Residence of liquids in the infra-junctional portion of the proximal stomach in patients with gastroesophageal reflux disease

Patients with gastroesophageal reflux disease may have disturbances of gastric motility, which could play a role in the pathophysiology of the disease. Recent studies have suggested that the gastric region just below the gastroesophageal junction may have a distinct physiological behavior. We determined whether patients with gastroesophageal reflux disease have abnormal residence of food in the infra-junctional portion of the stomach after ingesting a liquid nutrient meal. Fasted adult patients with reflux disease (N = 11) and healthy volunteers (N = 10) ingested a liquid meal (320 ml; 437 kcal) labeled with 99m technetium-phytate and their total gastric emptying half-time and regional emptying from the stomach infra-junctional region were determined. In 8 patients, episodes of postprandial acidic reflux to the esophagus were measured for 2 h using pH monitoring. There were no differences between reflux patients and controls regarding total gastric emptying time (median: 68 min; range: 39-123 min vs 65 min and 60-99 min, respectively; P > 0.50). Food residence in the infra-junctional area was similar for patients and controls: 23% (range: 20-30) vs 27% (range: 19-30%; P = 0.28) and emptying from this area paralleled total gastric emptying (Rs = 0.79; P = 0.04). There was no correlation between residence of food in the infra-junctional area and episodes of gastroesophageal reflux (Rs = 0.06; P = 0.88). We conclude that it is unlikely that regional motor disturbances involving the infra-junctional region of the stomach play a relevant role in the pathogenesis of acidic gastroesophageal reflux.

Distribution-Free Bounds for Serial Correlation Coefficients in Heteroskedastic Symmetric Time Series

We consider the problem of testing whether the observations X1, ..., Xn of a time series are independent with unspecified (possibly nonidentical) distributions symmetric about a common known median. Various bounds on the distributions of serial correlation coefficients are proposed: exponential bounds, Eaton-type bounds, Chebyshev bounds and Berry-Esséen-Zolotarev bounds. The bounds are exact in finite samples, distribution-free and easy to compute. The performance of the bounds is evaluated and compared with traditional serial dependence tests in a simulation experiment. The procedures proposed are applied to U.S. data on interest rates (commercial paper rate).

Fine structure in the time of flight distribution of C2 in laser produced plasma from graphite

Time resolved optical emission spectroscopy is employed to study the expansion dynamics of C2 species in a graphite plasma produced during the Nd : YAG ablation. At low laser fluences a single peak distribution with low kinetic energy is observed. At higher fluences a twin peak distribution is found. It has been noted that these double peak time of flight distribution splits into a triple peak structure at distances >_ 17mm from the target surface. The reason for the occurrence of multiple peak is due to different formation mechanisms of C2 species

Real-time expert system for fault location on high voltage underground distribution cables

To ensure minimum loss of system security and revenue it is essential that faults on underground cable systems be located and repaired rapidly. Currently in the UK, the impulse current method is used to prelocate faults, prior to using acoustic methods to pinpoint the fault location. The impulse current method is heavily dependent on the engineer's knowledge and experience in recognising/interpreting the transient waveforms produced by the fault. The development of a prototype real-time expert system aid for the prelocation of cable faults is described. Results from the prototype demonstrate the feasibility and benefits of the expert system as an aid for the diagnosis and location of faults on underground cable systems.

Automatic near real-time selection of flood water levels from high resolution Synthetic Aperture Radar images for assimilation into hydraulic models: a case study

Flood extents caused by fluvial floods in urban and rural areas may be predicted by hydraulic models. Assimilation may be used to correct the model state and improve the estimates of the model parameters or external forcing. One common observation assimilated is the water level at various points along the modelled reach. Distributed water levels may be estimated indirectly along the flood extents in Synthetic Aperture Radar (SAR) images by intersecting the extents with the floodplain topography. It is necessary to select a subset of levels for assimilation because adjacent levels along the flood extent will be strongly correlated. A method for selecting such a subset automatically and in near real-time is described, which would allow the SAR water levels to be used in a forecasting model. The method first selects candidate waterline points in flooded rural areas having low slope. The waterline levels and positions are corrected for the effects of double reflections between the water surface and emergent vegetation at the flood edge. Waterline points are also selected in flooded urban areas away from radar shadow and layover caused by buildings, with levels similar to those in adjacent rural areas. The resulting points are thinned to reduce spatial autocorrelation using a top-down clustering approach. The method was developed using a TerraSAR-X image from a particular case study involving urban and rural flooding. The waterline points extracted proved to be spatially uncorrelated, with levels reasonably similar to those determined manually from aerial photographs, and in good agreement with those of nearby gauges.

Bayesian Analysis for the Generalized Lognormal Distribution Applied to Failure Time Analysis

There are several versions of the lognormal distribution in the statistical literature, one is based in the exponential transformation of generalized normal distribution (GN). This paper presents the Bayesian analysis for the generalized lognormal distribution (logGN) considering independent non-informative Jeffreys distributions for the parameters as well as the procedure for implementing the Gibbs sampler to obtain the posterior distributions of parameters. The results are used to analyze failure time models with right-censored and uncensored data. The proposed method is illustrated using actual failure time data of computers.

Adaptive, Decentralized, And Real-Time Sampling Strategies For Resource Constrained Hydraulic And Hydrologic Sensor Networks

We discuss the development and performance of a low-power sensor node (hardware, software and algorithms) that autonomously controls the sampling interval of a suite of sensors based on local state estimates and future predictions of water flow. The problem is motivated by the need to accurately reconstruct abrupt state changes in urban watersheds and stormwater systems. Presently, the detection of these events is limited by the temporal resolution of sensor data. It is often infeasible, however, to increase measurement frequency due to energy and sampling constraints. This is particularly true for real-time water quality measurements, where sampling frequency is limited by reagent availability, sensor power consumption, and, in the case of automated samplers, the number of available sample containers. These constraints pose a significant barrier to the ubiquitous and cost effective instrumentation of large hydraulic and hydrologic systems. Each of our sensor nodes is equipped with a low-power microcontroller and a wireless module to take advantage of urban cellular coverage. The node persistently updates a local, embedded model of flow conditions while IP-connectivity permits each node to continually query public weather servers for hourly precipitation forecasts. The sampling frequency is then adjusted to increase the likelihood of capturing abrupt changes in a sensor signal, such as the rise in the hydrograph – an event that is often difficult to capture through traditional sampling techniques. Our architecture forms an embedded processing chain, leveraging local computational resources to assess uncertainty by analyzing data as it is collected. A network is presently being deployed in an urban watershed in Michigan and initial results indicate that the system accurately reconstructs signals of interest while significantly reducing energy consumption and the use of sampling resources. We also expand our analysis by discussing the role of this approach for the efficient real-time measurement of stormwater systems.

A new Pennsylvanian Oriocrassatellinae from Brazil and the distribution of the genus Oriocrassatella in space and time

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Electrical Power Distribution System modeling with VHDL-AMS for the construction of a Real-Time Digital Simulator using FPGAS devices

This paper presents a distribution feeder simulation using VHDL-AMS, considering the standard IEEE 13 node test feeder admitted as an example. In an electronic spreadsheet all calculations are performed in order to develop the modeling in VHDL-AMS. The simulation results are compared in relation to the results from the well knowing MatLab/Simulink environment, in order to verify the feasibility of the VHDL-AMS modeling for a standard electrical distribution feeder, using the software SystemVision™. This paper aims to present the first major developments for a future Real-Time Digital Simulator applied to Electrical Power Distribution Systems. © 2012 IEEE.

A Time-domain Harmonic Power-Flow Analysis in Electrical Energy Distribution Networks, Using Norton Models for Non-linear Loading

The purpose of this paper is to present the application of a three-phase harmonic propagation analysis time-domain tool, using the Norton model to approach the modeling of non-linear loads, making the harmonics currents flow more appropriate to the operation analysis and to the influence of mitigation elements analysis. This software makes it possible to obtain results closer to the real distribution network, considering voltages unbalances, currents imbalances and the application of mitigation elements for harmonic distortions. In this scenario, a real case study with network data and equipments connected to the network will be presented, as well as the modeling of non-linear loads based on real data obtained from some PCCs (Points of Common Coupling) of interests for a distribution company.

An investigation into the effects of resonances on the time delay estimate for leak detection in buried plastic water distribution pipes

In water distribution systems, old metallic pipes have been replaced by plastic pipes due to their deterioration over time. Although acoustic methods are effective in finding leaks in metallic pipes, they have been found to be problematic when applied to plastic pipes due to the high damping within the pipe wall and the surrounding medium. This is responsible for the leak signal not traveling long distances. Moreover, the leak energy in plastic pipes is generally located at a narrow frequency range located at low frequencies. However, the presence of resonances can narrow even more this frequency range. In order to minimise the influence of background noise and resonances on the calculation of the time delay estimate, band-pass filters are often used to supress undesirable frequency components of the noise. The objective of this paper is to investigate the influence of resonances in the pipe system (pipe, valves, connections and hydrants), on the time delay estimate calculated using acoustic signals. Analytical models and actual leak data collected in a bespoke rig located in the United Kingdom are used to investigate this feature.

A new Pennsylvanian Oriocrassatellinae from Brazil and the distribution of the genus Oriocrassatella in space and time

Oriocrassatella Etheridge Jr., 1907 is a long range crassatellid bivalve genus well recognized in shallow waters of epeiric seas throughout the upper part of Paleozoic. The first occurrences of this genus are recorded in the sedimentary successions of the Gondwana, both in Australia and South America. However, the geographic and age distribution of Oriocrassatella in Late Mississippian deposits of Australia and Argentina may indicate an earliest Visean or even a pre-Visean origin for the genus. Following its origin in Early Carboniferous a complex paleobiogeographic history from Southern to Northern Hemisphere took place in the Permian. During its initial dispersal phase from Late Carboniferous to the Early Permian the genus thrived in cold water environments associated to the Late Paleozoic Gondwana glaciation. Shallow-water bottoms of the warm waters of the central Gondwana fringe and Laurussia were colonized by Oriocrassatella only during Early Permian times when the genus became cosmopolitan. A new species of this genus is described herein, Oriocrassatella piauiensis n. sp., recorded from the Piaui Formation, Pennsylvanian of the Parnaiba Basin. This new species may represent an early adaptation to warm waters. However, based on available data, species of this genus seem to have adapted definitely to warm water environments probably related the Late Pennsylvanian interglacial phases. In these phases, climatic barrier were interrupted allowing the faunal interchange and larval dispersion following a South to North migration route through the eastern margins of Gondwana and the eastern Paleotethys.

Analysis and developments of uncertainty processors for real time flood forecasting

The hydrologic risk (and the hydro-geologic one, closely related to it) is, and has always been, a very relevant issue, due to the severe consequences that may be provoked by a flooding or by waters in general in terms of human and economic losses. Floods are natural phenomena, often catastrophic, and cannot be avoided, but their damages can be reduced if they are predicted sufficiently in advance. For this reason, the flood forecasting plays an essential role in the hydro-geological and hydrological risk prevention. Thanks to the development of sophisticated meteorological, hydrologic and hydraulic models, in recent decades the flood forecasting has made a significant progress, nonetheless, models are imperfect, which means that we are still left with a residual uncertainty on what will actually happen. In this thesis, this type of uncertainty is what will be discussed and analyzed. In operational problems, it is possible to affirm that the ultimate aim of forecasting systems is not to reproduce the river behavior, but this is only a means through which reducing the uncertainty associated to what will happen as a consequence of a precipitation event. In other words, the main objective is to assess whether or not preventive interventions should be adopted and which operational strategy may represent the best option. The main problem for a decision maker is to interpret model results and translate them into an effective intervention strategy. To make this possible, it is necessary to clearly define what is meant by uncertainty, since in the literature confusion is often made on this issue. Therefore, the first objective of this thesis is to clarify this concept, starting with a key question: should be the choice of the intervention strategy to adopt based on the evaluation of the model prediction based on its ability to represent the reality or on the evaluation of what actually will happen on the basis of the information given by the model forecast? Once the previous idea is made unambiguous, the other main concern of this work is to develope a tool that can provide an effective decision support, making possible doing objective and realistic risk evaluations. In particular, such tool should be able to provide an uncertainty assessment as accurate as possible. This means primarily three things: it must be able to correctly combine all the available deterministic forecasts, it must assess the probability distribution of the predicted quantity and it must quantify the flooding probability. Furthermore, given that the time to implement prevention strategies is often limited, the flooding probability will have to be linked to the time of occurrence. For this reason, it is necessary to quantify the flooding probability within a horizon time related to that required to implement the intervention strategy and it is also necessary to assess the probability of the flooding time.

A multi-objective genetic algorithm optimisation using variable speed pumps in water distribution systems

Due to its practical importance and inherent complexity, the optimisation of distribution networks for supplying drinking water has been the subject of extensive study for the past 30 years. The optimization is governed by sizing the pipes in the water distribution network (WDN) and / or optimises specific parts of the network such as pumps, tanks etc. or try to analyse and optimise the reliability of a WDN. In this thesis, the author has analysed two different WDNs (Anytown City and Cabrera city networks), trying to solve and optimise a multi-objective optimisation problem (MOOP). The main two objectives in both cases were the minimisation of Energy Cost (€) or Energy consumption (kWh), along with the total Number of pump switches (TNps) during a day. For this purpose, a decision support system generator for Multi-objective optimisation used. Its name is GANetXL and has been developed by the Center of Water System in the University of Exeter. GANetXL, works by calling the EPANET hydraulic solver, each time a hydraulic analysis has been fulfilled. The main algorithm used, was a second-generation algorithm for multi-objective optimisation called NSGA_II that gave us the Pareto fronts of each configuration. The first experiment that has been carried out was the network of Anytown city. It is a big network with a pump station of four fixed speed parallel pumps that are boosting the water dynamics. The main intervention was to change these pumps to new Variable speed driven pumps (VSDPs), by installing inverters capable to diverse their velocity during the day. Hence, it’s been achieved great Energy and cost savings along with minimisation in the number of pump switches. The results of the research are thoroughly illustrated in chapter 7, with comments and a variety of graphs and different configurations. The second experiment was about the network of Cabrera city. The smaller WDN had a unique FS pump in the system. The problem was the same as far as the optimisation process was concerned, thus, the minimisation of the energy consumption and in parallel the minimisation of TNps. The same optimisation tool has been used (GANetXL).The main scope was to carry out several and different experiments regarding a vast variety of configurations, using different pump (but this time keeping the FS mode), different tank levels, different pipe diameters and different emitters coefficient. All these different modes came up with a large number of results that were compared in the chapter 8. Concluding, it should be said that the optimisation of WDNs is a very interested field that has a vast space of options to deal with. This includes a large number of algorithms to choose from, different techniques and configurations to be made and different support system generators. The researcher has to be ready to “roam” between these choices, till a satisfactory result will convince him/her that has reached a good optimisation point.

Ecological distribution of semi-demersal fishes in space and time on the shelf of Antalya Gulf

In this study we provide a baseline data on semidemersal fish assemblages and biology in a heterogeneous and yet less studied portion of the shelf of Antalya Gulf. The distribution of fish abundance in three transects subjected to different fisheries regulations (fishery vs non fishery areas), and including depths of 10, 25, 75, 125, 200 m, was studied between May 2014 and February 2015 in representative months of winter, spring, summer and autumn seasons. A total of 76 fish species belonging to 40 families was collected and semidemersal species distribution was analyzed in comparison with the whole community. Spatial distribution of fish was driven mainly by depth and two main assemblages were observed: shallow waters (10-25; 75 m) and deep waters (125-200 m). Significant differences among transects were found for the whole community but not for the semidemersal species. Analysis showed that this was due to a strong relation of these species with local environmental characteristics rather than to a different fishing pressure over transects. Firstly all species distribute according to the bathymetrical gradient and secondly to the bottom type structure. Semidemersal species were then found more related to zooplankton and suspended matter availability. The main morphological characteristics, sex and size distribution of the target semidemersal species Spicara smaris (Linnaeus, 1758), Saurida undosquamis (Richardson, 1848), Pagellus acarne (Risso, 1827) were also investigated.