterisation of the phase structure, particularly in the case where there are two such parameters -- such as the Ising model with inverse temperature $\beta$ and external field $h$. In various two parameter calculable models the scalar curvature ${\cal R}$ of the information metric has been found to diverge at the phase transition point $\beta_c$ and a plausible scaling relation postulated: ${\cal R} \sim |\beta- \beta_c|^{\alpha - 2}$. For spin models the necessity of calculating in non-zero field has limited analytic consideration to 1D, mean-field and Bethe lattice Ising models. In this letter we use the solution in field of the Ising model on an ensemble of planar random graphs (where $\alpha=-1, \beta=1/2, \gamma=2$) to evaluate the scaling behaviour of the scalar curvature, and find ${\cal R} \sim | \beta- \beta_c |^{-2}$. The apparent discrepancy is traced back to the effect of a negative $\alpha$.Comment: Version accepted for publication in PRE, revtex

The household economic burden for acute coronary syndrome survivors in Australia

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.Background: Studies of chronic diseases are associated with a financial burden on households. We aimed to determine if survivors of acute coronary syndrome (ACS) experience household economic burden and to quantify any potential burden by examining level of economic hardship and factors associated with hardship. Methods: Australian patients admitted to hospital with ACS during 2-week period in May 2012, enrolled in SNAPSHOT ACS audit and who were alive at 18 months after index admission were followed-up via telephone/paper survey. Regression models were used to explore factors related to out-of-pocket expenses and economic hardship. Results: Of 1833 eligible patients at baseline, 180 died within 18 months, and 702 patients completed the survey. Mean out-of-pocket expenditure (n = 614) in Australian dollars was A$258.06 (median: A$126.50) per month. The average spending for medical services was A$120.18 (SD: A$310.35) and medications was A$66.25 (SD: A$80.78). In total, 350 (51 %) of patients reported experiencing economic hardship, 78 (12 %) were unable to pay for medical services and 81 (12 %) could not pay for medication. Younger age (18–59 vs ≥80 years (OR): 1.89), no private health insurance (OR: 2.04), pensioner concession card (OR: 1.80), residing in more disadvantaged area (group 1 vs 5 (OR): 1.77), history of CVD (OR: 1.47) and higher out-of-pocket expenses (group 4 vs 1 (OR): 4.57) were more likely to experience hardship. Conclusion: Subgroups of ACS patients are experiencing considerable economic burden in Australia. These findings provide important considerations for future policy development in terms of the cost of recommended management for patients

Dengue prevalence as an evidence of Climate change in Sri Lanka

Climate change is the main fundamental human development challenge of the 21st century. Sri Lanka is a developing island nation subject to tropical climate patterns; highly vulnerable to climate change impacts. High variability of rainfall patterns and increasing temperature experienced during the recent past in Sri Lanka could be one of the consequences of global climate change with the increase of Greenhouse gases in the atmosphere. The main objective of this study is to investigate the possibility to use the dengue prevalence as an evidence of climate change in Sri Lanka by establishing the correlation of climate factors and dengue incidence. Seven districts were randomly selected across all climatic zones for the study and dengue incidence, rainfall, and temperature statistics of last 10 years were collected from relevant governmental institutions. Data analysis was done using SPSS (version 21) and R (Rx64 3.5.1) Statistical Software. According to the findings of the study, rainfall and temperature difference have a statistically significant correlation with dengue incidents. Therefore, dengue prevalence can be used as an evidence of climate change in Sri Lanka. Hence, authorities should take necessary steps to mainstream Climate change into development policies in all sectors for a sustainable future. KEYWORDS: Adaptation, Climate change, Dengue, Mitigation, UNFCC

Spectral quantification of nonlinear behaviour of the nearshore seabed and correlations with potential forcings at Duck, N.C., U.S.A

Local bathymetric quasi-periodic patterns of oscillation are identified from monthly profile surveys taken at two shore-perpendicular transects at the USACE field research facility in Duck, North Carolina, USA, spanning 24.5 years and covering the swash and surf zones. The chosen transects are the two furthest (north and south) from the pier located at the study site. Research at Duck has traditionally focused on one or more of these transects as the effects of the pier are least at these locations. The patterns are identified using singular spectrum analysis (SSA). Possible correlations with potential forcing mechanisms are discussed by 1) doing an SSA with same parameter settings to independently identify the quasi-periodic cycles embedded within three potentially linked sequences: monthly wave heights (MWH), monthly mean water levels (MWL) and the large scale atmospheric index known as the North Atlantic Oscillation (NAO) and 2) comparing the patterns within MWH, MWL and NAO to the local bathymetric patterns. The results agree well with previous patterns identified using wavelets and confirm the highly nonstationary behaviour of beach levels at Duck; the discussion of potential correlations with hydrodynamic and atmospheric phenomena is a new contribution. The study is then extended to all measured bathymetric profiles, covering an area of 1100m (alongshore) by 440m (cross-shore), to 1) analyse linear correlations between the bathymetry and the potential forcings using multivariate empirical orthogonal functions (MEOF) and linear correlation analysis and 2) identify which collective quasi-periodic bathymetric patterns are correlated with those within MWH, MWL or NAO, based on a (nonlinear) multichannel singular spectrum analysis (MSSA). (...continued in submitted paper)Comment: 50 pages, 3 tables, 8 figure