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We perform a set of reactive transport simulations in three‐dimensional fracture networks to characterize the impact of geochemical reactions on flow channelization. Flow channelization, a frequently observed phenomenon in porous and fractured subsurface rock formations, results from the spatially variable hydraulic resistance offered by a geological structure. In addition to geo‐structural features such as network connectivity, geometry, and hydraulic resistance, geochemical reactions, for example, dissolution and precipitation, can dynamically inhibit or enhance flow channelization. These geochemical processes can change the fracture permeability leading to increased flow channelization, which are localized connected regions of high volumetric flow rates that are seemingly ubiquitous in the subsurface. In our simulations, fractures partially filled with quartz are gradually dissolved until quasi‐steady state conditions are obtained. We compare the flow field's initial unreacted and final dissolved states in terms of flow and transport observations. We observe that the dissolved fracture networks provide less resistance to flow and exhibit increased flow channelization when compared to their unreacted counterparts. However, there is substantial variability in the magnitude of these changes which implies that the channelization strongly depends on the network structure. In turn, we identify the interplay between the particular network structure and the impact of geochemical dissolution on flow channelization. The presented results indicate that geological systems that have been weathering or reactive for longer times in older landscapes are likely to have increased flow channelization compared to their equivalent but younger counterparts, which implies a time dependence on flow channelization in fractured media. Plain Language Summary: Fractures are the primary pathways for fluid flow and solute transport in Earth's subsurface. In many of these systems, fluids passing through the fractures are out of equilibrium with the resident minerals, and various geochemical reactions occur. These geochemical processes can change the resistance to flow offered by the fractures, leading to increased flow channelization, which are localized connected regions of high flow rates. However, quantification of these impacts has been limited to the computational burden of performing requisite simulations. Through a series of reactive transport simulations in fractured media, we characterize the influence of dissolution on flow channelization using observations of flow and transport properties. We compare flow and transport in the initial unreacted state and in the final dissolved state to better understand how geochemical reactions influences the flow properties of the network medium. We observe that the unreacted fracture networks provide lower resistance to flow and exhibit increased flow channelization. The results suggest that older geological systems ought to have increased flow channelization when compared to their younger counterparts. Key Points: We characterize the impact of geochemical dissolution on flow channelization in fractured media using reactive transport simulationsWe observe that the dissolved fracture networks provide less resistance to flow and exhibit increased flow channelizationThere is a dissolution feedback loop between primary sub‐networks and geochemical reactions on flow channelization [ABSTRACT FROM AUTHOR]

Exploratory data analysis (EDA) for functional data—data objects where observations are entire functions—is a difficult problem that has seen significant attention in recent literature. This surge in interest is motivated by the ubiquitous nature of functional data, which are prevalent in applications across fields such as meteorology, biology, medicine and engineering. Empirical probability density functions (PDFs) can be viewed as constrained functional data objects that must integrate to one and be nonnegative. They show up in contexts such as yearly income distributions, zooplankton size structure in oceanography and in connectivity patterns in the brain, among others. While PDF data are certainly common in modern research, little attention has been given to EDA specifically for PDFs. In this paper, we extend several methods for EDA on functional data for PDFs and compare them on simulated data that exhibit different types of variation, designed to mimic that seen in real‐world applications. We then use our new methods to perform EDA on the breakthrough curves observed in gas transport simulations for underground fracture networks. [ABSTRACT FROM AUTHOR]

We model flow and transport in fracture networks with varying degrees of fracture‐to‐fracture aperture heterogeneity and network intensity to show how changes in these properties can cause the emergence of anomalous flow and transport behavior. If fracture‐to‐fracture aperture heterogeneity is increased in sparse networks, velocity fluctuations inhibit high flow rates and solute transport can be delayed. Surprisingly, transport can be slowed even in cases where hydraulic aperture is monotonically increased. As the intensity of the networks is increased, more connected pathways allow for particles to bypass these effects. There exists transition behavior where with relatively few connected pathways in a network, first arrival times of particles are not heavily affected by fracture‐to‐fracture aperture heterogeneity, but the scaling behavior of the tails is strongly influenced. These results reinforce the importance of considering multi‐scale effects in fractured systems and can inform flow and transport processes in both natural and engineered fractured systems. Plain Language Summary: Fractured rocks are important to study to understand subsurface geology, hydrology, and engineered systems. Individual fractures often form connected networks with other fractures, which complicates the prediction of flow and transport behavior. In this work, we study how changes in fracture network properties such as the variability of fracture apertures and the number of fractures in a network, affect flow and transport observables, such as the amount of actively flowing network structure, as well as the arrival times of solutes. Our results point to rich behavior where there is a close link between how much variability exists between individual fracture apertures, the network intensity, and the behavior of the solute transport. When fracture networks have relatively few fractures, increases in the magnitude of the fracture apertures and the variability between individual apertures can cause unusual changes in the flow and transport, causing delays in solute transport times. However, these effects are gradually lost as the number of fractures in the network is increased. Our results can inform both natural hydrological processes, as well as engineered systems, such as enhanced geothermal systems and hydraulic fracturing because these systems often create high aperture fractures that connect to natural fractures with lower aperture. Key Points: We investigate the influence of multi‐scale heterogeneity in fracture networks on flow and transport using discrete fracture network modelsHigh aperture heterogeneity across a sparse fracture network results in counter‐intuitive flow and transport behaviorEffects of fracture‐to‐fracture aperture heterogeneity are limited at high network intensities [ABSTRACT FROM AUTHOR]

Fractured reservoirs are complex and multi‐scale systems composed of matrix and fractures. Accordingly, modeling flow in such geological media has been a great challenge. In this study, we investigated the effect of scale as well as matrix and fracture network characteristics on the effective permeability (keff) in matrix‐fracture systems under fully saturated conditions. We generated fracture networks, embedded within a matrix of permeability of 10−18 m2, with fracture lengths followed a truncated power‐law distribution with exponent α = 1.5, 2.0, and 2.5. We set fracture permeability equal to 10−16, 10−14, and 10−12 m2 and numerically simulated fluid flow to determine the keff at six fracture densities for 36 fractured reservoirs. Results showed that the effect of α and scale on the keff became more significant as the contrast between matrix and fracture permeabilities increased. We also fit the percolation‐based effective‐medium approximation (P‐EMA) to the simulations and optimized its two parameters critical fracture density and scaling exponent. Results exhibited that both P‐EMA model parameters were scale‐dependent. Through linear regression analysis, we found that the critical fracture density and scaling exponent were highly correlated to other matrix‐fracture system properties and proposed two regression‐based models evaluated using a new six sets of simulations. Comparing the estimated keff values with the simulated ones demonstrated the reliability and predictability of the P‐EMA. The matrix‐fracture systems studied here were finite in size. We also showed that one may extend results to infinitely large reservoirs using the P‐EMA framework. Key Points: Scale‐dependent effective permeability in matrix‐fracture systems is investigated using numerical simulations and theoretical modelingCritical fracture density and scaling exponent are linked to reservoir properties and its size, and results are extended to large systemsTheoretical estimations of effective permeability in six unseen fractured reservoirs agree with numerical simulations well [ABSTRACT FROM AUTHOR]

Understanding mechanistic causes of non‐Fickian transport in fractured media is important for many hydrogeologic processes and subsurface applications. This study elucidates the effects of dead‐end fractures on non‐Fickian transport in three‐dimensional (3D) fracture networks. Although dead‐end fractures have been identified as low‐velocity regions that could delay solute transport, the direct relation between dead‐end fractures and non‐Fickian transport has been elusive. We systematically generate a large number of 3D discrete fracture networks with different fracture length distributions and fracture densities. We then identify dead‐end fractures using a novel graph‐based method. The effect of dead‐end fractures on solute residence time maximizes at the critical fracture density of the percolation threshold, leading to strong late‐time tailing. As fracture density increases beyond the percolation threshold, the network connectivity increases, and dead‐end fractures diminish. Consequently, the increase in network connectivity leads to a reduction in the degree of late‐time tailing. We also show that dead‐end fractures can inform about main transport paths, such as the mean tortuosity of particle trajectories. This study advances our mechanistic understanding of solute transport in 3D fracture networks. Plain Language Summary: A critical phenomenon often observed in fractured rocks is an anomalously slow decay of solute concentration, which is often called solute tailing. Long retention of solute contaminants poses severe threats to human health, and predicting solute tailing is critical for remediation purposes. However, solute tailing is challenging to predict, and understanding the mechanisms inducing solute tailing is important for improving our predictive capability. Recent studies showed that dead‐end fractures form slow‐flow regions that could cause solute tailing. However, no study has explicitly quantified the effects of dead‐end fractures on solute tailing. By simulating flow and transport in three‐dimensional fracture networks over more than 200 realizations, we find that the relationship between fracture density and dead‐end fracture formation is non‐monotonic. Specifically, we observe that there exists a critical level of fracture density where the presence of dead‐end fractures is maximized. At the optimum level, solute particles' residence time in dead‐end fractures significantly increases, leading to strong solute tailing. As fracture density increases beyond the optimum, dead‐end fractures diminish due to the improved network connectivity, reducing solute tailing. This study improves our mechanistic understanding of how dead‐end fractures control solute tailing in fracture networks. Key Points: A new graph‐based measure that identifies dead‐end fractures is proposedLate‐time solute tailing is maximized at the percolation thresholdThe density of dead‐end fractures is a good predictor of non‐Fickian transport [ABSTRACT FROM AUTHOR]

Field measurements of apparent geochemical weathering reaction rates in subsurface fractured porous media are known to deviate from laboratory measurements by multiple orders of magnitude. To date, there is no geologically based explanation for this discrepancy that can be used to predict reaction rates in field systems. Proposed correction factors are typically based on ad hoc characterizations related to geochemical kinetic models. Through a series of high‐fidelity reactive transport simulations of mineral dissolution within explicit 3D discrete fracture networks, we are able to link the geo‐structural attributes with reactive transport observations. We develop a correction factor to linear transition state theory for the prediction of the apparent dissolution rate based on measurable geological properties. The modified rate law shows excellent agreement with numerical simulations, indicating that geological structure could be a primary reason for the discrepancy between laboratory and field observations of apparent dissolution rates in fractured media. Plain Language Summary: Fractures are the principal conduits for fluid flow through low permeability rock in the Earth's subsurface. In many of these systems, fluids passing through the fractures are out of equilibrium with the resident minerals, and various reactions, such as dissolution and precipitation, occur. These geochemical processes change the fracture permeability and drive fracture propagation, thereby dynamically changing flows. Field measurements of apparent geochemical weathering reaction rates are lower than laboratory measurements by multiple orders of magnitude, which makes predictions of geochemical reaction rates highly uncertain. These slow apparent dissolution rates are particularly pronounced in fracture networks where geo‐structural attributes, for example, the network connectivity and fracture geometry, determine the flow field structure and dictate transport. Through a series of high‐fidelity reactive transport simulations of mineral dissolution in fractured media, we uncovered a new link between the geo‐structural attributes of the underlying fracture network with reactive transport observations. Guided by this information, we develop a correction factor to linear transition state theory to predict the apparent dissolution rate that is based on these geological attributes. The excellent agreement of the proposed model with our numerical simulations indicates that geological structure could be one of the reasons for the commonly observed discrepancy. Key Points: Observations of apparent reaction rates in fractured media are orders of magnitude lower than those measured in laboratory conditionsReactive transport simulations are used to characterize the influence of 3D fracture network structure on apparent dissolution ratesA geo‐structurally based modification to linear transition state theory for the prediction of the apparent dissolution rate is presented [ABSTRACT FROM AUTHOR]

We incorporate observations of real fracture aperture variability observed in laboratory experiments into an ensemble of three‐dimensional discrete fracture network (DFN) simulations to characterize how variations of this micro‐scale feature can influence flow and transport behavior at the network scale. A shear fracture is created within a Marcellus shale sample, and the fracture aperture is measured using a triaxial direct‐shear device coupled with real‐time X‐ray imaging at in‐situ stress conditions. We construct an ensemble of fracture networks based on natural fractures in Marcellus shale and project regions of the experimental aperture field onto each fracture in the networks. Our calculations demonstrate that the degree of flow channelization, a network‐scale flow field structure, is dramatically increased by local changes in the aperture field that in turn affects flow and transport properties. Plain Language Summary: Fluid flow and solute transport through subsurface fractured media are inherently multi‐scale phenomena. Individual fractures connect to form complicated networks where relevant length scales span multiple orders of magnitude. In this letter, we address a long‐standing question in this research area regarding the relative impact of micro‐scale heterogeneity of fracture roughness, that is, internal aperture variability, on flow and transport at the network macro‐scale. To do so, we developed a methodology to incorporate real apertures obtained from in‐situ observations of dynamically fractured laboratory specimens into three‐dimensional discrete fracture network simulations for the first time. This methodology allows us to characterize how variations in fracture aperture can lead to increased flow channelization at the network scale, a phenomenon that we refer to as scale‐bridging. Our results show that this natural aperture variability not only modifies the local flow field within a single fracture but can re‐structure the global flow field of the entire network. In turn, the distribution of solute transport behavior is drastically modified, the networks' active surface area is drastically decreased, and the degree of flow channelization is markedly increased compared to reference networks that use equivalent smooth fractures. Key Points: We incorporate X‐ray imaged fracture apertures, obtained at high‐stress in‐situ conditions, into 3D DFN flow and transport simulationsWe observe the effects of incorporating real aperture data for fractures on network‐scale flow and transport properties for the first timeInclusion of aperture variability leads to scale‐bridging, where this small‐scale feature reorganizes the flow field at the network scale [ABSTRACT FROM AUTHOR]

We study how the interplay between fracture aperture heterogeneity and tracer injection mode controls fluid flow and tracer transport in three‐dimensional (3D) discrete fracture networks (DFNs). The direct 3‐D DFN simulations show that tracer injection mode has substantial effects on tracer spreading across all levels of aperture heterogeneity. The key controlling factor for effective transport is the initial Lagrangian velocity distribution, which is determined by the interplay between injection mode and aperture heterogeneity. The fundamental difference between initial Lagrangian velocity distribution and domain‐scale Eulerian velocity distribution plays a vital role in determining anomalous transport. We effectively capture the observed anomalous transport using an upscaled transport model that incorporates initial velocity distribution, stationary velocity distribution, velocity correlation length, and average advective tortuosity. With the upscaled transport model, we accurately capture the evolution of Lagrangian velocity distribution and predict longitudinal spreading in 3‐D DFN. Key Points: Tracer injection mode has strong impact on transport in 3‐D DFNs across all levels of aperture heterogeneityInitial Lagrangian velocity distribution determines the late‐time power‐law scaling of a breakthrough curveA Bernoulli CTRW model effectively captures anomalous transport in 3‐D DFNs [ABSTRACT FROM AUTHOR]

Flow channelization is a commonly observed phenomenon in fractured subsurface media where the flow of fluids is restricted primarily to highly transmissive fracture networks surrounded by a low‐permeability rock matrix. The multiscale structural heterogeneity of these networks results in multiscale flow channelization where preferential flow paths form at length scales ranging from the entire system down to the subfracture size. We present an analysis of how one of the largest scales in fractured media, the network density, influences the degree of flow channeling that occurs using an ensemble of semigeneric three‐dimensional discrete fracture network (DFN) simulations. We construct 10 DFNs, whose fracture lengths follow a power law distribution, at four densities for a total of 40 networks. We characterize their structure in terms of the network topology and geometry. Eulerian and Lagrangian observations of the steady‐state flow fields obtained within the networks are used to quantify the degree of flow channelization at the network scale. We introduce a measure for the importance‐ranking/hierarchy of different flow paths in the network using graph‐based analysis of Lagrangian transport by which the degree of flow channeling between networks is compared. These flow observations are then linked to the structural properties of the networks. In general, network‐scale flow channeling decreases as the network density increases. However, at low densities, there is more uniform flow within the entire connected network than in high‐density networks. We also demonstrate how standard transport observables can be used to infer the degree of flow channelization occurring within a fracture network. [ABSTRACT FROM AUTHOR]

Multiphase flow is ubiquitous in subsurface energy applications and natural processes, such as oil recovery, CO2 sequestration, and water flow in soils. Despite its importance, we still lack a thorough understanding of the coupling of multiphase flow and reaction of transported fluids with the confining media, including rock dissolution and mineral precipitation. Through the use of geomaterial microfluidic flow experiments and high‐performance computer simulations, we identify key pore‐scale mechanisms that control this coupling. We compare the reactivity of fractured limestone with CO2‐saturated brine (single phase) and a mixture of supercritical (sc) CO2 and CO2‐saturated brine (multiphase). We find that the presence of scCO2 bubbles significantly changes both the flow dynamics and the resulting reaction patterns from a single‐phase system, spatially homogenizing the rock dissolution. In addition, bubbles redirect oversaturated fluid into low‐velocity regions, thereby enhancing carbonate precipitation occurs. Plain Language Summary: The impact of pore‐scale multiphase flow on fluid‐solid reactions is poorly understood because direct observations of reactive multiphase fluids in real rock materials are not widely available and the necessary computing is intractable. Using high‐pressure/temperature geomaterial microfluidic experiments complemented by high‐performance computer direct numerical simulation of multiphase flow in those geometries, we elucidate the pore‐scale mechanisms that lead to homogenization of rock dissolution and enhancement of mineral precipitation. This study contributes to our ability to predict soil weathering and to optimize CO2 sequestration and hydrocarbon extraction. Key Points: Multiphase flow leads to homogenization of rock dissolution and enhancement of mineral precipitationThe identified pore‐scale mechanisms have fundamental implications for soil weathering and subsurface applicationsThe results provide a foundation for engineering design and predictive tools [ABSTRACT FROM AUTHOR]

We develop a theoretical model for power law tailing behavior of transport in fractured rock based on the relative dominance of the decay rate of the advective travel time distribution, modeled using a Pareto distribution (with tail decaying as ∼ time−(1+α)), versus matrix diffusion, modeled using a Lévy distribution. The theory predicts that when the advective travel time distribution decays sufficiently slowly (α<1), the late‐time decay rate of the breakthrough curve is −(1+α/2) rather than the classical −3/2. However, if α>1, the −3/2 decay rate is recovered. For weak matrix diffusion or short advective first breakthrough times, we identify an early‐time regime where the breakthrough curve follows the Pareto distribution, before transitioning to the late‐time decay rate. The theoretical predictions are validated against particle tracking simulations in the three‐dimensional discrete fracture network simulator dfnWorks, where matrix diffusion is incorporated using a time domain random walk. Key Points: A theoretical model is developed for power law tailing of breakthrough curves influenced by matrix diffusion and heterogeneous advectionA threshold decay rate for the advective travel time distribution is identified,below which matrix diffusion produces tail decay rates >−3/2Matrix diffusion is implemented in high‐fidelity three‐dimensioal discrete fracture network simulations to confirm theoretical predictions [ABSTRACT FROM AUTHOR]

ABSTRACT Restaurant foods are typically higher in calories than meals consumed at home. A goal of the 2010 Patient Protection and Affordable Care Act is to encourage healthier food choices at restaurants by providing consumers with information about the calorie content of menu items. However, doesn't a well-informed consumer already know that a 12-piece bucket of chicken has more calories than a salad? Following research in marketing science and behavioral economics, we evaluate a representative consumer's ability to discriminate between low-calorie and high-calorie menu items using only some basic 'rules of thumb' nutrition knowledge. Results reveal the extent to which menu labeling may increase consumers' knowledge about the calories in restaurant foods. [ABSTRACT FROM AUTHOR]

Although hydraulic fracturing has been used for natural gas production for the past couple of decades, there are significant uncertainties about the underlying mechanisms behind the production curves that are seen in the field. A discrete fracture network-based reservoir-scale work flow is used to identify the relative effect of flow of gas in fractures and matrix diffusion on the production curve. With realistic three-dimensional representations of fracture network geometry and aperture variability, simulated production decline curves qualitatively resemble observed production decline curves. The high initial peak of the production curve is controlled by advective fracture flow of free gas within the network and is sensitive to the fracture aperture variability. Matrix diffusion does not significantly affect the production decline curve in the first few years, but contributes to production after approximately 10 years. These results suggest that the initial flushing of gas-filled background fractures combined with highly heterogeneous flow paths to the production well are sufficient to explain observed initial production decline. These results also suggest that matrix diffusion may support reduced production over longer time frames. [ABSTRACT FROM AUTHOR]

Three phenomenological power law models for the permeability of porous media are derived from computational experiments with flow through explicit pore spaces. The pore spaces are represented by three-dimensional pore networks in 63 virtual porous media along with 15 physical pore networks. The power laws relate permeability to (i) porosity, (ii) squared mean hydraulic radius of pores, and (iii) their product. Their performance is compared to estimates derived via the Kozeny equation, which also uses the product of porosity with squared mean hydraulic pore radius to estimate permeability. The power laws provide tighter estimates than the Kozeny equation even after adjusting for the extra parameter they each require. The best fit is with the power law based on the Kozeny predictor, that is, the product of porosity with the square of mean hydraulic pore radius. [ABSTRACT FROM AUTHOR]

Food loss at the retail and consumer levels in the United States includes 14.8 billion pounds of fruit and 23.4 billion pounds of vegetables, valued at $15.1 billion and $27.7 billion, respectively, in 2008 retail market prices. The total value of these losses is $42.8 billion per year, or roughly $141 per capita. To most efficiently reduce the annual food loss, it may be beneficial to focus efforts on the four fruits (fresh apples, grapes, peaches and strawberries) and four vegetables (fresh and canned tomatoes and fresh and frozen potatoes) that have the greatest amount of loss. [ABSTRACT FROM AUTHOR]

Objectives: The National Health and Nutrition Examination Survey (NHANES III) 1988-1994 is one of the few nationally representative data sets with information on both private dental insurance and a clinical dental exam. The objective of this analysis was to examine the possible associations between private dental insurance and clinical exam outcomes, demographic variables, and dental visits.Methods: Using NHANES III data, analysis was limited to persons aged 20 years or older who had a dental exam and reported on their private dental insurance status. Initial analyses were based on comparisons between those with and without private dental insurance. Propensity scoring method was used to examine the effects of dental insurance on clinical exam variables.Results: The percentage of individuals with private dental insurance was significantly greater among non-Hispanic blacks, those with higher educational attainment, those living at/above the federal poverty level, and those with a dental visit in the past year compared to their respective counterparts. Those with untreated caries, those with a loss of attachment of greater than 4 mm, and those with 12-27 missing teeth were significantly less likely to have dental insurance (p < 0.05) than their respective counterparts.Conclusions: These results suggest that having private dental insurance is associated with better clinical oral health status. [ABSTRACT FROM AUTHOR]

Reid BC, Hyman JJ, Macek MD. Race/ethnicity and untreated dental caries: the impact of material and behavioral factors. Community Dent Oral Epidemiol 2004; 32: 329–36. © Blackwell Munksgaard, 2004 To use nationally representative data, group variables into categories of material and behavioral factors, and assess their relative contribution to racial/ethnic variation in untreated caries. Participants were from the Third National Health and Nutrition Examination Survey (NHANES III), aged 20–50 years. Material factors were income, education, employment status, dental insurance status, and urban residence. Behavioral factors were marital status, tobacco use, alcohol use, obesity, and social support. All models were additionally adjusted for age, gender, and quartile of missing teeth. The outcome was three or more carious teeth. Non-Hispanic blacks and Mexican-Americans displayed excess risk of untreated caries compared with non-Hispanic whites when adjusted for age, sex, and missing teeth (adjusted odds ratios 1.73 and 1.69, respectively). The addition of behavioral factors to this model resulted in virtually no changes in the adjusted odds ratios for race/ethnicity and untreated caries. When material factors were added to the basic model the excess risk for untreated caries among non-Hispanic blacks was reduced by approximately 21% and that of Mexican-Americans was no longer statistically significant compared with non-Hispanic whites (adjusted odds ratios 1.36 and 0.83, respectively). Much of the excess risk for untreated dental caries among non-Hispanic blacks and Mexican-Americans compared with non-Hispanic whites was eliminated when material factors were controlled, while no risk reductions were observed when behavioral factors were controlled. Addressing material factors may provide greater reductions in untreated caries disparities than behavioral interventions, and these risk reductions may vary with racial/ethnic group. [ABSTRACT FROM AUTHOR]

Background: Cigarette smoking is a significant risk factor for both chronic obstructive pulmonary disease (COPD) and periodontal disease. The goal of this study was to better understand the role of smoking in a possible relationship between periodontal disease and COPD. Methods: The study population consisted of 7.625 participants in the Third National Health and Nutrition Examination Survey (NHANES III) during 1988-1994 who were aged 30 years or older when examined and who received a spirometric examination. The data analysis employed logistic regression models and accounted for the complex sampling design used in NHANES III. Results: After adjustment for potential confounders, there was no statistically significant association between periodontal disease and COPD among former or non-smokers. Current smokers with ≥4 mm mean loss of attachment had an odds ratio of 3.71 (95% confidence interval: 1.74, 7.89). Conclusions: These results suggest that cigarette smoking may be a cofactor in the relationship between periodontal disease and chronic obstructive pulmonary disease. The key role played by smoking in the etiology of both periodontal disease and chronic obstructive pulmonary disease suggests that much of the observed increase in risk may actually reflect the exposure to smoking. Additional research into smoking-related effect modification is needed to clarify the role of periodontal disease in the etiology of smoking-related systemic diseases. [ABSTRACT FROM AUTHOR]

Abstract Objectives: The objective of this study was to identify variables related to periodontal loss of attachment (LOA). Materials and Methods: The study population consisted of a nationally representative sample of 12,325 US adults who participated in the National Health and Nutrition Examination Survey III. The analyses used survey multinomial logistic regression to account for the complex survey design. Results: The adjusted odds ratio for a mean LOA of 3 mm or more associated with current smoking was 18.55 (95% CI 9.44–36.45) among 20–49-year olds. Among those aged 50 years or more, the odds ratio for a mean LOA of 4 mm or more was 25.64 (13.04–50.40). Prior smoking, untreated decayed surfaces (on both person and site levels), and male gender were also associated with LOA. There was no excess risk observed among non-Hispanic blacks or Mexican-Americans. The adjusted population attributable fractions due to current smoking were 60% for persons aged 20–49 with the worst 10% of LOA (1.58 mm or more), and 47% for those aged 50 plus (LOA of 3.39 mm or more). Conclusion: These results support earlier findings regarding the central role of cigarette smoking in the etiology of periodontal loss of attachment, a role due in large part to the substantial relationship between smoking and severe periodontal disease. [ABSTRACT FROM AUTHOR]

Background: Cigarette smoking is a significant risk factor for both coronary heart disease and periodontal disease. The goal of this study was to better understand the role of smoking in the relationship between periodontal disease and heart attack history. Methods: The study population consisted of 5,285 participants in the Third National Health and Nutrition Examination Survey (NHANES) during 1988-1994 and who were age 40 years or older when examined. The data analysis employed logistic regression models and accounted for the complex sampling design used in NHANES. Results: After adjustment for potential confounders, we only found significant associations between periodontal loss of attachment (LOA) and heart attack history for smokers, with odds ratios and 95% confidence interval (CI) of 2.64 (1.48 to 4.71). 3.34 (1.22 to 12.10) and 5.87 (1.91 to 18.00) for those with 2.0 to 2.99, 3.0 to 3.99, and 4 mm or more mean LOA, respectively. When the analysis was stratified by smoking status and tertile of age at heart attack, the statistically significant associations were limited to smokers who had a heart attack between the ages of 25 and 50 years, with odds ratios and 95% CI associated with increasing mean LOA for this group of 3.29 (1.35 to 8.04), 7.32 (1.60 to 33.51), and 8.04 (1.91 to 18.00), respectively. Conclusions: These results suggest that cigarette smoking is a necessary cofactor in the relationship between periodontal disease and coronary heart disease, and the increase in risk appears to be age dependent. However, the key role played by smoking in the etiology of both periodontal and heart diseases makes it difficult to determine how much of the observed association resulted from periodontal disease. [ABSTRACT FROM AUTHOR]

Editorial. Comments on the complexities of comparative research on public policy toward vocational education and training. Limitations associated with comparative research; Problems of measuring comparability between systems of training, education and development; Inputs and outcomes of skill measurement; Tensions between neo-corporatism and neo-liberalism.

Reports the negotiation over occupational pensions and employee participation in the management of pension schemes in Great Britain. Reasons for a substantial rise in pensions as a component of labor cost; Absence of occupational pensions from mainstream industrial relations; Role of labor unions in improving current living standards.

The topology of natural fracture networks is inherently linked to the structure of the fluid velocity field and transport therein. Here we study the impact of network density on flow and transport behaviors. We stochastically generate fracture networks of varying density and simulate flow and transport with a discrete fracture network model, which fully resolves network topology at the fracture scale. We study conservative solute trajectories with Lagrangian particle tracking and find that as fracture density decreases, solute channelization to large local fractures increases, thereby reducing plume spreading. Furthermore, in sparse networks mean particle travel distance increases and local network features, such as velocity zones where flow is counter to the primary pressure gradient, become increasingly important for transport. As the network density increases, network statistics homogenize and such local features have a reduced impact. We quantify local topological influence on transport behavior with an effective tortuosity parameter, which measures the ratio of total advective distance to linear distance at the fracture scale; large tortuosity values are correlated to slow‐velocity regions. These large tortuosity, slow‐velocity regions delay downstream transport and enhance tailing on particle breakthrough curves. Finally, we predict transport with an upscaled, Bernoulli spatial Markov random walk model and parameterize local topological influences with a novel tortuosity parameter. Bernoulli model predictions improve when sampling from a tortuosity distribution, as opposed to a fixed value as has previously been done, suggesting that local network topological features must be carefully considered in upscaled modeling efforts of fracture network systems. Key Points: We investigate the impact of fracture density on transport in three‐dimensional fracture networksNegative velocity zones influence network scale transport behaviorA tortuosity dependent Bernoulli CTRW model is used to upscale topological heterogeneity [ABSTRACT FROM AUTHOR]

The article focuses on alienation and prisonization. It views prison as being similar to other types of formal organizations that are characterized by a system of rules, a rigid hierarchy of authority, a reliance of coercive power, and a low degree of client autonomy. One product of such characteristics is the alienation of the inmates. Two measures of alienation were investigated: societal alienation and alienation from the formal organization of the prison. Initially, the effect of duration of confinement on levels of alienation was evaluated. The expectation was that there would be a positive relationship between duration of exposure to the type of coercive organization that prisons typically represent and the extent to which inmates become alienated. Further, because alienation is also an important independent variable, the extent to which alienation was predictive of prisonization was assessed. A model was developed in order to account for the hypothesized relationships. The conceptual model tested in the article predicted that: as length of time incarcerated increases, contextual alienation, societal alienation, and prisonization increase; as contextual alienation increases, societal alienation and prisonization increase; as societal alienation increases, prisonization increases.

The article comments on the importance of determining confounding and effect modification in research on periodontal and systemic diseases. The putative associations between periodontal disease and systemic diseases is pertinent when dealing with research on smoking for smoking is a major risk factor for both periodontal disease and a number of systemic diseases. As an outcome, it is very difficult to disentangle the effects of smoking and periodontal disease in studies of systemic diseases.