The analysis of large-scale turbulence characteristics in the Indonesian seas derived from a regional model based on the Princeton Ocean Model

Turbulence characteristics in the Indonesian seas on the horizontal scale of order of 100 km were calculated with a regional model of the Indonesian seas circulation in the area based on the Princeton Ocean Model (POM). As is well known, the POM incorporates the Mellor–Yamada turbulence closure scheme. The calculated characteristics are: twice the turbulence kinetic energy per unit mass, <i>q</i>²; the turbulence master scale, &ell;; mixing coefficients of momentum, <i>K</i>_M; and temperature and salinity, <i>K</i>_H; etc. The analyzed turbulence has been generated essentially by the shear of large-scale ocean currents and by the large-scale wind turbulence. We focused on the analysis of turbulence around important topographic features, such as the Lifamatola Sill, the North Sangihe Ridge, the Dewakang Sill, and the North and South Halmahera Sea Sills. In general, the structure of turbulence characteristics in these regions turned out to be similar. For this reason, we have carried out a detailed analysis of the Lifamatola Sill region because dynamically this region is very important and some estimates of mixing coefficients in this area are available. <br><br> Briefly, the main results are as follows. The distribution of <i>q</i>² is quite adequately reproduced by the model. To the north of the Lifamatola Sill (in the Maluku Sea) and to the south of the Sill (in the Seram Sea), large values of <i>q</i>² occur in the deep layer extending several hundred meters above the bottom. The observed increase of <i>q</i>² near the very bottom is probably due to the increase of velocity shear and the corresponding shear production of <i>q</i>² very close to the bottom. The turbulence master scale, &ell;, was found to be constant in the main depth of the ocean, while &ell; rapidly decreases close to the bottom, as one would expect. However, in deep profiles away from the sill, the effect of topography results in the &ell; structure being unreasonably complicated as one moves towards the bottom. Values of 15 to 20 × 10^&minus;4 m² s^-1 were obtained for <i>K</i>_M and <i>K</i>_H in deep water in the vicinity of the Lifamatola Sill. These estimates agree well with basin-scale averaged values of 13.3 × 10^&minus;4 m² s^-1 found diagnostically for <i>K</i>_H in the deep Banda and Seram Seas (Gordon et al., 2003) and a value of 9.0 × 10^&minus;4 m² s^-1 found diagnostically for <i>K</i>_H for the deep Banda Sea system (van Aken et al., 1988). The somewhat higher simulated values can be explained by the presence of steep topography around the sill.

Preliminary results from follow-up of a large-scale population survey of antibodies to gliadin, reticulin and endomysium

Coeliac disease is often under-diagnosed, particularly in cases which are atypical or asymptomatic.

Regression analysis of spatial data

Many of the most interesting questions ecologists ask lead to analyses of spatial data. Yet, perhaps confused by the large number of statistical models and fitting methods available, many ecologists seem to believe this is best left to specialists. Here, we describe the issues that need consideration when analysing spatial data and illustrate these using simulation studies. Our comparative analysis involves using methods including generalized least squares, spatial filters, wavelet revised models, conditional autoregressive models and generalized additive mixed models to estimate regression coefficients from synthetic but realistic data sets, including some which violate standard regression assumptions. We assess the performance of each method using two measures and using statistical error rates for model selection. Methods that performed well included generalized least squares family of models and a Bayesian implementation of the conditional auto-regressive model. Ordinary least squares also performed adequately in the absence of model selection, but had poorly controlled Type I error rates and so did not show the improvements in performance under model selection when using the above methods. Removing large-scale spatial trends in the response led to poor performance. These are empirical results; hence extrapolation of these findings to other situations should be performed cautiously. Nevertheless, our simulation-based approach provides much stronger evidence for comparative analysis than assessments based on single or small numbers of data sets, and should be considered a necessary foundation for statements of this type in future.

Cognitive, global, and functional benefits of donepezil in Alzheimer's disease and vascular dementia:results from large-scale clinical trials

Alzheimer's disease (AD) and vascular dementia (VaD) are both associated with deficits in cholinergic neurotransmission that are amenable to therapeutic intervention. The cholinesterase inhibitor, donepezil, is clinically effective in both AD and VaD. Results from a 10-study metaanalysis of donepezil (5 or 10 mg/day) in AD and a two-study combined analysis of donepezil (5 or 10 mg/day) in VaD are presented to compare patient characteristics and donepezil treatment outcomes. The analyzed studies were randomized, placebo-controlled, and of up to 24 weeks duration. In both AD and VaD, donepezil provided significant benefits compared with placebo on measures of cognition and global function. Placebo-treated AD patients showed a decline in cognition and global function, whereas placebo-treated VaD patients remained stable, suggesting treatment effects of donepezil in VaD were driven by improvement rather than stabilization or reduced decline. More VaD patients than AD patients received concomitant medications. Cardiovascular adverse events were more common in VaD than AD patients but were not increased by donepezil. In conclusion, although there are differences between AD and VaD patients in comorbid conditions and concomitant medications, donepezil is effective and well tolerated in both types of dementia.

Polycyclic aromatic hydrocarbon (PAH) dispersion and deposition to vegetation and soil following a large scale chemical fire

Polycyclic aromatic hydrocarbons (PAHs) were determined in soil and vegetation following a large scale chemical fire involving 10,000 ton of polypropylene. In comparison with sites outside the plume from the fire, PAH concentrations were elevated in grass shoots (by up to 70-fold) and in soil (by up to 370-fold). The pattern of PAH dispersion under the plume was dependent on the physical-chemical properties of individual PAHs. The lighter, least hydrophobic PAHs were dispersed into the environment at greater distances than heavier, more hydrophobic PAHs. At the most distant sampling point (4.5 km) under the plume, the low molecular weight PAHs were still considerably elevated in vegetation samples compared to control sites. Dispersion appeared to be regulated by the compounds partitioning between the vapour and particulate phase, with dry particulate deposition occurring closer to the fire source than gaseous deposition. For all PAHs, the fire resulted in greater contamination of soils compared to grasses, with the relative ratio of plant/soil contamination decreasing as hydrophobicity increased.

Dioxin and furan residues in wood mice (Apodemus sylvaticus) following a large scale polyvinyl chloride (PVC) fire

A forest ecosystem was contaminated as a result of a fire involving 600 t of PVC. A wide range of 2,3,7,8-substituted dioxin and furan congeners were elevated (by up to 4-fold) on soil adjacent to the factory compared to a site 200 m from the factory perimeter. Livers of wood mice (Apodemus sylvaticus) caught on these areas were also analysed for dioxins and furans. Toxic equivalents (TEQs) were 9-fold higher in wood mice caught on the site 10 m from the factory perimeter compared with the site 200 m from the perimeter, with individual 2,3,7,8-substituted congeners being elevated by up to 30-fold. Wood mouse liver TEQs were found to be highly correlated with cadmium kidney concentrations, cadmium also being found at elevated concentrations at the accident site. There was also a significant positive correlation between wood mouse liver TEQs and relative liver weights (wet weights expressed as a percentage of total body weight). The results of this study are discussed in the wider context of dioxin contamination in the environment.

Large Scale Verification of MPI Programs Using Lamport Clocks with Lazy Update

We propose a dynamic verification approach for large-scale message passing programs to locate correctness bugs caused by unforeseen nondeterministic interactions. This approach hinges on an efficient protocol to track the causality between nondeterministic message receive operations and potentially matching send operations. We show that causality tracking protocols that rely solely on logical clocks fail to capture all nuances of MPI program behavior, including the variety of ways in which nonblocking calls can complete. Our approach is hinged on formally defining the matches-before relation underlying the MPI standard, and devising lazy update logical clock based algorithms that can correctly discover all potential outcomes of nondeterministic receives in practice. can achieve the same coverage as a vector clock based algorithm while maintaining good scalability. LLCP allows us to analyze realistic MPI programs involving a thousand MPI processes, incurring only modest overheads in terms of communication bandwidth, latency, and memory consumption. © 2011 IEEE.

Collectives of diagnostic biomarkers identify high-risk subpopulations of hematuria patients: exploiting heterogeneity in large-scale biomarker data

Background: Ineffective risk stratification can delay diagnosis of serious disease in patients with hematuria. We applied a systems biology approach to analyze clinical, demographic and biomarker measurements (n = 29) collected from 157 hematuric patients: 80 urothelial cancer (UC) and 77 controls with confounding pathologies.

Methods: On the basis of biomarkers, we conducted agglomerative hierarchical clustering to identify patient and biomarker clusters. We then explored the relationship between the patient clusters and clinical characteristics using Chi-square analyses. We determined classification errors and areas under the receiver operating curve of Random Forest Classifiers (RFC) for patient subpopulations using the biomarker clusters to reduce the dimensionality of the data.

Results: Agglomerative clustering identified five patient clusters and seven biomarker clusters. Final diagnoses categories were non-randomly distributed across the five patient clusters. In addition, two of the patient clusters were enriched with patients with ‘low cancer-risk’ characteristics. The biomarkers which contributed to the diagnostic classifiers for these two patient clusters were similar. In contrast, three of the patient clusters were significantly enriched with patients harboring ‘high cancer-risk” characteristics including proteinuria, aggressive pathological stage and grade, and malignant cytology. Patients in these three clusters included controls, that is, patients with other serious disease and patients with cancers other than UC. Biomarkers which contributed to the diagnostic classifiers for the largest ‘high cancer- risk’ cluster were different than those contributing to the classifiers for the ‘low cancer-risk’ clusters. Biomarkers which contributed to subpopulations that were split according to smoking status, gender and medication were different.

Conclusions: The systems biology approach applied in this study allowed the hematuric patients to cluster naturally on the basis of the heterogeneity within their biomarker data, into five distinct risk subpopulations. Our findings highlight an approach with the promise to unlock the potential of biomarkers. This will be especially valuable in the field of diagnostic bladder cancer where biomarkers are urgently required. Clinicians could interpret risk classification scores in the context of clinical parameters at the time of triage. This could reduce cystoscopies and enable priority diagnosis of aggressive diseases, leading to improved patient outcomes at reduced costs. © 2013 Emmert-Streib et al; licensee BioMed Central Ltd.

A review of spatial and temporal variation in grey and common seal diet in the United Kingdom and Ireland

Knowledge about the diet of fish-eating predators is critical when evaluating conflicts with the fishing industry. Numerous primary studies have examined the diet of grey seals Halichoerus grypus and common seals Phoca vitulina in a bid to understand the ecology of these predators. However, studies of large-scale spatial and temporal variation in seal diet are limited. Therefore this review combines the results of seal diet studies published between 1980 and 2000 to examine how seal diet varies at a range of spatial and temporal scales. Our results revealed extensive spatial variation in gadiform, perciform and flatfish consumption, likely reflecting variation in prey availability. Flatfish and gadiform consumption varied between years, reflecting changes in fish assemblages as a consequence of factors such as varying fishing pressures, climate change and natural fluctuations in populations. Perciform and gadiform consumption varied seasonally: in addition there was a significant interaction between season and seal species, indicating that grey and common seals exhibited different patterns of seasonal variation in their consumption of Perciformes and Gadiformes. Multivariate analysis of grey seal diet revealed spatial variation at a much smaller scale, with different species dominating the diet in different areas. The existence of spatial and temporal variation in seal diet emphasizes that future assessments of the impact of seal populations should not be based on past or localized estimates of diet and highlights the need for up-to-date, site specific estimates of diet composition in the context of understanding and resolving seal/fisheries conflict. © 2012 Marine Biological Association of the United Kingdom.

Coordinated Design of Phase Measurement Unit and Power System Stabilisers in Large Scale Power System

This paper presents a case-study of a PMU application with PSS support in a real large scale Chinese power system to suppress inter-area oscillations. The paper uses PMU measured feedback signals from a PSS input signal for dynamic torque analysis (DTA). In the paper, a mathematical model of multi-machine power system is described, followed by formation of the residue and DTA indices. Simulations of the model are used with a large-scale power system model to demonstrate the role of PSS and the equivalence of DTA residue indices.

Large-Scale Wind Generator Cascaded Tripping

Large scale wind farms are subject to tripping, as a consequence of turbine failure, over-sensitive protection, turbines not equipped with low-voltage ride through (LVRT), and reactive power compensation device defects which can lead to voltage rises. This paper considers pertinent issues which render tripping based on a study of LVRT and wind farm protection, with methods to avoid large scale wind generator tripping proposed. The results of LVRT field tests in Jiuquan, China in December 2012 show that the proposed approaches are effective. The paper also presents work which proposes an early warning system to forecast the risk of wind power tripping.

Lovastatin production by Aspergillus terreus using lignocellulose biomass in large scale packed bed reactor

The effect of superficial air velocity on lovastatin production by Aspergillus terreus PL10 using wheat bran and wheat straw was investigated in a 7 l and a 1200 l packed bed reactor. Mass transfer and reaction limitations on bioconversion in the 1200 l reactor was studied based on a central composite design of experiments constructed using the superficial air velocity and solid substrate composition as variables and lovastatin production as response.
The surface response prediction showed a maximum lovastatin production of 1.86 mg g-1 dry substrate on day 5 of the bioconversion process when the reactor was operated using 0.19 vvm airflow rate (23.37 cm min-1 superficial air velocity) and 54% substrate composition (wC). Lovastatin production did not increase significantly with superficial air velocity in the 7 l reactor. Variation in temperature and exit CO2 composition was recorded, and the Damköhler number was calculated for lovastatin production at these two scales. The results showed that in larger reactors mass transfer limitation controlled bioconversion while in smaller reactors bioconversion was controlled by reaction rate limitations. In addition, mass transfer limitations in larger reactors reduced the rate of metabolic heat removal, resulting in hot spots within the substrate bed.