bluuebunny/crossref_metadata_2025_split huggingface dataset:
Hyperthyroidism and suicide: a retrospective cohort study in Sweden
Authors: Abraham-Nordling Mirna , Lönn Stefan , Wallin Göran , Yin Li , Nyren Olof , Tullgren Owe , Hall Per , Törring Ove 
Published: January 2009

ObjectivesMental symptoms and impaired quality of life commonly occur in patients treated for hyperthyroidism. Our aim was to determine whether a history of hyperthyroidism implies an increased risk of suicide.DesignHistoric cohort study of 43 633 patients treated with radioiodine or surgery for hyperthyroidism between 1950 and 2005. The majority of the radioiodine-treated patients came from Stockholm. Two comparison cohorts consisted of 44 921 patients registered with an operation for atoxic nodular goitre between 1965 and 2005, and 354 861 patients with a cholecystectomy between 1965 and 2001.MethodsSubjects were followed from the date of diagnosis until death, emigration or end of follow-up. Information on outcome was obtained from population and health registers.ResultsThe number of observed suicide deaths was 134 in the study cohort. A naive comparison with the age-, sex- and calendar period-matched general Swedish population yielded a moderately increased standardized mortality ratio (SMR), but stratifications revealed that the excess was mainly driven by women from Stockholm, whose baseline suicide risk was higher than for women in the rest of Sweden. Using the population rates from Stockholm, the SMR among Stockholm women with Graves' disease was 1.14 (95% confidence intervals (CI) 0.66–1.86) and toxic goitre 0.99 (95% CI 0.51–1.72). A direct comparison between the study cohort and the combined comparison cohorts, with multiple adjustments (including adjustment for residence in Stockholm), yielded a relative risk of suicide of 0.93 (0.68–1.26).ConclusionsThis study did not confirm an increased risk of suicide among patients treated for hyperthyroidism.
Electrochemical Applications of Acoustic Streaming Generated by a Focused Ultrasonic Source
Authors: Stefan Ionel C. , Greber Isaac , Zanelli Claudio I. , Scherson Daniel A. 
Published: January 2009

AbstractVarious aspects of mass transport toward a static disk electrode embedded in a planar surface in the presence of convective flow induced by a focused ultrasonic source have been examined by electrochemical means using the reduction of solution phase [Fe(CN)6]3‐− in an aqueous electrolyte as a probe redox reaction. Experiments were performed by placing the main axis of the acoustic transducer normal to the plane of disk electrodes of various radii. The results obtained revealed that the limiting current for the reduction of [Fe(CN)6]3‐− is proportional to the acoustic power, Pac to the 3/8 power, and also to the concentration of the redox active species in the electrolyte. Numerical calculations based on Kamakura's formalism (Kamakura, T. et al. J. Acoust. Soc. Am., 1995, 97, 2740–2746) have shown that the axial velocity induced at the focal point of the source is proportional to the square root of the acoustical pressure. On this basis, the behavior of the system under the conditions employed is analogous to that of the jet impinging electrode geometry in the wall jet regime.
Deposition of Gold Nanoparticles on Thin Polyaniline Films
Authors: Sheffer Marisa , Martina Virginia , Seeber Renato , Mandler Daniel 
Published: January 2009

AbstractLocal and bulk deposition of gold particles was accomplished by the spontaneous reaction between chemically reduced polyaniline (PAN) thin films and AuCl. PAN layers were deposited on glass, indium tin oxide (ITO), and glassy carbon (GC) by the Langmuir–Blodgett method and spin‐coating. Characterization of the PAN films was carried out by microscopy, UV–vis spectroscopy, and electrochemistry. We found that the nature of the gold deposit was greatly affected by the thickness of the PAN.Scanning electrochemical microscopy was used as a means of locally depositing gold nanoparticles on an unbiased PAN film by anodically dissolving a gold micro‐electrode. This represents a generic approach whereby a variety of metal micro‐ and nanoparticles can be locally deposited on insulating supports.
Streamline-Assisted Ensemble Kalman Filter for Rapid and Continuous Reservoir Model Updating
Authors: Arroyo-Negrete Elkin , Devegowda Deepak , Datta-Gupta Akhil , Choe J. 
Published: January 2009

Summary
The use of the ensemble Kalman filter (EnKF) is a promising approach for data assimilation and assessment of uncertainties during reservoir characterization and performance forecasting. It provides a relatively straightforward approach to incorporating diverse data types, including production and/or time-lapse seismic data. Unlike traditional sensitivity-based history matching methods, the EnKF relies on a cross-covariance matrix computed from an ensemble of reservoir models to relate reservoir properties to production data. For practical field applications, we need to keep the ensemble size small for computational efficiency. However, this leads to poor approximations of the cross-covariance and, often, loss of geologic realism through parameter overshoots, in particular by introducing localized patches of low and high permeabilities. Because the EnKF estimates are "optimal" only for Gaussian variables and linear dynamics, these difficulties are compounded by the strong nonlinearity of the multiphase history matching problems and for non-Gaussian prior models. Specifically, the updated parameter distribution tends to become multi-Gaussian with loss of connectivities of extreme values, such as high permeability channels and low permeability barriers, which are of special significance during reservoir characterization.
We propose a novel approach to overcome some of these limitations by conditioning the cross-covariance matrix using information gleaned from streamline trajectories. Our streamline-assisted EnKF is analogous to the conventional assisted history matching, whereby the streamline trajectories are used to identify gridblocks contributing to the production response of a specific well. We then use these gridblocks only to compute the cross-covariance matrix and eliminate the influence of unrelated or distant observations and spurious correlations. We show that the streamline-assisted EnKF is an efficient and robust approach for history matching and continuous reservoir model updating. We illustrate the power and utility of our approach using both synthetic and field applications.
Using Probabilistic Decision Trees to Detect Fracture Corridors From Dynamic Data in Mature Oil Fields
Authors: Ozkaya S. I. 
Published: January 2009

Summary
This paper describes the procedure of building a probabilistic decision tree on the basis of the integration of data from multiple sources, conditional probabilities, and the application to map fracture corridors (FCs) in a mature oil field with abundant production data. An FC is a tabular, subvertical, fault-related fracture swarm that intersects the entire reservoir and extends laterally for several tens or hundreds of meters. Direct indicators of FCs, such as image logs, flow profiles, well tests, and seismic fault maps, are sometimes insufficient to map all FCs in a field. It is also necessary to use indirect FC indicators from well data, such as productivity index (PI), gross rate, water cut, and openhole logs. FCs from indirect indicators can be inferred by a probabilistic decision tree, which makes predictions by integrating data from multiple sources, giving preference to the indicators with the highest relevance. Decision trees are constructed by use of a training set that includes measurements of both direct and indirect FC indicators. In this study, wells with borehole images, production logs (flow profiles), and injector/producer short cuts are selected as the training set. The resulting decision trees reveal that total losses, gross production rates, and water cuts are the three most effective indirect indicators of fracture corridors in the test field.
Using Drillstem and Production Tests To Model Reservoir Relative Permeabilities
Authors: Matthews John D. , Carter Jonathan N. , Zimmerman Robert W. 
Published: January 2009

Summary
Relative permeabilities are fundamental to any assessment of reserves and reservoir management. When measurements on core samples are available, however, they often predict initial water production that is not experienced by individual wells. For example, dry oil production occurs from portions of reservoirs where the local water saturation is relatively high, even though the relative permeability data would predict a water cut in the range of 30 to 60%. This lack of agreement means that effective reservoir management is hampered because it is difficult for simulation models to mimic the observed reservoir production without use of data that may bear little resemblance to measurements.
After a brief discussion of relative permeability, the focus of this paper is first to examine the uncertainties in the data that are used for the predictions. This then provides a numerically structured approach to adjustments that need to be made to data so that history matching of simulation models can be achieved. The relative permeabilities, rather than saturations and fluid properties, are shown to be the least certain of the relevant data.
The second focus in the paper is to explore the reasons why the relative permeability data are so uncertain. The evidence points to the fact that oil emplacement and the subsequent geological history of the reservoirs have not been considered sufficiently in preparing core samples before making measurements. Greater reliance on drillstem and early production tests is, therefore, crucial for deriving reservoir relative permeabilities until laboratories are able to mimic oil emplacement within rock samples as experienced in the reservoir.
The main source of data is the abandoned UK North Sea reservoir Maureen (Block 16/29a). Inevitably, during the 36 years since discovery, some data have been misplaced. Nevertheless, sufficient data exist to highlight the potential need for a paradigm shift in understanding how relative permeabilities should be obtained for reservoir simulation.
Recovery Factors in High-Pressure Air Injection Projects Revisited
Authors: Gutiérrez D. , Taylor A. R. , Kumar V. K. , Ursenbach M. G. , Moore R. G. , Mehta S. A. 
Published: January 2009

Summary
High-pressure air injection (HPAI) is an improved-oil-recovery (IOR) process in which compressed air is injected into a deep light-oil reservoir with the expectation that the oxygen in the injected air will react with a fraction of the reservoir oil at an elevated temperature to produce carbon dioxide. The resulting flue-gas mixture provides the main mobilizing force to the oil downstream of the reaction region, sweeping it to production wells. The combustion zone itself may provide a critical part of the sweep mechanism.
In 1994, Fassihi et al. proposed a method for estimating recovery factors of light-oil air-injection projects on the basis of the performance of two successful HPAI projects. Their suggested method relies on the extrapolation of the field gas/oil ratio (GOR) up to an economic limit. In other words, it treats HPAI as an immiscible gasflood and neglects any potential oil that could be recovered by the combustion front. The truth is that, although early production during an HPAI process is caused mostly by repressurization and gasflood effects, once a pore volume of air has been injected, the combustion front becomes the main driving mechanism. Moreover, one of the unique features of air injection is the self-correcting nature of the combustion zone, which promotes good volumetric sweep of the reservoir.
This paper presents laboratory and field evidence of the presence of a thermal front during HPAI operations and evidence of its beneficial impact on oil recovery. An analysis of the three HPAI projects in Buffalo field, which are the oldest HPAI projects currently in operation, shows that only a small fraction of the reservoir has been burned and, if time allows and the projects are managed appropriately, burning of more reservoir volumes could result in much higher oil recoveries than those predicted by the gasflood approach.
The Application of Unstructured-Gridding Techniques for Full-Field Simulation of a Giant Carbonate Reservoir Developed With Long Horizontal Wells
Authors: Vestergaard H. , Olsen H. , Sikandar A. S. , Noman R. 
Published: January 2009

Summary
This paper presents a gridding study relating to reservoir simulation of a giant, complex, low-permeability carbonate reservoir developed with 75 ultraong horizontal wells in a densely spaced alternating injector/producer pattern.
The lateral magnitude of the Al Shaheen field in Qatar and the radial layout of the multiple ultralong horizontal wells in the field posed a challenge in modeling of individual well performance using a manageable grid size with an acceptable run time for history matching. Reservoir modeling was complicated further by the complex reservoir characteristics with a tilting free-water level (FWL), separate gas caps, large lateral variations in oil properties, and wettability-dependent flow characteristics. These features had to be incorporated into the initialization and dynamic modeling of the reservoir, which added further to the memory requirements of the simulation model.
This paper describes the process of selecting a suitable simulation grid for history matching the performance of this reservoir on a full-field basis. Conventional Cartesian gridding techniques, including the use of local grid refinements (LGRs) in areas of interest, were pursued initially but were shown to be inadequate for full-field modeling of this complex reservoir. The gridding problem was solved by the use of 2.5D perpendicular-bisector (PEBI) grids around each of the horizontal wells in the field. This allowed for sufficient resolution between wells and also aligned the grid with the well paths, thereby avoiding grid nonorthogonality issues.
The efficiency of the PEBI model was also demonstrated by the comparison of CPU performances. Run times for the full-field PEBI model were equivalent to that of a conventional Cartesian model with suitable local grids covering only 20% of the wells. Both models had approximately 700,000 active cells and required 3-4 GB of memory. A full-field model relying on conventional LGRs around all wells was not built because it would involve significantly more grid cells and, therefore, would become considerably slower and require more memory.
A Parametric Study on the Benefits of Drilling Horizontal and Multilateral Wells in Coalbed Methane Reservoirs
Authors: Maricic Nikola , Mohaghegh Shahab D. , Artun Emre 
Published: January 2009

Summary
Recent years have witnessed a renewed interest in development of coalbed methane (CBM) reservoirs. Optimizing CBM production is of interest to many operators. Drilling horizontal and multilateral wells is gaining popularity in many different coalbed reservoirs, with varying results. This study concentrates on variations of horizontal-and multilateral-well configurations and their potential benefits.
In this study, horizontal and several multilateral drilling patterns for CBM reservoirs are studied. The reservoir parameters that have been studied include gas content, permeability, and desorption characteristics. Net present value (NPV) has been used as the yard stick for comparing different drilling configurations. Configurations that have been investigated are single-, dual-, tri-, and quad-lateral wells along with fishbone (also known as pinnate) wells. In these configurations, the total length of horizontal wells and the spacing between laterals (SBL) have been studied. It was determined that in the cases that have been studied in this paper (all other circumstances being equal), quadlateral wells are the optimum well configuration.
Seismic Facies Identification and Classification Using Simple Statistics
Authors: John Abraham K. , Lake Larry W. , Torres-Verdin Carlos , Srinivasan Sanjay 
Published: January 2009

Summary
The identification and mapping of rock facies is important to reliable reservoir characterization. Traditionally, facies identification and mapping are based on inspection of core data and/or well-log signatures, a procedure that has subjective aspects because it is relies on samples from only a very small portion of the reservoir. Such identification is also difficult to perform at the onset of the exploration stage because of lack of sufficient well data. This paper demonstrates a simple practical approach to identify and classify facies from seismic-amplitude data using basic statistical concepts.
Within a geologic facies, measured properties [in this case acoustic impedance (AI)] are assumed to differ mainly as a result of random additive events and are modeled by a normal distribution, as justified by the central-limit theorem. The facies are identified by estimating the combination of facies volume fractions and distribution parameters (means and standard deviations of the facies probability-density function) that best fit the population distribution of AI. A simple form of Bayes theorem is then used to compute the probability of occurrence of each of the facies at the measured locations. This generates a volume of facies probabilities corresponding to the seismic volume. Such a volume can be used to perform facies-specific petrophysical analysis or be a starting point to generate multiple realizations of petrophysical properties. The approach is simple and transparent to use, with no significant computational requirements even on large data sets.
We describe an application of the procedure to a synthetic reference data set and a Gulf of Mexico AI data set. Mapped probabilities of the individual facies show the spatial continuity and geologic character of the underlying depositional environment. Property values within the mapped regions are substantially less variable than the original data across the entire region. The within-facies semivariograms exhibit much less spatial correlation than across all facies. Since the facies are mapped across an exhaustive data volume, this approach considerably reduces the need for the geostatistical construction of property distributions within them as long as a high correlation exists between the seismic attribute and petrophysical properties.
Effects of Self-Management Support on Structure, Process, and Outcomes Among Vulnerable Patients With Diabetes
Authors: Schillinger Dean , Handley Margaret , Wang Frances , Hammer Hali 
Published: January 2009

OBJECTIVE
Despite the importance of self-management support (SMS), few studies have compared SMS interventions, involved diverse populations, or entailed implementation in safety net settings. We examined the effects of two SMS strategies across outcomes corresponding to the Chronic Care Model.

RESEARCH DESIGN AND METHODS
A total of 339 outpatients with poorly controlled diabetes from county-run clinics were enrolled in a three-arm trial. Participants, more than half of whom spoke limited English, were uninsured, and/or had less than a high school education, were randomly assigned to usual care, interactive weekly automated telephone self-management support with nurse follow-up (ATSM), or monthly group medical visits with physician and health educator facilitation (GMV). We measured 1-year changes in structure (Patient Assessment of Chronic Illness Care [PACIC]), communication processes (Interpersonal Processes of Care [IPC]), and outcomes (behavioral, functional, and metabolic).

RESULTS
Compared with the usual care group, the ATSM and GMV groups showed improvements in PACIC, with effect sizes of 0.48 and 0.50, respectively (P &lt; 0.01). Only the ATSM group showed improvements in IPC (effect sizes 0.40 vs. usual care and 0.25 vs. GMV, P &lt; 0.05). Both SMS arms showed improvements in self-management behavior versus the usual care arm (P &lt; 0.05), with gains being greater for the ATSM group than for the GMV group (effect size 0.27, P = 0.02). The ATSM group had fewer bed days per month than the usual care group (−1.7 days, P = 0.05) and the GMV group (−2.3 days, P &lt; 0.01) and less interference with daily activities than the usual care group (odds ratio 0.37, P = 0.02). We observed no differences in A1C change.

CONCLUSIONS
Patient-centered SMS improves certain aspects of diabetes care and positively influences self-management behavior. ATSM seems to be a more effective communication vehicle than GMV in improving behavior and quality of life.
Changes in Albumin Excretion in the Diabetes Prevention Program
Authors:   Diabetes Prevention Program Research Group
Published: January 2009

OBJECTIVE
Increased urinary albumin excretion rates have been linked to nephropathy and macrovascular disease. We here describe the baseline prevalence and effect of Diabetes Prevention Program (DPP) interventions on the development and reversal of elevated albumin excretion.

RESEARCH DESIGN AND METHODS
Urine albumin-to-creatinine ratios (ACRs) were calculated from untimed urine collections. Analyses compared participants by treatment group, diabetes and hypertension status, and use of ACE inhibitors or angiotensin II receptor blockers (ARBs).

RESULTS
Elevated ACR levels (≥30 mg/g creatinine) were present at baseline in 198 (6.2%) of 3,188 participants: placebo 5.3%, metformin 6.5%, and intensive lifestyle (ILS) 6.8%. Of the 2,802 with ACR measurements at baseline and at the end of the study, the percentage with elevated levels declined (incident and regression) from 6.2 to 6.1%, with no significant differences between the groups even with adjustment for ACE inhibitor and ARB use. The odds of developing an elevated ACR were 59% higher for a participant who developed diabetes compared with one who did not.

CONCLUSIONS
At entry into the DPP, an elevated ACR was present in 6.2%. Despite the marked decrease in progression to diabetes and the improvement in insulin resistance and other cardiovascular risk markers in the ILS and metformin groups, there was no improvement in ACR, on average, in those two groups. However, the frequency of an elevated ACR was higher in participants who developed diabetes. An increased ACR may have multiple causes, thus obscuring the improvements that might have been expected with the reduction in insulin resistance seen in the DPP.