No description available.

Background: Cellulitis is a common infectious disease. Although blood culture is frequently used in the diagnosis and subsequent treatment of cellulitis, it is a contentious diagnostic test. To help clinicians determine which patients should undergo blood culture for the management of cellulitis, a diagnostic scoring system referred to as the Bacteremia Score of Cellulitis was developed. Methods: Univariable and multivariable logistic regression analyses were performed as part of a retrospective cohort study of all adults diagnosed with cellulitis in a tertiary teaching hospital in Taiwan in 2013. Patients who underwent blood culture were used to develop a diagnostic prediction model where the main outcome measures were true bacteremia in cellulitis cases. Area under the receiver operating characteristics curve (AUC) was used to demonstrate the predictive power of the model, and bootstrapping was then used to validate the performance. Results: Three hundred fifty one cases with cellulitis who underwent blood culture were enrolled. The overall prevalence of true bacteremia was 33/351 cases (9.4 %). Multivariable logistic regression analysis showed optimal diagnostic discrimination for the combination of age >= 65 years (odds ratio [OR] = 3.9; 95 % confidence interval (CI), 1.5-10.1), involvement of non-lower extremities (OR = 4.0; 95 % CI, 1.5-10.6), liver cirrhosis (OR = 6.8; 95 % CI, 1.8-25.3), and systemic inflammatory response syndrome (SIRS) (OR = 15.2; 95 % CI, 4.8-48.0). These four independent factors were included in the initial formula, and the AUC for this combination of factors was 0.867 (95 % CI, 0.806-0.928). The rounded formula was 1 x (age >= 65 years) + 1.5 x (involvement of non-lower extremities) + 2 x (liver cirrhosis) + 2.5 x (SIRS). The overall prevalence of true bacteremia (9.4 %) in this study could be lowered to 1.0 % (low risk group, score <= 1.5) or raised to 14.7 % (medium risk group, score 2-3.5) and 41.2 % (high risk group, score >= 4.0), depending on different clinical scores. Conclusions: Determining the risk of bacteremia in patients with cellulitis will allow a more efficient use of blood cultures in the diagnosis and treatment of this condition. External validation of this preliminary scoring system in future trials is needed to optimize the test.

The thesis describes a method for predicting avalanche activity in Scotland, based primarily on meteorological and topographical data, and this is incorporated into a framework for avalanche forecasting. A literature review identifies the main meteorological and topographical factors causing avalanche release. Snow accumulation, cold temperatures or thaws are identified as the major meteorological factors causing avalanches, and the thesis so distinguishes two basic avalanche types---the direct-action avalanche caused by fresh snow accumulation, and the climax avalanche caused by temperature changes. Slope angle, surface roughness, slope geometry and catchment area are identified as the major topographical controls on the location of avalanche activity. The thesis presents data on avalanche activity in Scotland over the last two hundred and eighty years, with particular emphasis on the Cairngorm Mountains. Avalanche locations, types and magnitudes for almost a thousand avalanches are described. Data on Scottish weather and terrain conditions are also presented, also with particular emphasis on the Cairngorm area. Major periods of snow accumulation, cold temperatures and thaws are identified between the winters of 1977/78 and 1979/80, and the location of steep slopes, smooth surfaces and large catchment areas in the Cairngorms is described. Data on the characteristics of the Scottish snow cover, based on work performed in the Cairngorms by E. Langmuir, B. Beattie and the author are then presented. Correlations between avalanche activity and meteorological, topographical and glaciological conditions are demonstrated, and this enables a predictive model to be developed which assesses avalanche probability on the basis of the amount of fresh snowfall and the prevailing temperature. Fresh snowfall of 200 mm., and either several days of cold weather with maximum temperatures below -4&deg;C or two or three days of warm weather with maximum temperatures above 0&deg;C lead to avalanche activity. The model can be continually up-dated and permits a continuous avalanche probability assessment to be made.

No description available.

Sorghum ergot, caused by Claviceps africana Frederickson, Mantle & de Milliano, is a disease that affects non-fertilized ovaries in sorghum male-sterile plants and infects hybrids if there is pollen sterility at flowering time. Sphacelia containing macroconidia could play a role in the survival of the pathogen. This study developed risk assessment models and evaluated environmental conditions affecting viability of macroconidia and transition from sphacelial to sclerotial tissues. Effect of weather on ergot severity was evaluated under natural conditions (in monthly planting dates) in nine sorghum genotypes at College Station, Weslaco, Rio Bravo, and Celaya. Panicles were inoculated daily beginning at flower initiation with a suspension of 1.6 x 106 C. africana conidia ml-1. Weather triad values were used to identify weather parameters correlated with the disease. Ergot severity was statistically greater in A-lines than hybrids because of the possible interference of pollen on some dates. Celaya had the greatest amount of ergot in hybrids. A-line ATx2752 had the lowest average ergot severity throughout years, locations and planting dates, as did the hybrid NC+8R18. Maximum and minimum temperature had a negative correlation with ergot at Rio Bravo, College Station and Weslaco, while at Celaya it was positive. The highest correlation was 7 to 9 days before initiation of flowering, suggesting that cooler temperatures during this period could cause male sterility. A-lines showed the same relationships between ergot and maximum and minimum temperatures after initiation of flowering. Minimum relative humidity had a positive correlation with ergot after initiation of flowering in both sorghum plant types. Sphacelia stored under cool temperatures (-3oC to 7oC) maintained conidial viability, and newly-formed sphacelia located on the sphacelia surface had the highest conidial viability. However, they show a greater viability reduction through time compared with conidia from older sphacelia, showing that conidial maturity can play a role in the survival of the conidia. Sphacelia on plants grown at 10oC, 20oC and 30oC with low relative humidity did not had any sclerotial development up to 4 weeks after formation of sphacelia. However, higher temperatures promoted an increase in the sphacelia dry weight during that time.

No description available.

Fracture diagnostics is a key technology for well performance prediction of a horizontal well in a shale reservoir. The combination of multiple fracture diagnostic techniques gives reliable results, and temperature data has potential to provide more reliability on the results. In this work, we show an application of a temperature prediction model for a horizontal well with multiple hydraulic fractures in order to investigate the possibility of evaluating reservoir and hydraulic fracture parameters using temperature data. The model consists of wellbore model and reservoir model. The wellbore model was formulated based on mass, momentum and energy balance. The reservoir flow model was solved by a numerical reservoir simulation, and the reservoir thermal model was formulated by transient energy balance equation considering viscous dissipation heating and temperature variation caused by fluid expansion besides heat conduction and convection. The reservoir flow and reservoir thermal model were coupled with the wellbore model to predict temperature distribution in a horizontal well considering boundary conditions at the contact of reservoir and wellbore. In the reservoir system, primary hydraulic fractures which are transverse to the horizontal well were modeled with thin grid cells explicitly, and the hydraulically-induced fracture network around the horizontal well was modeled as higher permeable zone to unstimulated matrix zone. The reservoir grids between two primary fractures were logarithmically spaced in order to capture transient flow behavior. We applied the model to synthetic examples: horizontal well with identical five fractures and with different five fractures. The results show two fundamental mechanisms: heat conduction between formation and wellbore fluid at non-perforated zone, and wellbore fluid mixing effect at each fracture. The synthetic example with identical fractures shows that fracture locations affect wellbore temperature distribution because of fluid mixing effect between reservoir inflow and wellbore fluid. And also, the synthetic example with different fractures shows that the fracture heterogeneity causes different magnitude of temperature change due to inflow variation per fracture. In addition, the model was applied to synthetic examples without network fracture region in order to find the effects by the network. It reveals that under constant rate condition, network fracture masks large temperature change due to small pressure change at the contact between fracture and formation, and that under constant BHP condition, network fracture augments temperature change with the increase of flow rate in wellbore and inflow rate from reservoir. Sensitivity studies were performed on temperature distribution to identify influential parameters out of the reservoir and hydraulic fracture parameters including reservoir porosity, reservoir permeability, fracture half-length, fracture height, fracture permeability, fracture porosity, fracture network parameters, and fracture interference between multiple clusters. In this work, in order to find contributions by a target fracture, temperature change sensitivity is evaluated. Single fracture case reveals that fracture permeability, network fracture parameters and fracture geometries are primary influential parameters on temperature change at the fracture location. And also, multiple fractures case shows that temperature change is augmented with the increase of fracture geometry and is decreased with the increase of fracture permeability. These results show the possibility of using temperature to determine these sensitive parameters, and also the quantified parameter sensitivities provide better understandings of the temperature behavior of horizontal well with multiple fractures.

No description available.

Invasions of exotic species are one of the primary causes of biodiversity loss on our planet (National Research Council 1995). In the marine environment, all habitat types including estuaries, coral reefs, mud flats, and rocky intertidal shorelines have been impacted (e.g. Bertness et al. 2001). Recently, the topic of invasive species has caught the public's attention. In particular, there is worldwide concern about the aquarium strain of the green alga Caulerpa taxifolia (Vahl) C. Agardh that was introduced to the Mediterranean Sea in 1984 from the Monaco Oceanographic Museum. Since that time, it has flourished in thousands of hectares of near-shore waters. More recently, C. taxifolia has invaded southern Californian and Australian waters. Since the waters of Florida are similar to the waters of the Mediterranean Sea and other invasive sites my study will focus on determining potential invasion locations in Florida. I will look at the present distribution of C. taxifolia - native strain in Florida as well as the distribution of the whole genus around the state. During this study, I address three questions: 1) What is the current distribution of Caulerpa spp. in Florida? 2) Can I predict the location of potential Caulerpa spp. invasions using a set of environmental parameters and correlate them to the occurrence of the algae with the support of Geographic Information System (GIS) maps? 3) Using the results of part two, is there an ecological preferred environment for one or all Caulerpa spp. in Florida? To answer these questions, I surveyed 24 areas in each of 6 zones chosen in a stratified manner along the Floridian coastline to evaluate the association of potential indicators Caulerpa. Latitude, presence or absence of seagrass beds, human population density, and proximity to marinas were chosen as the 4 parameters expected to correlate to Caulerpa occurrences. A logistic regression model assessing the association of Caulerpa occurrence with measured variables has been developed to predict current and future probabilities of Caulerpa spp. presence throughout the state. Fourteen different species of Caulerpa spp. were found in 26 of the 132 sites visited. There was a positive correlation between Caulerpa spp. and seagrass beds presence and proximity to marinas. There was a negative correlation with latitude and human population density. C. taxifolia – aquarium strain wasn't found. Percent correct for our model was of 61.5% for presence and 98.1% for absence. This prediction model will allow us to focus on particular areas for future surveys.

Water distribution utilities are responsible for supplying both clean and safe drinking water, while under constraints of operating at an efficient and acceptable performance level. The City of Kingston, Ontario is currently experiencing elevated costs to repair its aging buried water main assets. Utilities Kingston is opting for a more efficient and practical means of forecasting pipe breaks and the application of a predictive water main break models allows Utilities Kingston to forecast future pipe failures and plan accordingly. The objective of this thesis is to develop an artificial neural network (ANN) model to forecast pipe breaks in the Kingston water distribution network. Data supplied by Utilities Kingston was used to develop the predictive ANN water main break model incorporating multiple variables including pipe age, diameter, length, and surrounding soil type. The constructed ANN model from historical break data was utilized to forecast pipe breaks for 1-year, 2-year, and 5-year planning periods. Simulated results were evaluated by statistical performance metrics, proving the overall model to be adequate for testing and forecasting. Predicted breaks were as follows, 33 breaks for 2011-2012, 22 breaks for 2012-2013 and 35 breaks for 2013-2016. Additionally, GIS plots were developed to highlight areas in need of potential rehabilitation for the distribution system. The goal of the model is to provide a practical means to assist in the management and development of Kingston’s pipe rehabilitation program, and to enable Utilities Kingston to reduce water main repair costs and to improve water quality at the customer's tap. / Thesis (Master, Civil Engineering) -- Queen's University, 2013-10-21 15:30:10.288