1,188 research outputs found

    Survival Analysis of Bridge Superstructures in Wisconsin

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    Although survival analyses have long been used in biomedical research, their application to engineering in general, and bridge engineering in particular, is a more recent phenomenon. In this research, survival (reliability) of bridge superstructures in Wisconsin was investigated using the Hypertabastic accelerated failure time model. The 2012 National Bridge Inventory (NBI) data for the State ofWisconsin were used for the analyses. A recorded NBI superstructure condition rating of 5 was chosen as the end of service life. The type of bridge superstructure, bridge age, maximum span length (MSL) and average daily traffic (ADT) were considered as possible risk factors in the survival of bridge superstructures. Results show that ADT and MSL can substantially affect the survival of bridge superstructures at various ages. The reliability of Wisconsin superstructures at the ages of 50 and 75 years is on the order of 63% and 18%, respectively, when the ADT and MSL values are at Wisconsin’s mean values

    Conditional survival analysis for concrete bridge decks

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    Bridge decks are a significant factor in the deterioration of bridges, and substantially affect long-term bridge maintenance decisions. In this study, conditional survival (reliability) analysis techniques are applied to bridge decks to evaluate the age at the end of service life using the National Bridge Inventory records. As bridge decks age, the probability of survival and the expected service life would change. The additional knowledge gained from the fact that a bridge deck has already survived a specific number of years alters (increases) the original probability of survival at subsequent years based on the conditional probability theory. The conditional expected service life of a bridge deck can be estimated using the original and conditional survival functions. The effects of average daily traffic and deck surface area are considered in the survival calculations. Using Wisconsin data, relationships are provided to calculate the probability of survival of bridge decks as well as expected service life at various ages. The concept of survival dividend is presented and the age when rapid deterioration begins is defined

    Survival Analyses for Bridge Decks in Northern United States

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    The use of deicing salts in northern regions of the United States is a major contributor to the long-term deterioration of bridge decks. In this study, the 2008 U.S. National Bridge Inventory (NBI) records were used to develop survival models for non-reconstructed bridge decks in six northern states of Minnesota, Wisconsin, Michigan, Ohio, Pennsylvania, and New York. The hypertabastic accelerated failure model was used to develop survival (reliability) and hazard (failure rate) functions for all six states. The NBI parameters included were the deck rating, type of superstructure (concrete or steel), deck surface area, age, and average daily traffic (ADT). A recorded NBI deck rating of 5 was considered to be the end of service life. Results show that ADT and deck surface area are both important factors affecting reliability and failure rates in all six states studied. In general, deck reliability and failure rates correspond reasonably well with qualitative measure of the harshness of each state’s winters. The type of superstructure has a varied influence in different states. It is recommended that deck area and ADT be considered as important factors when planning maintenance operations

    Nutrient concentrations and accumulations in precipitation over the north central region

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    The many facets of plant nutrients (e.g., N, P, and S) in the biosphere have become major environmental issues within the past decade. This concern is justified because of the increasing contamination of air and water resources by various substances on local and regional levels, especially in areas close to point sources. Little information is available, however, on variation in the amounts and concentrations of some of the substances present in air and natural water in various parts of the United States. Such information is essential for a better understanding of the transport and perhaps the fates of pollutants in the biosphere. The atmospheric component of the N and S cycles often can be a significant part of the various pools of their respective cycles (Allison, 1965; Erickson, 1963; Feth, 1966; Gambell and Fisher, 1964; Meetham, 1950; Robinson and Robbins, 1970), but the atmospheric component of the P cycle seems to be of minor significance to the cycling of this element in the environment. Among the various chemical elements present in precipitation (e.g., N, S, K, Cl, and Ca), N and S deserve special attention because N added by precipitation may contribute to nitrate pollution of surface and ground water. Sulfur and N may cause acid rain that can lead to increased leaching from soils of Ca and other nutrient elements, deterioration of aquatic ecosystems, damage to vegetation and buildings, and other agricultural and urban problems. On the other hand, the limited amounts of N and S brought down by precipitation might be useful to meet crop requirements for these elements in areas where soils have limited supplies of N and S (Allway et al., 1937; Erdman, 1923; Olson et al., 1973; Schuman and Burwell, 1974; Tabatabai and Bremner, 1972; Walker, 1969; Widdowson and Hanway, 1974)

    A Simple Alkaline Hydrolysis Method for Estimating Nitrogen Mineralization Potential of Soils

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    A simple, precise and rapid alkaline hydrolysis method for determining nitrogen (N) availability index of soils is described. It involves direct steam distillation of 1 g field-moist soil and 1 M KOH, NaOH, LiOH or phosphate-borate buffer (pH 11.8) and the amount of NH4+-N released trapped in boric acid and its concentration determined successively every 5 min for a total of 40 min. The cumulative N hydrolyzed was fitted to a hyperbolic equation to determine the maximum hydrolyzable N (Nmax) and the time required to hydrolyze one-half of Nmax (Kt) by linear regression of the transformed data. First-order equation was also used to estimate the potentially hydrolyzable N (No), hydrolysis rate constant (k) and the time required to hydrolyze one-half of No (t1/2). Results showed that for each soil and reagent, Nmax and No values were similar, but differed significantly among soils, suggesting differences in the chemical nature or reactivity of organic N in the soils. In general, Nmax and No values ranged from 401 to 1667 mg kg-1 soil and accounted for 12-56% of total organic N in the soils. The Kt values ranged between 15 and 30 min. Among the reagents tested, KOH and NaOH showed the best promise for estimating the total hydrolyzable organic N pool in the soils. The Nmax and No values were significantly correlated with the amounts of N mineralized in two weeks under aerobic and anaerobic conditions at 30 oC, N released by 2 M KCl extraction at 80oC for 20 h, and the initial NH4+-N present in the soils. We concluded that direct steam distillation of soils with 1M KOH or NaOH offer a quick and precise mean for estimating the potentially mineralizable organic N pool and availability index in soils

    Hyperbolastic modeling of tumor growth with a combined treatment of iodoacetate and dimethylsulphoxide

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    <p>Abstract</p> <p>Background</p> <p>An understanding of growth dynamics of tumors is important in understanding progression of cancer and designing appropriate treatment strategies. We perform a comparative study of the hyperbolastic growth models with the Weibull and Gompertz models, which are prevalently used in the field of tumor growth.</p> <p>Methods</p> <p>The hyperbolastic growth models H1, H2, and H3 are applied to growth of solid Ehrlich carcinoma under several different treatments. These are compared with results from Gompertz and Weibull models for the combined treatment.</p> <p>Results</p> <p>The growth dynamics of the solid Ehrlich carcinoma with the combined treatment are studied using models H1, H2, and H3, and the models are highly accurate in representing the growth. The growth dynamics are also compared with the untreated tumor, the tumor treated with only iodoacetate, and the tumor treated with only dimethylsulfoxide, and the combined treatment.</p> <p>Conclusions</p> <p>The hyperbolastic models prove to be effective in representing and analyzing the growth dynamics of the solid Ehrlich carcinoma. These models are more precise than Gompertz and Weibull and show less error for this data set. The precision of H3 allows for its use in a comparative analysis of tumor growth rates between the various treatments.</p

    Non-reciprocal interactions spatially propagate fluctuations in a 2D Ising model

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    Motivated by the anisotropic interactions between fish, we implement spatially anisotropic and therefore non-reciprocal interactions in the 2D Ising model. First, we show that the model with non-reciprocal interactions alters the system critical temperature away from that of the traditional 2D Ising model. Further, local perturbations to the magnetization in this out-of-equilibrium system manifest themselves as traveling waves of spin states along the lattice, also seen in a mean-field model of our system. The speed and directionality of these traveling waves are controllable by the orientation and magnitude of the non-reciprocal interaction kernel as well as the proximity of the system to the critical temperature.Comment: 4 figure

    Hypertabastic survival model

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    A new two-parameter probability distribution called hypertabastic is introduced to model the survival or time-to-event data. A simulation study was carried out to evaluate the performance of the hypertabastic distribution in comparison with popular distributions. We then demonstrate the application of the hypertabastic survival model by applying it to data from two motivating studies. The first one demonstrates the proportional hazards version of the model by applying it to a data set from multiple myeloma study. The second one demonstrates an accelerated failure time version of the model by applying it to data from a randomized study of glioma patients who underwent radiotherapy treatment with and without radiosensitizer misonidazole. Based on the results from the simulation study and two applications, the proposed model shows to be a flexible and promising alternative to practitioners in this field
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