Engine dynamic analysis with general nonlinear finite element codes. Part 2: Bearing element implementation overall numerical characteristics and benchmaking

Finite element codes are used in modelling rotor-bearing-stator structure common to the turbine industry. Engine dynamic simulation is used by developing strategies which enable the use of available finite element codes. benchmarking the elements developed are benchmarked by incorporation into a general purpose code (ADINA); the numerical characteristics of finite element type rotor-bearing-stator simulations are evaluated through the use of various types of explicit/implicit numerical integration operators. Improving the overall numerical efficiency of the procedure is improved

La modélisation stochastique des étiages: une revue bibliographique

La croissance continue de la population mondiale et l'augmentation du niveau de vie dans certaines parties de la planète exercent une pression de plus en plus forte sur la demande quantitative et qualitative de la ressource hydrique, nécessitant ainsi une gestion plus adéquate. Afin d'évaluer la fiabilité d'un système de ressources en eau et de déterminer son mode de gestion durant un étiage, il est utile d'avoir un outil de modélisation. Nous présentons ici une synthèse des travaux de modélisation réalisés dans le cadre de l'approche stochastique. Nous faisons d'abord le point sur la différence entre une sécheresse et un étiage, termes qui sont souvent confondus dans les publications, pour ensuite en présenter quelques indicateurs. L'approche stochastique peut être subdivisée en deux catégories: l'étude fréquentielle et les processus stochastiques. La plupart des études d'analyse de fréquence ont pour objet de calculer des débits d'étiage critiques xT correspondant à une certaine période de retour T, tel que P(X<xT)=1/T. L'approche par les processus stochastiques consiste à modéliser les événements de déficit ou les variables d'intérêt sans utiliser directement des modèles de débit. L'analyse de fréquence des débits ne tient pas compte des durées et émet des hypothèses trop simplistes de stationnarité. L'analyse des séquences permet l'obtention des lois de durées uniquement pour des processus de débits très simples. L'avantage de l'approche des processus ponctuels par rapport à l'analyse des séquences est qu'elle permet d'étudier des processus complexes, dépendants et non stationnaires. De plus, les processus ponctuels alternés permettent la modélisation des durée et la génération synthétique des temps d'occurrence des séries de surplus et de déficit. Nous présentons dans cet article les travaux de modélisation des étiages basés sur l'analyse fréquentielle, la théorie des séquences et sur les processus ponctuels. Nous n'avons pas inclus les études qui développent des distributions des faibles débits à partir de modèles physiques, ni les études de type régional.The increasing pressure on the water resources requires better management of the water deficit situations may it be unusual droughts or yearly recurring low-flows. It is therefore important to model the occurrence of these deficit events in order to quantify the related risks. Many approaches exist for the modeling of low-flow/drought events. We present here a literature review of the stochastic methods. We start by clarifying the difference between low-flows and droughts, two terms which are often used interchangeably. We then present some low-flow and drought indicators. The stochastic approach may be divided into two categories: Frequency analysis and stochastic processes. Most frequency analysis studies aim to assign to a flow value X a cumulative frequency, either directly using empirical distribution functions, or by fitting a theoretical distribution. This allows the computation of a critical flow xT corresponding to a return period T, such that P(X<xT)=1/T. These studies use mostly the annual minima of daily flows where the hydrological data is assumed independent and identically distributed. It is also common to analyze Qm, the annual minimum of the m-consecutive days average flow, m being generally 7, 10, 30, 60, 90, or 120 days, and to adopt as critical flow the m-day average having a return period of T years. The distributions which are used include the Normal, Weibull, Gumbel, Gamma, Log-Normal (2), Log-Pearson (3), Generalized Extreme Value, Pearson type 3, and Pearson type 5 distributions (GUMBEL, 1954; MATALAS, 1963; BERNIER, 1964; JOSEPH, 1970; CONDIE and NIX, 1975; HOANG, 1978; TASKER, 1987; RAYNAL-VILLASENOR and DOURIET, 1987; NATHAN and MCMAHON, 1990; ADAMCZYK, 1992).The approach using stochastic processes for low-flows may be direct (analytical) or indirect (experimental) (YEVJEVICH et al., 1983). The indirect approach (not described in this literature review) consists of obtaining flow models, generating synthetic flows and then empirically studying certain drought variables obtained from the synthetic data. The direct approach models deficit events and related variables without explicitely modeling flows. The stochastic processes are of two types and differ in the way that randomness is introduced in the model: ·- State modeling: The process may be modeled as a probabilistic transition between various states (Markov processes for example). The states of the process {Xt } are obtained from the hydrological observations {Yt } using thresholds. The number of states of {Xt } is finite and run series analysis may be used to study the properties of the drought parameters; or- Event modeling: The concept of random occurrence of an event is introduced, where an event is a transition between surplus and deficit and vice-versa. In this approach, stochastic point processes are appropriate. A deficit event is then considered a rare event and is characterized by its occurrence time.We review the low-flows studies based on frequency analysis, run series analysis and on point processes. However, we do not include the physically-based models nor the regional analysis studies.Run series analysis is applied to processes derived from flows and thresholds. A two-state process is obtained and Markov processes are often applied. The variables of interest are the duration of a deficit defined by the run length of series below the threshold (RL), the severity corresponding to the deficit volume over a negative run of length n (RSn), and the intensity In defined by the ratio RSn /RL (SALDARRIGA and YEVJEVICH, 1970; SEN, 1977; MILLAN and YEVJEVICH, 1971; MILLAN, 1972; SEN, 1980A; SEN, 1980B; SEN, 1980C; GÜVEN, 1983; MOYÉ et al., 1988; SEN, 1990). It is often assumed that the flow process is either independent or autoregressive of order 1 and that it is stationary except for SEN, 1980B.Point processes are based on the notion of the occurrence of an event. They are defined by the occurrence time tj of an event ej. We present a classification of some of the pertinent processes and their relation to each other. These include the Poisson process, both homongeneous and non-homogeneous, the renewal process, the doubly stochastic process and the self-exciting process. These processes are well suited for obtaining models of deficit durations (NORTH, 1981; LEE et al., 1986; ZELENHASIC et SALVAI, 1987; CHANG, 1989; MADSEN and ROSBJERG, 1995; ABI-ZEID, 1997). The advantage of this approach is its ability to take into account nonstationarity where alternating surplus-deficit point processes are defined from daily flow data. ABI-ZEID (1997) proposed a physically-based alternating non-homogeneous Poisson process that takes into account precipitation and temperature, and defined low-flow risk indices computed from these developed models.In conclusion, we remark that frequency analysis does not take into account well the duration aspcets and uses simplifying stationnarity hypothesis. Series analysis provides duration distributions for simple flow processes. The advantage of point processes is that they can model complex, dependent and non-stationary processes. Furthermore, alternating point processes can be used to model deficit durations and generate synthetic data such as occurrences of deficit and surplus events. We argue that the duration of low-flows is an important issue which has not received a lot of attention

On an elliptic equation with singular cylindrical growth

In the present paper, an elliptic equation with singular cylindrical grouwth, is considered. By using the Nehari manifold and mountain pass theorem, the existence of at least four distinct solutions is obtained. The result depends crucially on the parameters k, λ, g and u

Revue de processus ponctuels et synthèse de tests statistiques pour le choix d'un type de processus

Nous nous intéressons dans ce travail de recherche à la modélisation d'une série d'événements par la théorie des processus ponctuels temporels. Un processus ponctuel est défini comme étant un processus stochastique pour lequel chaque réalisation constitue une collection de points. Un grand nombre d'ouvrages traitent particulièrement de ces processus, cependant, il existe dans la littérature peu de travaux qui se préoccupent de l'analyse de séries d'événements. On identifie deux catégories de séries d'événements : une série d'un seul type d'événements et une série de plusieurs types d'événements.L'objectif de ce travail est de mettre en évidence les différents tests statistiques appliqués aux séries d'un seul ou de plusieurs types d'événements et de proposer une classification de ces tests. Nous présentons d'abord une revue de littérature des processus ponctuels temporels, accompagnée d'une classification de ces modèles. Par la suite, nous identifions les tests statistiques de séries d'un seul type d'événements et nous examinons leur applicabilité pour une série de deux ou de plusieurs types d'événements. Les tests statistiques identifiés sont répartis en quatre classes : analyse graphique, tests appliqués au processus de Poisson homogène et non homogène, tests appliqués au processus de renouvellement homogène et les tests de discrimination entre deux processus ponctuels. Ce travail est réalisé avec l'idée d'une application ultérieure dans le cadre de l'analyse du risque.Les résultats de cette recherche ont montré qu'il n'existe dans la littérature que des tests d'une série d'un seul type d'événements et ils sont, généralement, valables pour les processus ponctuels suivants : Poisson homogène et renouvellement homogène. L'application de ces tests aux séries de deux ou de plusieurs types d'événements est possible dans le cas où les événements sont définis par leurs nombres et leurs temps d'occurrence seulement, i.e. la durée de chaque événement n'est pas prise en considération.The design and management of hydraulic structures require a good knowledge of the characteristics of extreme hydrologic events such as floods and droughts, that may occur at the site of interest. Occurrences of such events may be modelled as temporal point processes. This modelling approach allows the derivation of various performance indices related to the design and operation of this infrastructure, as well as to the quantification and management of the associated risks. In this paper, we present statistical tests that may be applied for the modelling of a series of events by temporal point processes. A point process is defined as a stochastic process for which each realisation constitutes a series of points. Although a large body of literature dealt with temporal point processes, very few focused on the analysis of a series of events.In the present paper we identify two types of series of events: the first represents a series of only one type of event, and the second represents a series of several types of events. The main objective of this research is to comprehensively review the statistical tests applied to the series of one or several types of events and to propose a classification of these tests. This comprehensive review of statistical tests applied to point processes is carried out with the ultimate objective of applying these tests to real case studies within the framework of risk analysis. For example, an extended low-flow event constitutes a risk that may place a water resources system in a state of failure. Thus, it's important to identify and quantify this risk in order to ensure the optimal management of water resources. The modelling of the observed series of events by point processes can provide some statistical results, such as the distribution of number of events or the shape of the intensity function. These results are useful in a risk analysis framework, which includes two steps: risk evaluation and risk management. In the first part of the paper, a review and classification of the various temporal point processes are presented. These include the homogeneous and nonhomogeneous Poisson processes, the Negative Binomial process, the cluster point processes (such as the Neyman-Scott and the Bartlett-Lewis processes), the doubly stochastic Poisson processes, the self-exciting point processes, the homogeneous and nonhomogeneous renewal processes and the semi-markov processes. Also, we illustrate the various links and relationships that exist between these point processes. This classification is elaborated by considering the homogeneous Poisson process as the starting point. The simplicity and the wide use of this process in the statistical and hydrological literature justify this choice.In the second part of the paper, statistical tests of a series of one type of event are identified. A series of events may be characterised by the number of events, the occurrence times of the events or by the duration of each event. These characteristics are considered as random variables that must be represented by suitable statistical distributions. A series of events may also be characterised by the intensity function, which represents the instantaneous average rate of occurrence of an event. Clearly, the choice of the statistical distribution to model the number of events in a series or the intensity function depends on the nature of the observed data. For example, a stationary series of events may be represented by a constant intensity function. Thus, it is necessary to conduct an analysis of the observed series of the events, such as graphical analysis and statistical testing in order to select and validate the hypothesis underlying the point process model. The hypotheses that may be verified include trend analysis, homogeneity analysis, periodicity analysis, independence of intervals between events, and the adequacy of a given distribution for the number of events and for the time intervals separating events.In the third part, the applicability of the tests identified in the second part to the case of a series of two or more types of events is examined. In this part, our goal is to analyse the global point process (or the pooled output) obtained by the superposition of the p subsidiary point processes. The decomposition of the global process into p point processes necessitates an identification of each type of event, characterised generally by the number of occurrences and by the intervals between the successive events of the same type. We also examine the applicability of the statistical tests identified in the second part to the case where the global point process is characterised by the duration of each type of event. We investigate more specifically the case of two subsidiary point processes (p=2) where the two event types alternate in the time (an alternating point process). Finally, statistical tests identified in the second part are classified into four categories: tests based on graphical analysis; tests applied to the homogeneous and nonhomogeneous Poisson processes; tests applied to the homogeneous renewal process; and finally tests of discrimination between two specific processes. Theses tests of discrimination include the selection among the Poisson process and the renewal process, the Poisson process and the Binomial point process, and finally, the selection among these three point processes: Cox process, Neyman-Scott process and renewal process.The results of this research indicate that, in the past, mostly tests for a series of one type of event were presented in the literature. These tests are only valid for the following point processes: a homogenous Poisson process or a homogenous renewal process. The application of these tests to a series of two or several types of events is possible as long as these events are only described by their number and time of occurrence i.e. the duration of each event can not be taken into consideration. Otherwise, these tests are applicable to the alternating point process, which is characterised only by the number and the duration of the two types of events

HO-1 Upregulation Attenuates Adipocyte Dysfunction, Obesity, and Isoprostane Levels in Mice Fed High Fructose Diets

Background. Fructose metabolism is an unregulated metabolic pathway and excessive fructose consumption is known to activate ROS.HO-1 is a potent antioxidant gene that plays a key role in decreasing ROS and isoprostanes.We examinedwhether the fructosemediated increase in adipocyte dysfunction involves an increase in isoprostanes and that pharmacological induction ofHO-1would decrease both isoprostane levels and adipogenesis. Methods and Results. We examined the effect of fructose, on adipogenesis in human MSCs in the presence and absence of CoPP, an inducer of HO-1. Fructose increased adipogenesis and the number of large lipid droplets while decreasing the number of small lipid droplets ( \u3c 0.05). Levels of heme and isoprostane in fructose treated MSC-derived adipocytes were increased. CoPP reversed these effects andmarkedly increasedHO-1 and theWnt signaling pathway. Thehigh fructose diet increased heme levels in adipose tissue and increased circulating isoprostane levels ( \u3c 0.05 versus control). Fructose diets decreasedHO-1 and adiponectin levels in adipose tissue. Induction ofHO-1 by CoPP decreased isoprostane synthesis ( \u3c 0.05 versus fructose). Conclusion. Fructose treatment resulted in increased isoprostane production and adipocyte dysfunction, which was reversed by the increased expression of HO-1

New Polymer Syntheses Part: 55#. Novel Conducting Arylidene Polymers and Copolymers Based on Methyl-Cyclohexanone Moiety

A new interesting class of conducting polymers based on methyl-cyclohexanone in the polymer main chain has been synthesized by solution polycondensation of terephthalaldehyde with methyl-cyclohexanone. Copolymers containing different cycloalkanone moieties were also synthesized using solution polycondensation technique. The model compound I was synthesized by the interaction of methyl-cyclohexanone monomer with benzaldehyde, and its structure was confirmed by elemental and spectral analyses. The resulting new polymers and copolymers were characterized by elemental and spectral analyses, beside solubility and viscometry measurements. The thermal properties of those polymer and copolymers were evaluated by TGA, DrTGA and DTA measurements and correlated to their structural units. PDT as well as T10 was in the range from 205 to 370 ºC. In addition, T10 thermal stability for all the polymers was in theorder: VI&gt; II &gt; III &gt; IV &gt; V. X–ray analysis showed that it has some degree of crystallinity in the region 2q = 5–60 degree.The UV– visible spectra of some selected polymers were measured in DMSO solution and showed absorption bands in the range 265-397 nm, due to n – π* and π – π* transition. The morphological properties of copolymer IV as selected examples were tested by SEM. The electrical conductivities of the synthesized polymers and copolymers enhanced to become in the range of 10-9-10-8 S cm-1 by doping with iodine

Identification of Candidate Genes and Genomic Regions Associated with Adult Plant Resistance to Stripe Rust in Spring Wheat

Wheat stripe rust (caused by Puccinia striiformis f. sp. tritici) is a major disease that damages wheat plants and affects wheat yield all over the world. In recent years, stripe rust became a major problem that affects wheat yield in Egypt. New races appeared and caused breakdowns in the resistant genotypes. To improve resistance in the Egyptian genotypes, new sources of resistance are urgently needed. In the recent research, a set of 95 wheat genotypes collected from 19 countries, including Egypt, were evaluated for their resistance against the Egyptian race(s) of stripe rust under field conditions in the two growing seasons 2018/2019 and 2019/2020. A high genetic variation was found among the tested genotypes. Single marker analysis was conducted using a subset of 71 genotypes and 424 diversity array technology (DArT) markers, well distributed across the genome. Out of the tested markers, 13 stable markers were identified that were significantly associated with resistance in both years (p-value ≤ 0.05). By using the sequence of the DArT markers, the chromosomal position of the significant DArT markers was detected, and nearby gene models were identified. Two markers on chromosomes 5A and 5B were found to be located within gene models functionally annotated with disease resistance in plants. These two markers could be used in markerassisted selection for stripe rust resistance under Egyptian conditions. Two German genotypes were carrying the targeted allele of all the significant DArT markers associated with stripe rust resistance and could be used to improve resistance under Egyptian conditions

Why Does Obesity Lead to Hypertension? Further Lessons from the Intersalt Study.

Objectives To analyze correlations between major determinants of blood pressure (BP), in efforts to generate and compare predictive models that explain for variance in systolic, diastolic, and mean BP amongst participants of the Intersalt study. Methods Data from the Intersalt study, consisting of nearly 10,000 subjects from 32 different countries, were reviewed and analyzed. Published mean values of 24 hour urinary electrolyte excretion (Na+, K+), 24 hour urine creatinine excretion, body mass index (BMI, kg/m^2), and blood pressure data were extracted and imported into Matlab™ for stepwise linear regression analysis. Results As shown earlier, strong correlations between urinary sodium excretion (UNaV) and systolic, diastolic and mean blood pressure were noted as well as between UNaV and the age dependent increase in systolic blood pressure. Of interest, BMI and urinary creatinine excretion rate (UCrV) also both correlated with systolic blood pressure, but the ratio of BMI/UCrV, constructed to be a measure of obesity, correlated negatively with systolic blood pressure. Conclusions Our results offer population-based evidence suggesting that increased size due to muscle mass rather than adiposity may correspond more to blood pressure. Additional data bases will need to be sampled and analyzed to further validate these observations

Predicting Adverse Outcomes in End Stage Renal Disease: Machine Learning Applied to the United States Renal Data System

We examined machine learning methods to predict death within six months using data derived from the United States Renal Data System (USRDS). We specifically evaluated a generalized linear model, a support vector machine, a decision tree and a random forest evaluated within the context of K-10 fold validation using the CARET package available within the open source architecture R program. We compared these models with the feed forward neural network strategy that we previously reported on with this data set

The Energy-Momentum Tensor in Noncommutative Gauge Field Models

We discuss the different possibilities of constructing the various energy-momentum tensors for noncommutative gauge field models. We use Jackiw's method in order to get symmetric and gauge invariant stress tensors--at least for commutative gauge field theories. The noncommutative counterparts are analyzed with the same methods. The issues for the noncommutative cases are worked out.Comment: 11 pages, completed reference