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Sample records for pubertal timing predicts

  1. Off-Time Pubertal Timing Predicts Physiological Reactivity to Postpuberty Interpersonal Stress

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    Smith, Anne Emilie; Powers, Sally I.

    2009-01-01

    We investigated associations between retrospectively assessed timing of pubertal development, interpersonal interactions, and hypothalamic-pituitary-adrenal axis reactivity to an interpersonal stress task in 110 young adult women. Participants provided salivary cortisol samples at points prior and subsequent to a video-taped conflict discussion…

  2. The value of shoe size for prediction of the timing of the pubertal growth spurt

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    Verkerke Gijsbertus J

    2011-01-01

    Full Text Available Abstract Background Knowing the timing of the pubertal growth spurt of the spine, represented by sitting height, is essential for the prognosis and therapy of adolescent idiopathic scoliosis. There are several indicators that reflect growth or remaining growth of the patient. For example, distal body parts have their growth spurt earlier in adolescence, and therefore the growth of the foot can be an early indicator for the growth spurt of sitting height. Shoe size is a good alternative for foot length, since patients can remember when they bought new shoes and what size these shoes were. Therefore the clinician already has access to some longitudinal data at the first visit of the patient to the outpatient clinic. The aim of this study was to describe the increase in shoe size during adolescence and to determine whether the timing of the peak increase could be an early indicator for the timing of the peak growth velocity of sitting height. Methods Data concerning shoe sizes of girls and boys were acquired from two large shoe shops from 1991 to 2008. The longitudinal series of 242 girls and 104 boys were analysed for the age of the "peak increase" in shoe size, as well as the age of cessation of foot growth based on shoe size. Results The average peak increase in shoe size occurred at 10.4 years (SD 1.1 in girls and 11.5 years (SD 1.5 in boys. This was on average 1.3 years earlier than the average peak growth velocity of sitting height in girls, and 2.5 years earlier in boys. The increase in shoe size diminishes when the average peak growth velocity of sitting height takes place at respectively 12.0 (SD 0.8 years in girls, and 13.7 (SD 1.0 years in boys. Conclusions Present data suggest that the course of the shoe size of children visiting the outpatient clinic can be a useful first tool for predicting the timing of the pubertal growth spurt of sitting height, as a representative for spinal length. This claim needs verification by direct

  3. Pubertal timing and adolescent sexual behavior in girls.

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    Moore, Sarah R; Harden, K Paige; Mendle, Jane

    2014-06-01

    Girls who experience earlier pubertal timing relative to peers also exhibit earlier timing of sexual intercourse and more unstable sexual relationships. Although pubertal development initiates feelings of physical desire, the transition into romantic and sexual relationships involves complex biological and social processes contributing both to physical maturation and to individual interpretations of pubertal experiences. Using a sample of female sibling pairs (n = 923 pairs) from the National Longitudinal Study of Adolescent Health, the present study investigated associations among menarche and perceived pubertal timing, age of first sexual intercourse (AFI), and adolescent dating and sexual behavior using a behavioral genetic approach. Genetic factors influencing age at menarche and perceived pubertal timing predicted AFI through shared genetic pathways, whereas genetic factors related only to perceived pubertal timing predicted engagement in dating, romantic sex, and nonromantic sex in the previous 18 months. These results suggest that a girl's interpretation of her pubertal timing beyond objective timing is important to consider for the timing and the contexts of romantic and reproductive behavior. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  4. Pubertal Onset in Boys and Girls Is Influenced by Pubertal Timing of Both Parents

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    Wohlfahrt-Veje, Christine; Mouritsen, Annette; Hagen, Casper P

    2016-01-01

    CONTEXT: Epidemiological evidence on maternal and paternal heritability of the wide normal variation within pubertal timing is sparse. OBJECTIVE: We aimed to estimate the impact of parental pubertal timing on the onset of puberty in boys and girls. DESIGN: Annual pubertal examinations of healthy...... children in a longitudinal cohort study. Information on parental timing of puberty (earlier, comparable to, or later compared to peers) and menarche age was retrieved from questionnaires. PARTICIPANTS: A total of 672 girls and 846 boys. MAIN OUTCOME MEASURES: Age at onset of pubic hair (PH2+), breasts (B2......+), and menarche in girls; and PH2+, genital stage (G2+), and testis >3 mL with orchidometer (Tvol3+) in boys. RESULTS: In boys, pubertal onset was significantly associated with pubertal timing of both parents. PH2+ and Tvol3+ were earlier: -11.8 months (95% confidence interval, -16.8, -6.8)/-8.9 (-12.8, -4...

  5. Modeling pubertal timing and tempo and examining links to behavior problems.

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    Beltz, Adriene M; Corley, Robin P; Bricker, Josh B; Wadsworth, Sally J; Berenbaum, Sheri A

    2014-12-01

    Research on the role of puberty in adolescent psychological development requires attention to the meaning and measurement of pubertal development. Particular questions concern the utility of self-report, the need for complex models to describe pubertal development, the psychological significance of pubertal timing vs. tempo, and sex differences in the nature and psychological significance of pubertal development. We used longitudinal self-report data to model linear and logistic trajectories of pubertal development, and used timing and tempo estimates from these models, and from traditional approaches (age at menarche and time from onset of breast development to menarche), to predict psychological outcomes of internalizing and externalizing behavior problems, and early sexual activity. Participants (738 girls, 781 boys) reported annually from ages 9 through 15 on their pubertal development, and they and their parents reported on their behavior in mid-to-late adolescence and early adulthood. Self-reports of pubertal development provided meaningful data for both boys and girls, producing good trajectories, and estimates of individuals' pubertal timing and tempo. A logistic model best fit the group data. Pubertal timing was estimated to be earlier in the logistic compared to linear model, but linear, logistic, and traditional estimates of pubertal timing correlated highly with each other and similarly with psychological outcomes. Pubertal tempo was not consistently estimated, and associations of tempo with timing and with behavior were model dependent. Advances in modeling facilitate the study of some questions about pubertal development, but assumptions of the models affect their utility in psychological studies. PsycINFO Database Record (c) 2014 APA, all rights reserved.

  6. The Stability of Perceived Pubertal Timing across Adolescence

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    Cance, Jessica Duncan; Ennett, Susan T.; Morgan-Lopez, Antonio A.; Foshee, Vangie A.

    2011-01-01

    It is unknown whether perceived pubertal timing changes as puberty progresses or whether it is an important component of adolescent identity formation that is fixed early in pubertal development. The purpose of this study is to examine the stability of perceived pubertal timing among a school-based sample of rural adolescents aged 11 to 17 (N=6,425; 50% female; 53% White). Two measures of pubertal timing were used, stage-normative, based on the Pubertal Development Scale, a self-report scale of secondary sexual characteristics, and peer-normative, a one-item measure of perceived pubertal timing. Two longitudinal methods were used: one-way random effects ANOVA models and latent class analysis. When calculating intraclass correlation coefficients using the one-way random effects ANOVA models, which is based on the average reliability from one time point to the next, both measures had similar, but poor, stability. In contrast, latent class analysis, which looks at the longitudinal response pattern of each individual and treats deviation from that pattern as measurement error, showed three stable and distinct response patterns for both measures: always early, always on-time, and always late. Study results suggest instability in perceived pubertal timing from one age to the next, but this instability is likely due to measurement error. Thus, it may be necessary to take into account the longitudinal pattern of perceived pubertal timing across adolescence rather than measuring perceived pubertal timing at one point in time. PMID:21983873

  7. Pubertal Timing and Adolescent Sexual Behavior in Girls

    Science.gov (United States)

    Moore, Sarah R.; Harden, K. Paige; Mendle, Jane

    2014-01-01

    Girls who experience earlier pubertal timing relative to peers also exhibit earlier timing of sexual intercourse and more unstable sexual relationships. Although pubertal development initiates feelings of physical desire, the transition into romantic and sexual relationships involves complex biological and social processes contributing both to…

  8. Pubertal timing and sexual risk behaviors among rural African American male youth: testing a model based on life history theory.

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    Kogan, Steven M; Cho, Junhan; Simons, Leslie Gordon; Allen, Kimberly A; Beach, Steven R H; Simons, Ronald L; Gibbons, Frederick X

    2015-04-01

    Life History Theory (LHT), a branch of evolutionary biology, describes how organisms maximize their reproductive success in response to environmental conditions. This theory suggests that challenging environmental conditions will lead to early pubertal maturation, which in turn predicts heightened risky sexual behavior. Although largely confirmed among female adolescents, results with male youth are inconsistent. We tested a set of predictions based on LHT with a sample of 375 African American male youth assessed three times from age 11 to age 16. Harsh, unpredictable community environments and harsh, inconsistent, or unregulated parenting at age 11 were hypothesized to predict pubertal maturation at age 13; pubertal maturation was hypothesized to forecast risky sexual behavior, including early onset of intercourse, substance use during sexual activity, and lifetime numbers of sexual partners. Results were consistent with our hypotheses. Among African American male youth, community environments were a modest but significant predictor of pubertal timing. Among those youth with high negative emotionality, both parenting and community factors predicted pubertal timing. Pubertal timing at age 13 forecast risky sexual behavior at age 16. Results of analyses conducted to determine whether environmental effects on sexual risk behavior were mediated by pubertal timing were not significant. This suggests that, although evolutionary mechanisms may affect pubertal development via contextual influences for sensitive youth, the factors that predict sexual risk behavior depend less on pubertal maturation than LHT suggests.

  9. Pituitary volume mediates the relationship between pubertal timing and depressive symptoms during adolescence.

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    Whittle, Sarah; Yücel, Murat; Lorenzetti, Valentina; Byrne, Michelle L; Simmons, Julian G; Wood, Stephen J; Pantelis, Christos; Allen, Nicholas B

    2012-07-01

    Early timing of puberty (i.e., advanced pubertal maturation relative to peers) has been linked to the onset of depressive symptoms during the early adolescent phase. However, the precise neurobiological mechanisms linking early pubertal timing to adolescent depressive symptoms are not clear. We investigated whether the volume of the pituitary gland, a key component of the hypothalamic-pituitary-gonadal (HPG) and hypothalamic-pituitary-adrenal (HPA) axes, mediated the relationship between pubertal timing and depressive symptoms in 155 adolescents (72 females) both cross-sectionally and longitudinally. At baseline (M age 12.7, SD 0.5 years), early pubertal timing predicted larger pituitary gland volume and higher depressive symptoms (especially for girls), but there was no mediation effect. Longitudinally, however, larger pituitary gland volume at baseline was found to mediate the relationship between early pubertal timing and increased depressive symptoms over time (M follow-up period=2.57 years, SD=0.26) for both boys and girls. Our findings suggest that neurobiological mechanisms are partly responsible for the link between early pubertal timing and depressive symptoms in adolescents. We speculate that an enlarged pituitary gland in adolescents with early pubertal timing might be associated with hyperactivation of the hormonal stress response, leading to increased susceptibility to environmental stressors, and subsequent development of depressive symptoms. Given the well-established relationship between increasing depressive symptoms in adolescence and later disorder, these findings have implications for targeted prevention and early intervention strategies for depressive disorders in adolescence. Copyright © 2011 Elsevier Ltd. All rights reserved.

  10. Early Pubertal Timing and Girls' Problem Behavior: Integrating Two Hypotheses

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    Stattin, Hakan; Kerr, Margaret; Skoog, Therese

    2011-01-01

    Girls' early pubertal timing has been linked in many studies to behavioral problems such as delinquency and substance use. The theoretical explanations for these links have often involved the girls' peer relationships, but contexts have also been considered important in some explanations. By integrating two theoretical models, the…

  11. Understanding the Link Between Pubertal Timing in Girls and the Development of Depressive Symptoms: The Role of Sexual Harassment.

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    Skoog, Therése; Bayram Özdemir, Sevgi; Stattin, Håkan

    2016-02-01

    The link between sexual maturation, or pubertal timing, in girls and adolescent depressive symptoms is well-documented, but the underlying processes remain unclear. We examined whether sexual harassment, which has previously been linked to both pubertal timing and depressive symptoms, mediates this link, using a two-wave longitudinal study including 454 girls in 7th (M age  = 13.42, SD = .53) and 8th grade (M age  = 14.42, SD = .55). Pubertal timing was linked to depressive symptoms in both age groups, and predicted an increase in depressive symptoms among the 7th graders. Sexual harassment significantly mediated the link between pubertal timing and depressive symptoms among the 7th, but not the 8th grade girls. Together, our findings suggest that one way to prevent depressive symptoms among early-maturing girls could be to address sexual harassment in preventive intervention in early adolescence.

  12. Association Between Urinary Phthalates and Pubertal Timing in Chinese Adolescents

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    Huijing Shi

    2015-09-01

    Full Text Available Background: Phthalates are synthetic chemicals and ubiquitous environmental contaminants, with hormonal activity that may alter the course of pubertal development in children. Objectives: To determine whether exposure to phthalate metabolites is associated with timing of pubertal development in a cross-sectional study of a school-based clustered sample of 503 children from a suburban district in Shanghai, China, who were 7–14 years of age at enrollment (2010 October to November. Methods: We analyzed six phthalate metabolites in urine samples by isotope-dilution liquid chromatography tandem mass spectrometry. The associations of exposures to phthalates with pubertal timing of testes, breast, and pubic hair development (represented as Tanner stages were evaluated using an ordered logistic regression model adjusted for chronological age, body fat proportion (BF%, and parental education. Results: In boys, urinary mono-n-butyl phthalate (MBP levels were negatively associated with testicular volume, and mono (2-ethyl-5-hydroxyhexyl phthalate (MEHHP and mono (2-ethyl-5-oxohexyl phthalate (MEOHP levels were negatively associated with pubic hair stages. The odds of being in an advanced stage were decreased by 43%–51%. In girls, mono (2-ethylhexyl phthalate (MEHP, MEHHP, and MEOHP levels, as well as the sum of these levels, were positively associated with breast stages, and the association was much stronger in girls with high BF%; the odds of being in an advanced stage were increase by 29% to 50%. Conclusions: Phthalate metabolites investigated in this study show significant associations with pubertal timing both in boys and in girls, especially among girls with high BF%.

  13. Pubertal timing and adult obesity and cardiometabolic risk in women and men: a systematic review and meta-analysis.

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    Prentice, P; Viner, R M

    2013-08-01

    Obesity has complex multifactorial aetiology. It has been suggested by many, but not all, reports that earlier pubertal maturation may increase adult obesity risk. We conducted a systemic review and meta-analysis in both women and men, and hypothesised that any association between pubertal timing and adult obesity is likely to be confounded by childhood adiposity. In addition, we investigated whether pubertal timing is related to other cardiometabolic risk and long-term cardiovascular morbidity/mortality. Literature search was undertaken using MEDLINE, EMBASE, Web of Knowledge and TRIP databases, with a hand search of references. Both authors independently reviewed and extracted pre-defined data from all selected papers. Meta-analyses were conducted using Review Manager (RevMan) 5.0.24. A total of 48 papers were identified. Out of 34 studies, 30 reported an inverse relationship between pubertal timing and adult body mass index (BMI), the main adiposity measure used. Meta-analysis of 10 cohorts showed association between early menarche (menarche metabolic syndrome (MetS) and abnormal glycaemia. Earlier pubertal timing is predictive of higher adult BMI and greater risk of obesity. This effect appears to be partially independent of childhood BMI. Earlier pubertal development appears to also be inversely correlated with risk of other cardiometabolic risk factors and cardiovascular mortality. Further work is needed to examine potential mechanisms and the level at which interventions may be targeted.

  14. Sex differences in time to task failure during early pubertal development.

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    Rudroff, Thorsten; Holmes, Matthew R; Melanson, Edward L; Kelsey, Megan M

    2014-06-01

    We compared fatigability and activation of elbow flexor muscles in children at 3 pubertal stages during a sustained submaximal contraction. In 72 healthy children (39 boys) aged 11 ± 3 years (range, 8-14 years), differences in fatigability (time to task failure) and muscle activation were compared at 3 Tanner stages (T1-T3). Time to task failure and muscle activation were similar between boys and girls at prepubertal Tanner stage 1. Time to task failure was briefer for girls than boys at Tanner stages 2 and 3 and was predicted by the coactivation indices and percent body fat in girls. Muscle torque was the only predictor for the time to task failure in boys. Differences in fatigability and muscle coactivation were evident during the initial pubertal stages (T2 and T3), but not before the onset of puberty (T1). Copyright © 2013 Wiley Periodicals, Inc.

  15. Current Changes in Pubertal Timing: Revised Vision in Relation with Environmental Factors Including Endocrine Disruptors.

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    Parent, Anne-Simone; Franssen, Delphine; Fudvoye, Julie; Pinson, Anneline; Bourguignon, Jean-Pierre

    2016-01-01

    The aim of this chapter is to revise some common views on changes in pubertal timing. This revision is based on recent epidemiological findings on the clinical indicators of pubertal timing and data on environmental factor effects and underlying mechanisms. A current advancement in timing of female puberty is usually emphasized. It appears, however, that timing is also changing in males. Moreover, the changes are towards earliness for initial pubertal stages and towards lateness for final stages in both sexes. Such observations indicate the complexity of environmental influences on pubertal timing. The mechanisms of changes in pubertal timing may involve both the central neuroendocrine control and peripheral effects at tissues targeted by gonadal steroids. While sufficient energy availability is a clue to the mechanism of pubertal development, changes in the control of both energy balance and reproduction may vary under the influence of common determinants such as endocrine-disrupting chemicals (EDCs). These effects can take place right before puberty as well as much earlier, during fetal and neonatal life. Finally, environmental factors can interact with genetic factors in determining changes in pubertal timing. Therefore, the variance in pubertal timing is no longer to be considered under absolutely separate control by environmental and genetic determinants. Some recommendations are provided for evaluation of EDC impact in the management of pubertal disorders and for possible reduction of EDC exposure along the precautionary principle.

  16. Pubertal timing and health-related behaviours in adolescence - socio- economic outcomes in a follow-up study from Finland

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    Leena K Koivusilta

    2006-03-01

    Full Text Available

    Background. Pubertal timing is connected with health-related lifestyle in adulthood. We studied whether early or late pubertal timing is predictive of socio-economic outcomes in early adulthood and whether the associations are mediated by health behaviours.

    Methods. Survey data (1981, 1983, 1985, 1987 from samples of 14-year-old Finns (N=4246, response rate 85% were linked with respondents’ attained educational level, socio-economic and labour market position in 2001 (ages 28-34. Ages of menarche and first ejaculation indicated pubertal timing.

    Results. As compared to adolescents with average age pubertal timing, boys and girls maturing at an early age more often participated in health-compromising behaviours, while those maturing at a later age participated less frequently. Pubertal timing was not associated with attained educational level or socioeconomic position in girls and not with labour market position at the time of follow-up in either sex. In boys, independently of health behaviours, early or late onset of puberty predicted low educational level, while late onset predicted low socio-economic position.

    Conclusion. Timing of puberty has a stronger connection with socio-economic outcomes in boys than in girls. Deviance from the normative pace of physical development, especially late maturation, is among boys slightly depicted in the hierarchy of socio-economic positions of the society. As pubertal timing is connected with health-related behaviours – especially with smoking – the pacing of developmental transitions should be considered in planning programmes preventing unhealthy behavioural patterns often linked with negative attitudes towards schooling.

  17. Pubertal Timing and Depressive Symptoms in Early Adolescents: The Roles of Romantic Competence and Romantic Experiences

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    Stroud, Catherine B.; Davila, Joanne

    2008-01-01

    In spite of the large literature supporting the link between early pubertal timing and depression in adolescent girls, there are some exceptions. This suggests that there may be factors that interact with pubertal timing, increasing risk for depression in some girls, but not others. This study examined two such factors, romantic competence and…

  18. Ethnicity, Perceived Pubertal Timing, Externalizing Behaviors, and Depressive Symptoms among Black Adolescent Girls

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    Carter, Rona; Caldwell, Cleopatra Howard; Matusko, Niki; Antonucci, Toni; Jackson, James S.

    2011-01-01

    An accumulation of research evidence suggests that early pubertal timing plays a significant role in girls' behavioral and emotional problems. If early pubertal timing is a problematic event, then early developing Black girls should manifest evidence of this crisis because they tend to be the earliest to develop compared to other girls from…

  19. Recent changes in pubertal timing in healthy Danish boys

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    Sørensen, K; Aksglæde, Lise; Petersen, Jørgen Holm;

    2010-01-01

    In the 1990s, the American population-based study NHANES III renewed the focus on possible secular trends in male puberty. However, no conclusions could be made on pubertal onset due to the lack of compatible data....

  20. Childhood body size and pubertal timing in relation to adult mammographic density phenotype.

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    Schoemaker, Minouk J; Jones, Michael E; Allen, Steven; Hoare, Jean; Ashworth, Alan; Dowsett, Mitch; Swerdlow, Anthony J

    2017-02-07

    An earlier age at onset of breast development and longer time between pubertal stages has been implicated in breast cancer risk. It is not clear whether associations of breast cancer risk with puberty or predictors of onset of puberty, such as weight and height, are mediated via mammographic density, an important risk factor for breast cancer. We investigated whether childhood body size and pubertal timing and tempo, collected by questionnaire, are associated with percentage and absolute area mammographic density at ages 47-73 years in 1105 women recruited to a prospective study. After controlling for adult adiposity, weight at ages 7 and 11 years was strongly significantly inversely associated with percentage and absolute dense area (p trend density (p trend = 0.016). Later age at menarche and age at when regular periods were established was associated with increased density, but additional adjustment for childhood weight attenuated the association. A longer interval between thelarche and menarche, and between thelarche and regular periods, was associated with increased dense area, even after adjusting for childhood weight (p trend = 0.013 and 0.028, respectively), and was independent of age at pubertal onset. Greater prepubertal weight and earlier pubertal onset are associated with lower adult breast density, but age at pubertal onset does not appear to have an independent effect on adult density after controlling for childhood adiposity. A possible effect of pubertal tempo on density needs further investigation.

  1. Dioxin and Polychlorinated Biphenyl Concentrations in Mother's Serum and the Timing of Pubertal Onset in Sons

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    Humblet, Olivier; Williams, Paige L.; Korrick, Susan A.; Sergeyev, Oleg; Emond, Claude; Birnbaum, Linda S.; Burns, Jane S.; Altshul, Larisa; Patterson, Donald G.; Turner, Wayman E.; Lee, Mary M.; Revich, Boris; Hauser, Russ

    2013-01-01

    Background Animal studies have demonstrated that timing of pubertal onset can be altered by prenatal exposure to dioxins or polychlorinated biphenyls (PCBs), but studies of human populations have been quite limited. Methods We assessed the association between maternal serum concentrations of dioxins and PCBs and the sons’ age of pubertal onset in a prospective cohort of 489 mother–son pairs from Chapaevsk, Russia, a town contaminated with these chemicals during past industrial activity. The boys were recruited at ages 8 to 9 years, and 4 years of annual follow-up data were included in the analysis. Serum samples were collected at enrollment from both mothers and sons for measurement of dioxin and PCB concentrations using high-resolution mass spectrometry. The sons’ pubertal onset—defined as pubertal stage 2 or higher for genitalia (G) or pubic hair (P), or testicular volume >3 mL—was assessed annually by the same physician. Results In multivariate Cox models, elevated maternal serum PCBs were associated with earlier pubertal onset defined by stage G2 or higher (4th quartile hazard ratio = 1.7 [95% confidence interval = 1.1– 2.5]), but not for stage P2 or higher or for testicular volume >3 mL. Maternal serum concentrations of dioxin toxic equivalents were not consistently associated with the sons’ pubertal onset, although a dose-related delay in pubertal onset (only for G2 or higher) was seen among boys who breast-fed for 6 months or more. Conclusions Maternal PCB serum concentrations measured 8 or 9 years after sons’ births—which may reflect sons’ prenatal and early-life exposures—were associated with acceleration in some, but not all, measures of pubertal onset. PMID:21968773

  2. Genome-wide Association and Longitudinal Analyses Reveal Genetic Loci Linking Pubertal Height Growth, Pubertal Timing, and Childhood Adiposity

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    Cousminer, Diana L; Berry, Diane J; Timpson, Nicholas J

    2013-01-01

    and adverse cardiometabolic health. The only gene so far associated with pubertal height growth, LIN28B, pleiotropically influences childhood growth, puberty, and cancer progression, pointing to shared underlying mechanisms.To discover genetic loci influencing pubertal height and growth and place them...

  3. The Role of Pubertal Timing in What Adolescent Boys Do Online

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    Skoog, Therese; Stattin, Hakan; Kerr, Margaret

    2009-01-01

    The aim of this study was to investigate associations between pubertal timing and boys' Internet use, particularly their viewing of pornography. We used a sample comprising of 97 boys in grade 8 (M age, 14.22 years) from two schools in a medium-sized Swedish town. This age should be optimal for differentiating early, on-time, and later-maturing…

  4. [Contribution of anthropometric characteristics to pubertal stage prediction in young male individuals].

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    Medeiros, Radamés Maciel Vitor; Arrais, Ricardo Fernando; de Azevedo, Jenner Chrystian Veríssimo; do Rêgo, Jeferson Tafarel Pereira; de Medeiros, Jason Azevedo; de Andrade, Ricardo Dias; Dantas, Paulo Moreira Silva

    2014-09-01

    To identify the contribution of anthropometric variables to predict the maturational stage in young males. Cross-sectional study that enrolled 190 male subjects aged between eight and 18 years, randomly selected from public and private schools in Natal, Northeast Brazil. Thirty-two anthropometric variables were measured following the recommendations of the International Society for the Advancement of Kineanthropometry (ISAK). The assessment of sexual maturation was based on the observation of two experienced experts, who identified the pubertal development according to Tanner guidelines (1962). The anthropometric variables showed a significant increase of their values during the advancement of pubertal development (p<0.05). The following variables showed the best value for prediction of maturational groups: sitting height, femoral biepicondylar diameter, forearm girth, triceps skinfold, tibiale laterale and acromiale-radiale bone lenghts. These variables were able to estimate the pubertal stages in 76.3% of the sujects. The anthropometric characteristics showed significant differences between the moments of maturational stages, being found, representatively, seven variables that best predict the stages of sexual maturation. Copyright © 2014 Sociedade de Pediatria de São Paulo. Publicado por Elsevier Editora Ltda. All rights reserved.

  5. Pubertal Timing and Early Sexual Intercourse in the Offspring of Teenage Mothers

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    De Genna, Natacha M.; Larkby, Cynthia; Cornelius, Marie D.

    2011-01-01

    Early puberty is associated with stressful family environments, early sexual intercourse, and teenage pregnancy. We examined pubertal timing and sexual debut among the 14-year-old offspring of teenage mothers. Mothers (71% Black, 29% White) were recruited as pregnant teenagers (12-18 years old). Data were collected during pregnancy and when…

  6. Early adolescent boys’ exposure to Internet pornography: relationships to pubertal timing, sensation seeking, and academic performance

    NARCIS (Netherlands)

    I. Beyens; L. Vandenbosch; S. Eggermont

    2014-01-01

    Research has demonstrated that adolescents regularly use Internet pornography. This two-wave panel study aimed to test an integrative model in early adolescent boys (Mage = 14.10; N = 325) that (a) explains their exposure to Internet pornography by looking at relationships with pubertal timing and s

  7. Pubertal Timing and Mexican-Origin Girls' Internalizing and Externalizing Symptoms: The Influence of Harsh Parenting

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    Deardorff, Julianna; Cham, Heining; Gonzales, Nancy A.; White, Rebecca M. B.; Tein, Jenn-Yun; Wong, Jessie J.; Roosa, Mark W.

    2013-01-01

    Early-maturing girls are at risk for internalizing and externalizing problems. Research concerning pubertal timing and mental health among Mexican Americans or the influence of parenting behaviors on these relations has been scarce. This study addressed these gaps. This was a prospective examination of 362 Mexican-origin girls and their mothers in…

  8. Pubertal Timing and Early Sexual Intercourse in the Offspring of Teenage Mothers

    Science.gov (United States)

    De Genna, Natacha M.; Larkby, Cynthia; Cornelius, Marie D.

    2011-01-01

    Early puberty is associated with stressful family environments, early sexual intercourse, and teenage pregnancy. We examined pubertal timing and sexual debut among the 14-year-old offspring of teenage mothers. Mothers (71% Black, 29% White) were recruited as pregnant teenagers (12-18 years old). Data were collected during pregnancy and when…

  9. Early Adolescent Boys' Exposure to Internet Pornography: Relationships to Pubertal Timing, Sensation Seeking, and Academic Performance

    Science.gov (United States)

    Beyens, Ine; Vandenbosch, Laura; Eggermont, Steven

    2015-01-01

    Research has demonstrated that adolescents regularly use Internet pornography. This two-wave panel study aimed to test an integrative model in early adolescent boys (M[subscript age] = 14.10; N = 325) that (a) explains their exposure to Internet pornography by looking at relationships with pubertal timing and sensation seeking, and (b) explores…

  10. Early Pubertal Timing and the Union Formation Behaviors of Young Women

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    Cavanagh, Shannon E.

    2011-01-01

    This study examined whether the transition into adolescence, proxied by pubertal timing, shaped the transition into adulthood, proxied by union formation behaviors, among contemporary American women. In a sample drawn from Add Health (n = 7,523), early maturing girls reported an accelerated transition to marriage and cohabitation in young…

  11. Early adolescent boys’ exposure to Internet pornography: relationships to pubertal timing, sensation seeking, and academic performance

    NARCIS (Netherlands)

    Beyens, I.; Vandenbosch, L.; Eggermont, S.

    2015-01-01

    Research has demonstrated that adolescents regularly use Internet pornography. This two-wave panel study aimed to test an integrative model in early adolescent boys (Mage = 14.10; N = 325) that (a) explains their exposure to Internet pornography by looking at relationships with pubertal timing and s

  12. Early Adolescent Boys' Exposure to Internet Pornography: Relationships to Pubertal Timing, Sensation Seeking, and Academic Performance

    Science.gov (United States)

    Beyens, Ine; Vandenbosch, Laura; Eggermont, Steven

    2015-01-01

    Research has demonstrated that adolescents regularly use Internet pornography. This two-wave panel study aimed to test an integrative model in early adolescent boys (M[subscript age] = 14.10; N = 325) that (a) explains their exposure to Internet pornography by looking at relationships with pubertal timing and sensation seeking, and (b) explores…

  13. Subjective Age in Early Adolescence: Relationships with Chronological Age, Pubertal Timing, Desired Age, and Problem Behaviors

    Science.gov (United States)

    Hubley, Anita M.; Arim, Rubab G.

    2012-01-01

    Subjective age generally refers to the age that one feels. In a cross-sectional questionnaire study of 245 adolescents ages 10-14 years, we examined (a) whether, and when, a cross-over in subjective age occurs, (b) differences in subjective age among pubertal timing groups, (c) correlations between subjective age and each of desired age and five…

  14. Associations of Peripubertal Serum Dioxin and Polychlorinated Biphenyl Concentrations with Pubertal Timing among Russian Boys.

    Science.gov (United States)

    Burns, Jane S; Lee, Mary M; Williams, Paige L; Korrick, Susan A; Sergeyev, Oleg; Lam, Thuy; Revich, Boris; Hauser, Russ

    2016-11-01

    Dioxins, furans, and polychlorinated biphenyls (PCBs), dioxin-like and non-dioxin-like, have been linked to alterations in puberty. We examined the association of peripubertal serum levels of these compounds [and their toxic equivalents (TEQs)] with pubertal onset and maturity among Russian boys enrolled at ages 8-9 years and followed prospectively through ages 17-18 years. At enrollment, 473 boys had serum dioxin-like compounds and PCBs measured. At the baseline visit and annually until age 17-18 years, a physician performed pubertal staging [genitalia (G), pubarche (P), and testicular volume (TV)]. Three hundred fifteen subjects completed the follow-up visit at 17-18 years of age. Pubertal onset was defined as TV > 3 mL, G2, or P2. Sexual maturity was defined as TV ≥ 20 mL, G5, or P5. Multivariable interval-censored models were used to evaluate associations of lipid-standardized concentrations with pubertal timing. Medians (interquartile ranges) of the sum of dioxin-like compounds, TEQs, and non-dioxin-like PCBs were 362 pg/g lipid (279-495), 21.1 pg TEQ/g lipid (14.4-33.2), and 250 ng/g lipid (164-395), respectively. In adjusted models, the highest compared to lowest TEQ quartile was associated with later pubertal onset [TV = 11.6 months (95% CI: 3.8, 19.4); G2 = 10.1 months (95% CI: 1.4, 18.8)] and sexual maturity [TV = 11.6 months (95% CI: 5.7, 17.6); G5 = 9.7 months (95% CI: 3.1, 16.2)]. However, the highest compared to the lowest quartile of non-dioxin-like PCBs, when co-adjusted by TEQs, was associated with earlier pubertal onset [TV = -8.3 months (95% CI:-16.2, -0.3)] and sexual maturity [TV = -6.3 months (95% CI:-12.2, -0.3); G5 = -7.2 months (95% CI:-13.8, -0.6)]; the non-dioxin-like PCB associations were only significant when adjusted for TEQs. TEQs and PCBs were not significantly associated with pubic hair development. Our results suggest that TEQs may delay, while non-dioxin-like PCBs advance, the timing of male puberty. Citation: Burns JS, Lee MM

  15. Genome-wide association and longitudinal analyses reveal genetic loci linking pubertal height growth, pubertal timing and childhood adiposity

    NARCIS (Netherlands)

    Cousminer, Diana L.; Berry, Diane J.; Timpson, Nicholas J.; Ang, Wei; Thiering, Elisabeth; Byrne, Enda M.; Taal, H. Rob; Huikari, Ville; Bradfield, Jonathan P.; Kerkhof, Marjan; Groen-Blokhuis, Maria M.; Kreiner-Moller, Eskil; Marinelli, Marcella; Holst, Claus; Leinonen, Jaakko T.; Perry, John R. B.; Surakka, Ida; Pietilainen, Olli; Kettunen, Johannes; Anttila, Verneri; Kaakinen, Marika; Sovio, Ulla; Pouta, Anneli; Das, Shikta; Lagou, Vasiliki; Power, Chris; Prokopenko, Inga; Evans, David M.; Kemp, John P.; St Pourcain, Beate; Ring, Susan; Palotie, Aarno; Kajantie, Eero; Osmond, Clive; Lehtimaki, Terho; Viikari, Jorma S.; Kahonen, Mika; Warrington, Nicole M.; Lye, Stephen J.; Palmer, Lyle J.; Tiesler, Carla M. T.; Flexeder, Claudia; Montgomery, Grant W.; Medland, Sarah E.; Hofman, Albert; Hakonarson, Hakon; Guxens, Monica; Bartels, Meike; Salomaa, Veikko; Murabito, Joanne M.; Kaprio, Jaakko; Sorensen, Thorkild I. A.; Ballester, Ferran; Bisgaard, Hans; Boomsma, Dorret I.; Koppelman, Gerard H.; Grant, Struan F. A.; Jaddoe, Vincent W. V.; Martin, Nicholas G.; Heinrich, Joachim; Pennell, Craig E.; Raitakari, Olli T.; Eriksson, Johan G.; Smith, George Davey; Hypponen, Elina; Jarvelin, Marjo-Riitta; McCarthy, Mark I.; Ripatti, Samuli; Widen, Elisabeth

    2013-01-01

    The pubertal height growth spurt is a distinctive feature of childhood growth reflecting both the central onset of puberty and local growth factors. Although little is known about the underlying genetics, growth variability during puberty correlates with adult risks for hormone-dependent cancer and

  16. The influence of early sexual debut and pubertal timing on psychological distress among Taiwanese adolescents.

    Science.gov (United States)

    Chiao, Chi; Ksobiech, Kate

    2015-01-01

    This study examined the relative influence of early sexual debut (ESD) and pubertal timing on psychological distress from adolescence to young adulthood in Taiwan, a non-Western society with a distinct cultural and family context. Data were from a cohort sample of 15-year-olds (N = 2595) first interviewed in 2000, with four follow-ups during a 7-year period. Psychological distress was assessed by a reduced form of the Symptom Checklist-90 Revised. ESD was defined by first intercourse at age 15 or younger. Multivariate analyses via growth curve modeling found a greater increase in psychological distress over time in adolescents with ESD (β = .28, p influence of both ESD and pubertal timing on distress trajectories, independent of parental and family characteristics.

  17. Pubertal status, pre-meal drink composition, and later meal timing interact in determining children's appetite and food intake.

    Science.gov (United States)

    Patel, Barkha P; Hamilton, Jill K; Vien, Shirley; Thomas, Scott G; Anderson, G Harvey

    2016-09-01

    Puberty is a period of development that alters energy intake patterns. However, few studies have examined appetite and food intake (FI) regulation during development of puberty in children and adolescents. Therefore, the objective was to measure the effect of pubertal status on FI and subjective appetite after pre-meal glucose and whey protein drinks in 9- to 14-year-old boys and girls. In a within-subject, randomized, repeated-measures design, children (21 pre-early pubertal, 15 mid-late pubertal) received equally sweetened drinks containing Sucralose (control), glucose, or whey protein (0.75 g/kg body weight) in 250 mL of water 2 h after a standardized breakfast on 6 separate mornings. Ad libitum FI was measured either 30 or 60 min later and appetite was measured over time. In pre-early and mid-late pubertal boys and girls there was no effect of sex on total FI (kcal). Glucose and whey protein drinks reduced calorie intake similarly at 30 min. But at 60 min, whey protein reduced FI (p children, but not in mid-late pubertal children. However, sex was a factor (p = 0.041) when FI was expressed per kilogram body weight. Pubertal status did not affect FI/kilogram body weight in boys, but it was 32% lower in mid-late pubertal girls than at pre-early puberty (p = 0.010). Appetite was associated with FI in mid-late pubertal children only. In conclusion, pubertal development affects appetite and FI regulation in children.

  18. Sex 'n' drugs 'n' rock 'n' roll: the meaning and social consequences of pubertal timing.

    Science.gov (United States)

    Waylen, Andrea; Wolke, Dieter

    2004-11-01

    This is a brief review of the normal changes in adolescent behaviour and the interplay between biology and social factors that occur at and around puberty, in an attempt to explain when this transition may become problematic The onset of puberty is a biological marker for an individual's transition from a non-reproductive to a reproductive state. Adolescence is a normal developmental transition associated with clearly visible physical changes, reorganization and pruning of neuronal circuits in the brain and the occurrence of new behaviours and interests. It is a time when new life tasks (orientation towards peers of the other sex, romantic and sexual involvement and mastering an educational career) need to be mastered. Parent-child conflict increases and becomes more intense as the adolescent struggles for more independence while still requiring support. These normal changes can become problematic if biological and social expectations diverge e.g. entering puberty very early or very late. While early pubertal onset in boys is likely to have beneficial effects, in girls precocious pubertal timing may have a negative impact on body-image, affect (or emotional well-being) and sex-role expectations. Other individual biological predispositions and genetic endowment may interact with social factors (e.g. peers, parenting style, neighbourhood) making adolescence either an adaptive or a challenging transition. There is a lack of sufficiently large longitudinal studies that have been able to study this interaction between genetics, biology and social environment on adolescent development. The Avon Longitudinal Study of Parents and Children (ALSPAC) cohort provides a unique opportunity to investigate the impact of pubertal timing on social behaviour. Planned assessments and concepts are outlined.

  19. The Effect of Pubertal and Psychosocial Timing on Adolescents' Alcohol Use: What Role Does Alcohol-Specific Parenting Play?

    Science.gov (United States)

    Schelleman-Offermans, Karen; Knibbe, Ronald A.; Engels, Rutger C. M. E.; Burk, William J.

    2011-01-01

    In scientific literature, early pubertal timing emerges as a risk factor of adolescents' drinking, whereas alcohol-specific rules (the degree to which parents permit their children to consume alcohol in various situations) showed to protect against adolescents' drinking. This study investigated whether alcohol-specific rules mediate and/or…

  20. Effects of Pubertal Timing on Communication Behaviors and Stress Reactivity in Young Women during Conflict Discussions with Their Mothers

    Science.gov (United States)

    Weichold, Karina; Buttig, Sabine; Silbereisen, Rainer K.

    2008-01-01

    Individuation, a process whereby adolescents gain autonomy from their parents while maintaining emotional relatedness, is displayed by characteristic styles of verbal exchanges. Negotiating this developmental transition is often stressful for adolescents and their parents. This study deals with the association between pubertal timing,…

  1. Recent changes in pubertal timing in healthy Danish boys: associations with body mass index

    DEFF Research Database (Denmark)

    Sørensen, Kaspar; Aksglaede, Lise; Petersen, Jørgen Holm;

    2010-01-01

    In the 1990s, the American population-based study NHANES III renewed the focus on possible secular trends in male puberty. However, no conclusions could be made on pubertal onset due to the lack of compatible data....

  2. Brief Report: Fathers' and Mothers' Marital Relationship Predicts Daughters' Pubertal Development Two Years Later

    Science.gov (United States)

    Saxbe, Darby E.; Repetti, Rena L.

    2009-01-01

    Parents of 50 4th grade girls reported on their marital relationships and then, two years later, rated their daughters' pubertal development. Fathers' ratings of marital dissatisfaction, mothers' ratings of less emotional support from husbands, and both parents' ratings of aversive marital conflict were correlated with more advanced pubertal…

  3. Pubertal Development, Personality, and Substance Use: A 10-Year Longitudinal Study From Childhood to Adolescence

    Science.gov (United States)

    Castellanos-Ryan, Natalie; Parent, Sophie; Vitaro, Frank; Tremblay, Richard E.; Séguin, Jean R.

    2013-01-01

    Most research linking early pubertal development to substance use has focused on the effects of pubertal timing (age at which a certain stage of pubertal development is reached or pubertal status at a particular age—related to the maturation disparity hypothesis), but little research has focused on pubertal tempo (rate of growth through pubertal stages—related to the maturation compression hypothesis). However, both timing and tempo have not only been identified as important components of pubertal development, with different predictors, but have also been shown to be independently associated with other adolescent psychopathologies. Using latent growth-curve modeling, this study examined how pubertal status at age 12 and pubertal tempo (between 11 and 13 years) related to substance use from 15 to 16 years in boys from low socioeconomic backgrounds (N = 871). Results showed that both pubertal status at age 12 and tempo were significant predictors of increased levels of substance use and problems in mid to late adolescence. In an attempt to identify mechanisms that may explain the association between pubertal development and substance use it was found that sensation seeking partially mediated the association between pubertal status at age 12 and substance use behaviors. Impulse control was found to moderate the association sensation seeking had with marijuana use frequency, with high sensation-seeking scores predicting higher marijuana use frequency only at low levels of impulse control. These findings highlight the importance of considering multiple sources of individual variability in the pubertal development of boys and provide support for both the maturational disparity and compression hypotheses. PMID:24016016

  4. Pubertal development, personality, and substance use: a 10-year longitudinal study from childhood to adolescence.

    Science.gov (United States)

    Castellanos-Ryan, Natalie; Parent, Sophie; Vitaro, Frank; Tremblay, Richard E; Séguin, Jean R

    2013-08-01

    Most research linking early pubertal development to substance use has focused on the effects of pubertal timing (age at which a certain stage of pubertal development is reached or pubertal status at a particular age--related to the maturation disparity hypothesis), but little research has focused on pubertal tempo (rate of growth through pubertal stages--related to the maturation compression hypothesis). However, both timing and tempo have not only been identified as important components of pubertal development, with different predictors, but have also been shown to be independently associated with other adolescent psychopathologies. Using latent growth-curve modeling, this study examined how pubertal status at age 12 and pubertal tempo (between 11 and 13 years) related to substance use from 15 to 16 years in boys from low socioeconomic backgrounds (N = 871). Results showed that both pubertal status at age 12 and tempo were significant predictors of increased levels of substance use and problems in mid to late adolescence. In an attempt to identify mechanisms that may explain the association between pubertal development and substance use it was found that sensation seeking partially mediated the association between pubertal status at age 12 and substance use behaviors. Impulse control was found to moderate the association sensation seeking had with marijuana use frequency, with high sensation-seeking scores predicting higher marijuana use frequency only at low levels of impulse control. These findings highlight the importance of considering multiple sources of individual variability in the pubertal development of boys and provide support for both the maturational disparity and compression hypotheses.

  5. Peer and Individual Risk Factors in Adolescence Explaining the Relationship Between Girls' Pubertal Timing and Teenage Childbearing.

    Science.gov (United States)

    Hendrick, C Emily; Cance, Jessica Duncan; Maslowsky, Julie

    2016-05-01

    Girls with early pubertal timing are at elevated risk for teenage childbearing; however, the modifiable mechanisms driving this relationship are not well understood. The objective of the current study was to determine whether substance use, perceived peer substance use, and older first sexual partners mediate the relationships among girls' pubertal timing, sexual debut, and teenage childbearing. Data are from Waves 1-15 of the female cohort of the National Longitudinal Surveys of Youth 1997 (NLSY97), a nationwide, ongoing cohort study of U.S. men and women born between 1980 and 1984. The analytic sample (n = 2066) was 12-14 years old in 1997 and ethnically diverse (51 % white, 27 % black, 22 % Latina). Using structural equation modeling, we found substance use in early adolescence and perceived peer substance use each partially mediated the relationships among girls' pubertal timing, sexual debut, and teenage childbearing. Our findings suggest early substance use behavior as one modifiable mechanism to be targeted by interventions aimed at preventing teenage childbearing among early developing girls.

  6. Developmental variations in environmental influences including endocrine disruptors on pubertal timing and neuroendocrine control: Revision of human observations and mechanistic insight from rodents.

    Science.gov (United States)

    Parent, Anne-Simone; Franssen, Delphine; Fudvoye, Julie; Gérard, Arlette; Bourguignon, Jean-Pierre

    2015-07-01

    Puberty presents remarkable individual differences in timing reaching over 5 years in humans. We put emphasis on the two edges of the age distribution of pubertal signs in humans and point to an extended distribution towards earliness for initial pubertal stages and towards lateness for final pubertal stages. Such distortion of distribution is a recent phenomenon. This suggests changing environmental influences including the possible role of nutrition, stress and endocrine disruptors. Our ability to assess neuroendocrine effects and mechanisms is very limited in humans. Using the rodent as a model, we examine the impact of environmental factors on the individual variations in pubertal timing and the possible underlying mechanisms. The capacity of environmental factors to shape functioning of the neuroendocrine system is thought to be maximal during fetal and early postnatal life and possibly less important when approaching the time of onset of puberty.

  7. Consequences of Early Life Programing by Genetic and Environmental Influences: A Synthesis Regarding Pubertal Timing.

    Science.gov (United States)

    Roth, Christian L; DiVall, Sara

    2016-01-01

    Sexual maturation is closely tied to growth and body weight gain, suggesting that regulative metabolic pathways are shared between somatic and pubertal development. The pre- and postnatal environment affects both growth and pubertal development, indicating that common pathways are affected by the environment. Intrauterine and early infantile developmental phases are characterized by high plasticity and thereby susceptibility to factors that affect metabolic function as well as related reproductive function throughout life. In children born small for gestational age, poor nutritional conditions during gestation can modify metabolic systems to adapt to expectations of chronic undernutrition. These children are potentially poorly equipped to cope with energy-dense diets and are possibly programmed to store as much energy as possible, causing rapid weight gain with the risk for adult disease and premature onset of puberty. Environmental factors can cause modifications to the genome, so-called epigenetic changes, to affect gene expression and subsequently modify phenotypic expression of genomic information. Epigenetic modifications, which occur in children born small for gestational age, are thought to underlie part of the metabolic programming that subsequently effects both somatic and pubertal development. © 2016 S. Karger AG, Basel.

  8. 遗传因素对青春期启动时间的调控%Genetics of pubertal timing

    Institute of Scientific and Technical Information of China (English)

    马晓宇

    2010-01-01

    青春期是性成熟并获得生殖能力的重要发育阶段.遗传因素是对个体青春期启动时间影响最大的因素.近来分子遗传学的分析逐渐阐明了一些青春发育时间异常疾病的遗传学基础,例如特发性低促性腺激素性性功能减退症和Kallmann综合征.一般人群青春启动时间变异的遗传学基础成为目前研究的热点,然而迄今为止却没有一个基因位点被证实与性发育时间有关.该文主要阐述与青春期启动时间异常有关的基因学研究进展,并讨论与正常青春期启动时间有关的基因.%Puberty is an important developmental stage that leads to sexual maturation and reproductive capability. Genetic factors play a significant role in regulating the variation of pubertal timing. Recent genetic analysis are increasingly elucidating the genetic basis of disorders of pubertal timing such as hypogonadotropic hypogonadism and Kallmann syndrome. Ongoing studies are also investigating the genetic control of puberty in the general population, although no genetic loci have been reproducibly associated with pubertal timing thus far. This review summarizes an update of the genes implicated in disorders of puberty,discusses genes that may be involved in the timing of normal puberty.

  9. Racial disparities in pubertal development.

    Science.gov (United States)

    Ramnitz, Mary Scott; Lodish, Maya B

    2013-09-01

    The question of whether or not children, particularly girls, are entering puberty earlier than they did in the past has been a concern in both the medical community and the general population. A secular trend analysis of the current data on pubertal timing in boys and girls is limited by variations in the study design, the population assessed, and the methods used to determine pubertal development. These differences present a challenge when interpreting the available data, especially when comparing multiple studies. The influence of race on pubertal timing and development had not been assessed before the 1970s. The purpose of this article is to review the reported variations in pubertal timing among different racial/ethnic groups. Data suggest African American girls enter puberty earlier and reach menarche earlier than Caucasian and Hispanic girls. In addition, the trend toward earlier timing of puberty seems to be occurring faster in African American girls compared with Caucasian girls over the past 25 years. While the mechanism and understanding of the cause of racial disparities in pubertal development remain to be discerned, genetic and/or environmental factors may play a role and require further investigation.

  10. Is Time Predictability Quantifiable?

    DEFF Research Database (Denmark)

    Schoeberl, Martin

    2012-01-01

    -case execution time. To compare different approaches we would like to quantify time predictability. That means we need to measure time predictability. In this paper we discuss the different approaches for these measurements and conclude that time predictability is practically not quantifiable. We can only......Computer architects and researchers in the realtime domain start to investigate processors and architectures optimized for real-time systems. Optimized for real-time systems means time predictable, i.e., architectures where it is possible to statically derive a tight bound of the worst...... compare the worst-case execution time bounds of different architectures....

  11. Elite athletes and pubertal delay.

    Science.gov (United States)

    Kapczuk, Karina

    2017-10-01

    Intensive physical training and participation in competitive sports during childhood and early adolescence may affect athletes' pubertal development. On the other hand, pubertal timing, early or late, may impact on an athlete selection for a particular sport. Genetic predisposition, training load, nutritional status and psychological stress determine athletes' pubertal timing. Athletes that practice esthetic sports, especially gymnasts, are predisposed to a delay in pubertal development. The growing evidence indicates that energy deficiency, not a systemic training per se, plays a crucial role in the pathogenesis of functional hypothalamic hypogonadism in female athletes. Metabolic and psychologic stress activate hypothalamic-pituitary-adrenal axis and suppress hypothalamic-pituitary-ovarian axis. Female athletes who do not begin secondary sexual development by the age of 14 or menstruation by the age of 16 warrant a comprehensive evaluation and a targeted treatment. Somatic growth and sexual maturation of elite female athletes are largely sport-specific since each sport favors a particular somatotype and requires a specific training. Chronic negative energy balance resulting from a systemic physical training and inadequate energy intake may delay pubertal development in elite athletes. Youth athletes, especially those engaged in competitive sports that emphasize prepubertal or lean appearance, are at risk of developing relative energy deficiency in sport associated with disordered eating or eating disorders. Management strategies should address the complex conditions underlying functional hypothalamic hypogonadism.

  12. Forty years trends in timing of pubertal growth spurt in 157,000 Danish school children

    DEFF Research Database (Denmark)

    Aksglæde, Lise; Olsen, Lina Wøhlk; Sørensen, Thorkild I.A.;

    2008-01-01

    BACKGROUND: Entering puberty is an important milestone in reproductive life and secular changes in the timing of puberty may be an important indicator of the general reproductive health in a population. Too early puberty is associated with several psychosocial and health problems. The aim of our...... a secular trend towards earlier sexual maturation of Danish children born between 1930 and 1969. Only minor changes were observed in duration of puberty assessed by the difference in ages at OGS and PHV Udgivelsesdato: 2008...

  13. Time-predictable architectures

    CERN Document Server

    Rochange, Christine; Uhrig , Sascha

    2014-01-01

    Building computers that can be used to design embedded real-time systems is the subject of this title. Real-time embedded software requires increasingly higher performances. The authors therefore consider processors that implement advanced mechanisms such as pipelining, out-of-order execution, branch prediction, cache memories, multi-threading, multicorearchitectures, etc. The authors of this book investigate the timepredictability of such schemes.

  14. Pubertal development in Danish children

    DEFF Research Database (Denmark)

    Juul, A; Teilmann, G; Scheike, Thomas Harder

    2006-01-01

    differences between USA and Denmark, as well as to look for possible secular trends in pubertal development. Healthy Caucasian children from public schools in Denmark participated in the study which was carried out in 1991-1993. A total number of 826 boys and 1,100 girls (aged 6.0-19.9 years) were included......Two recent epidemiological studies (PROS and NHANES III) from the USA noted earlier sexual maturation in girls, leading to increased attention internationally to the age at onset of puberty. We studied the timing of puberty in a large cohort of healthy Danish children in order to evaluate......, and pubertal stages were assessed by clinical examination according to methods of Tanner. In boys testicular volume was determined using an orchidometer. We found that age at breast development 2 (B2) was 10.88 years, and mean menarcheal age was 13.42 years. Girls with body mass index (BMI) above the median...

  15. Hormonal determinants of pubertal growth.

    NARCIS (Netherlands)

    Delamarre-van Waal, H.A.; Coeverden, S.C. van; Rotteveel, J.J.

    2001-01-01

    Pubertal growth results from increased sex steroid and growth hormone (GH) secretion. Estrogens appear to play an important role in the regulation of pubertal growth in both girls and boys. In girls, however, estrogens cannot be the only sex steroids responsible for pubertal growth, as exogenous est

  16. Nutrition and pubertal development

    Directory of Open Access Journals (Sweden)

    Ashraf Soliman

    2014-01-01

    Full Text Available Nutrition is one of the most important factors affecting pubertal development. Puberty entails a progressive nonlinear process starting from prepubescent to full sexual maturity through the interaction and cooperation of biological, physical, and psychological changes. Consuming an adequate and balanced healthy diet during all phases of growth (infancy, childhood and puberty appears necessary both for proper growth and normal pubertal development. Girls begin puberty at an earlier age compared to past decades. Excessive eating of many processed, high-fat foods, may be the cause of this phenomenon. Overweight or obese children are more likely to enter puberty early. Some evidence suggests that obesity can accelerate the onset of puberty in girls and may delay the onset of puberty in boys. Moreover, the progression of puberty is affected by nutrition. On the other hand, puberty triggers a growth spurt, which increases nutritional needs including macro and micronutrients. Increased caloric, protein, iron, calcium, zinc and folate needs have to be provided during this critical period of rapid growth. Severe primary or secondary malnutrition also can delay the onset and progression of puberty. The higher incidence of anorexia nervosa and bulimia in adolescents imposes a nutritional risk on pubertal development. Moreover, many environmental endocrine disruptors (EDs have been identified that can significantly impair the normal course of puberty. This mini-review sums up some important findings in this important complex that link nutrition and pubertal development.

  17. Season of birth is associated with birth weight, pubertal timing, adult body size and educational attainment: a UK Biobank study

    Directory of Open Access Journals (Sweden)

    Felix R. Day

    2015-10-01

    Full Text Available Season of birth, a marker of in utero vitamin D exposure, has been associated with a wide range of health outcomes. Using a dataset of ∼450,000 participants from the UK Biobank study, we aimed to assess the impact of this seasonality on birth weight, age at menarche, adult height and body mass index (BMI. Birth weight, age at menarche and height, but not BMI, were highly significantly associated with season of birth. Individuals born in summer (June–July–August had higher mean birth weight (P = 8 × 10−10, later pubertal development (P = 1.1 × 10−45 and taller adult height (P = 6.5 × 10−9 compared to those born in all other seasons. Concordantly, those born in winter (December–January–February showed directionally opposite differences in these outcomes. A secondary comparison of the extreme differences between months revealed higher odds ratios [95% confidence intervals (CI] for low birth weight in February vs. September (1.23 [1.15–1.32], P = 4.4 × 10−10, for early puberty in September vs. July (1.22 [1.16–1.28], P = 7.3 × 10−15 and for short stature in December vs. June (1.09 [1.03–1.17], P = 0.006. The above associations were also seen with total hours of sunshine during the second trimester, but not during the first three months after birth. Additional associations were observed with educational attainment; individuals born in autumn vs. summer were more likely to continue in education post age 16 years (P = 1.1 × 10−91 or attain a degree-level qualification (P = 4 × 10−7. However, unlike other outcomes, an abrupt difference was seen between those born in August vs. September, which flank the start of the school year. Our findings provide support for the ‘fetal programming’ hypothesis, refining and extending the impact that season of birth has on childhood growth and development. Whilst other mechanisms may contribute to these associations, these findings are consistent with a possible role of in utero

  18. Predicting Nonlinear Time Series

    Science.gov (United States)

    1993-12-01

    response becomes R,(k) = f (Y FV,(k)) (2.4) where Wy specifies the weight associated with the output of node i to the input of nodej in the next layer and...interconnections for each of these previous nodes. 18 prr~~~o• wfe :t iam i -- ---- --- --- --- Figure 5: Delay block for ATNN [9] Thus, nodej receives the...computed values, aj(tn), and dj(tn) denotes the desired output of nodej at time in. In this thesis, the weights and time delays update after each input

  19. Time-predictable Stack Caching

    DEFF Research Database (Denmark)

    Abbaspourseyedi, Sahar

    complicated and less imprecise. Time-predictable computer architectures provide solutions to this problem. As accesses to the data in caches are one source of timing unpredictability, devising methods for improving the timepredictability of caches are important. Stack data, with statically analyzable......Embedded systems are computing systems for controlling and interacting with physical environments. Embedded systems with special timing constraints where the system needs to meet deadlines are referred to as real-time systems. In hard real-time systems, missing a deadline causes the system to fail...... addresses, provides an opportunity to predict and tighten the WCET of accesses to data in caches. In this thesis, we introduce the time-predictable stack cache design and implementation within a time-predictable processor. We introduce several optimizations to our design for tightening the WCET while...

  20. Pubertal development in Danish children

    DEFF Research Database (Denmark)

    Juul, A; Teilmann, G; Scheike, Thomas Harder

    2006-01-01

    Two recent epidemiological studies (PROS and NHANES III) from the USA noted earlier sexual maturation in girls, leading to increased attention internationally to the age at onset of puberty. We studied the timing of puberty in a large cohort of healthy Danish children in order to evaluate differe...... genetic polymorphisms, nutrition, physical activity or endocrine disrupting chemicals must therefore also be considered. Therefore, we believe it is crucial to monitor the pubertal development closely in Denmark in the coming decades.......Two recent epidemiological studies (PROS and NHANES III) from the USA noted earlier sexual maturation in girls, leading to increased attention internationally to the age at onset of puberty. We studied the timing of puberty in a large cohort of healthy Danish children in order to evaluate...

  1. Time series prediction in agroecosystems

    Science.gov (United States)

    Cortina-Januchs, M. G.; Quintanilla-Dominguez, J.; Vega-Corona, A.; Andina, D.

    2012-04-01

    This work proposes a novel model to predict time series such as frost, precipitation, temperature, solar radiation, all of them important variables for the agriculture process. In the proposed model, Artificial Neural Networks (ANN) combined with clustering algorithms and sensor data fusion are used. The real time series are obtained from different sensors. The clustering algorithms find relationships between variables, clustering involves the task of dividing data sets, which assigns the same label to members who belong to the same group, so that each group is homogeneous and distinct from the others. Those relationships provide information to the ANN in order to obtain the time series prediction. The most important issue of ANN in time series prediction is generalization, which refers to their ability to produce reasonable predictions on data sets other than those used for the estimation of the model parameters.

  2. 中学生攻击行为与自感青春发动时相及学校因素的关系%Association of aggressive behavior with perceived pubertal timing and school factors in middle school students

    Institute of Scientific and Technical Information of China (English)

    俞荷俊; 乔淮燕; 张戎; 周英; 姚荣英

    2013-01-01

    目的 按不同性别探索中学生攻击行为与自感青春发动时相及学校因素的关系.方法 对2 791名中学生进行青春发育状况、攻击行为的问卷调查.结果 不同自感青春发动时相中学生攻击行为得分差异有统计学意义(F=14.676,P<0.05);不同学校风气、师生关系、同学关系、好朋友数中学生攻击行为得分差异有统计学意义(P<0.05);多重线性回归显示,男生攻击行为的影响因素为学校风气、自感青春发动时相、师生关系(β分别为-0.134、-0.114、-0.098,P<0.05);女生攻击行为的影响因素为师生关系、好朋友数、学校风气、自感青春发动时相(β分别为-0.120、-0.103、-0.102、-0.089,P<0.05).结论 自感青春发动时相及学校因素对中学生攻击行为的影响存在性别差异,在预防上应将时相偏离(提前或推迟)的男生,时相提前的女生列入重点对象.%Objective To explore the relationship between perceived pubertal timing together with school factors and the aggressive behavior in middle school students with different genders.Methods A total of 2 791 middle school students were surveyed by a questionnaire for youth development status and aggressive behavior.Results The score of aggressive behavior was significantly different in middle school students with different perceived pubertal timing (F =14.676,P < 0.05).The score of aggressive behavior was significantly different in middle school students with different general mood of school,relationship between classmates and teachers and the number of close friends (P < 0.05).Multiple linear regression analysis indicated that the influencing factors of male students' aggressive behavior were general mood of school,perceived pubertal timing and the relationship with teachers (β =-0.134,-0.114,-0.098,respectively,P < 0.05).The influencing factors of female students' aggressive behavior were the relationship with teachers,the number of

  3. Time-Predictable Virtual Memory

    DEFF Research Database (Denmark)

    Puffitsch, Wolfgang; Schoeberl, Martin

    2016-01-01

    Virtual memory is an important feature of modern computer architectures. For hard real-time systems, memory protection is a particularly interesting feature of virtual memory. However, current memory management units are not designed for time-predictability and therefore cannot be used...... in such systems. This paper investigates the requirements on virtual memory from the perspective of hard real-time systems and presents the design of a time-predictable memory management unit. Our evaluation shows that the proposed design can be implemented efficiently. The design allows address translation...... and address range checking in constant time of two clock cycles on a cache miss. This constant time is in strong contrast to the possible cost of a miss in a translation look-aside buffer in traditional virtual memory organizations. Compared to a platform without a memory management unit, these two additional...

  4. 青春发动时相提前与女生攻击行为的关联性分析%The correlation of the early pubertal timing and aggressive behavior of girls

    Institute of Scientific and Technical Information of China (English)

    俞荷俊; 周英; 顾璇; 朋文佳; 姚荣英

    2014-01-01

    目的:了解女中学生青春发动时相、攻击行为、外显自尊和亲子依恋的状况,探索青春发动时相与攻击行为之间的关联机制,揭示外显自尊和亲子依恋在青春发动时相提前与攻击行为中的中介作用。方法:采用问卷法,对1130名女中学生进行青春发育状况、攻击行为、外显自尊、亲子依恋的调查。结果:初中女生外显自尊和父子依恋的得分均高于高中女生(P<0.01),高中女生青春发育得分高于初中女生(P<0.05)。女中学生青春发动时相与攻击行为呈显著正相关关系(P<0.01),与母子依恋、外显自尊均呈负相关关系(P<0.05和P<0.01);外显自尊和母子依恋在青春发动时相提前对攻击行为的影响中起部分中介作用,中介作用大小分别为33.87%和25.98%。标准化回归系数7条显著路径,青春发动时相提前、外显自尊和母子依恋均对攻击行为有直接作用,同时青春发动时相提前通过外显自尊和母子依恋对攻击行为产生间接作用。结论:在攻击行为的预防上,引导青春发动时相提前的女中学生,正确把握自尊弹性,改善亲子依恋关系,可缓解和降低青春发动时相提前的女中学生的攻击行为水平。%Objective:To investigate of the early pubertal development,aggressive behavior,self-esteem and parent-child attachment of middle school girl,explore the mechanism of pubertal development and aggressive behavior,and reveal the intermediary role of selfesteem and parent-child attachment in the early pubertal timing and aggressive behavior of girls. Methods:The pubertal development, aggressive behavior,self-esteem and parent-child attachment of 1130 middle school girls were investigated by questionnaire. Results: The scores of self-esteem and parent-child attachment in middle school girls were higher than those in high school girls(P <0. 01),the score of pubertal development in high school girls was

  5. Age at pubertal onset and educational outcomes

    DEFF Research Database (Denmark)

    Essen, Emma von; Dreber, Anna; Ranehill, Eva

    2011-01-01

    Education has important short and long run implications for individual outcomes. In this paper we explore the association between age at pubertal onset and educational outcomes in a sample of Swedish girls. Previous research suggests that girls that mature earlier perform worse in school compared...... to girls that mature later. To test if this is also true among Swedish girls, we investigate the association between pubertal development and grades, educational aspirations and educational choice. We also investigate whether changes in risk attitudes, time preferences and priorities concerning school...... versus friends mediate this potential correlation. We confirm that earlier maturing girls have lower grades and lower educational aspirations, but find that they make educational choices similar to those of later maturing girls. Furthermore, we do not find that these differences in grades and aspirations...

  6. Update on statural growth and pubertal development in obese children

    Directory of Open Access Journals (Sweden)

    Chiara De Leonibus

    2012-12-01

    Full Text Available Childhood obesity is a growing and alarming problem, associated with several short-term and long-term metabolic and cardiovascular complications. In addition, it has also been suggested that excess adiposity during childhood influences growth and pubertal development. Several studies have shown that during pre-pubertal years, obese patients present higher growth velocity and that this pre-pubertal advantage tends to gradually decrease during puberty, leading to similar final heights between obese and non-obese children. Excess body weight might also influence pubertal onset, leading to earlier timing of puberty in girls. In addition, obese girls are at increased risk of hyperandrogenism and polycystic ovary syndrome. In boys, a clear evidence does not exist: some studies suggesting an earlier puberty associated with the obesity status, whereas other have found a delayed pubertal onset. Overall, the existing evidence of an association between obesity and modification of growth and pubertal patterns underlines a further reason for fighting the epidemics of childhood obesity.

  7. Time-Predictable Computer Architecture

    Directory of Open Access Journals (Sweden)

    Schoeberl Martin

    2009-01-01

    Full Text Available Today's general-purpose processors are optimized for maximum throughput. Real-time systems need a processor with both a reasonable and a known worst-case execution time (WCET. Features such as pipelines with instruction dependencies, caches, branch prediction, and out-of-order execution complicate WCET analysis and lead to very conservative estimates. In this paper, we evaluate the issues of current architectures with respect to WCET analysis. Then, we propose solutions for a time-predictable computer architecture. The proposed architecture is evaluated with implementation of some features in a Java processor. The resulting processor is a good target for WCET analysis and still performs well in the average case.

  8. Time estimation predicts mathematical intelligence.

    Directory of Open Access Journals (Sweden)

    Peter Kramer

    Full Text Available BACKGROUND: Performing mental subtractions affects time (duration estimates, and making time estimates disrupts mental subtractions. This interaction has been attributed to the concurrent involvement of time estimation and arithmetic with general intelligence and working memory. Given the extant evidence of a relationship between time and number, here we test the stronger hypothesis that time estimation correlates specifically with mathematical intelligence, and not with general intelligence or working-memory capacity. METHODOLOGY/PRINCIPAL FINDINGS: Participants performed a (prospective time estimation experiment, completed several subtests of the WAIS intelligence test, and self-rated their mathematical skill. For five different durations, we found that time estimation correlated with both arithmetic ability and self-rated mathematical skill. Controlling for non-mathematical intelligence (including working memory capacity did not change the results. Conversely, correlations between time estimation and non-mathematical intelligence either were nonsignificant, or disappeared after controlling for mathematical intelligence. CONCLUSIONS/SIGNIFICANCE: We conclude that time estimation specifically predicts mathematical intelligence. On the basis of the relevant literature, we furthermore conclude that the relationship between time estimation and mathematical intelligence is likely due to a common reliance on spatial ability.

  9. Does neighborhood environment influence girls' pubertal onset? findings from a cohort study

    Directory of Open Access Journals (Sweden)

    Deardorff Julianna

    2012-03-01

    Full Text Available Abstract Background Pubertal onset occurs earlier than in the past among U.S. girls. Early onset is associated with numerous deleterious outcomes across the life course, including overweight, breast cancer and cardiovascular health. Increases in childhood overweight have been implicated as a key reason for this secular trend. Scarce research, however, has examined how neighborhood environment may influence overweight and, in turn, pubertal timing. The current study prospectively examined associations between neighborhood environment and timing of pubertal onset in a multi-ethnic cohort of girls. Body mass index (BMI was examined as a mediator of these associations. Methods Participants were 213 girls, 6-8 years old at baseline, in an on-going longitudinal study. The current report is based on 5 time points (baseline and 4 annual follow-up visits. Neighborhood environment, assessed at baseline, used direct observation. Tanner stage and anthropometry were assessed annually in clinic. Survival analysis was utilized to investigate the influence of neighborhood factors on breast and pubic hair onset, with BMI as a mediator. We also examined the modifying role of girls' ethnicity. Results When adjusting for income, one neighborhood factor (Recreation predicted delayed onset of breast and pubic hair development, but only for African American girls. BMI did not mediate the association between Recreation and pubertal onset; however, these associations persisted when BMI was included in the models. Conclusions For African American girls, but not girls from other ethnic groups, neighborhood availability of recreational outlets was associated with onset of breast and pubic hair. Given the documented risk for early puberty among African American girls, these findings have important potential implications for public health interventions related to timing of puberty and related health outcomes in adolescence and adulthood.

  10. Pubertal assessment: targeted educational intervention for pediatric trainees.

    Science.gov (United States)

    Khokhar, Aditi; Nagarajan, Sairaman; Ravichandran, Yagnaram; Perez-Colon, Sheila

    2017-08-18

    Background Timely and periodic pubertal assessment in children is vital to identify puberty related disorders. Pediatricians need to have working knowledge of puberty time and tempo. Pediatric residency is an important platform to acquire physical examination skills including pubertal assessment. Objective An educational intervention for teaching pubertal assessment was piloted on pediatric residents at our institution. Methods The intervention comprised of interactive lecture series, ID badge size Tanner stage cards and Tanner posters placed in residents' continuity clinics. Pre-intervention, post-intervention and 3 months post-intervention surveys for participating trainees were administered to determine the effectiveness of the intervention. Attitudes, practices, knowledge scores, and barriers to Tanner staging conduct were analyzed. Results Forty-three residents participated in the intervention. Knowledge scores of PGY1 (5.95 ± 1.6 vs. 7.47 ± 1.4, p < 0.01) improved right after the intervention, as did self-reported clinical practices of all trainees 3 months post- intervention with regards to conducting external genital examination and performing pubertal assessment. Confidence levels of pediatric trainees in conducting pubertal assessment and comfort levels in assessing the need for endocrine referral based on abnormal Tanner staging improved after the intervention, although the effect was not statistically significant. Conclusion Our intervention is a worthwhile technique for teaching pubertal assessment to residents as it is simple to conduct, easily reproducible, provides baseline knowledge needed for recognition of normal pubertal development and puberty related conditions, and instills confidence in residents.

  11. BMI percentile-for-age overestimates adiposity in early compared with late maturing pubertal children

    DEFF Research Database (Denmark)

    Sørensen, Kaspar; Juul, Anders

    2015-01-01

    .041) was found with early compared with late maturation, despite similar BIA-estimated body fat percentage (BIA-BF%). Neither BMI nor BIA-BF% differed for a given stage of maturation. BMI percentile-for-age and prevalence of overweight/obesity were higher in the early compared with late matured pubertal children......OBJECTIVE: Early pubertal timing is consistently associated with increased BMI percentile-for-age in pubertal girls, while data in boys are more ambiguous. However, higher BMI percentile-for-age may be a result of the earlier puberty per se rather than vice versa. The aim was to evaluate markers...... of adiposity in relation to pubertal timing and reproductive hormone levels in healthy pubertal boys and girls. STUDY DESIGN: Population-based cross-sectional study (The Copenhagen Puberty Study). Eight-hundred and two healthy Caucasian children and adolescents (486 girls) aged 8.5-16.5 years participated. BMI...

  12. Transitions in Body and Behavior : A Meta-Analytic Study on the Relationship Between Pubertal Development and Adolescent Sexual Behavior

    OpenAIRE

    Baams, Laura; Dubas, Judith Semon; Overbeek, Geertjan; Aken, Marcel A. G.

    2015-01-01

    The present meta-analysis studies the relations of pubertal timing and status with sexual behavior and sexual risk behavior among youth aged 10.5-22.4 years. We included biological sex, age, and ethnicity as potential moderators. Four databases were searched for studies (published between 1980 and 2012) on the relation between pubertal timing or status and sexual behavior. The outcomes were (1) sexual intercourse; (2) combined sexual behavior; and (3) risky sexual behavior. Earlier pubertal t...

  13. Dioxin Exposure and Age of Pubertal Onset among Russian Boys

    Science.gov (United States)

    Lee, Mary M.; Williams, Paige L.; Sergeyev, Oleg; Burns, Jane S.; Patterson, Donald G.; Turner, Wayman E.; Needham, Larry L.; Altshul, Larisa; Revich, Boris; Hauser, Russ

    2011-01-01

    Background: Animal data demonstrate associations of dioxin, furan, and polychlorinated biphenyl (PCB) exposures with altered male gonadal maturation. It is unclear whether these associations apply to human populations. Objectives: We investigated the association of dioxins, furans, PCBs, and corresponding toxic equivalent (TEQ) concentrations with pubertal onset among boys in a dioxin-contaminated region. Methods: Between 2003 and 2005, 499 boys 8–9 years of age were enrolled in a longitudinal study in Chapaevsk, Russia. Pubertal onset [stage 2 or higher for genitalia (G2+) or testicular volume (TV) > 3 mL] was assessed annually between ages 8 and 12 years. Serum levels at enrollment were analyzed by the Centers for Disease Control and Prevention, Atlanta, Georgia, USA. We used Cox proportional hazards models to assess age at pubertal onset as a function of exposure adjusted for potential confounders. We conducted sensitivity analyses excluding boys with pubertal onset at enrollment. Results: The median (range) total serum TEQ concentration was 21 (4–175) pg/g lipid, approximately three times higher than values in European children. At enrollment, boys were generally healthy and normal weight (mean body mass index, 15.9 kg/m2), with 30% having entered puberty by G2+ and 14% by TV criteria. Higher dioxin TEQs were associated with later pubertal onset by TV (hazard ratio = 0.68, 95% confidence interval, 0.49–0.95 for the highest compared with the lowest quartile). Similar associations were observed for 2,3,7,8-tetrachlorodibenzo-p-dioxin and dioxin concentrations for TV but not G2+. Results were robust to sensitivity analyses. Conclusions: Findings support an association of higher peripubertal serum dioxin TEQs and concentrations with later male pubertal onset reflected in delayed testicular maturation. PMID:21527364

  14. Acceleration of pubertal development following pituitary radiotherapy for Cushing's disease

    Energy Technology Data Exchange (ETDEWEB)

    Nicholl, R.M.; Kirk, J.M.W.; Grossman, A.B.; Plowman, P.N.; Besser, G.M.; Savage, M.O. (Saint Bartholomew' s Hospital, London (United Kingdom))

    1993-01-01

    A 7-year-old boy with pituitary dependent Cushing's disease was treated with pituitary irradiation following unsuccessful microadenomectomy. This led to normalization of the hypercortisolaemia, but was followed by GH deficiency. Two years after radiotherapy he had the onset of pubertal development with testicular enlargement to 8 ml bilaterally. Pubertal regression was induced using the long-acting GnRH analogue goserelin. Acceleration of skeletal maturation was also arrested, resulting in improvement of final height prediction. Irradiation directly to the hypothalamo-pituitary region, as well as whole brain irradiation, may thus be associated with accelerated pubertal development. (author).

  15. Guias clínicos e radiográficos utilizados para a predição do surto de crescimento puberal Clinical and radiographic guidelines to predict pubertal growth spurt

    Directory of Open Access Journals (Sweden)

    Monica Tirre de Souza Araujo

    2011-10-01

    Full Text Available OBJETIVO: o objetivo desse artigo é chamar a atenção para a organização das informações disponíveis nos exames e durante o tratamento ortodôntico de indivíduos em crescimento, as quais servem como guias para a predição do estágio do surto de crescimento puberal. CONCLUSÃO: tais informações fornecem oportunidades de acréscimos no diagnóstico e prognóstico dos casos e na tomada de decisões do planejamento, evolução do tratamento e da fase de contenção, principalmente daqueles pacientes que apresentam más oclusões associadas a desarmonias esqueléticas.OBJECTIVE: The aim of this paper is to draw attention to the organization of information available on exams and during orthodontic treatment in growing patients, which serve as guides for predicting the stage of pubertal growth spurt. CONCLUSION: these data provide opportunities for increments in diagnosis and prognosis of cases and decisions in the planning, evolution of treatment and contention phase, especially those patients with malocclusion associated with skeletal disharmonies.

  16. The physiology and timing of male puberty

    DEFF Research Database (Denmark)

    Tinggaard, Jeanette; Mieritz, Mikkel Grunnet; Sørensen, Kaspar

    2012-01-01

    To describe available markers of male puberty, discuss associations between adiposity and pubertal timing and to review recent evidence of a possible secular trend in male pubertal timing.......To describe available markers of male puberty, discuss associations between adiposity and pubertal timing and to review recent evidence of a possible secular trend in male pubertal timing....

  17. Improving the prediction of chaotic time series

    Institute of Scientific and Technical Information of China (English)

    李克平; 高自友; 陈天仑

    2003-01-01

    One of the features of deterministic chaos is sensitive to initial conditions. This feature limits the prediction horizons of many chaotic systems. In this paper, we propose a new prediction technique for chaotic time series. In our method, some neighbouring points of the predicted point, for which the corresponding local Lyapunov exponent is particularly large, would be discarded during estimating the local dynamics, and thus the error accumulated by the prediction algorithm is reduced. The model is tested for the convection amplitude of Lorenz systems. The simulation results indicate that the prediction technique can improve the prediction of chaotic time series.

  18. Urinary phthalate excretion in 555 healthy Danish boys with and without pubertal gynaecomastia

    DEFF Research Database (Denmark)

    Mieritz, Mikkel G; Frederiksen, Hanne; Sørensen, Kaspar;

    2012-01-01

    Pubertal gynaecomastia is a clinical sign of an oestrogen-androgen imbalance, which occurs in 40-60% of adolescent Caucasian boys. In most cases no underlying endocrinopathy can be identified. A recent study reports higher plasma phthalate levels in Turkish boys with pubertal gynaecomastia....... Therefore, we asked whether there was an association between concurrent measures of urinary phthalate metabolites and pubertal timing as well as the presence of gynaecomastia in otherwise healthy boys. We studied a total of 555 healthy boys (age 6.07-19.83 years) as part of the COPENHAGEN Puberty Study...

  19. Trend prediction of chaotic time series

    Institute of Scientific and Technical Information of China (English)

    Li Aiguo; Zhao Cai; Li Zhanhuai

    2007-01-01

    To predict the trend of chaotic time series in time series analysis and time series data mining fields, a novel predicting algorithm of chaotic time series trend is presented, and an on-line segmenting algorithm is proposed to convert a time series into a binary string according to ascending or descending trend of each subsequence. The on-line segmenting algorithm is independent of the prior knowledge about time series. The naive Bayesian algorithm is then employed to predict the trend of chaotic time series according to the binary string. The experimental results of three chaotic time series demonstrate that the proposed method predicts the ascending or descending trend of chaotic time series with few error.

  20. Transitions in body and behavior: a meta-analytic study on the relationship between pubertal development and adolescent sexual behavior.

    Science.gov (United States)

    Baams, Laura; Dubas, Judith Semon; Overbeek, Geertjan; van Aken, Marcel A G

    2015-06-01

    The present meta-analysis studies the relations of pubertal timing and status with sexual behavior and sexual risk behavior among youth aged 10.5-22.4 years. We included biological sex, age, and ethnicity as potential moderators. Four databases were searched for studies (published between 1980 and 2012) on the relation between pubertal timing or status and sexual behavior. The outcomes were (1) sexual intercourse; (2) combined sexual behavior; and (3) risky sexual behavior. Earlier pubertal timing or more advanced pubertal status was related to earlier and more sexual behavior, and earlier pubertal timing was related to more risky sexual behavior. Further, the links between (1) pubertal status and combined sexual behavior and (2) pubertal timing and sexual intercourse status, combined sexual behavior, and risky sexual behavior were stronger for girls than boys. Most links between pubertal status, timing, and sexual behavior and sexual risk behavior were stronger for younger adolescents. Moderation by ethnicity did not yield consistent results. There was significant variation in results among studies that was not fully explained by differences in biological sex, age, and ethnicity. Future research is needed to identify moderators that explain the variation in effects and to design sexual health interventions for young adolescents. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

  1. Interactions of timing and prediction error learning.

    Science.gov (United States)

    Kirkpatrick, Kimberly

    2014-01-01

    Timing and prediction error learning have historically been treated as independent processes, but growing evidence has indicated that they are not orthogonal. Timing emerges at the earliest time point when conditioned responses are observed, and temporal variables modulate prediction error learning in both simple conditioning and cue competition paradigms. In addition, prediction errors, through changes in reward magnitude or value alter timing of behavior. Thus, there appears to be a bi-directional interaction between timing and prediction error learning. Modern theories have attempted to integrate the two processes with mixed success. A neurocomputational approach to theory development is espoused, which draws on neurobiological evidence to guide and constrain computational model development. Heuristics for future model development are presented with the goal of sparking new approaches to theory development in the timing and prediction error fields.

  2. Pubertal development in healthy children is mirrored by DNA methylation patterns in peripheral blood

    DEFF Research Database (Denmark)

    Almstrup, Kristian; Johansen, Marie Lindhardt; Busch, Alexander S.

    2016-01-01

    Puberty marks numerous physiological processes which are initiated by central activation of the hypothalamic–pituitary–gonadal axis, followed by development of secondary sexual characteristics. To a large extent, pubertal timing is heritable, but current knowledge of genetic polymorphismsonly...... explains few months in the large inter-individual variation in the timing of puberty. We have analysed longitudinal genome-wide changes in DNA methylation in peripheral blood samples (n = 102) obtained from 51 healthy children before and after pubertal onset. We show that changes in single methylation...... sites are tightly associated with physiological pubertal transition and altered reproductive hormone levels. These methylation sites cluster in and around genes enriched for biological functions related to pubertal development. Importantly, we identified that methylation of the genomic region containing...

  3. Combination prediction method of chaotic time series

    Institute of Scientific and Technical Information of China (English)

    ZHAO DongHua; RUAN Jiong; CAI ZhiJie

    2007-01-01

    In the present paper, we propose an approach of combination prediction of chaotic time series. The method is based on the adding-weight one-rank local-region method of chaotic time series. The method allows us to define an interval containing a future value with a given probability, which is obtained by studying the prediction error distribution. Its effectiveness is shown with data generated by Logistic map.

  4. Can We Predict Patient Wait Time?

    Science.gov (United States)

    Pianykh, Oleg S; Rosenthal, Daniel I

    2015-10-01

    The importance of patient wait-time management and predictability can hardly be overestimated: For most hospitals, it is the patient queues that drive and define every bit of clinical workflow. The objective of this work was to study the predictability of patient wait time and identify its most influential predictors. To solve this problem, we developed a comprehensive list of 25 wait-related parameters, suggested in earlier work and observed in our own experiments. All parameters were chosen as derivable from a typical Hospital Information System dataset. The parameters were fed into several time-predicting models, and the best parameter subsets, discovered through exhaustive model search, were applied to a large sample of actual patient wait data. We were able to discover the most efficient wait-time prediction factors and models, such as the line-size models introduced in this work. Moreover, these models proved to be equally accurate and computationally efficient. Finally, the selected models were implemented in our patient waiting areas, displaying predicted wait times on the monitors located at the front desks. The limitations of these models are also discussed. Optimal regression models based on wait-line sizes can provide accurate and efficient predictions for patient wait time. Copyright © 2015 American College of Radiology. Published by Elsevier Inc. All rights reserved.

  5. Vigorous physical activity rather than sedentary behaviour predicts overweight and obesity in pubertal boys: a 2-year follow-up study.

    Science.gov (United States)

    Lätt, Evelin; Mäestu, Jarek; Ortega, Francisco B; Rääsk, Triin; Jürimäe, Toivo; Jürimäe, Jaak

    2015-05-01

    Current physical activity (PA) recommendations indicate that children should get involved in 60 minutes of moderate-to-vigorous PA (MVPA), and should include vigorous-intensity PA at least three days a week. However, it is not known how many minutes of vigorous PA they should do. Using objective methods and a longitudinal design, this study aimed to examine how different PA intensities and sedentary behaviour relate with the risk of being overweight and obese during puberty over a two-year period. A sample of 136 10-12-year-old (at baseline) boys participated. PA was measured by seven-day accelerometry. From MVPA thresholds, only 90 minutes per day of MVPA had important odds ratios (OR) for being overweight at baseline (OR=8.14, 95% confidence interval [CI] 1.03-64.04). A significant cut-off point for being overweight was indicated by 59 minutes per day of MVPA with at least 14 minutes per day of vigorous PA, and 55 minutes per day MVPA with at least 10 minutes per day of vigorous PA for those who were obese. Sedentary behaviour did not have any significant ORs for being overweight or obese. Subjects who did not meet the thresholds of 5 and 20 minutes per day of vigorous PA at baseline had an increased risk of being overweight (OR=4.05, 95% CI 1.41-11.59, and OR=4.14, 95% CI 1.35-12.73, respectively) and obese (OR=6.54, 95% CI 1.97-21.69, and OR=8.75, 95% CI 1.12-68.51, respectively) two years later. The results indicate that vigorous PA in particular predicts overweight and obesity in boys. They should aim to do at least 60 minutes per day of MVPA. These results contribute to the recommendations suggesting that a minimum of 15 minutes per day of vigorous PA is desired to reduce the risk of developing overweight/obesity in later puberty. © 2015 the Nordic Societies of Public Health.

  6. Modeling and prediction of surgical procedure times

    NARCIS (Netherlands)

    P.S. Stepaniak (Pieter); C. Heij (Christiaan); G. de Vries (Guus)

    2009-01-01

    textabstractAccurate prediction of medical operation times is of crucial importance for cost efficient operation room planning in hospitals. This paper investigates the possible dependence of procedure times on surgeon factors like age, experience, gender, and team composition. The effect of these f

  7. Improving predictions by cross pollination in time

    Science.gov (United States)

    Schevenhoven, Francine; Selten, Frank

    2016-04-01

    Given a set of imperfect weather models, one could ask how these models can be combined in order to improve weather predictions produced with these models. In this study we explore a technique called cross-pollination in time (CPT, Smith 2001). In the CPT approach the models exchange states during the prediction. The number of possible predictions grows quickly with time and a strategy to retain only a small number of predictions, called pruning, needs to be developed. In the learning phase a pruning strategy is proposed based on retaining those solutions that remain closest to the truth. From the learning phase probabilities are derived that determine weights to be applied to the imperfect models in the forecast phase. The CPT technique is explored using low-order dynamical systems and applied to a global atmospheric model. First results indicate that the CPT approach improves the forecast quality over the individual models.

  8. Candidate gene expression in Bos indicus ovarian tissues: pre-pubertal and post-pubertal heifers in diestrus

    Directory of Open Access Journals (Sweden)

    Mayara Morena Del Cambre Amaral Weller

    2016-10-01

    Full Text Available Growth factors such as bone morphogenetic proteins 6, 7, 15 and two isoforms of transforming growth factor-beta (BMP6, BMP7, BMP15, TGFB1 and TGFB2 and insulin-like growth factor system act as local regulators of ovarian follicular development. To elucidate if these factors as well as others candidate genes such as estrogen receptor 1 (ESR1, growth differentiation factor 9 (GDF9, follicle stimulating hormone receptor (FSHR, luteinizing hormone receptor (LHR, bone morphogenetic protein receptor, type 2 (BMPR2, type 1 insulin-like growth factor receptor (IGFR1, and key steroidogenic enzymes cytochrome P450 aromatase and 3-β-hydroxysteroid dehydrogenase (CYP19A1 and HSD3B1 could modulate or influence diestrus on the onset of puberty in Brahman heifers, their ovarian mRNA expression was measured before and after puberty (luteal phase. Six post-pubertal (POST heifers were euthanized on the luteal phase of their second cycle, confirmed by corpus luteum observation, and six pre-pubertal (PRE heifers were euthanized in the same day. Quantitative real-time PCR analysis showed that the expression of FSHR, BMP7, CYP19A1, IGF1 and IGFR1 mRNA was greater in PRE heifers, when contrasted to POST heifers. The expression of LHR and HSD3B1 was lower in PRE heifers. Differential expression of ovarian genes could be associated with changes in follicular dynamics and different cell populations that have emerged as consequence of puberty and the luteal phase. The emerging hypothesis is that BMP7 and IGF1 are co-expressed and may modulate the expression of FSHR, LHR and IGFR1 and CYP19A1. BMP7 could influence the down-regulation of LHR and up-regulation of FSHR and CYP19A1, which mediates the follicular dynamics in heifer ovaries. Up-regulation of IGF1 expression pre-puberty, compared to post-puberty diestrus, correlates with increased levels FSHR and CYP19A1. Thus, BMP7 and IGF1 may play synergic roles and were predicted to interact, from the expression data (P = 0

  9. Breastfeeding versus formula-feeding and girls' pubertal development.

    Science.gov (United States)

    Kale, Aarti; Deardorff, Julianna; Lahiff, Maureen; Laurent, Cecile; Greenspan, Louise C; Hiatt, Robert A; Windham, Gayle; Galvez, Maida P; Biro, Frank M; Pinney, Susan M; Teitelbaum, Susan L; Wolff, Mary S; Barlow, Janice; Mirabedi, Anousheh; Lasater, Molly; Kushi, Lawrence H

    2015-03-01

    To examine the association of breastfeeding or its duration with timing of girls' pubertal onset, and the role of BMI as a mediator in these associations. A population of 1,237 socio-economically and ethnically diverse girls, ages 6-8 years, was recruited across three geographic locations (New York City, Cincinnati, and the San Francisco Bay Area) in a prospective study of predictors of pubertal maturation. Breastfeeding practices were assessed using self-administered questionnaire/interview with the primary caregiver. Girls were seen on at least annual basis to assess breast and pubic hair development. The association of breastfeeding with pubertal timing was estimated using parametric survival analysis while adjusting for body mass index, ethnicity, birth-weight, mother's education, mother's menarcheal age, and family income. Compared to formula fed girls, those who were mixed-fed or predominantly breastfed showed later onset of breast development [hazard ratios 0.90 (95 % CI 0.75, 1.09) and 0.74 (95 % CI 0.59, 0.94), respectively]. Duration of breastfeeding was also directly associated with age at onset of breast development (p trend = 0.008). Associations between breastfeeding and pubic hair onset were not significant. In stratified analysis, the association of breastfeeding and later breast onset was seen in Cincinnati girls only. The association between breast feeding and pubertal onset varied by study site. More research is needed about the environments within which breastfeeding takes place in order to better understand whether infant feeding practices are a potentially modifiable risk factor that may influence age at onset of breast development and subsequent risk for disease in adulthood.

  10. Breastfeeding versus Formula-Feeding & Girls’ Pubertal Development

    Science.gov (United States)

    Kale, Aarti; Deardorff, Julianna; Lahiff, Maureen; Laurent, Cecile; Greenspan, Louise C.; Hiatt, Robert A.; Windham, Gayle; Galvez, Maida P.; Biro, Frank M.; Pinney, Susan M.; Teitelbaum, Susan L.; Wolff, Mary S.; Barlow, Janice; Mirabedi, Anousheh; Lasater, Molly; Kushi, Lawrence H.

    2014-01-01

    Objective To examine the association of breastfeeding or its duration with timing of girls’ pubertal onset, and the role of BMI as a mediator in these associations. Methods A population of 1,237 socio-economically and ethnically diverse girls, ages 6–8 years, was recruited across three geographic locations (New York City, Cincinnati, and the San Francisco Bay Area) in a prospective study of predictors of pubertal maturation. Breastfeeding practices were assessed using self-administered questionnaire/interview with the primary caregiver. Girls were seen on at least annual basis to assess breast and pubic hair development. The association of breastfeeding with pubertal timing was estimated using parametric survival analysis while adjusting for body mass index, ethnicity, birth-weight, mother’s education, mother’s menarcheal age, and family income. Results Compared to formula fed girls, those who were mixed-fed or predominantly breastfed showed later onset of breast development (Hazard Ratios 0.90 [95% CI, 0.75–1.09] and 0.74 [95% CI, 0.59–0.94], respectively). Duration of breastfeeding was also directly associated with age at onset of breast development (p trend = 0.008). Associations between breastfeeding and pubic hair onset were not significant. In stratified analysis, the association of breastfeeding and later breast onset was seen in Cincinnati girls only. Conclusion The association between breast feeding and pubertal onset varied by study site. More research is needed about the environments within which breastfeeding takes place in order to better understand whether infant feeding practices are a potentially modifiable risk factor that may influence age at onset of breast development and subsequent risk for disease in adulthood. PMID:24916206

  11. DNA Methylation Patterns in the Hypothalamus of Female Pubertal Goats.

    Science.gov (United States)

    Yang, Chen; Ye, Jing; Li, Xiumei; Gao, Xiaoxiao; Zhang, Kaifa; Luo, Lei; Ding, Jianping; Zhang, Yunhai; Li, Yunsheng; Cao, Hongguo; Ling, Yinghui; Zhang, Xiaorong; Liu, Ya; Fang, Fugui

    2016-01-01

    Female pubertal development is tightly controlled by complex mechanisms, including neuroendocrine and epigenetic regulatory pathways. Specific gene expression patterns can be influenced by DNA methylation changes in the hypothalamus, which can in turn regulate timing of puberty onset. In order to understand the relationship between DNA methylation changes and gene expression patterns in the hypothalamus of pubertal goats, whole-genome bisulfite sequencing and RNA-sequencing analyses were carried out. There was a decline in DNA methylation levels in the hypothalamus during puberty and 268 differentially methylated regions (DMR) in the genome, with differential patterns in different gene regions. There were 1049 genes identified with distinct expression patterns. High levels of DNA methylation were detected in promoters, introns and 3'-untranslated regions (UTRs). Levels of methylation decreased gradually from promoters to 5'-UTRs and increased from 5'-UTRs to introns. Methylation density analysis demonstrated that methylation level variation was consistent with the density in the promoter, exon, intron, 5'-UTRs and 3'-UTRs. Analyses of CpG island (CGI) sites showed that the enriched gene contents were gene bodies, intergenic regions and introns, and these CGI sites were hypermethylated. Our study demonstrated that DNA methylation changes may influence gene expression profiles in the hypothalamus of goats during the onset of puberty, which may provide new insights into the mechanisms involved in pubertal onset.

  12. Predictions of noncommutative space-time

    OpenAIRE

    Viet, Nguyen Ai

    1994-01-01

    An unified structure of noncommutative space-time for both gravity and particle physics is presented. This gives possibilities of testing the idea of noncommutative space-time at the currently available energy scale. There are several arguments indicating that noncommutative space-time is visible already at the electroweak scale. This noncommutative space-time predicts the top quark mass m_t \\sim 172 GeV, the Higgs mass M_H \\sim 241 GeV and the existence of a vector meson and a scalar, which ...

  13. HELCATS Prediction of Planetary CME arrival times

    Science.gov (United States)

    Boakes, Peter; Moestl, Christian; Davies, Jackie; Harrison, Richard; Byrne, Jason; Barnes, David; Isavnin, Alexey; Kilpua, Emilia; Rollett, Tanja

    2015-04-01

    We present the first results of CME arrival time prediction at different planetary locations and their comparison to the in situ data within the HELCATS project. The EU FP7 HELCATS (Heliospheric Cataloguing, Analysis & Techniques Service) is a European effort to consolidate the exploitation of the maturing field of heliospheric imaging. HELCATS aims to catalogue solar wind transients, observed by the NASA STEREO Heliospheric Imager (HI) instruments, and validate different methods for the determination of their kinematic properties. This validation includes comparison with arrivals at Earth, and elsewhere in the heliosphere, as well as onsets at the Sun (http://www.helcats-fp7.eu/). A preliminary catalogue of manually identified CMEs, with over 1000 separate events, has been created from observations made by the STEREO/HI instruments covering the years 2007-2013. Initial speeds and directions of each CME have been derived through fitting the time elongation profile to the state of the art Self-Similar Expansion Fitting (SSEF) geometric technique (Davies et al., 2012). The technique assumes that, in the plane corresponding to the position angle of interest, CMEs can be modelled as circles subtending a fixed angular width to Sun-center and propagating anti-sunward in a fixed direction at a constant speed (we use an angular width of 30 degrees in our initial results). The model has advantages over previous geometric models (e.g. harmonic mean or fixed phi) as it allows one to predict whether a CME will 'hit' a specific heliospheric location, as well as to what degree (e.g. direct assault or glancing blow). We use correction formulae (Möstl and Davies, 2013) to convert CME speeds, direction and launch time to speed and arrival time at any in situ location. From the preliminary CME dataset, we derive arrival times for over 400 Earth-directed CMEs, and for over 100 Mercury-, Venus-, Mars- and Saturn-directed CMEs predicted to impact each planet. We present statistics of

  14. Maths performance as a function of sex, laterality, and age of pubertal onset.

    Science.gov (United States)

    Sappington, John; Topolski, Richard

    2005-07-01

    Sex differences in math/spatial performance demand explanations. Within the biological view, the complexity and number of variables make the explanation difficult at best. Laterality and age of pubertal onset have been investigated prominently in this context but rarely considered as interactions in the same study. Some 468 college subjects with SAT MATH (SAT M) scores were divided into 12 groups defined by sex, laterality, and age (early, middle, and late) of pubertal onset. Significant main effects for sex and age of onset emerged, as did an interaction between lateral preference and pubertal onset. Generally males outperformed females. The combination of maleness, sinistrality, and early maturation was associated with high SAT M scores. Sinistrality and late maturation among females predicted very poor math performance.

  15. Predicting road accidents: Structural time series approach

    Science.gov (United States)

    Junus, Noor Wahida Md; Ismail, Mohd Tahir

    2014-07-01

    In this paper, the model for occurrence of road accidents in Malaysia between the years of 1970 to 2010 was developed and throughout this model the number of road accidents have been predicted by using the structural time series approach. The models are developed by using stepwise method and the residual of each step has been analyzed. The accuracy of the model is analyzed by using the mean absolute percentage error (MAPE) and the best model is chosen based on the smallest Akaike information criterion (AIC) value. A structural time series approach found that local linear trend model is the best model to represent the road accidents. This model allows level and slope component to be varied over time. In addition, this approach also provides useful information on improving the conventional time series method.

  16. Recent secular trends in pubertal timing

    DEFF Research Database (Denmark)

    Sørensen, Kaspar; Mouritsen, Annette; Aksglaede, Lise

    2012-01-01

    The decline in age at puberty in the general population has been paralleled by an increase in the number of girls referred for evaluation of precocious puberty (PP). In 1999, The Lawson Wilkins Pediatric Endocrine Society recommended a lowering of the age limit for evaluation of PP in girls. Howe...

  17. Globally disruptive events show predictable timing patterns

    Science.gov (United States)

    Gillman, Michael P.; Erenler, Hilary E.

    2017-01-01

    Globally disruptive events include asteroid/comet impacts, large igneous provinces and glaciations, all of which have been considered as contributors to mass extinctions. Understanding the overall relationship between the timings of the largest extinctions and their potential proximal causes remains one of science's great unsolved mysteries. Cycles of about 60 Myr in both fossil diversity and environmental data suggest external drivers such as the passage of the Solar System through the galactic plane. While cyclic phenomena are recognized statistically, a lack of coherent mechanisms and a failure to link key events has hampered wider acceptance of multi-million year periodicity and its relevance to earth science and evolution. The generation of a robust predictive model of timings, with a clear plausible primary mechanism, would signal a paradigm shift. Here, we present a model of the timings of globally disruptive events and a possible explanation of their ultimate cause. The proposed model is a symmetrical pattern of 63 Myr sequences around a central value, interpreted as the occurrence of events along, and parallel to, the galactic midplane. The symmetry is consistent with multiple dark matter disks, aligned parallel to the midplane. One implication of the precise pattern of timings and the underlying physical model is the ability to predict future events, such as a major extinction in 1-2 Myr.

  18. A Time-predictable Stack Cache

    DEFF Research Database (Denmark)

    Abbaspour, Sahar; Brandner, Florian; Schoeberl, Martin

    2013-01-01

    Real-time systems need time-predictable architectures to support static worst-case execution time (WCET) analysis. One architectural feature, the data cache, is hard to analyze when different data areas (e.g., heap allocated and stack allocated data) share the same cache. This sharing leads to less...... precise results of the cache analysis part of the WCET analysis. Splitting the data cache for different data areas enables composable data cache analysis. The WCET analysis tool can analyze the accesses to these different data areas independently. In this paper we present the design and implementation...... of a cache for stack allocated data. Our port of the LLVM C++ compiler supports the management of the stack cache. The combination of stack cache instructions and the hardware implementation of the stack cache is a further step towards timepredictable architectures....

  19. Message Passing on a Time-predictable Multicore Processor

    DEFF Research Database (Denmark)

    Sørensen, Rasmus Bo; Puffitsch, Wolfgang; Schoeberl, Martin

    2015-01-01

    Real-time systems need time-predictable computing platforms. For a multicore processor to be time-predictable, communication between processor cores needs to be time-predictable as well. This paper presents a time-predictable message-passing library for such a platform. We show how to build up...

  20. Time-dependence in mixture toxicity prediction.

    Science.gov (United States)

    Dawson, Douglas A; Allen, Erin M G; Allen, Joshua L; Baumann, Hannah J; Bensinger, Heather M; Genco, Nicole; Guinn, Daphne; Hull, Michael W; Il'Giovine, Zachary J; Kaminski, Chelsea M; Peyton, Jennifer R; Schultz, T Wayne; Pöch, Gerald

    2014-12-04

    The value of time-dependent toxicity (TDT) data in predicting mixture toxicity was examined. Single chemical (A and B) and mixture (A+B) toxicity tests using Microtox(®) were conducted with inhibition of bioluminescence (Vibrio fischeri) being quantified after 15, 30 and 45-min of exposure. Single chemical and mixture tests for 25 sham (A1:A2) and 125 true (A:B) combinations had a minimum of seven duplicated concentrations with a duplicated control treatment for each test. Concentration/response (x/y) data were fitted to sigmoid curves using the five-parameter logistic minus one parameter (5PL-1P) function, from which slope, EC25, EC50, EC75, asymmetry, maximum effect, and r(2) values were obtained for each chemical and mixture at each exposure duration. Toxicity data were used to calculate percentage-based TDT values for each individual chemical and mixture of each combination. Predicted TDT values for each mixture were calculated by averaging the TDT values of the individual components and regressed against the observed TDT values obtained in testing, resulting in strong correlations for both sham (r(2)=0.989, n=25) and true mixtures (r(2)=0.944, n=125). Additionally, regression analyses confirmed that observed mixture TDT values calculated for the 50% effect level were somewhat better correlated with predicted mixture TDT values than at the 25 and 75% effect levels. Single chemical and mixture TDT values were classified into five levels in order to discern trends. The results suggested that the ability to predict mixture TDT by averaging the TDT of the single agents was modestly reduced when one agent of the combination had a positive TDT value and the other had a minimal or negative TDT value. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  1. Real Time Seismic Prediction while Drilling

    Science.gov (United States)

    Schilling, F. R.; Bohlen, T.; Edelmann, T.; Kassel, A.; Heim, A.; Gehring, M.; Lüth, S.; Giese, R.; Jaksch, K.; Rechlin, A.; Kopf, M.; Stahlmann, J.; Gattermann, J.; Bruns, B.

    2009-12-01

    Efficient and safe drilling is a prerequisite to enhance the mobility of people and goods, to improve the traffic as well as utility infrastructure of growing megacities, and to ensure the growing energy demand while building geothermal and in hydroelectric power plants. Construction within the underground is often building within the unknown. An enhanced risk potential for people and the underground building may arise if drilling enters fracture zones, karsts, brittle rocks, mixed solid and soft rocks, caves, or anthropogenic obstacles. Knowing about the material behavior ahead of the drilling allows reducing the risk during drilling and construction operation. In drilling operations direct observations from boreholes can be complemented with geophysical investigations. In this presentation we focus on “real time” seismic prediction while drilling which is seen as a prerequisite while using geophysical methods in modern drilling operations. In solid rocks P- and S-wave velocity, refraction and reflection as well as seismic wave attenuation can be used for the interpretation of structures ahead of the drilling. An Integrated Seismic Imaging System (ISIS) for exploration ahead of a construction is used, where a pneumatic hammer or a magnetostrictive vibration source generate repetitive signals behind the tunneling machine. Tube waves are generated which travel along the tunnel to the working face. There the tube waves are converted to mainly S- but also P-Waves which interact with the formation ahead of the heading face. The reflected or refracted waves travel back to the working front are converted back to tube waves and recorded using three-component geophones which are fit into the tips of anchor rods. In near real time, the ISIS software allows for an integrated 3D imaging and interpretation of the observed data, geological and geotechnical parameters. Fracture zones, heterogeneities, and variations in the rock properties can be revealed during the drilling

  2. Advances in pubertal growth and factors influencing it: Can we increase pubertal growth?

    Directory of Open Access Journals (Sweden)

    Ashraf Soliman

    2014-01-01

    Full Text Available Puberty is a period of development characterized by partially concurrent changes which includes growth acceleration, alteration in body composition and appearance of secondary sex characteristics. Puberty is characterized by an acceleration and then deceleration in skeletal growth. The initiation, duration and amount of growth vary considerably during the growth spurt. Pubertal growth and biological maturation are dynamic processes regulated by a variety of genetic and environmental factors. Changes in skeletal maturation and bone mineral accretion concomitant with the stage of pubertal development constitute essential components in the evaluation of growth during this pubertal period. Genetic, endocrine and nutritional factors and ethnicity contribute variably to the amount of growth gained during this important period of rapid changes. Many studies investigated the possibility of increasing pubertal growth to gain taller final adult height in adolescents with idiopathic short stature (ISS. The pattern of pubertal growth, its relation to sex maturity rating and factors affecting them has been addressed in this review. The results of different trials to increase final adult height of adolescents using different hormones have been summarized. These data enables Endocrinologists to give in-depth explanations to patients and families about the efficacy and clinical significance as well as the safety of using these therapies in the treatment of adolescents with ISS.

  3. Putative effects of endocrine disrupters on pubertal development in the human

    DEFF Research Database (Denmark)

    Teilmann, Grete; Juul, Anders; Skakkebaek, Niels E

    2002-01-01

    Pubertal development is regulated by gonadotrophins and sex hormones. There has been a clear secular trend in the timing of puberty during the last century, puberty becoming earlier. Although improved nutrition is assumed to be the cause, this could partly be associated with exposure to so-called...

  4. The improved local linear prediction of chaotic time series

    Institute of Scientific and Technical Information of China (English)

    Meng Qing-Fang; Peng Yu-Hua; Sun Jia

    2007-01-01

    Based on the Bayesian information criterion, this paper proposes the improved local linear prediction method to predict chaotic time aeries. This method uses spatial correlation and temporal correlation simultaneously. Simulation results show that the improved local linear prediction method can effectively make multi-step and one-step prediction of chaotic time aeries and the multi-step prediction performance and one-step prediction accuracy of the improved local linear prediction method are superior to those of the traditional local linear prediction method.

  5. Bernstein polynomials for evolutionary algebraic prediction of short time series

    Science.gov (United States)

    Lukoseviciute, Kristina; Howard, Daniel; Ragulskis, Minvydas

    2017-07-01

    Short time series prediction technique based on Bernstein polynomials is presented in this paper. Firstly, the straightforward Bernstein polynomial extrapolation scheme is improved by extending the interval of approximation. Secondly, the forecasting scheme is designed in the evolutionary computational setup which is based on the conciliation between the coarseness of the algebraic prediction and the smoothness of the time average prediction. Computational experiments with the test time series suggest that this time series prediction technique could be applicable for various forecasting applications.

  6. Real-time travel time prediction framework for departure time and route advice

    NARCIS (Netherlands)

    Calvert, S.C.; Snelder, M.; Bakri, T.; Heijligers, B.; Knoop, V.L.

    2015-01-01

    Heavily used urban networks remain a challenge for travel time prediction because traffic flow is rarely homogeneous and is also subject to a wide variety of disturbances. Various models, some of which use traffic flow theory and some of which are data driven, have been developed to predict traffic

  7. Real-time travel time prediction framework for departure time and route advice

    NARCIS (Netherlands)

    Calvert, S.C.; Snelder, M.; Bakri, T.; Heijligers, B.; Knoop, V.L.

    2015-01-01

    Heavily used urban networks remain a challenge for travel time prediction because traffic flow is rarely homogeneous and is also subject to a wide variety of disturbances. Various models, some of which use traffic flow theory and some of which are data driven, have been developed to predict traffic

  8. Male pubertal development: are endocrine-disrupting compounds shifting the norms?

    Science.gov (United States)

    Zawatski, William; Lee, Mary M

    2013-01-01

    Endocrine-disrupting compounds (EDCs) are synthetic or natural compounds that interfere with endogenous endocrine action. The frequent use of chemicals with endocrine active properties in household products and contamination of soil, water, and food sources by persistent chemical pollutants result in ubiquitous exposures. Wildlife observations and animal toxicological studies reveal adverse effects of EDCs on reproductive health. In humans, a growing number of epidemiological studies report an association with altered pubertal timing and progression. While these data are primarily reported in females, this review will focus on the small number of studies performed in males that report an association of polychlorinated biphenyls with earlier sexual maturity rating and confirm subtle effects of lead, dioxins, and endosulfan on delaying pubertal onset and progression in boys. Recent studies have also demonstrated that EDC exposure may affect pubertal testosterone production without having a noticeable effect on sexual maturity rating. A limitation to understand the effects of EDCs in humans is the potential for confounding due to the long temporal lag from early-life exposures to adult outcomes. The complex interplay of multiple environmental exposures over time also complicates the interpretation of human studies. These studies have identified critical windows of vulnerability during development when exposures to EDCs alter critical pathways and affect postnatal reproductive health. Contemporaneous exposures can also disrupt the hypothalamic-pituitary-gonadal axis. This paper will review the normal process of puberty in males and summarize human data that suggest potential perturbations in pubertal onset and tempo with early-life exposures to EDCs.

  9. Influence of Pubertal Timing to Adolescent Heterosexual Behaviors and Reproductive Health Information Seeking Practices%青春发动时相对于职校学生性行为及网络生殖健康信息获取的影响

    Institute of Scientific and Technical Information of China (English)

    张珊; 史慧静; 张越; 余春艳

    2011-01-01

    目的:分析青春发动时相对于职校学生性行为和网络生殖健康信息获取的影响.方法:在随机整群选取的1 846名中等职业技术学校学生中,问卷调查青春发育时间、异性间性行为、以及生殖健康信息获取经历.结果:青春发动时相提前男、女生的各种性行为自我报告率均显著高于适时组和延迟组.互联网是职校生寻求性生殖健康信息的重要来源之一,青春发动时相提前对于其网络性生殖健康信息寻求具有独立作用.结论:在开展有针对性的职校生性生殖健康教育中,尤其要关注和合理引导青春发动时相偏离正常的学生.%Objective: To investigate the influence of pubertal timing to vocational high school students' heterosexual behaviors as well as their practices of online seeking for reproductive health information.Methods: By using structural self-administered questionnaire, self-perceived pubertal timing, heterosexual behaviors, and perceived valuable and helpful ways of obtaining reproductive health information, as well as experiences of Internet surfing reproductive health information were obtained from a cluster-randomized sample of 1 864 vocational high school students in Shanghai.Results: Of various information sources of sex and reproductive health, Internet surfing was much more preferred and recognized by all respondents.In both males and females, self-reported rates of heterosexual behaviors in the earlier puberty group were significantly higher than those in the ordinary and delayed groups.Percentages of those vocational high school students, surfing online for sex and reproductive health knowledge were highest in earlier puberty group, followed by delayed group and ordinary group.The independent effect of pubertal timing on the sex and reproductive information seeking via Internet was existed even after controlling for age, sex, hours of internet use per day, selfperceived study achievement and averaged parents

  10. Trend prediction of chaotic time series

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Trend prediction of chaotic ti me series is anin-teresting probleminti me series analysis andti me se-ries data mining(TSDM)fields[1].TSDM-basedmethods can successfully characterize and predictcomplex,irregular,and chaotic ti me series.Somemethods have been proposed to predict the trend ofchaotic ti me series.In our knowledge,these meth-ods can be classified into t wo categories as follows.The first category is based on the embeddedspace[2-3],where rawti me series data is mapped to areconstructed phase spac...

  11. A combined form of hypothyroidism in pubertal patients with non-mosaic Klinefelter syndrome.

    Science.gov (United States)

    Tahani, Natascia; Ruga, Gilda; Granato, Simona; Spaziani, Matteo; Panimolle, Francesca; Anzuini, Antonella; Lenzi, Andrea; Radicioni, Antonio Francesco

    2017-02-01

    Klinefelter syndrome has been associated with thyroid abnormalities, the genesis of which is not yet fully clear. The aim of this study was to evaluate thyroid function in Klinefelter syndrome subjects during the pubertal period. Chemiluminescent microparticle immunoassay was used to analyze Thyroid-Stimulating Hormone, fT3 and fT4 concentration in serum samples from 40 Klinefelter syndrome pubertal boys with classic 47,XXY karyotype and 157 healthy age-matched controls. 13 Klinefelter syndrome patients also underwent Thyrotropin-Releasing Hormone testing to evaluate hypothalamic-pituitary function. fT3 levels were significantly lower in Klinefelter syndrome patients than in age-matched controls (p Klinefelter syndrome patients tended to cluster around the lower part of the reference range for the assay. Three of the thirteen Klinefelter syndrome patients undergoing the Thyrotropin-Releasing Hormone test had an adequate response, one had a prolonged response at 60 min and nine responded inadequately. This study demonstrated for the first time that pubertal Klinefelter syndrome patients have significantly lower fT3 serum levels than do healthy age-matched boys, whereas Thyroid-Stimulating Hormone and fT4 are normal, albeit at the lower end of the reference range. Most patients showed an inadequate/prolonged response to pituitary stimulation with Thyrotropin-Releasing Hormone. These findings suggest a combined form of both central and peripheral hypothyroidism in Klinefelter syndrome boys during pubertal development.

  12. Pubertal pair-housing facilitates adult sexual behavior in male rats.

    Science.gov (United States)

    Molenda-Figueira, Heather A; Bell, Margaret R; De Lorme, Kayla C; Sisk, Cheryl L

    2017-01-01

    This study examined the effects of pubertal testosterone (T) and social housing manipulations on male sexual behavior in adult rats. Prepubertal rats were castrated at 21 days of age (P21) and implanted with either blank or T-releasing pellets. At the onset of puberty, P28, half the rats in each treatment group were either single- or pair-housed with a male of the same hormone condition through P56, at which time pellets were removed and all rats were single-housed. In adulthood (P84), all rats received T replacement and were tested for sexual behavior. Rats pair-housed during adolescence showed more sexual behavior and greater improvement of sexual performance over repeated tests than single-housed rats, regardless of pubertal T status. Pubertal T, however, did facilitate the frequency of anogenital investigation. Thus, in male rats, social interactions during adolescence are more important than exposure to pubertal T in enhancing adult sexual behavior. © 2016 Wiley Periodicals, Inc.

  13. [Insulin resistance and hyperinsulinemia--risk factors of the metabolic syndrome in the pubertal population].

    Science.gov (United States)

    Otto Buczkowska, Ewa

    2005-01-01

    Pubertal insulin resistance has been well documented, the fall in insulin sensitivity (Sl) during puberty is associated with a compensatory increase in insulin secretion. Observation of pubertal insulin resistance showed that insulin-stimulated glucose metabolism was approximately 30% lower in a sample of children at Tanner stages II-IV compared with children at Tanner stage I or adults. Although the phenomenon of pubertal insulin resistance is well documented, the mechanism has not been clearly determined. Pubertal insulin resistance occurs during a time of profound changes in body composition and hormone levels. Resistance of the body to the actions of insulin results in increased production of this hormone by the pancreas and ensuing hyperinsulinemia. Obesity beginning in childhood often precedes the hyperinsulinemic state. Other components of the insulin resistance syndrome are also present in children and adolescents. Conditions of insulin resistance, hyperinsulinemia, dyslipidemia, hypertension and obesity, especially in constellation, are potent risk factors of coronary atherosclerosis among adolescents and young adults. Early conservative intervention with diet, exercise, and behavioral therapy may prevent the complications of insulin resistance.

  14. Plasma Nesfatin-1 and Leptin in pubertal and non-pubertal Murrah buffalo heifers (Bubalus bubalis

    Directory of Open Access Journals (Sweden)

    Gorakh Nath Prajapati

    2015-12-01

    Full Text Available Buffaloes mostly suffer from delayed puberty, anestrus, sub–estrus, summer infertility, prolonged inter-calving interval and postpartum uterine disorders. Nesfatin-1 and Leptin are directly or indirectly related with body weight (BW, feed parameters and regulation of puberty. The objective of this study was to investigate the influence of Nesfatin-1 and Leptin in pubertal and non-pubertal Murrah buffalo heifers. The Murrah buffalo heifers (n=13 were randomly selected and divided into two groups; pubertal group (PG and non-pubertal group (NG. Heifers with plasma progesterone (P4 level of ≥1 ng/mL were classified as PG. Blood samples were collected at fortnight intervals for analysis of plasma Nesfatin-1, Leptin, P4, glucose and non-esterified fatty acids. Body weight, dry matter intake and feed conversion efficiency were recorded at fortnight intervals. The mean (±SEM plasma Nesfatin-1, Leptin, P4, BW and feed conversion efficiency (% were significantly (P<0.01 higher in PG as compared to NG. Dry matter intake by the heifers was also significantly (P<0.001 higher in PG than NG. Plasma metabolites (glucose and NEFA did not differ significantly between the groups. The findings of this study suggest that Nesfatin-1 and Leptin have indispensable role in the onset of puberty in buffalo heifers by affecting BW and feed parameters.

  15. Pubertal Stage, Body Mass Index, and Cardiometabolic Risk in Children and Adolescents in Bogotá, Colombia: The Cross-Sectional Fuprecol Study

    Directory of Open Access Journals (Sweden)

    Robinson Ramírez-Vélez

    2017-06-01

    Full Text Available This study explored the association between pubertal stage and anthropometric and cardiometabolic risk factors in youth. A cross-sectional study was conducted in 2877 Colombian children and adolescents (9–17.9 years of age. Weight, height, and waist circumference were measured and body mass index (BMI was calculated. A biochemical study was performed to determine the cardiometabolic risk index (CMRI. Blood pressure was evaluated and pubertal stage was assessed with the Tanner criteria. Hierarchical multiple regression analyses were performed. The most significant variable (p < 0.05 in the prognosis of cardiometabolic risk was found to be the BMI in both boys and girls. In the case of girls, the pubertal stage was also a CMRI predictive factor. In conclusion, BMI was an important indicator of cardiovascular risk in both sexes. Pubertal stage was associated with cardiovascular risk only in the girls.

  16. Prediction of Commuter’s Daily Time Allocation

    Directory of Open Access Journals (Sweden)

    Fang Zong

    2013-10-01

    Full Text Available This paper presents a model system to predict the time allocation in commuters’ daily activity-travel pattern. The departure time and the arrival time are estimated with Ordered Probit model and Support Vector Regression is introduced for travel time and activity duration prediction. Applied in a real-world time allocation prediction experiment, the model system shows a satisfactory level of prediction accuracy. This study provides useful insights into commuters’ activity-travel time allocation decision by identifying the important influences, and the results are readily applied to a wide range of transportation practice, such as travel information system, by providing reliable forecast for variations in travel demand over time. By introducing the Support Vector Regression, it also makes a methodological contribution in enhancing prediction accuracy of travel time and activity duration prediction.

  17. The pubertal transition in 179 healthy Danish children

    DEFF Research Database (Denmark)

    Mouritsen, Annette; Aksglæde, Lise; Sørensen, Kaspar

    2013-01-01

    Pubertal onset is usually defined by breast development in girls and testicular growth in boys. Pubarche is defined as the attainment of pubic hair and is considered as a sign of pubertal transition. Pubarche is preceded by a gradual increase in production of adrenal androgens, DHEA and Δ4...

  18. Pubertal development in The Netherlands 1965-1997

    NARCIS (Netherlands)

    D. Mul (Dick); A.M. Fredriks; S. van Buuren (Stef); W. Oostdijk (Wilma); S.P. Verloove-Vanhorick; J.M. Wit (Jan)

    2001-01-01

    textabstractWe investigated pubertal development of 4019 boys and 3562 girls >8 y of age participating in a cross-sectional survey in The Netherlands and compared the results with those of two previous surveys. Reference curves for all pubertal stages were constructed. The 50th per

  19. Pubertal development in The Netherlands 1965-1997

    NARCIS (Netherlands)

    D. Mul (Dick); A.M. Fredriks; S. van Buuren (Stef); W. Oostdijk (Wilma); S.P. Verloove-Vanhorick; J.M. Wit (Jan)

    2001-01-01

    textabstractWe investigated pubertal development of 4019 boys and 3562 girls >8 y of age participating in a cross-sectional survey in The Netherlands and compared the results with those of two previous surveys. Reference curves for all pubertal stages were constructed. The 50th per

  20. Prevalence and incidence of precocious pubertal development in Denmark

    DEFF Research Database (Denmark)

    Teilmann, Grete; Pedersen, Carsten; Jensen, Tina Kold

    2005-01-01

    To our knowledge, no population-based epidemiologic studies on the incidence and prevalence of precocious pubertal development have been published. Danish national registries provide sufficient data for estimating the prevalence and incidence of this condition. The aim of this study was to estimate...... the prevalence and incidence of precocious pubertal development in Denmark in a 9-year period....

  1. Time series prediction using wavelet process neural network

    Institute of Scientific and Technical Information of China (English)

    Ding Gang; Zhong Shi-Sheng; Li Yang

    2008-01-01

    In the real world, the inputs of many complicated systems are time-varying functions or processes. In order to predict the outputs of these systems with high speed and accuracy, this paper proposes a time series prediction model based on the wavelet process neural network, and develops the corresponding learning algorithm based on the expansion of the orthogonal basis functions. The effectiveness of the proposed time series prediction model and its learning algorithm is proved by the Mackey-Glass time series prediction, and the comparative prediction results indicate that the proposed time series prediction model based on the wavelet process neural network seems to perform well and appears suitable for using as a good tool to predict the highly complex nonlinear time series.

  2. Reproductive ability of pubertal male and female rats

    Directory of Open Access Journals (Sweden)

    T. Zemunik

    2003-07-01

    Full Text Available Ten Fisher rats 50 to 55 days of age made up the pubertal group, and ten rats 90 to 95 days of age served as the controls. The testicular and epididymal weights and volumes of the pubertal males were lower than those of the controls (P0.05. At the beginning of gestation, the pubertal dams weighed less than the controls (P<0.001 but following uterectomy the body weights were equal. Pubertal dams delivered fewer pups than the controls (8.1 ± 2.5 vs 10.4 ± 1.3, P<0.05. There was no difference in the body weights of their offspring or in the weights of their placentas. The results suggest that, in contrast to their female counterparts, pubertal male rats are not fully mature and have not reached complete reproductive capacity at 50-55 days of age.

  3. Continuous-Discrete Time Prediction-Error Identification Relevant for Linear Model Predictive Control

    DEFF Research Database (Denmark)

    Jørgensen, John Bagterp; Jørgensen, Sten Bay

    2007-01-01

    model is realized from a continuous-discrete-time linear stochastic system specified using transfer functions with time-delays. It is argued that the prediction-error criterion should be selected such that it is compatible with the objective function of the predictive controller in which the model......A Prediction-error-method tailored for model based predictive control is presented. The prediction-error method studied are based on predictions using the Kalman filter and Kalman predictors for a linear discrete-time stochastic state space model. The linear discrete-time stochastic state space...

  4. A novel time series link prediction method: Learning automata approach

    Science.gov (United States)

    Moradabadi, Behnaz; Meybodi, Mohammad Reza

    2017-09-01

    Link prediction is a main social network challenge that uses the network structure to predict future links. The common link prediction approaches to predict hidden links use a static graph representation where a snapshot of the network is analyzed to find hidden or future links. For example, similarity metric based link predictions are a common traditional approach that calculates the similarity metric for each non-connected link and sort the links based on their similarity metrics and label the links with higher similarity scores as the future links. Because people activities in social networks are dynamic and uncertainty, and the structure of the networks changes over time, using deterministic graphs for modeling and analysis of the social network may not be appropriate. In the time-series link prediction problem, the time series link occurrences are used to predict the future links In this paper, we propose a new time series link prediction based on learning automata. In the proposed algorithm for each link that must be predicted there is one learning automaton and each learning automaton tries to predict the existence or non-existence of the corresponding link. To predict the link occurrence in time T, there is a chain consists of stages 1 through T - 1 and the learning automaton passes from these stages to learn the existence or non-existence of the corresponding link. Our preliminary link prediction experiments with co-authorship and email networks have provided satisfactory results when time series link occurrences are considered.

  5. [Psychopathology related to women pubertal precocity].

    Science.gov (United States)

    Purper-Ouakil, D; Didillon, A

    2016-10-01

    associated with psychosocial stressors and at-risk environments. The early development of secondary sexual characteristics in girls attracts older and more deviant peers, raising probability of sexual contacts but also of drug use and of a disengagement in school activities. Adolescence is the life stage during which prevalence of depressive disorders rises significantly, especially in girls. Hormonal changes and increase of the Body Mass Index leading to dissatisfaction with body image, have been put forward to explain this trend. Psychosocial challenges (emerging sexuality, instability of identity and social role) are other sources of stress at this particular period of life characterized by emotional hyper-reactivity. These stressors may have greater impact in young people showing a discrepancy between physical and affective maturation. Follow-up studies have shown that emotional and behavioral problems tend to lessen with time. Nevertheless, a heightened risk of depressive disorder remains in girls having had an early onset of puberty when other risk factors co-exist. Early puberty, especially in girls, has been associated with a number of emotional and behavioral symptoms and difficulties in adaptive functioning. Even though these adverse outcomes seem to lessen with time, heightened risk for depression and negative impact on socio-professional outcomes persist in subjects with other risk factors. The impact of treatment of precocious puberty on psycho-behavioral outcomes is currently unknown. However, clinicians should be aware that the social and emotional challenges these adolescents with atypical pubertal development have to face put them at risk for psychopathology and are potentially accessible to preventive actions. Copyright © 2016 L'Encéphale, Paris. Published by Elsevier Masson SAS. All rights reserved.

  6. Retrospective cohort study of relationship between pubertal growth spurt and body mass index%围青春期体脂与青春发动时相关系的回顾性队列研究

    Institute of Scientific and Technical Information of China (English)

    张珊; 史慧静; 杨鞭; 张越

    2011-01-01

    Objective To examine peri-pubertal body mass index ( BMI) in relation to pubertal timing, as asseased by age at onset of pubertal growth spurt ( AOGS) and at peak height velocity ( APHV ), among children and adolescents. Methods A cluster sample of 329 nine-grade students was selected from 3 schools in Shanghai. For each subject, annual measurements of height and weight from grade one to grade nine were obtained from school health record. Age at OGS and PHV, criterion for pubertal timing, were calculated by using the cubic spline fit function. Results Advanced pubertal growth spurt was estimated by using P67 of peak height velocity of pubertal growth. BMI -Z score at pre-puberty, early puberty,and middle/late puberty were analyzed in relation to pubertal timing. The increments of BMI - Z score during pre-puberty to early puberty and during early to middle/late puberty were compared between advanced and non-advanced pubertal timing groups. Results In both of girls and boys, advanced growth spurt was associated with higher BMI -Z scores in pre-puberty, early puberty and middle/late puberty. Advanced growth spurt was significantly associated with greater increment of BMI -Z scores during pre-puberty to early puberty, which is not found in boys. Conclusion Higher level of BMI in pre-puberty and greater increments of BMI - Z score during pre-puberty to early puberty may predict advance growth spurt in adolescence as well as adulthood.%目的 研究不同青春发动时相的儿童青少年在围青春期的体脂水平及增长模式,为青春发动机制的研究和肥胖防控工作提供依据.方法 整群选择上海市3所学校的329名九年级学生,回溯一~九年级时的身高和体重体检记录,用Cubic Spline Fit函数拟合得到身高突增启动年龄和身高突增高峰年龄,并以此为青春发动时相界定的依据,分析围青春期不同阶段体质量指数(BMI)-Z值和BMI-Z增加值与青春发动时相的关系.结果 女生青春发

  7. Evidence of secular trend in mandibular pubertal growth.

    Science.gov (United States)

    Patcas, Raphael; Wiedemeier, Daniel B; Markic, Goran; Beit, Philipp; Keller, Heidi

    2017-04-20

    During puberty, mandibular growth follows a growth curve comparable to somatic growth. This study aimed to review the relationship between mandibular pubertal peak height velocity (PHV) and skeletal age, and to investigate the possibility of a secular trend. Retrospective analysis was performed of two historical craniofacial growth studies (Denver Growth Study; observational time: 1943-1965, and Zurich Growth Study; observational time: 1982-1984) of healthy untreated subjects. Two mandibular growth measures (Articulare-Pogonion [Ar-Pg], Condylion-Pogonion [Co-Pg]) were retrieved from cephalograms (n: 990) and corresponding skeletal age based on hand-wrist radiographs. Mandibular growth velocity was related to skeletal age, PHV was established by use of cubic smoothing splines and variability was calculated by bootstrap resampling for every growth study and gender separately. Sexual dimorphism in mandibular growth was apparent in both cohorts. In subjects of the Denver Growth Study, mandibular PHV occurred at a more advanced skeletal age than in subjects of the Zurich Growth Study. This trend was more pronounced in males, for whom PHV of Co-Pg shifted from 14.4 to 13.8 years and of Ar-Pg from 14.6 to 13.7 years. This tendency was more subtle in females: PHV of Co-Pg shifted from 12.7 to 12.4 years and of Ar-Pg from 12.6 to 11.8 years. Mandibular growth appears to be subject to a secular trend. When related to skeletal age, this secular trend seems to be more accentuated than the established secular trend for somatic pubertal growth.

  8. Predicting Chaotic Time Series Using Recurrent Neural Network

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jia-Shu; XIAO Xian-Ci

    2000-01-01

    A new proposed method, i.e. the recurrent neural network (RNN), is introduced to predict chaotic time series. The effectiveness of using RNN for making one-step and multi-step predictions is tested based on remarkable few datum points by computer-generated chaotic time series. Numerical results show that the RNN proposed here is a very powerful tool for making prediction of chaotic time series.

  9. Time-series prediction and applications a machine intelligence approach

    CERN Document Server

    Konar, Amit

    2017-01-01

    This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications. It also proposes new uncertainty management techniques in an economic time-series using type-2 fuzzy sets for prediction of the time-series at a given time point from its preceding value in fluctuating business environments. It employs machine learning to determine repetitively occurring similar structural patterns in the time-series and uses stochastic automaton to predict the most probabilistic structure at a given partition of the time-series. Such predictions help in determining probabilistic moves in a stock index time-series Primarily written for graduate students and researchers in computer science, the book is equally useful for researchers/professionals in business intelligence and stock index prediction. A background of undergraduate level mathematics is presumed, although not mandatory, for most of the sections. Exercises with tips are provided at...

  10. Learning and Prediction of Relational Time Series

    Science.gov (United States)

    2013-03-01

    genetic algorithms can generate a sequence of events to maximize some functions or the likelihood to achieve the assumed goals. With reference...Reinforcement learning is not the same as relational time-series learning mainly because its main focus is to learn a set of policies to maximize the...scope blending, and has been applied to machine poetry generation [48] and the generation of animation characters [49]. Tan and Kowk [50] applied the

  11. Adolescents' increasing stress response to social evaluation: pubertal effects on cortisol and alpha-amylase during public speaking.

    Science.gov (United States)

    van den Bos, Esther; de Rooij, Mark; Miers, Anne C; Bokhorst, Caroline L; Westenberg, P Michiel

    2014-01-01

    Stress responses to social evaluation are thought to increase during adolescence, which may be due to pubertal maturation. However, empirical evidence is scarce. This study is the first to investigate the relation between pubertal development and biological responses to a social-evaluative stressor longitudinally. Participants performed the Leiden Public Speaking Task twice, with a 2-year interval (N = 217; age at Time 1: 8-17 years). The results support an increase in sensitivity to social evaluation during adolescence. The overall cortisol and alpha-amylase responses increased-both between and within participants-and were more strongly related to self-reported pubertal development than to age. The cortisol response shifted from speech delivery toward anticipation. The alpha-amylase response increased in both phases. © 2013 The Authors. Child Development © 2013 Society for Research in Child Development, Inc.

  12. Evaluation of Fast-Time Wake Vortex Prediction Models

    Science.gov (United States)

    Proctor, Fred H.; Hamilton, David W.

    2009-01-01

    Current fast-time wake models are reviewed and three basic types are defined. Predictions from several of the fast-time models are compared. Previous statistical evaluations of the APA-Sarpkaya and D2P fast-time models are discussed. Root Mean Square errors between fast-time model predictions and Lidar wake measurements are examined for a 24 hr period at Denver International Airport. Shortcomings in current methodology for evaluating wake errors are also discussed.

  13. ISOL Yield Predictions from Holdup-Time Measurements

    Energy Technology Data Exchange (ETDEWEB)

    Spejewski, Eugene H. [Oak Ridge Associated Universities (ORAU); Carter, H Kennon [Oak Ridge Associated Universities (ORAU); Mervin, Brenden T. [Oak Ridge Associated Universities (ORAU); Prettyman, Emily S. [Oak Ridge Associated Universities (ORAU); Kronenberg, Andreas [Oak Ridge Associated Universities (ORAU); Stracener, Daniel W [ORNL

    2008-01-01

    A formalism based on a simple model is derived to predict ISOL yields for all isotopes of a given element based on a holdup-time measurement of a single isotope of that element. Model predictions, based on parameters obtained from holdup-time measurements, are compared to independently-measured experimental values.

  14. A hybrid travel time prediction framework for planned motorway roadworks

    NARCIS (Netherlands)

    Calvert, S.C.; Lint, J.W.C. van; Hoogendoorn, S.P.

    2010-01-01

    In this paper we propose a hybrid motorway travel time prediction framework aimed at providing pre-trip travel information in case of roadworks. The framework utilises a first order macroscopic traffic flow model to predict the consequences in travel time of changes in both traffic demand and roadwa

  15. Facing changes and changing faces in adolescence: a new model for investigating adolescent-specific interactions between pubertal, brain and behavioral development.

    Science.gov (United States)

    Scherf, K Suzanne; Behrmann, Marlene; Dahl, Ronald E

    2012-04-01

    Adolescence is a time of dramatic physical, cognitive, emotional, and social changes as well as a time for the development of many social-emotional problems. These characteristics raise compelling questions about accompanying neural changes that are unique to this period of development. Here, we propose that studying adolescent-specific changes in face processing and its underlying neural circuitry provides an ideal model for addressing these questions. We also use this model to formulate new hypotheses. Specifically, pubertal hormones are likely to increase motivation to master new peer-oriented developmental tasks, which will in turn, instigate the emergence of new social/affective components of face processing. We also predict that pubertal hormones have a fundamental impact on the re-organization of neural circuitry supporting face processing and propose, in particular, that, the functional connectivity, or temporal synchrony, between regions of the face-processing network will change with the emergence of these new components of face processing in adolescence. Finally, we show how this approach will help reveal why adolescence may be a period of vulnerability in brain development and suggest how it could lead to prevention and intervention strategies that facilitate more adaptive functional interactions between regions within the broader social information processing network. Copyright © 2011 Elsevier Ltd. All rights reserved.

  16. Assessing the Predictability of Scheduled-Vehicle Travel Times

    DEFF Research Database (Denmark)

    Tiesyte, Dalia; Jensen, Christian Søndergaard

    2009-01-01

    One of the most desired and challenging services in collective transport systems is the real-time prediction of the near-future travel times of scheduled vehicles, especially public buses, thus improving the experience of the transportation users, who may be able to better schedule their travel......, and also enabling system operators to perform real-time monitoring. While travel-time prediction has been researched extensively during the past decade, the accuracies of existing techniques fall short of what is desired, and proposed mathematical prediction models are often not transferable to other...... systems because the properties of the travel-time-related data of vehicles are highly context-dependent, making the models difficult to fit. We propose a framework for evaluating various predictability types of the data independently of the model, and we also compare predictability analysis results...

  17. Environmental Phenols And Pubertal Development In Girls

    Science.gov (United States)

    Wolff, Mary S.; Teitelbaum, Susan L.; McGovern, Kathleen; Pinney, Susan M.; Windham, Gayle C.; Galvez, Maida; Pajak, Ashley; Rybak, Michael; Calafat, Antonia M.; Kushi, Lawrence H.; Biro, Frank M.

    2015-01-01

    Environmental exposures to many phenols are documented worldwide and exposures can be quite high (>1 micromolar of urine metabolites). Phenols have a range of hormonal activity, but knowledge of effects on child reproductive development is limited, coming mostly from cross-sectional studies. We undertook a prospective study of pubertal development among 1239 girls recruited at three U.S. sites when they were 6–8 years old and were followed annually for 7 years to determine age at first breast or pubic hair development. Ten phenols were measured in urine collected at enrollment (benzophenone-3, enterolactone, bisphenol A, three parabens (methyl-, ethyl-, propyl-), 2,5-dichlorophenol, triclosan, genistein, daidzein). We used multivariable adjusted Cox proportional hazards ratios (HR (95% confidence intervals)) and Kaplan-Meier survival analyses to estimate relative risk of earlier or later age at puberty associated with phenol exposures. For enterolactone and benzophenone-3, girls experienced breast development 5–6 months later, adjusted HR 0.79 (0.64–0.98) and HR 0.80 (0.65–0.98) respectively for the 5th vs 1st quintiles of urinary biomarkers (μg/g-creatinine). Earlier breast development was seen for triclosan and 2,5- dichlorophenol: 4–9 months sooner for 5th vs 1st quintiles of urinary concentrations (HR 1.17 (0.96–1.43) and HR 1.37 (1.09–1.72), respectively). Association of breast development with enterolactone, but not the other three phenols, was mediated by body size. These phenols may be antiadipogens (benzophenone-3 and enterolactone) or thyroid agonists (triclosan and 2,5- dichlorophenol), and their ubiquity and relatively high levels in children would benefit from further investigation to confirm these findings and to establish whether there are certain windows of susceptibility during which exposure can affect pubertal development. PMID:26335517

  18. Assessing the Predictability of Scheduled-Vehicle Travel Times

    DEFF Research Database (Denmark)

    Tiesyte, Dalia; Jensen, Christian Søndergaard

    2009-01-01

    One of the most desired and challenging services in collective transport systems is the real-time prediction of the near-future travel times of scheduled vehicles, especially public buses, thus improving the experience of the transportation users, who may be able to better schedule their travel...... of travel times with the actual prediction errors for real bus trajectories. We have applied the proposed framework to real-time data collected from buses operating in Copenhagen, Denmark......., and also enabling system operators to perform real-time monitoring. While travel-time prediction has been researched extensively during the past decade, the accuracies of existing techniques fall short of what is desired, and proposed mathematical prediction models are often not transferable to other...

  19. Method for Predicting Which Customers' Time Deposit Balances Will Increase

    Science.gov (United States)

    Ono, Toshiyuki; Yoshikawa, Hiroshi; Morita, Masahiro; Komoda, Norihisa

    This paper proposes a method of predicting which customers' account balances will increase by using data mining to effectively and efficiently promote sales. Prediction by mining all the data in a business is difficult because of much time required to collect, process, and calculate it. The selection of which features are used for prediction is a critical issue. We propose a method of selecting features to improve the accuracy of prediction within practical time limits. It consists of three parts: (1) converting collected features into financial behavior features that reflect customer actions, (2) extracting features affecting increases in account balances from these collected and financial behavior features, and (3) predicting customers whose account balances will increase based on the extracted features. We found the accuracy of prediction in an experiment with our method to be higher than with other conventional methods.

  20. Safety-critical Java on a time-predictable processor

    DEFF Research Database (Denmark)

    Korsholm, Stephan E.; Schoeberl, Martin; Puffitsch, Wolfgang

    2015-01-01

    For real-time systems the whole execution stack needs to be time-predictable and analyzable for the worst-case execution time (WCET). This paper presents a time-predictable platform for safety-critical Java. The platform consists of (1) the Patmos processor, which is a time-predictable processor......; (2) a C compiler for Patmos with support for WCET analysis; (3) the HVM, which is a Java-to-C compiler; (4) the HVM-SCJ implementation which supports SCJ Level 0, 1, and 2 (for both single and multicore platforms); and (5) a WCET analysis tool. We show that real-time Java programs translated to C...... and compiled to a Patmos binary can be analyzed by the AbsInt aiT WCET analysis tool. To the best of our knowledge the presented system is the second WCET analyzable real-time Java system; and the first one on top of a RISC processor....

  1. Safety-Critical Java on a Time-predictable Processor

    DEFF Research Database (Denmark)

    Korsholm, Stephan Erbs; Schoeberl, Martin; Puffitsch, Wolfgang

    2015-01-01

    For real-time systems the whole execution stack needs to be time-predictable and analyzable for the worst-case execution time (WCET). This paper presents a time-predictable platform for safety-critical Java. The platform consists of (1) the Patmos processor, which is a time-predictable processor......; (2) a C compiler for Patmos with support for WCET analysis; (3) the HVM, which is a Java-to-C compiler; (4) the HVM-SCJ implementation which supports SCJ Level 0, 1, and 2 (for both single and multicore platforms); and (5) a WCET analysis tool. We show that real-time Java programs translated to C...... and compiled to a Patmos binary can be analyzed by the AbsInt aiT WCET analysis tool. To the best of our knowledge the presented system is the second WCET analyzable real-time Java system; and the first one on top of a RISC processor....

  2. Impact of pubertal development on endothelial function and arterial elasticity.

    Science.gov (United States)

    Marlatt, Kara L; Steinberger, Julia; Dengel, Donald R; Sinaiko, Alan; Moran, Antoinette; Chow, Lisa S; Steffen, Lyn M; Zhou, Xia; Kelly, Aaron S

    2013-11-01

    Little is known about the relation of pubertal development on endothelial function and arterial elasticity in children and adolescents; therefore, we compared brachial artery flow-mediated dilation and carotid artery elasticity across Tanner (pubertal) stages in children and adolescents. Blood pressure, fasting lipids, glucose and insulin, body fat, insulin sensitivity adjusted for lean body mass, brachial flow-mediated dilation (percent dilation and area under the curve), endothelium-independent dilation (peak dilation and area under the curve), and carotid artery elasticity were evaluated across pubertal stages (Tanner I vs Tanner II-IV vs Tanner V) in 344 children and adolescents (184 males, 160 females; ages 6 to 21 years). One hundred twenty-four subjects (mean age 8.23 ± 0.15 years; 52 females) were Tanner stage I; 105 subjects (mean age 13.19 ± 0.17 years; 47 females) were Tanner stages II-IV; and 115 subjects (mean age 17.19 ± 0.16 years; 61 females) were Tanner stage V. There were no significant differences for any of the measures of vascular structure and function across pubertal stages. Results of the current study indicate that smooth-muscle and endothelial function, as well as carotid artery elasticity, do not differ throughout pubertal development and that accounting for pubertal stage when reporting vascular data in children and adolescents may be unnecessary. Copyright © 2013 Mosby, Inc. All rights reserved.

  3. On the Scalability of Time-predictable Chip-Multiprocessing

    DEFF Research Database (Denmark)

    Puffitsch, Wolfgang; Schoeberl, Martin

    2012-01-01

    simple processors is not an option for embedded systems with high demands on computing power. In order to provide high performance and predictability we argue to use multiprocessor systems with a time-predictable memory interface. In this paper we present the scalability of a Java chip...

  4. Three Millennia of Seemingly Time-Predictable Earthquakes, Tell Ateret

    Science.gov (United States)

    Agnon, Amotz; Marco, Shmuel; Ellenblum, Ronnie

    2014-05-01

    Among various idealized recurrence models of large earthquakes, the "time-predictable" model has a straightforward mechanical interpretation, consistent with simple friction laws. On a time-predictable fault, the time interval between an earthquake and its predecessor is proportional to the slip during the predecessor. The alternative "slip-predictable" model states that the slip during earthquake rupture is proportional to the preceding time interval. Verifying these models requires extended records of high precision data for both timing and amount of slip. The precision of paleoearthquake data can rarely confirm or rule out predictability, and recent papers argue for either time- or slip-predictable behavior. The Ateret site, on the trace of the Dead Sea fault at the Jordan Gorge segment, offers unique precision for determining space-time patterns. Five consecutive slip events, each associated with deformed and offset sets of walls, are correlated with historical earthquakes. Two correlations are based on detailed archaeological, historical, and numismatic evidence. The other three are tentative. The offsets of three of the events are determined with high precision; the other two are not as certain. Accepting all five correlations, the fault exhibits a striking time-predictable behavior, with a long term slip rate of 3 mm/yr. However, the 30 October 1759 ~0.5 m rupture predicts a subsequent rupture along the Jordan Gorge toward the end of the last century. We speculate that earthquakres on secondary faults (the 25 November 1759 on the Rachaya branch and the 1 January 1837 on the Roum branch, both M≥7) have disrupted the 3 kyr time-predictable pattern.

  5. Transitions in Body and Behavior: A Meta-Analytic Study on the Relationship Between Pubertal Development and Adolescent Sexual Behavior

    NARCIS (Netherlands)

    Baams, L.; Dubas, J.S.; Overbeek, G.J.; van Aken, M.A.G.

    2015-01-01

    The present meta-analysis studies the relations of pubertal timing and status with sexual behavior and sexual risk behavior among youth aged 10.5-22.4 years. We included biological sex, age, and ethnicity as potential moderators. Four databases were searched for studies (published between 1980 and 2

  6. Weight Suppression Predicts Time to Remission from Bulimia Nervosa

    Science.gov (United States)

    Lowe, Michael R.; Berner, Laura A.; Swanson, Sonja A.; Clark, Vicki L.; Eddy, Kamryn T.; Franko, Debra L.; Shaw, Jena A.; Ross, Stephanie; Herzog, David B.

    2011-01-01

    Objective: To investigate whether, at study entry, (a) weight suppression (WS), the difference between highest past adult weight and current weight, prospectively predicts time to first full remission from bulimia nervosa (BN) over a follow-up period of 8 years, and (b) weight change over time mediates the relationship between WS and time to first…

  7. Weight Suppression Predicts Time to Remission from Bulimia Nervosa

    Science.gov (United States)

    Lowe, Michael R.; Berner, Laura A.; Swanson, Sonja A.; Clark, Vicki L.; Eddy, Kamryn T.; Franko, Debra L.; Shaw, Jena A.; Ross, Stephanie; Herzog, David B.

    2011-01-01

    Objective: To investigate whether, at study entry, (a) weight suppression (WS), the difference between highest past adult weight and current weight, prospectively predicts time to first full remission from bulimia nervosa (BN) over a follow-up period of 8 years, and (b) weight change over time mediates the relationship between WS and time to first…

  8. Prediction and interpolation of time series by state space models

    OpenAIRE

    Helske, Jouni

    2015-01-01

    A large amount of data collected today is in the form of a time series. In order to make realistic inferences based on time series forecasts, in addition to point predictions, prediction intervals or other measures of uncertainty should be presented. Multiple sources of uncertainty are often ignored due to the complexities involved in accounting them correctly. In this dissertation, some of these problems are reviewed and some new solutions are presented. A state space approach...

  9. Pre-menarche pubertal development following unique form of immigration: the case of girls adopted from China.

    Science.gov (United States)

    Tan, Tony Xing; Camras, Linda A

    2015-02-01

    Our study tested the hypothesis that drastic social-cultural change has an impact on girls' pre-menarche pubertal development. We focused on a unique group of Chinese immigrants who migrated out of China in infancy through international adoption. Our sample included 298 Chinese girls who were 7.3-11.1 years in 2011 (Mean = 8.8, SD = 0.9) and were adopted at 7-24 months (Mean = 12.6, SD = 3.4). We found that 34% showed at least one of four signs of pubertal development: Growth spurt, body fat increase, breast development, and body hair. Logistic regression analyses showed that the odds of growth spurt was raised by the girls' age in 2011, behavior problems in 2005, but lowered by the adoptive families' household income; the odds of body fat increase in 2011 was raised by the adopted Chinese girls' weight in 2007 and behavior problems in 2005, but was lowered by the adoptive mother's education level; the odds for breast development in 2011 was raised by the girls' age in 2011, weight in 2007, and behavior problems in 2009. For body hair, none of the factors predicted the odds. Prevalence of precocious puberty, based on the criterion of breast development before 8 years, was 3.5%. Overall, our study suggests that the pre-menarche pubertal development of adopted Chinese girls may be slightly advanced but also is affected by factors that affect non-adopted girls' pubertal development.

  10. Statistical characteristics of irreversible predictability time in regional ocean models

    Directory of Open Access Journals (Sweden)

    P. C. Chu

    2005-01-01

    Full Text Available Probabilistic aspects of regional ocean model predictability is analyzed using the probability density function (PDF of the irreversible predictability time (IPT (called τ-PDF computed from an unconstrained ensemble of stochastic perturbations in initial conditions, winds, and open boundary conditions. Two-attractors (a chaotic attractor and a small-amplitude stable limit cycle are found in the wind-driven circulation. Relationship between attractor's residence time and IPT determines the τ-PDF for the short (up to several weeks and intermediate (up to two months predictions. The τ-PDF is usually non-Gaussian but not multi-modal for red-noise perturbations in initial conditions and perturbations in the wind and open boundary conditions. Bifurcation of τ-PDF occurs as the tolerance level varies. Generally, extremely successful predictions (corresponding to the τ-PDF's tail toward large IPT domain are not outliers and share the same statistics as a whole ensemble of predictions.

  11. A Time-predictable Memory Network-on-Chip

    DEFF Research Database (Denmark)

    Schoeberl, Martin; Chong, David VH; Puffitsch, Wolfgang

    2014-01-01

    To derive safe bounds on worst-case execution times (WCETs), all components of a computer system need to be time-predictable: the processor pipeline, the caches, the memory controller, and memory arbitration on a multicore processor. This paper presents a solution for time-predictable memory...... arbitration and access for chip-multiprocessors. The memory network-on-chip is organized as a tree with time-division multiplexing (TDM) of accesses to the shared memory. The TDM based arbitration completely decouples processor cores and allows WCET analysis of the memory accesses on individual cores without...

  12. A Time-predictable Memory Network-on-Chip

    DEFF Research Database (Denmark)

    Schoeberl, Martin; Chong, David VH; Puffitsch, Wolfgang

    2014-01-01

    To derive safe bounds on worst-case execution times (WCETs), all components of a computer system need to be time-predictable: the processor pipeline, the caches, the memory controller, and memory arbitration on a multicore processor. This paper presents a solution for time-predictable memory...... arbitration and access for chip-multiprocessors. The memory network-on-chip is organized as a tree with time-division multiplexing (TDM) of accesses to the shared memory. The TDM based arbitration completely decouples processor cores and allows WCET analysis of the memory accesses on individual cores without...

  13. Pubertal development among girls with classical congenital adrenal hyperplasia initiated on treatment at different ages

    Directory of Open Access Journals (Sweden)

    Bindu Kulshreshtha

    2012-01-01

    Full Text Available Introduction: Children with congenital adrenal hyperplasia (CAH provide us an opportunity to study the clinical effects of androgen excess in humans. We studied the sequence of pubertal development in girls with congenital adrenal hyperplasia initiated on treatment at different ages, to assess the effects of androgen exposure on the Hypothalamic-Pituitary-Ovarian (HPO axis. Materials and Methods: Girls more than 18 years of age, with CAH, on follow-up at this hospital were the subjects for this study. Details of history, physical findings, laboratory evaluation, and medication were noted from their case records and verified from the patients and their / parents, in addition to assessment of their present health status. Result: We studied 24 patients of classical CAH (SW-2, SV-22, average age - 24.5 ± 6.6 years. All had varying degrees of genital ambiguity (Prader stage 3 (n = 13, Prader stage 2 (n = 10, Prader stage 1 (n = 1. Among them were13 girls, who were started on steroids after eight years of age. Girls who received treatment from infancy and early childhood had normal pubertal development (mean age at menarche 11.4 ± 1.7 years. Hirsutism was not a problem among them. Untreated children had progressive clitoral enlargement throughout childhood, developed pubic hair at around three to six years of age, and facial hair between nine and eleven years. Plasma testosterone ranged from 3 to 6 ng / ml prior to treatment. Six of the 13 untreated CAH girls had subtle breast development starting at ages 11 - 16 years and three had spontaneous infrequent vaginal bleeding starting at ages 11 - 17. Steroid supplementation initiated pubertal changes in older girls in two-to-six months′ time. Conclusion: There was a delay in HPO axis maturation (as evidenced by delayed pubertal development in the absence of treatment in girls with CAH. This could be corrected with steroid supplementation.

  14. Pubertal assessment: a national survey of attitudes, knowledge and practices of the US pediatric trainees.

    Science.gov (United States)

    Khokhar, Aditi; Ravichandran, Yagnaram; Stefanov, Dimitre G; Perez-Colon, Sheila

    2017-07-06

    Background and objective Sex maturity rating (SMR), defines different levels of sexual maturity, based on the development of secondary sexual characteristics. Periodic assessment of pubertal maturation by physicians is crucial for timely identification of puberty-related disorders. With this pilot study, we aimed to assess the attitudes, knowledge and practices of pubertal assessment by current US pediatric trainees. Methods An anonymous online survey questionnaire was sent to categorical pediatric residents at different levels of training and pediatric chief residents across the US. Results We received responses from 2496 pediatric residents from all over the US. We found that 96% of trainees understand the importance of assessing SMR, 62% feel confident in assessing it and 55% feel comfortable assessing the need for an endocrinology referral. Only 33% of trainees performed external genital exams during all regular clinic visits while 26.9% never performed them during sick visits and 6% never assessed SMR during any of the patient visits. Higher levels of training and having completed an endocrinology rotation were associated with improvement in comfort level, practice and knowledge of trainees regarding pubertal assessment. Conclusion This study revealed that the current clinical practices of performing external genital exams and SMR among pediatric residents need improvement. Stronger reinforcement from continuity clinic preceptors and/or online and clinic based resources for SMR assessment for trainees may improve adherence to the recommended guidelines.

  15. Scalable Prediction of Energy Consumption using Incremental Time Series Clustering

    Energy Technology Data Exchange (ETDEWEB)

    Simmhan, Yogesh; Noor, Muhammad Usman

    2013-10-09

    Time series datasets are a canonical form of high velocity Big Data, and often generated by pervasive sensors, such as found in smart infrastructure. Performing predictive analytics on time series data can be computationally complex, and requires approximation techniques. In this paper, we motivate this problem using a real application from the smart grid domain. We propose an incremental clustering technique, along with a novel affinity score for determining cluster similarity, which help reduce the prediction error for cumulative time series within a cluster. We evaluate this technique, along with optimizations, using real datasets from smart meters, totaling ~700,000 data points, and show the efficacy of our techniques in improving the prediction error of time series data within polynomial time.

  16. Grammar-based feature generation for time-series prediction

    CERN Document Server

    De Silva, Anthony Mihirana

    2015-01-01

    This book proposes a novel approach for time-series prediction using machine learning techniques with automatic feature generation. Application of machine learning techniques to predict time-series continues to attract considerable attention due to the difficulty of the prediction problems compounded by the non-linear and non-stationary nature of the real world time-series. The performance of machine learning techniques, among other things, depends on suitable engineering of features. This book proposes a systematic way for generating suitable features using context-free grammar. A number of feature selection criteria are investigated and a hybrid feature generation and selection algorithm using grammatical evolution is proposed. The book contains graphical illustrations to explain the feature generation process. The proposed approaches are demonstrated by predicting the closing price of major stock market indices, peak electricity load and net hourly foreign exchange client trade volume. The proposed method ...

  17. Pubertal development in adolescents with menstrual disorders

    Directory of Open Access Journals (Sweden)

    Alberto Roteta Dorado

    2010-07-01

    Full Text Available Introduction: Abnormal uterine bleeding is the presence of an excessive and prolonged menstrual bleeding over several consecutive cycles. It is one of the first complaints in pediatric gynecology and is the most common cause dysfunctional uterine bleeding. Objective: To characterize adolescents with menstrual disorders attending gynecology clinic in child and adolescent onset of puberty. Method: A descriptive, longitudinal and prospective. Universe: 88 adolescents seen at the gynecology children and youth in the province of Cienfuegos with menstrual disorders in 2008. Sample: 64 patients with rhythm disturbances of the menstrual cycle and excessive bleeding. Procedure: During the first consultation was found in the following medical records: age, onset of puberty, age at menarche, breast development and pubic hair development. The data were processed by SPSS program and expressed as numbers and percentages. Results: 43.8% of the adolescents studied were between 14 and 16 years, 29.7% began puberty at age 9, 31.3% had their menarche at age 11, 46, 87% were in Tanner stage IV of breast development and 56.25% in Tanner stage IV for pubic hair. Conclusion: There were no alterations in pubertal development in adolescents with menstrual disorders studied.

  18. LS-SVR and AGO Based Time Series Prediction Method

    Institute of Scientific and Technical Information of China (English)

    ZHANG Shou-peng; LIU Shan; CHAI Wang-xu; ZHANG Jia-qi; GUO Yang-ming

    2016-01-01

    Recently , fault or health condition prediction of complex systems becomes an interesting research topic.However, it is difficult to establish precise physical model for complex systems , and the time series properties are often necessary to be incorporated for the prediction in practice .Currently ,the LS -SVR is widely adopted for prediction of systems with time series data .In this paper , in order to improve the prediction accuracy, accumulated generating operation (AGO) is carried out to improve the data quality and regularity of raw time series data based on grey system theory;then, the inverse accumulated generating operation ( IAGO) is performed to obtain the prediction results .In addition , due to the reason that appropriate kernel function plays an important role in improving the accuracy of prediction through LS-SVR, a modified Gaussian radial basis function (RBF) is proposed.The requirements of distance functions-based kernel functions are satisfied , which ensure fast damping at the place adjacent to the test point and a moderate damping at infinity .The presented model is applied to the analysis of benchmarks .As indicated by the results , the proposed method is an effective prediction one with good precision .

  19. Clinical time series prediction: Toward a hierarchical dynamical system framework.

    Science.gov (United States)

    Liu, Zitao; Hauskrecht, Milos

    2015-09-01

    Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. We tested our framework by first learning the time series model from data for the patients in the training set, and then using it to predict future time series values for the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive performance. Copyright © 2014 Elsevier B.V. All rights reserved.

  20. Clinical time series prediction: towards a hierarchical dynamical system framework

    Science.gov (United States)

    Liu, Zitao; Hauskrecht, Milos

    2014-01-01

    Objective Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Materials and methods Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. Results We tested our framework by first learning the time series model from data for the patient in the training set, and then applying the model in order to predict future time series values on the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. Conclusion A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive

  1. Predicting travel time variability for cost-benefit analysis

    NARCIS (Netherlands)

    Peer, S.; Koopmans, C.; Verhoef, E.T.

    2010-01-01

    Unreliable travel times cause substantial costs to travelers. Nevertheless, they are not taken into account in many cost-benefit-analyses (CBA), or only in very rough ways. This paper aims at providing simple rules on how variability can be predicted, based on travel time data from Dutch highways.

  2. Predicting travel time variability for cost-benefit analysis

    NARCIS (Netherlands)

    S. Peer; C. Koopmans; E.T. Verhoef

    2010-01-01

    Unreliable travel times cause substantial costs to travelers. Nevertheless, they are not taken into account in many cost-benefit-analyses (CBA), or only in very rough ways. This paper aims at providing simple rules on how variability can be predicted, based on travel time data from Dutch highways. T

  3. Prediction of travel time variability for cost-benefit analysis

    NARCIS (Netherlands)

    Peer, S.; Koopmans, C.C.; Verhoef, E.T.

    2012-01-01

    Unreliable travel times cause substantial costs to travelers. Nevertheless, they are often not taken into account in cost-benefit analyses (CBA), or only in very rough ways. This paper aims at providing simple rules to predict variability, based on travel time data from Dutch highways. Two different

  4. Avionics Applications on a Time-Predictable Chip-Multiprocessor

    DEFF Research Database (Denmark)

    Rocha, André; Silva, Cláudio; Sørensen, Rasmus Bo;

    2016-01-01

    Avionics applications need to be certified for the highest criticality standard. This certification includes schedulability analysis and worst-case execution time (WCET) analysis. WCET analysis is only possible when the software is written to be WCET analyzable and when the platform is time......-predictable. In this paper we present prototype avionics applications that have been ported to the time-predictable T-CREST platform. The applications are WCET analyzable, and T-CREST is supported by the aiT WCET analyzer. This combination allows us to provide WCET bounds of avionic tasks, even when executing on a multicore...

  5. The dynamics of bone structure development during pubertal growth.

    Science.gov (United States)

    Rauch, F

    2012-03-01

    The pubertal growth spurt is a time of rapid changes in bone length, mass and structure, followed by the cessation of longitudinal growth. The two best studied anatomical areas in this respect are the metaphyses and the diaphyses of peripheral long bones. A model is presented here in which the speed of longitudinal growth and the resulting age gradient in metaphyseal bone are key factors in explaining the high incidence of distal radius fractures during puberty. As growth in length accelerates, the age of the bone structural elements at a given distance to the growth plate decreases, leaving less time for cortical thickening through trabecular coalescence. This leads to a discrepancy between stagnant metaphyseal bone strength and increasing mechanical requirements in the case of accidents. In comparison to the metaphysis, diaphyseal bone develops more in line with the increasing mechanical requirements, presumably because the bone formation rates needed for diaphyseal growth in width are only a fraction of the apposition rates in the metaphysis. It remains largely unexplored how local and systemic signals are integrated to achieve site-specific changes in bone structure.

  6. Chaotic time series. Part II. System Identification and Prediction

    Directory of Open Access Journals (Sweden)

    Bjørn Lillekjendlie

    1994-10-01

    Full Text Available This paper is the second in a series of two, and describes the current state of the art in modeling and prediction of chaotic time series. Sample data from deterministic non-linear systems may look stochastic when analysed with linear methods. However, the deterministic structure may be uncovered and non-linear models constructed that allow improved prediction. We give the background for such methods from a geometrical point of view, and briefly describe the following types of methods: global polynomials, local polynomials, multilayer perceptrons and semi-local methods including radial basis functions. Some illustrative examples from known chaotic systems are presented, emphasising the increase in prediction error with time. We compare some of the algorithms with respect to prediction accuracy and storage requirements, and list applications of these methods to real data from widely different areas.

  7. Chaotic time series; 2, system identification and prediction

    CERN Document Server

    Lillekjendlie, B

    1994-01-01

    This paper is the second in a series of two, and describes the current state of the art in modelling and prediction of chaotic time series. Sampled data from deterministic non-linear systems may look stochastic when analysed with linear methods. However, the deterministic structure may be uncovered and non-linear models constructed that allow improved prediction. We give the background for such methods from a geometrical point of view, and briefly describe the following types of methods: global polynomials, local polynomials, multi layer perceptrons and semi-local methods including radial basis functions. Some illustrative examples from known chaotic systems are presented, emphasising the increase in prediction error with time. We compare some of the algorithms with respect to prediction accuracy and storage requirements, and list applications of these methods to real data from widely different areas.

  8. Financial Time Series Prediction Using Elman Recurrent Random Neural Networks

    Directory of Open Access Journals (Sweden)

    Jie Wang

    2016-01-01

    (ERNN, the empirical results show that the proposed neural network displays the best performance among these neural networks in financial time series forecasting. Further, the empirical research is performed in testing the predictive effects of SSE, TWSE, KOSPI, and Nikkei225 with the established model, and the corresponding statistical comparisons of the above market indices are also exhibited. The experimental results show that this approach gives good performance in predicting the values from the stock market indices.

  9. Model for Predicting End User Web Page Response Time

    CERN Document Server

    Nagarajan, Sathya Narayanan

    2012-01-01

    Perceived responsiveness of a web page is one of the most important and least understood metrics of web page design, and is critical for attracting and maintaining a large audience. Web pages can be designed to meet performance SLAs early in the product lifecycle if there is a way to predict the apparent responsiveness of a particular page layout. Response time of a web page is largely influenced by page layout and various network characteristics. Since the network characteristics vary widely from country to country, accurately modeling and predicting the perceived responsiveness of a web page from the end user's perspective has traditionally proven very difficult. We propose a model for predicting end user web page response time based on web page, network, browser download and browser rendering characteristics. We start by understanding the key parameters that affect perceived response time. We then model each of these parameters individually using experimental tests and statistical techniques. Finally, we d...

  10. Financial Time Series Prediction Using Elman Recurrent Random Neural Networks.

    Science.gov (United States)

    Wang, Jie; Wang, Jun; Fang, Wen; Niu, Hongli

    2016-01-01

    In recent years, financial market dynamics forecasting has been a focus of economic research. To predict the price indices of stock markets, we developed an architecture which combined Elman recurrent neural networks with stochastic time effective function. By analyzing the proposed model with the linear regression, complexity invariant distance (CID), and multiscale CID (MCID) analysis methods and taking the model compared with different models such as the backpropagation neural network (BPNN), the stochastic time effective neural network (STNN), and the Elman recurrent neural network (ERNN), the empirical results show that the proposed neural network displays the best performance among these neural networks in financial time series forecasting. Further, the empirical research is performed in testing the predictive effects of SSE, TWSE, KOSPI, and Nikkei225 with the established model, and the corresponding statistical comparisons of the above market indices are also exhibited. The experimental results show that this approach gives good performance in predicting the values from the stock market indices.

  11. HVMTP: A time predictable and portable java virtual machine for hard real-time embedded systems

    DEFF Research Database (Denmark)

    Luckow, Kasper Søe; Thomsen, Bent; Korsholm, Stephan

    2016-01-01

    We present HVMTP, a time predictable and portable Java virtual machine (JVM) implementation with applications in resource-constrained, hard real-time embedded systems, which implements all levels of the safety critical Java (SCJ) specification. Time predictability is achieved by a combination...... can be obtained using the tool TETASARTSJVM. The timing model readily integrates with the rest of the TETASARTS tool set for temporal verification of SCJ systems. We will also show how a complete timing scheme in terms of safe worst-case execution times and best-case execution times of the Java...

  12. State-based Communication on Time-predictable Multicore Processors

    DEFF Research Database (Denmark)

    Sørensen, Rasmus Bo; Schoeberl, Martin; Sparsø, Jens

    2016-01-01

    Some real-time systems use a form of task-to-task communication called state-based or sample-based communication that does not impose any flow control among the communicating tasks. The concept is similar to a shared variable, where a reader may read the same value multiple times or may not read...... a given value at all. This paper explores time-predictable implementations of state-based communication in network-on-chip based multicore platforms through five algorithms. With the presented analysis of the implemented algorithms, the communicating tasks of one core can be scheduled independently...... of tasks on other cores. Assuming a specific time-predictable multicore processor, we evaluate how the read and write primitives of the five algorithms contribute to the worst-case execution time of the communicating tasks. Each of the five algorithms has specific capabilities that make them suitable...

  13. Chaotic time series prediction and additive white Gaussian noise

    Energy Technology Data Exchange (ETDEWEB)

    Lim, Teck Por [Department of Mathematics, 6M30 Huxley, Imperial College London, 180 Queen' s Gate, London, SW7 2BZ (United Kingdom)]. E-mail: teckpor@gmail.com; Puthusserypady, Sadasivan [Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, Singapore 117576 (Singapore)]. E-mail: elespk@nus.edu.sg

    2007-06-04

    Taken's delay embedding theorem states that a pseudo state-space can be reconstructed from a time series consisting of observations of a chaotic process. However, experimental observations are inevitably corrupted by measurement noise, which can be modelled as Additive White Gaussian Noise (AWGN). This Letter analyses time series prediction in the presence of AWGN using the triangle inequality and the mean of the Nakagami distribution. It is shown that using more delay coordinates than those used by a typical delay embedding can improve prediction accuracy, when the mean magnitude of the input vector dominates the mean magnitude of AWGN.

  14. Local dimension and finite time prediction in coupled map lattices

    Indian Academy of Sciences (India)

    P Muruganandam; G Francisco

    2005-03-01

    Forecasting, for obvious reasons, often become the most important goal to be achieved. For spatially extended systems (e.g. atmospheric system) where the local nonlinearities lead to the most unpredictable chaotic evolution, it is highly desirable to have a simple diagnostic tool to identify regions of predictable behaviour. In this paper, we discuss the use of the bred vector (BV) dimension, a recently introduced statistics, to identify the regimes where a finite time forecast is feasible. Using the tools from dynamical systems theory and Bayesian modelling, we show the finite time predictability in two-dimensional coupled map lattices in the regions of low BV dimension.

  15. Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

    Science.gov (United States)

    Lee, Hanbong

    2016-01-01

    Accurate taxi time prediction is required for enabling efficient runway scheduling that can increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. Currently NASA and American Airlines are jointly developing a decision-support tool called Spot and Runway Departure Advisor (SARDA) that assists airport ramp controllers to make gate pushback decisions and improve the overall efficiency of airport surface traffic. In this presentation, we propose to use Linear Optimized Sequencing (LINOS), a discrete-event fast-time simulation tool, to predict taxi times and provide the estimates to the runway scheduler in real-time airport operations. To assess its prediction accuracy, we also introduce a data-driven analytical method using machine learning techniques. These two taxi time prediction methods are evaluated with actual taxi time data obtained from the SARDA human-in-the-loop (HITL) simulation for Charlotte Douglas International Airport (CLT) using various performance measurement metrics. Based on the taxi time prediction results, we also discuss how the prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast time simulation model before implementing it with an airport scheduling algorithm in a real-time environment.

  16. Two leptin genes and a leptin receptor gene of female chub mackerel (Scomber japonicus): Molecular cloning, tissue distribution and expression in different obesity indices and pubertal stages.

    Science.gov (United States)

    Ohga, Hirofumi; Matsumori, Kojiro; Kodama, Ryoko; Kitano, Hajime; Nagano, Naoki; Yamaguchi, Akihiko; Matsuyama, Michiya

    2015-10-01

    Leptin is a hormone produced by fat cells that regulates the amount of fat stored in the body and conveys nutritional status to the reproductive axis in mammals. In the present study we identified two subtypes of leptin genes (lepa and lepb) and a leptin receptor gene (lepr) from chub mackerel (Scomber japonicus) and there gene expression under different feeding conditions (control and high-feed) and pubertal development stages was analyzed using quantitative real-time PCR. The protein lengths of LepA, LepB and LepR were 161 amino acids (aa), 163 aa and 1149 aa, respectively and both leptin subtypes shared only 15% similarity in aa sequences. In pubertal females, lepa was expressed in the brain, pituitary gland, liver, adipose tissue and ovary; however, in adult (gonadal maturation after the second in the life) females, lepa was expressed only in the liver. lepb was expressed primarily in the brain of all fish tested and was expressed strongly in the adipose tissue of adults. lepr was characterized by expression in the pituitary. The high-feed group showed a high conditioning factor level; unexpectedly, hepatic lepa and brain lepr were significantly more weakly expressed compared with the control-feed group. Furthermore, the expression levels of lepa, lepb and lepr genes showed no significant differences between pre-pubertal and post-pubertal fish. On the other hand, pituitary fshβ and lhβ showed no significant differences between different feeding groups of pre-pubertal fish. In contrast, fshβ and lhβ expressed abundantly in the post-pubertal fish of control feed group. Based on these results, whether leptin plays an important role in the nutritional status and pubertal onset of chub mackerel remains unknown.

  17. Time-To-Complete Prediction for Data Transfers

    CERN Document Server

    Toler, Wesley

    2016-01-01

    Currently, there is no prediction provided to users for the amount of time a particular data transfer from one site in the Worldwide LHC Computing Grid to another will take to complete. To develop a time-to-complete prediction, network performance data and per-file information is gathered from two separate databases and fused, and the resulting cleaned data is fitted using random forest regression. Results are shown for two separate links: the link from CERN Data Centre to Brookhaven National Laboratory’s ATLAS data center, and the link from CERN Data Centre to SARA-MATRIX in Amsterdam. A total RMS error of 25.93 minutes between predicted and test data is found for the CERN-PROD -> BNL-ATLAS link, while the CERN-PROD -> SARA-MATRIX link yields a total RMS error of 3.00 minutes.

  18. The pattern of cognitive symptoms predicts time to dementia onset.

    NARCIS (Netherlands)

    Sacuiu, S.; Gustafson, D.; Johansson, B.; Thorvaldsson, V.; Berg, S.; Sjogren, J.M.C.; Guo, X.; Ostling, S.; Skoog, I.

    2009-01-01

    BACKGROUND: Few studies have examined whether cognitive symptom patterns differ by age and length of time before dementia onset. Our objective was to investigate whether different patterns of cognitive symptoms at ages 70, 75, and 79 years predict short-term (< or =5 years) and long-term (>5 y

  19. Long-term time series prediction using OP-ELM.

    Science.gov (United States)

    Grigorievskiy, Alexander; Miche, Yoan; Ventelä, Anne-Mari; Séverin, Eric; Lendasse, Amaury

    2014-03-01

    In this paper, an Optimally Pruned Extreme Learning Machine (OP-ELM) is applied to the problem of long-term time series prediction. Three known strategies for the long-term time series prediction i.e. Recursive, Direct and DirRec are considered in combination with OP-ELM and compared with a baseline linear least squares model and Least-Squares Support Vector Machines (LS-SVM). Among these three strategies DirRec is the most time consuming and its usage with nonlinear models like LS-SVM, where several hyperparameters need to be adjusted, leads to relatively heavy computations. It is shown that OP-ELM, being also a nonlinear model, allows reasonable computational time for the DirRec strategy. In all our experiments, except one, OP-ELM with DirRec strategy outperforms the linear model with any strategy. In contrast to the proposed algorithm, LS-SVM behaves unstably without variable selection. It is also shown that there is no superior strategy for OP-ELM: any of three can be the best. In addition, the prediction accuracy of an ensemble of OP-ELM is studied and it is shown that averaging predictions of the ensemble can improve the accuracy (Mean Square Error) dramatically. Copyright © 2013 Elsevier Ltd. All rights reserved.

  20. The pattern of cognitive symptoms predicts time to dementia onset.

    NARCIS (Netherlands)

    Sacuiu, S.; Gustafson, D.; Johansson, B.; Thorvaldsson, V.; Berg, S.; Sjogren, J.M.C.; Guo, X.; Ostling, S.; Skoog, I.

    2009-01-01

    BACKGROUND: Few studies have examined whether cognitive symptom patterns differ by age and length of time before dementia onset. Our objective was to investigate whether different patterns of cognitive symptoms at ages 70, 75, and 79 years predict short-term (< or =5 years) and long-term (>5 y

  1. The pattern of cognitive symptoms predicts time to dementia onset.

    NARCIS (Netherlands)

    Sacuiu, S.; Gustafson, D.; Johansson, B.; Thorvaldsson, V.; Berg, S.; Sjogren, J.M.C.; Guo, X.; Ostling, S.; Skoog, I.

    2009-01-01

    BACKGROUND: Few studies have examined whether cognitive symptom patterns differ by age and length of time before dementia onset. Our objective was to investigate whether different patterns of cognitive symptoms at ages 70, 75, and 79 years predict short-term (< or =5 years) and long-term (>5

  2. Time-varying Combinations of Predictive Densities using Nonlinear Filtering

    NARCIS (Netherlands)

    M. Billio (Monica); R. Casarin (Roberto); F. Ravazzolo (Francesco); H.K. van Dijk (Herman)

    2012-01-01

    textabstractWe propose a Bayesian combination approach for multivariate predictive densities which relies upon a distributional state space representation of the combination weights. Several specifications of multivariate time-varying weights are introduced with a particular focus on weight dynamics

  3. Skin surface lipid composition, acne, pubertal development, and urinary excretion of testosterone and 17-ketosteroids in children.

    Science.gov (United States)

    Pochi, P E; Strauss, J S; Downing, D T

    1977-11-01

    Fifty-two children, age 5-10, from acne-prone families, were studied for a period of 1 year to examine the interrelationship between sebum, acne, pubertal development, and urinary steroid excretion. In each of the subjects, 30 boys and 22 girls, the composition of forehead skin lipid was determined 4 times yearly by thin-layer chromatography, with measurement of triglycerides, diglycerides, free fatty acids, wax esters, squalene, cholesterol, and cholesterol esters. Twice yearly, examination was made of the presence or absence of acne, pubertal maturation and the 24-hour urinary excretion of testosterone as determined by radioimmunnoassay, and of total 17-ketosteroids, dehydroepiandrosterone, androsterone, and etiocholanolone, as determined by paper chromatography. The relative amount of sebaceous lipids was positively correlated with age of the subjects (wax esters p less than .001, squalene p less than .05), as was the triglyceride-diglyceride component (p less than .05). No significant correlation was seen with the fatty acids. Acne, primarily comedonal, occurred in 27/52 subjects (15 girls, 12 boys) and was associated with higher sebum values. One-half of the children with acne had no signs of pubertal development. A significantly positive correlation was observed between the relative amount of sebaceous lipid and the urinary excretion of 17-ketosteroids, androsterone, and etiocholanolone in both sexes, and of testosterone and dehydroepiandrosterone in boys. The development of acne in children is an early pubertal event, often evident before other signs of pubertal maturation, and it is associated with an increase in sebum and in the urinary excretion of androgenic steroids.

  4. Support for the Logical Execution Time Model on a Time-predictable Multicore Processor

    DEFF Research Database (Denmark)

    Kluge, Florian; Schoeberl, Martin; Ungerer, Theo

    2016-01-01

    The logical execution time (LET) model increases the compositionality of real-time task sets. Removal or addition of tasks does not influence the communication behavior of other tasks. In this work, we extend a multicore operating system running on a time-predictable multicore processor to support...... the LET model. For communication between tasks we use message passing on a time-predictable network-on-chip to avoid the bottleneck of shared memory. We report our experiences and present results on the costs in terms of memory and execution time....

  5. Individual differences in time perspective predict autonoetic experience.

    Science.gov (United States)

    Arnold, Kathleen M; McDermott, Kathleen B; Szpunar, Karl K

    2011-09-01

    Tulving (1985) posited that the capacity to remember is one facet of a more general capacity-autonoetic (self-knowing) consciousness. Autonoetic consciousness was proposed to underlie the ability for "mental time travel" both into the past (remembering) and into the future to envision potential future episodes (episodic future thinking). The current study examines whether individual differences can predict autonoetic experience. Specifically, the Zimbardo Time Perspective Inventory (ZTPI, Zimbardo & Boyd, 1999) was administered to 133 undergraduate students, who also rated phenomenological experiences accompanying autobiographical remembering and episodic future thinking. Scores on two of the five subscales of the ZTPI (Future and Present-Hedonistic) predicted the degree to which people reported feelings of mentally traveling backward (or forward) in time and the degree to which they reported re- or pre-experiencing the event, but not ten other rated properties less related to autonoetic consciousness.

  6. Traffic Prediction Based on SVM Training Sample Divided by Time

    Directory of Open Access Journals (Sweden)

    Lingli Li

    2013-07-01

    Full Text Available In recent years, the volume of traffic is rapidly increasing. When vehicles running through the tunnel are more intensive or move slowly, the tunnel environment occurs deteriorated sharply, which affects the normal operation of the vehicle in the tunnel. This paper uses the result of previous mining association rules to select feature items and to establish four training samples divided by time. Then the training samples are utilized to create the SVM classification model. Finally the trained SVM model is used to prediction the tunnel traffic situation. Through traffic situation prediction, effective decisions can be made before traffic jams, and ensure that the tunnel traffic is normal.  

  7. The neural substrate of predictive motor timing in spinocerebellar ataxia.

    Science.gov (United States)

    Bares, Martin; Lungu, Ovidiu V; Liu, Tao; Waechter, Tobias; Gomez, Christopher M; Ashe, James

    2011-06-01

    The neural mechanisms involved in motor timing are subcortical, involving mainly cerebellum and basal ganglia. However, the role played by these structures in predictive motor timing is not well understood. Unlike motor timing, which is often tested using rhythm production tasks, predictive motor timing requires visuo-motor coordination in anticipation of a future event, and it is evident in behaviors such as catching a ball or shooting a moving target. We examined the role of the cerebellum and striatum in predictive motor timing in a target interception task in healthy (n = 12) individuals and in subjects (n = 9) with spinocerebellar ataxia types 6 and 8. The performance of the healthy subjects was better than that of the spinocerebellar ataxia. Successful performance in both groups was associated with increased activity in the cerebellum (right dentate nucleus, left uvula (lobule V), and lobule VI), thalamus, and in several cortical areas. The superior performance in the controls was related to activation in thalamus, putamen (lentiform nucleus) and cerebellum (right dentate nucleus and culmen-lobule IV), which were not activated either in the spinocerebellar subjects or within a subgroup of controls who performed poorly. Both the cerebellum and the basal ganglia are necessary for the predictive motor timing. The degeneration of the cerebellum associated with spinocerebellar types 6 and 8 appears to lead to quantitative rather than qualitative deficits in temporal processing. The lack of any areas with greater activity in the spinocerebellar group than in controls suggests that limited functional reorganization occurs in this condition.

  8. Traffic Incident Clearance Time and Arrival Time Prediction Based on Hazard Models

    Directory of Open Access Journals (Sweden)

    Yang beibei Ji

    2014-01-01

    Full Text Available Accurate prediction of incident duration is not only important information of Traffic Incident Management System, but also an effective input for travel time prediction. In this paper, the hazard based prediction models are developed for both incident clearance time and arrival time. The data are obtained from the Queensland Department of Transport and Main Roads’ STREAMS Incident Management System (SIMS for one year ending in November 2010. The best fitting distributions are drawn for both clearance and arrival time for 3 types of incident: crash, stationary vehicle, and hazard. The results show that Gamma, Log-logistic, and Weibull are the best fit for crash, stationary vehicle, and hazard incident, respectively. The obvious impact factors are given for crash clearance time and arrival time. The quantitative influences for crash and hazard incident are presented for both clearance and arrival. The model accuracy is analyzed at the end.

  9. Predicting Time Series Outputs and Time-to-Failure for an Aircraft Controller Using Bayesian Modeling

    Science.gov (United States)

    He, Yuning

    2015-01-01

    Safety of unmanned aerial systems (UAS) is paramount, but the large number of dynamically changing controller parameters makes it hard to determine if the system is currently stable, and the time before loss of control if not. We propose a hierarchical statistical model using Treed Gaussian Processes to predict (i) whether a flight will be stable (success) or become unstable (failure), (ii) the time-to-failure if unstable, and (iii) time series outputs for flight variables. We first classify the current flight input into success or failure types, and then use separate models for each class to predict the time-to-failure and time series outputs. As different inputs may cause failures at different times, we have to model variable length output curves. We use a basis representation for curves and learn the mappings from input to basis coefficients. We demonstrate the effectiveness of our prediction methods on a NASA neuro-adaptive flight control system.

  10. Model predictive control of P-time event graphs

    Science.gov (United States)

    Hamri, H.; Kara, R.; Amari, S.

    2016-12-01

    This paper deals with model predictive control of discrete event systems modelled by P-time event graphs. First, the model is obtained by using the dater evolution model written in the standard algebra. Then, for the control law, we used the finite-horizon model predictive control. For the closed-loop control, we used the infinite-horizon model predictive control (IH-MPC). The latter is an approach that calculates static feedback gains which allows the stability of the closed-loop system while respecting the constraints on the control vector. The problem of IH-MPC is formulated as a linear convex programming subject to a linear matrix inequality problem. Finally, the proposed methodology is applied to a transportation system.

  11. Time Series Outlier Detection Based on Sliding Window Prediction

    Directory of Open Access Journals (Sweden)

    Yufeng Yu

    2014-01-01

    Full Text Available In order to detect outliers in hydrological time series data for improving data quality and decision-making quality related to design, operation, and management of water resources, this research develops a time series outlier detection method for hydrologic data that can be used to identify data that deviate from historical patterns. The method first built a forecasting model on the history data and then used it to predict future values. Anomalies are assumed to take place if the observed values fall outside a given prediction confidence interval (PCI, which can be calculated by the predicted value and confidence coefficient. The use of PCI as threshold is mainly on the fact that it considers the uncertainty in the data series parameters in the forecasting model to address the suitable threshold selection problem. The method performs fast, incremental evaluation of data as it becomes available, scales to large quantities of data, and requires no preclassification of anomalies. Experiments with different hydrologic real-world time series showed that the proposed methods are fast and correctly identify abnormal data and can be used for hydrologic time series analysis.

  12. Metabolic Syndrome in Children and Adolescents: a Critical Approach Considering the Interaction between Pubertal Stage and Insulin Resistance.

    Science.gov (United States)

    Reinehr, Thomas

    2016-01-01

    Pediatricians increasingly diagnose the metabolic syndrome (MetS) in recent years to describe cardiovascular risk and to guide management of the obese child. However, there is an ongoing discussion about how to define the MetS in childhood and adolescence. Since insulin resistance-the major driver of MetS-is influenced by pubertal stage, it is questionable to use definitions for MetS in children and adolescents that do not take into account pubertal status. A metabolic healthy status in prepubertal stage does not predict a metabolic healthy status during puberty. Furthermore, cardiovascular risk factors improve at the end of puberty without treatment. However, having a uniform internationally accepted definition of the MetS for children and adolescents would be very helpful for the description of populations in different studies. Therefore, the concept of MetS has to be revisited under the influence of puberty stage.

  13. Robust Continuous-time Generalized Predictive Control for Large Time-delay System

    Institute of Scientific and Technical Information of China (English)

    WEI Huan; PAN Li-deng; ZHEN Xin-ping

    2008-01-01

    A simple delay-predictive continuous-time generalized predictive controller with filter (F - SDCGPC) is proposed. By using modified predictive output signal and cost function, the delay compensator is incorporated in the control law with observer structure, and a filter is added for enhancing robustness. The design of filter does not affect the nominal set-point response, and it is more flexible than the design of observer polynomial. The analysis and simulation results show that the F - SDCGPC has better robustness than the observer structure without filter when large time-delay error is considered.

  14. Optimal model-free prediction from multivariate time series.

    Science.gov (United States)

    Runge, Jakob; Donner, Reik V; Kurths, Jürgen

    2015-05-01

    Forecasting a time series from multivariate predictors constitutes a challenging problem, especially using model-free approaches. Most techniques, such as nearest-neighbor prediction, quickly suffer from the curse of dimensionality and overfitting for more than a few predictors which has limited their application mostly to the univariate case. Therefore, selection strategies are needed that harness the available information as efficiently as possible. Since often the right combination of predictors matters, ideally all subsets of possible predictors should be tested for their predictive power, but the exponentially growing number of combinations makes such an approach computationally prohibitive. Here a prediction scheme that overcomes this strong limitation is introduced utilizing a causal preselection step which drastically reduces the number of possible predictors to the most predictive set of causal drivers making a globally optimal search scheme tractable. The information-theoretic optimality is derived and practical selection criteria are discussed. As demonstrated for multivariate nonlinear stochastic delay processes, the optimal scheme can even be less computationally expensive than commonly used suboptimal schemes like forward selection. The method suggests a general framework to apply the optimal model-free approach to select variables and subsequently fit a model to further improve a prediction or learn statistical dependencies. The performance of this framework is illustrated on a climatological index of El Niño Southern Oscillation.

  15. Predicting Physical Time Series Using Dynamic Ridge Polynomial Neural Networks

    Science.gov (United States)

    Al-Jumeily, Dhiya; Ghazali, Rozaida; Hussain, Abir

    2014-01-01

    Forecasting naturally occurring phenomena is a common problem in many domains of science, and this has been addressed and investigated by many scientists. The importance of time series prediction stems from the fact that it has wide range of applications, including control systems, engineering processes, environmental systems and economics. From the knowledge of some aspects of the previous behaviour of the system, the aim of the prediction process is to determine or predict its future behaviour. In this paper, we consider a novel application of a higher order polynomial neural network architecture called Dynamic Ridge Polynomial Neural Network that combines the properties of higher order and recurrent neural networks for the prediction of physical time series. In this study, four types of signals have been used, which are; The Lorenz attractor, mean value of the AE index, sunspot number, and heat wave temperature. The simulation results showed good improvements in terms of the signal to noise ratio in comparison to a number of higher order and feedforward neural networks in comparison to the benchmarked techniques. PMID:25157950

  16. Financial time series prediction using spiking neural networks.

    Science.gov (United States)

    Reid, David; Hussain, Abir Jaafar; Tawfik, Hissam

    2014-01-01

    In this paper a novel application of a particular type of spiking neural network, a Polychronous Spiking Network, was used for financial time series prediction. It is argued that the inherent temporal capabilities of this type of network are suited to non-stationary data such as this. The performance of the spiking neural network was benchmarked against three systems: two "traditional", rate-encoded, neural networks; a Multi-Layer Perceptron neural network and a Dynamic Ridge Polynomial neural network, and a standard Linear Predictor Coefficients model. For this comparison three non-stationary and noisy time series were used: IBM stock data; US/Euro exchange rate data, and the price of Brent crude oil. The experiments demonstrated favourable prediction results for the Spiking Neural Network in terms of Annualised Return and prediction error for 5-Step ahead predictions. These results were also supported by other relevant metrics such as Maximum Drawdown and Signal-To-Noise ratio. This work demonstrated the applicability of the Polychronous Spiking Network to financial data forecasting and this in turn indicates the potential of using such networks over traditional systems in difficult to manage non-stationary environments.

  17. Financial time series prediction using spiking neural networks.

    Directory of Open Access Journals (Sweden)

    David Reid

    Full Text Available In this paper a novel application of a particular type of spiking neural network, a Polychronous Spiking Network, was used for financial time series prediction. It is argued that the inherent temporal capabilities of this type of network are suited to non-stationary data such as this. The performance of the spiking neural network was benchmarked against three systems: two "traditional", rate-encoded, neural networks; a Multi-Layer Perceptron neural network and a Dynamic Ridge Polynomial neural network, and a standard Linear Predictor Coefficients model. For this comparison three non-stationary and noisy time series were used: IBM stock data; US/Euro exchange rate data, and the price of Brent crude oil. The experiments demonstrated favourable prediction results for the Spiking Neural Network in terms of Annualised Return and prediction error for 5-Step ahead predictions. These results were also supported by other relevant metrics such as Maximum Drawdown and Signal-To-Noise ratio. This work demonstrated the applicability of the Polychronous Spiking Network to financial data forecasting and this in turn indicates the potential of using such networks over traditional systems in difficult to manage non-stationary environments.

  18. Predicting physical time series using dynamic ridge polynomial neural networks.

    Directory of Open Access Journals (Sweden)

    Dhiya Al-Jumeily

    Full Text Available Forecasting naturally occurring phenomena is a common problem in many domains of science, and this has been addressed and investigated by many scientists. The importance of time series prediction stems from the fact that it has wide range of applications, including control systems, engineering processes, environmental systems and economics. From the knowledge of some aspects of the previous behaviour of the system, the aim of the prediction process is to determine or predict its future behaviour. In this paper, we consider a novel application of a higher order polynomial neural network architecture called Dynamic Ridge Polynomial Neural Network that combines the properties of higher order and recurrent neural networks for the prediction of physical time series. In this study, four types of signals have been used, which are; The Lorenz attractor, mean value of the AE index, sunspot number, and heat wave temperature. The simulation results showed good improvements in terms of the signal to noise ratio in comparison to a number of higher order and feedforward neural networks in comparison to the benchmarked techniques.

  19. Techniques for building timing-predictable embedded systems

    CERN Document Server

    Guan, Nan

    2016-01-01

    This book describes state-of-the-art techniques for designing real-time computer systems. The author shows how to estimate precisely the effect of cache architecture on the execution time of a program, how to dispatch workload on multicore processors to optimize resources, while meeting deadline constraints, and how to use closed-form mathematical approaches to characterize highly variable workloads and their interaction in a networked environment. Readers will learn how to deal with unpredictable timing behaviors of computer systems on different levels of system granularity and abstraction. Introduces promising techniques for dealing with challenges associated with deploying real-time systems on multicore platforms; Provides a complete picture of building timing-predictable computer systems, at the program level, component level and system level; Leverages different levels of abstraction to deal with the complexity of the analysis.

  20. Serum inhibin B in healthy pubertal and adolescent boys

    DEFF Research Database (Denmark)

    Andersson, A M; Juul, A; Petersen, J H;

    1997-01-01

    Inhibin B levels were measured in serum from 400 healthy Danish prepubertal, pubertal, and adolescent males, aged 6-20 yr, in a cross-sectional study using a recently developed immunoassay that is specific for inhibin B, the physiologically important inhibin form in men. In addition, serum levels...

  1. Validity of self-assessment of pubertal maturation

    DEFF Research Database (Denmark)

    Rasmussen, Anna; Wohlfahrt-Veje, Christine; Tefre de Renzy-Martin, Katrine;

    2015-01-01

    BACKGROUND AND OBJECTIVES: Studies of adolescents often use self-assessment of pubertal maturation, the reliability of which has shown conflicting results. We aimed to examine the reliability of child and parent assessments of healthy boys and girls. METHODS: A total of 898 children (418 girls, 480...

  2. Radial basis function network design for chaotic time series prediction

    Energy Technology Data Exchange (ETDEWEB)

    Shin, Chang Yong; Kim, Taek Soo; Park, Sang Hui [Yonsei University, Seoul (Korea, Republic of); Choi, Yoon Ho [Kyonggi University, Suwon (Korea, Republic of)

    1996-04-01

    In this paper, radial basis function networks with two hidden layers, which employ the K-means clustering method and the hierarchical training, are proposed for improving the short-term predictability of chaotic time series. Furthermore the recursive training method of radial basis function network using the recursive modified Gram-Schmidt algorithm is proposed for the purpose. In addition, the radial basis function networks trained by the proposed training methods are compared with the X.D. He A Lapedes`s model and the radial basis function network by non-recursive training method. Through this comparison, an improved radial basis function network for predicting chaotic time series is presented. (author). 17 refs., 8 figs., 3 tabs.

  3. Earthquake prediction in Japan and natural time analysis of seismicity

    Science.gov (United States)

    Uyeda, S.; Varotsos, P.

    2011-12-01

    M9 super-giant earthquake with huge tsunami devastated East Japan on 11 March, causing more than 20,000 casualties and serious damage of Fukushima nuclear plant. This earthquake was predicted neither short-term nor long-term. Seismologists were shocked because it was not even considered possible to happen at the East Japan subduction zone. However, it was not the only un-predicted earthquake. In fact, throughout several decades of the National Earthquake Prediction Project, not even a single earthquake was predicted. In reality, practically no effective research has been conducted for the most important short-term prediction. This happened because the Japanese National Project was devoted for construction of elaborate seismic networks, which was not the best way for short-term prediction. After the Kobe disaster, in order to parry the mounting criticism on their no success history, they defiantly changed their policy to "stop aiming at short-term prediction because it is impossible and concentrate resources on fundamental research", that meant to obtain "more funding for no prediction research". The public were and are not informed about this change. Obviously earthquake prediction would be possible only when reliable precursory phenomena are caught and we have insisted this would be done most likely through non-seismic means such as geochemical/hydrological and electromagnetic monitoring. Admittedly, the lack of convincing precursors for the M9 super-giant earthquake has adverse effect for us, although its epicenter was far out off shore of the range of operating monitoring systems. In this presentation, we show a new possibility of finding remarkable precursory signals, ironically, from ordinary seismological catalogs. In the frame of the new time domain termed natural time, an order parameter of seismicity, κ1, has been introduced. This is the variance of natural time kai weighted by normalised energy release at χ. In the case that Seismic Electric Signals

  4. State Predictive Model Following Control System for Linear Time Delays

    Institute of Scientific and Technical Information of China (English)

    Da-Zhong Wang; Shu-Jing Wu; Shigenori Okubo

    2009-01-01

    In this paper, we propose a new state predictive model following control system (MFCS). The considered system has linear time delays. With the MFCS method, we obtain a simple input control law. The bounded property of the internal states for the control is given and the utility of this control design is guaranteed. Finally, an example is given to illustrate the effectiveness of the proposed method.

  5. Model for Predicting End User Web Page Response Time

    OpenAIRE

    Nagarajan, Sathya Narayanan; Ravikumar, Srijith

    2012-01-01

    Perceived responsiveness of a web page is one of the most important and least understood metrics of web page design, and is critical for attracting and maintaining a large audience. Web pages can be designed to meet performance SLAs early in the product lifecycle if there is a way to predict the apparent responsiveness of a particular page layout. Response time of a web page is largely influenced by page layout and various network characteristics. Since the network characteristics vary widely...

  6. Tests of equal predictive ability with real-time data

    OpenAIRE

    Todd E. Clark; Michael W. McCracken

    2008-01-01

    This paper examines the asymptotic and finite-sample properties of tests of equal forecast accuracy applied to direct, multi-step predictions from both non-nested and nested linear regression models. In contrast to earlier work -- including West (1996), Clark and McCracken (2001, 2005),and McCracken (2006) -- our asymptotics take account of the real-time, revised nature of the data. Monte Carlo simulations indicate that our asymptotic approximations yield reasonable size and power properties ...

  7. Putative effects of endocrine disrupters on pubertal development in the human

    DEFF Research Database (Denmark)

    Teilmann, Grete; Juul, Anders; Skakkebaek, Niels E

    2002-01-01

    Pubertal development is regulated by gonadotrophins and sex hormones. There has been a clear secular trend in the timing of puberty during the last century, puberty becoming earlier. Although improved nutrition is assumed to be the cause, this could partly be associated with exposure to so......-called endocrine disrupters. Precocious puberty has been described in several case reports of accidental exposure to oestrogenic compounds in cosmetic products, food and pharmaceuticals. Local epidemics of premature thelarche have also been suggested to be linked to endocrine disrupters. Children adopted from...

  8. Time series prediction of mining subsidence based on a SVM

    Institute of Scientific and Technical Information of China (English)

    Li Peixian; Tan Zhixiang; Yah Lili; Deng Kazhong

    2011-01-01

    In order to study dynamic laws of surface movements over coal mines due to mining activities,a dynamic prediction model of surface movements was established,based on the theory of support vector machines (SVM) and times-series analysis.An engineering application was used to verify the correctness of the model.Measurements from observation stations were analyzed and processed to obtain equal-time interval surface movement data and subjected to tests of stationary,zero means and normality.Then the data were used to train the SVM model.A time series model was established to predict mining subsidence by rational choices of embedding dimensions and SVM parameters.MAPE and WIA were used asindicators to evaluate the accuracy of the model and for generalization performance.In the end,the model was used to predict future surface movements.Data from observation stations in Huaibei coal mining area were used as an example.The results show that the maximum absolute error of subsidence is 9 mm,the maximum relative error 1.5%.the maximum absolute error of displacement 7 mm and the maximum relative error 1.8%.The accuracy and reliability of the model meet the requirements of on-site engineering.The results of the study provide a new approach to investigate the dynamics of surface movements.

  9. NMR-based metabolomic profiling of overweight adolescents – an elucidation of the effects of inter-/intra-individual differences, gender, pubertal development and physical activity

    DEFF Research Database (Denmark)

    Zheng, Hong; Yde, Christian Clement; Arnberg, Karina;

    2014-01-01

    The plasma and urine metabolome of 192 overweight 12-15-year-old adolescents (BMI of 25.4 ± 2.3 kg/m(2)) were examined in order to elucidate gender, pubertal development measured as Tanner stage, physical activity measured as number of steps taken daily, and intra-/interindividual differences...... in the metabolome are being commenced already in childhood. The relationship between Tanner stage and the metabolome showed that pubertal development stage was positively related to urinary creatinine excretion and negatively related to urinary citrate content. No relations between physical activity...... and the metabolome could be identified. The present study for the first time provides comprehensive information about associations between the metabolome and gender, pubertal development, and physical activity in overweight adolescents, which is an important subject group to approach in the prevention of obesity...

  10. On Prediction of Depreciation Time of Fossil Fuel in Malaysia

    Directory of Open Access Journals (Sweden)

    Tey Jin Pin

    2012-01-01

    Full Text Available Problem statement: The fossil fuels play a crucial role in the world energy markets. Demand for fossil fuels become increasingly high and worrisome, because of fossil fuels will be significantly reduced and ultimately exhausted. This study was conducted to predict the depreciation time of fossil fuels in Malaysia and estimate the time remaining before the fossil fuels will finish. Approach: To predict the depreciation time of fossil fuels, the reserves, consumption and prices of fossil fuel will be used. The prediction of fossil fuel reserves were estimated using ratio of fossil fuel reserve versus consumption, Klass Model and Modified Klass Model. The prediction time will give us the opportunity to prepare for the coming energy crisis and discover new energy sources. The results from the analysis will be concluded alongside with the Olduvai Theory and Hubbert Peak Theory. Both of the theories are highly related to the energy crisis. The Olduvai Theory states that the industrial civilization will last for approximately 100 year: circa 1930-2030. As for Hubbert Peak Theory, it can estimate the total amount of fossil fuels available based on the production rate from time to time. Results: Due to the vast usage of petroleum, it will be depleted faster than natural gas and coal. After 14 years, natural gas and coal will replace petroleum as a fossil fuel and coal would then be the major fossil fuels. Based on the results from Hubbert Peak Theory, the rate of production of petroleum has reached the maximum level in 2004 and started to decline since that time; while in the Olduvai theory, it has explained that the life expectancy of the industrial civilization was found to be ended in 2030. Petroleum will be spent over in 2020, followed by natural gas in 2058 and coal around the year 2066. Conclusion: So far, Malaysia has not facing disconnection of electricity as other developed countries. When this happens, it gives the meaning of the end of the

  11. Chaos Time Series Prediction Based on Membrane Optimization Algorithms

    Directory of Open Access Journals (Sweden)

    Meng Li

    2015-01-01

    Full Text Available This paper puts forward a prediction model based on membrane computing optimization algorithm for chaos time series; the model optimizes simultaneously the parameters of phase space reconstruction (τ,m and least squares support vector machine (LS-SVM (γ,σ by using membrane computing optimization algorithm. It is an important basis for spectrum management to predict accurately the change trend of parameters in the electromagnetic environment, which can help decision makers to adopt an optimal action. Then, the model presented in this paper is used to forecast band occupancy rate of frequency modulation (FM broadcasting band and interphone band. To show the applicability and superiority of the proposed model, this paper will compare the forecast model presented in it with conventional similar models. The experimental results show that whether single-step prediction or multistep prediction, the proposed model performs best based on three error measures, namely, normalized mean square error (NMSE, root mean square error (RMSE, and mean absolute percentage error (MAPE.

  12. Linear and nonlinear dynamic systems in financial time series prediction

    Directory of Open Access Journals (Sweden)

    Salim Lahmiri

    2012-10-01

    Full Text Available Autoregressive moving average (ARMA process and dynamic neural networks namely the nonlinear autoregressive moving average with exogenous inputs (NARX are compared by evaluating their ability to predict financial time series; for instance the S&P500 returns. Two classes of ARMA are considered. The first one is the standard ARMA model which is a linear static system. The second one uses Kalman filter (KF to estimate and predict ARMA coefficients. This model is a linear dynamic system. The forecasting ability of each system is evaluated by means of mean absolute error (MAE and mean absolute deviation (MAD statistics. Simulation results indicate that the ARMA-KF system performs better than the standard ARMA alone. Thus, introducing dynamics into the ARMA process improves the forecasting accuracy. In addition, the ARMA-KF outperformed the NARX. This result may suggest that the linear component found in the S&P500 return series is more dominant than the nonlinear part. In sum, we conclude that introducing dynamics into the ARMA process provides an effective system for S&P500 time series prediction.

  13. Two-parameter Failure Model Improves Time-independent and Time-dependent Failure Predictions

    Energy Technology Data Exchange (ETDEWEB)

    Huddleston, R L

    2004-01-27

    A new analytical model for predicting failure under a generalized, triaxial stress state was developed by the author and initially reported in 1984. The model was validated for predicting failure under elevated-temperature creep-rupture conditions. Biaxial data for three alloy steels, Types 304 and 316 stainless steels and Inconel 600, demonstrated two to three orders of magnitude reduction in the scatter of predicted versus observed creep-rupture times as compared to the classical failure models of Mises, Tresca, and Rankine. In 1990, the new model was incorporated into American Society of Mechanical Engineers (ASME) Code Case N47-29 for design of components operating under creep-rupture conditions. The current report provides additional validation of the model for predicting failure under time-independent conditions and also outlines a methodology for predicting failure under cyclic, time-dependent, creep-fatigue conditions. The later extension of the methodology may have the potential to improve failure predictions there as well. These results are relevant to most design applications, but they have special relevance to high-performance design applications such as components for high-pressure equipment, nuclear reactors, and jet engines.

  14. Two-parameter Failure Model Improves Time-independent and Time-dependent Failure Predictions

    Energy Technology Data Exchange (ETDEWEB)

    Huddleston, R L

    2004-01-27

    A new analytical model for predicting failure under a generalized, triaxial stress state was developed by the author and initially reported in 1984. The model was validated for predicting failure under elevated-temperature creep-rupture conditions. Biaxial data for three alloy steels, Types 304 and 316 stainless steels and Inconel 600, demonstrated two to three orders of magnitude reduction in the scatter of predicted versus observed creep-rupture times as compared to the classical failure models of Mises, Tresca, and Rankine. In 1990, the new model was incorporated into American Society of Mechanical Engineers (ASME) Code Case N47-29 for design of components operating under creep-rupture conditions. The current report provides additional validation of the model for predicting failure under time-independent conditions and also outlines a methodology for predicting failure under cyclic, time-dependent, creep-fatigue conditions. The later extension of the methodology may have the potential to improve failure predictions there as well. These results are relevant to most design applications, but they have special relevance to high-performance design applications such as components for high-pressure equipment, nuclear reactors, and jet engines.

  15. Predicting chaotic time series with a partial model.

    Science.gov (United States)

    Hamilton, Franz; Berry, Tyrus; Sauer, Timothy

    2015-07-01

    Methods for forecasting time series are a critical aspect of the understanding and control of complex networks. When the model of the network is unknown, nonparametric methods for prediction have been developed, based on concepts of attractor reconstruction pioneered by Takens and others. In this Rapid Communication we consider how to make use of a subset of the system equations, if they are known, to improve the predictive capability of forecasting methods. A counterintuitive implication of the results is that knowledge of the evolution equation of even one variable, if known, can improve forecasting of all variables. The method is illustrated on data from the Lorenz attractor and from a small network with chaotic dynamics.

  16. Forecasts of time averages with a numerical weather prediction model

    Science.gov (United States)

    Roads, J. O.

    1986-01-01

    Forecasts of time averages of 1-10 days in duration by an operational numerical weather prediction model are documented for the global 500 mb height field in spectral space. Error growth in very idealized models is described in order to anticipate various features of these forecasts and in order to anticipate what the results might be if forecasts longer than 10 days were carried out by present day numerical weather prediction models. The data set for this study is described, and the equilibrium spectra and error spectra are documented; then, the total error is documented. It is shown how forecasts can immediately be improved by removing the systematic error, by using statistical filters, and by ignoring forecasts beyond about a week. Temporal variations in the error field are also documented.

  17. NASA AVOSS Fast-Time Wake Prediction Models: User's Guide

    Science.gov (United States)

    Ahmad, Nash'at N.; VanValkenburg, Randal L.; Pruis, Matthew

    2014-01-01

    The National Aeronautics and Space Administration (NASA) is developing and testing fast-time wake transport and decay models to safely enhance the capacity of the National Airspace System (NAS). The fast-time wake models are empirical algorithms used for real-time predictions of wake transport and decay based on aircraft parameters and ambient weather conditions. The aircraft dependent parameters include the initial vortex descent velocity and the vortex pair separation distance. The atmospheric initial conditions include vertical profiles of temperature or potential temperature, eddy dissipation rate, and crosswind. The current distribution includes the latest versions of the APA (3.4) and the TDP (2.1) models. This User's Guide provides detailed information on the model inputs, file formats, and the model output. An example of a model run and a brief description of the Memphis 1995 Wake Vortex Dataset is also provided.

  18. Local discrete cosine transformation domain Volterra prediction of chaotic time series

    Institute of Scientific and Technical Information of China (English)

    张家树; 李恒超; 肖先赐

    2005-01-01

    In this paper a local discrete cosine transformation (DCT) domain Volterra prediction method is proposed to predict chaotic time series, where the DCT is used to lessen the complexity of solving the coefficient matrix. Numerical simulation results show that the proposed prediction method can effectively predict chaotic time series and improve the prediction accuracy compared with the traditional local linear prediction methods.

  19. Predicting the decay time of solid body electric guitar tones.

    Science.gov (United States)

    Paté, Arthur; Le Carrou, Jean-Loïc; Fabre, Benoît

    2014-05-01

    Although it can be transformed by various electronic devices, the sound of the solid body electric guitar originates from, and is strongly linked with, the string vibration. The coupling of the string with the guitar alters its vibration and can lead to decay time inhomogeneities. This paper implements and justifies a framework for the study of decay times of electric guitar tones. Two damping mechanisms are theoretically and experimentally identified: the string intrinsic damping and the damping due to mechanical coupling with the neck of the guitar. The electromagnetic pickup is shown to not provide any additional damping to the string. The pickup is also shown to be far more sensitive to the out-of-plane polarization of the string. Finally, an accurate prediction of the decay time of electric guitar tones is made possible, whose only requirements are the knowledge of the isolated string dampings and the out-of-plane conductance at the neck of the guitar. This prediction can be of great help for instrument makers and manufacturers.

  20. Predictive modeling of respiratory tumor motion for real-time prediction of baseline shifts

    Science.gov (United States)

    Balasubramanian, A.; Shamsuddin, R.; Prabhakaran, B.; Sawant, A.

    2017-03-01

    Baseline shifts in respiratory patterns can result in significant spatiotemporal changes in patient anatomy (compared to that captured during simulation), in turn, causing geometric and dosimetric errors in the administration of thoracic and abdominal radiotherapy. We propose predictive modeling of the tumor motion trajectories for predicting a baseline shift ahead of its occurrence. The key idea is to use the features of the tumor motion trajectory over a 1 min window, and predict the occurrence of a baseline shift in the 5 s that immediately follow (lookahead window). In this study, we explored a preliminary trend-based analysis with multi-class annotations as well as a more focused binary classification analysis. In both analyses, a number of different inter-fraction and intra-fraction training strategies were studied, both offline as well as online, along with data sufficiency and skew compensation for class imbalances. The performance of different training strategies were compared across multiple machine learning classification algorithms, including nearest neighbor, Naïve Bayes, linear discriminant and ensemble Adaboost. The prediction performance is evaluated using metrics such as accuracy, precision, recall and the area under the curve (AUC) for repeater operating characteristics curve. The key results of the trend-based analysis indicate that (i) intra-fraction training strategies achieve highest prediction accuracies (90.5-91.4%) (ii) the predictive modeling yields lowest accuracies (50-60%) when the training data does not include any information from the test patient; (iii) the prediction latencies are as low as a few hundred milliseconds, and thus conducive for real-time prediction. The binary classification performance is promising, indicated by high AUCs (0.96-0.98). It also confirms the utility of prior data from previous patients, and also the necessity of training the classifier on some initial data from the new patient for reasonable

  1. Prediction of Non-Cavitation Propeller Noise in Time Domain

    Institute of Scientific and Technical Information of China (English)

    YE Jin-ming; XIONG Ying; XIAO Chang-run; BI Yi

    2011-01-01

    The blade frequency noise of non-cavitation propeller in a uniform flow is analyzed in time domain.The unsteady loading (dipole source) on the blade surface is calculated by a potential-based surface panel method.Then the timedependent pressure data is used as the input for Ffowcs Williams-Hawkings formulation to predict the acoustics pressure.The integration of noise source is performed over the true blade surface rather than the nothickness blade surface,and the effect of hub can be considered.The noise characteristics of the non-cavitation propeller and the numerical discretization forms are discussed.

  2. Nonlinear analysis and prediction of time series in multiphase reactors

    CERN Document Server

    Liu, Mingyan

    2014-01-01

    This book reports on important nonlinear aspects or deterministic chaos issues in the systems of multi-phase reactors. The reactors treated in the book include gas-liquid bubble columns, gas-liquid-solid fluidized beds and gas-liquid-solid magnetized fluidized beds. The authors take pressure fluctuations in the bubble columns  as time series for nonlinear analysis, modeling and forecasting. They present qualitative and quantitative non-linear analysis tools which include attractor phase plane plot, correlation dimension, Kolmogorov entropy and largest Lyapunov exponent calculations and local non-linear short-term prediction.

  3. Memory controllers for real-time embedded systems predictable and composable real-time systems

    CERN Document Server

    Akesson, Benny

    2012-01-01

      Verification of real-time requirements in systems-on-chip becomes more complex as more applications are integrated. Predictable and composable systems can manage the increasing complexity using formal verification and simulation.  This book explains the concepts of predictability and composability and shows how to apply them to the design and analysis of a memory controller, which is a key component in any real-time system. This book is generally intended for readers interested in Systems-on-Chips with real-time applications.   It is especially well-suited for readers looking to use SDRAM memories in systems with hard or firm real-time requirements. There is a strong focus on real-time concepts, such as predictability and composability, as well as a brief discussion about memory controller architectures for high-performance computing. Readers will learn step-by-step how to go from an unpredictable SDRAM memory, offering highly variable bandwidth and latency, to a predictable and composable shared memory...

  4. HVM-TP: A Time Predictable, Portable Java Virtual Machine for Hard Real-Time Embedded Systems

    DEFF Research Database (Denmark)

    Luckow, Kasper Søe; Thomsen, Bent; Korsholm, Stephan Erbs

    2014-01-01

    We present HVMTIME; a portable and time predictable JVM implementation with applications in resource-constrained hard real-time embedded systems. In addition, it implements the Safety Critical Java (SCJ) Level 1 specification. Time predictability is achieved by a combination of time predictable...

  5. Time-dependent Predictive Values of Prognostic Biomarkers with Failure Time Outcome.

    Science.gov (United States)

    Zheng, Yingye; Cai, Tianxi; Pepe, Margaret S; Levy, Wayne C

    2008-01-01

    In a prospective cohort study, information on clinical parameters, tests and molecular markers is often collected. Such information is useful to predict patient prognosis and to select patients for targeted therapy. We propose a new graphical approach, the positive predictive value (PPV) curve, to quantify the predictive accuracy of prognostic markers measured on a continuous scale with censored failure time outcome. The proposed method highlights the need to consider both predictive values and the marker distribution in the population when evaluating a marker, and it provides a common scale for comparing different markers. We consider both semiparametric and nonparametric based estimating procedures. In addition, we provide asymptotic distribution theory and resampling based procedures for making statistical inference. We illustrate our approach with numerical studies and datasets from the Seattle Heart Failure Study.

  6. Data assimialation for real-time prediction and reanalysis

    Science.gov (United States)

    Shprits, Y.; Kellerman, A. C.; Podladchikova, T.; Kondrashov, D. A.; Ghil, M.

    2015-12-01

    We discuss the how data assimilation can be used for the analysis of individual satellite anomalies, development of long-term evolution reconstruction that can be used for the specification models, and use of data assimilation to improve the now-casting and focusing of the radiation belts. We also discuss advanced data assimilation methods such as parameter estimation and smoothing.The 3D data assimilative VERB allows us to blend together data from GOES, RBSP A and RBSP B. Real-time prediction framework operating on our web site based on GOES, RBSP A, B and ACE data and 3D VERB is presented and discussed. In this paper we present a number of application of the data assimilation with the VERB 3D code. 1) Model with data assimilation allows to propagate data to different pitch angles, energies, and L-shells and blends them together with the physics based VERB code in an optimal way. We illustrate how we use this capability for the analysis of the previous events and for obtaining a global and statistical view of the system. 2) The model predictions strongly depend on initial conditions that are set up for the model. Therefore the model is as good as the initial conditions that it uses. To produce the best possible initial condition data from different sources ( GOES, RBSP A, B, our empirical model predictions based on ACE) are all blended together in an optimal way by means of data assimilation as described above. The resulting initial condition does not have gaps. That allows us to make a more accurate predictions.

  7. Satellite attitude prediction by multiple time scales method

    Science.gov (United States)

    Tao, Y. C.; Ramnath, R.

    1975-01-01

    An investigation is made of the problem of predicting the attitude of satellites under the influence of external disturbing torques. The attitude dynamics are first expressed in a perturbation formulation which is then solved by the multiple scales approach. The independent variable, time, is extended into new scales, fast, slow, etc., and the integration is carried out separately in the new variables. The theory is applied to two different satellite configurations, rigid body and dual spin, each of which may have an asymmetric mass distribution. The disturbing torques considered are gravity gradient and geomagnetic. Finally, as multiple time scales approach separates slow and fast behaviors of satellite attitude motion, this property is used for the design of an attitude control device. A nutation damping control loop, using the geomagnetic torque for an earth pointing dual spin satellite, is designed in terms of the slow equation.

  8. Time series prediction by feedforward neural networks - is it difficult?

    CERN Document Server

    Rosen-Zvi, M; Kinzel, W

    2003-01-01

    The difficulties that a neural network faces when trying to learn from a quasi-periodic time series are studied analytically using a teacher-student scenario where the random input is divided into two macroscopic regions with different variances, 1 and 1/gamma sup 2 (gamma >> 1). The generalization error is found to decrease as epsilon sub g propor to exp(-alpha/gamma sup 2), where alpha is the number of examples per input dimension. In contradiction to this very slow vanishing generalization error, the next output prediction is found to be almost free of mistakes. This picture is consistent with learning quasi-periodic time series produced by feedforward neural networks, which is dominated by enhanced components of the Fourier spectrum of the input. Simulation results are in good agreement with the analytical results.

  9. Predicting aquifer response time for application in catchment modeling.

    Science.gov (United States)

    Walker, Glen R; Gilfedder, Mat; Dawes, Warrick R; Rassam, David W

    2015-01-01

    It is well established that changes in catchment land use can lead to significant impacts on water resources. Where land-use changes increase evapotranspiration there is a resultant decrease in groundwater recharge, which in turn decreases groundwater discharge to streams. The response time of changes in groundwater discharge to a change in recharge is a key aspect of predicting impacts of land-use change on catchment water yield. Predicting these impacts across the large catchments relevant to water resource planning can require the estimation of groundwater response times from hundreds of aquifers. At this scale, detailed site-specific measured data are often absent, and available spatial data are limited. While numerical models can be applied, there is little advantage if there are no detailed data to parameterize them. Simple analytical methods are useful in this situation, as they allow the variability in groundwater response to be incorporated into catchment hydrological models, with minimal modeling overhead. This paper describes an analytical model which has been developed to capture some of the features of real, sloping aquifer systems. The derived groundwater response timescale can be used to parameterize a groundwater discharge function, allowing groundwater response to be predicted in relation to different broad catchment characteristics at a level of complexity which matches the available data. The results from the analytical model are compared to published field data and numerical model results, and provide an approach with broad application to inform water resource planning in other large, data-scarce catchments. © 2014, CommonWealth of Australia. Groundwater © 2014, National Ground Water Association.

  10. MULTI SCALE TIME SERIES PREDICTION FOR INTRUSION DETECTION

    Directory of Open Access Journals (Sweden)

    G. Palanivel

    2014-01-01

    Full Text Available We propose an anomaly-based network intrusion detection system, which analyzes traffic features to detect anomalies. The proposed system can be used both in online as well as off-line mode for detecting deviations from the expected behavior. Although our approach uses network packet or flow data, it is general enough to be adaptable for use with any other network variable, which may be used as a signal for anomaly detection. It differs from most existing approaches in its use of wavelet transform for generating different time scales for a signal and using these scales as an input to a two-stage neural network predictor. The predictor predicts the expected signal value and labels considerable deviations from this value as anomalies. The primary contribution of our work would be to empirically evaluate the effectiveness of multi resolution analysis as an input to neural network prediction engine specifically for the purpose of intrusion detection. The role of Intrusion Detection Systems (IDSs, as special-purpose devices to detect anomalies and attacks in a network, is becoming more important. First, anomaly-based methods cannot achieve an outstanding performance without a comprehensive labeled and up-to-date training set with all different attack types, which is very costly and time-consuming to create if not impossible. Second, efficient and effective fusion of several detection technologies becomes a big challenge for building an operational hybrid intrusion detection system.

  11. Predicting Sequences of Progressive Events Times with Time-dependent Covariates

    CERN Document Server

    Cai, Song; Newlands, Nathaniel

    2010-01-01

    This paper presents an approach to modeling progressive event-history data when the overall objective is prediction based on time-dependent covariates. This approach does not model the hazard function directly. Instead, it models the process of the state indicators of the event history so that the time-dependent covariates can be incorporated and predictors of the future events easily formulated. Our model can be applied to a range of real-world problems in medical and agricultural science.

  12. Using timing of ice retreat to predict timing of fall freeze-up in the Arctic

    Science.gov (United States)

    Stroeve, Julienne C.; Crawford, Alex D.; Stammerjohn, Sharon

    2016-06-01

    Reliable forecasts of the timing of sea ice advance are needed in order to reduce risks associated with operating in the Arctic as well as planning of human and environmental emergencies. This study investigates the use of a simple statistical model relating the timing of ice retreat to the timing of ice advance, taking advantage of the inherent predictive power supplied by the seasonal ice-albedo feedback and ocean heat uptake. Results show that using the last retreat date to predict the first advance date is applicable in some regions, such as Baffin Bay and the Laptev and East Siberian seas, where a predictive skill is found even after accounting for the long-term trend in both variables. Elsewhere, in the Arctic, there is some predictive skills depending on the year (e.g., Kara and Beaufort seas), but none in regions such as the Barents and Bering seas or the Sea of Okhotsk. While there is some suggestion that the relationship is strengthening over time, this may reflect that higher correlations are expected during periods when the underlying trend is strong.

  13. Female Pubertal Timing and Problem Behaviour: The Role of Culture

    Science.gov (United States)

    Skoog, Therese; Stattin, Hakan; Ruiselova, Zdena; Ozdemir, Metin

    2013-01-01

    We tested the peer-socialization/contextual-amplification explanation for the link between early female puberty and problem behaviour. We propose that in cultures with high tolerance for adolescent heterosexual involvement, early puberty should be linked with problem behaviour--not in other cultures. We compared girls in two cultures (Slovakia and…

  14. Female Pubertal Timing and Problem Behaviour: The Role of Culture

    Science.gov (United States)

    Skoog, Therese; Stattin, Hakan; Ruiselova, Zdena; Ozdemir, Metin

    2013-01-01

    We tested the peer-socialization/contextual-amplification explanation for the link between early female puberty and problem behaviour. We propose that in cultures with high tolerance for adolescent heterosexual involvement, early puberty should be linked with problem behaviour--not in other cultures. We compared girls in two cultures (Slovakia and…

  15. Gut microbiota may predict host divergence time during Glires evolution.

    Science.gov (United States)

    Li, Huan; Qu, Jiapeng; Li, Tongtong; Yao, Minjie; Li, Jiaying; Li, Xiangzhen

    2017-03-01

    The gut microbial communities of animals play key roles in host evolution. However, the possible relationship between gut microbiota and host divergence time remains unknown. Here, we investigated the gut microbiota of eight Glires species (four lagomorph species and four rodent species) distributed throughout the Qinghai-Tibet plateau and Inner Mongolia grassland. Lagomorphs and rodents had distinct gut microbial compositions. Three out of four lagomorph species were dominated by Firmicutes, while rodents were dominated by Bacteroidetes in general. The alpha diversity values (Shannon diversity and evenness) exhibited significant differences between any two species within the lagomorphs, whereas there were no significant differences among rodents. The structure of the gut microbiota showed significant differences between lagomorphs and rodents. In addition, we calculated host phylogeny and divergence times, and used a phylogenetic approach to reconstruct how the animal gut microbiota has diverged from their ancestral species. Some core bacterial genera (e.g. Prevotella and Clostridium) shared by more than nine-tenths of all the Glires individuals associated with plant polysaccharide degradation showed marked changes within lagomorphs. Differences in Glires gut microbiota (based on weighted UniFrac and Bray-Curtis dissimilarity metrics) were positively correlated with host divergence time. Our results thus suggest the gut microbial composition is associated with host phylogeny, and further suggest that dissimilarity of animal gut microbiota may predict host divergence time. © FEMS 2017. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

  16. Sex steroids and brain structure in pubertal boys and girls.

    Science.gov (United States)

    Peper, Jiska S; Brouwer, Rachel M; Schnack, Hugo G; van Baal, G Caroline; van Leeuwen, Marieke; van den Berg, Stéphanie M; Delemarre-Van de Waal, Henriëtte A; Boomsma, Dorret I; Kahn, René S; Hulshoff Pol, Hilleke E

    2009-04-01

    Sex steroids exert important organizational effects on brain structure. Early in life, they are involved in brain sexual differentiation. During puberty, sex steroid levels increase considerably. However, to which extent sex steroid production is involved in structural brain development during human puberty remains unknown. The relationship between pubertal rises in testosterone and estradiol levels and brain structure was assessed in 37 boys and 41 girls (10-15 years). Global brain volumes were measured using volumetric-MRI. Regional gray and white matter were quantified with voxel-based morphometry (VBM), a technique which measures relative concentrations ('density') of gray and white matter after individual global differences in size and shape of brains have been removed. Results showed that, corrected for age, global gray matter volume was negatively associated with estradiol levels in girls, and positively with testosterone levels in boys. Regionally, a higher estradiol level in girls was associated with decreases within prefrontal, parietal and middle temporal areas (corrected for age), and with increases in middle frontal-, inferior temporal- and middle occipital gyri. In boys, estradiol and testosterone levels were not related to regional brain structures, nor were testosterone levels in girls. Pubertal sex steroid levels could not explain regional sex differences in regional gray matter density. Boys were significantly younger than girls, which may explain part of the results. In conclusion, in girls, with the progression of puberty, gray matter development is at least in part directly associated with increased levels of estradiol, whereas in boys, who are in a less advanced pubertal stage, such steroid-related development could not (yet) be found. We suggest that in pubertal girls, estradiol may be implicated in neuronal changes in the cerebral cortex during this important period of brain development.

  17. Prevalence of acne in primary school children and the relationship of acne with pubertal maturation

    OpenAIRE

    Hilal Kaya Erdoğan; İlknur Kıvanç Altunay; Serap Turan

    2014-01-01

    Background and Design: Although acne vulgaris is generally regarded as a disease of adolescence period, it can occur in infancy, early childhood and prepubertal period. Acne may emerge as the first sign of pubertal maturation. In our study, we aimed to determine the acne prevalence in primary school children, then, evaluate the pubertal signs in those children; examine the correlation of the presence and severity of acne with pubertal signs, and finally, revise the concept of prepubertal a...

  18. Effects of programmed physical activity on body composition in post-pubertal schoolchildren.

    Science.gov (United States)

    Farias, Edson Dos Santos; Gonçalves, Ezequiel Moreira; Morcillo, André Moreno; Guerra-Júnior, Gil; Amancio, Olga Maria Silverio

    2015-01-01

    To assess body composition modifications in post-pubertal schoolchildren after practice of a physical activity program during one school year. The sample consisted of 386 students aged between 15 and 17 years and divided into two groups: the study group (SG) comprised 195 students and the control group (CG), 191. The SG was submitted to a physical activity program and the CG attended conventional physical education classes. Body composition was assessed using body mass index (BMI), percentage of body fat (%BF), fat mass (FM), and lean mass (LM). A positive effect of the physical activity program on body composition in the SG (p<0.001) was observed, as well as on the interaction time x group in all the variables analyzed in both genders. A reduction in %BF (mean of differences = -5.58%) and waist circumference (-2.33 cm), as well as an increase in LM (+2.05 kg) were observed in the SG for both genders, whereas the opposite was observed in the CG. The practice of programmed physical activity promotes significant reduction of body fat in post-pubertal schoolchildren. Copyright © 2013 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

  19. Predicting Mean Survival Time from Reported Median Survival Time for Cancer Patients

    DEFF Research Database (Denmark)

    Lousdal, Mette L; Kristiansen, Ivar S; Møller, Bjørn;

    2016-01-01

    BACKGROUND: Mean duration of survival following treatment is a prerequisite for cost-effectiveness analyses used for assessing new and costly life-extending therapies for cancer patients. Mean survival time is rarely reported due to censoring imposed by limited follow-up time, whereas the median...... survival time often is. The empirical relationship between mean and median survival time for cancer patients is not known. AIM: To derive the empirical associations between mean and median survival time across cancer types and to validate this empirical prediction approach and compare it with the standard...... approach of fitting a Weibull distribution. METHODS: We included all patients in Norway diagnosed from 1960 to 1999 with one of the 13 most common solid tumor cancers until emigration, death, or 31 December 2011, whichever came first. Observed median, restricted mean, and mean survival times were obtained...

  20. Visual prediction: psychophysics and neurophysiology of compensation for time delays.

    Science.gov (United States)

    Nijhawan, Romi

    2008-04-01

    A necessary consequence of the nature of neural transmission systems is that as change in the physical state of a time-varying event takes place, delays produce error between the instantaneous registered state and the external state. Another source of delay is the transmission of internal motor commands to muscles and the inertia of the musculoskeletal system. How does the central nervous system compensate for these pervasive delays? Although it has been argued that delay compensation occurs late in the motor planning stages, even the earliest visual processes, such as phototransduction, contribute significantly to delays. I argue that compensation is not an exclusive property of the motor system, but rather, is a pervasive feature of the central nervous system (CNS) organization. Although the motor planning system may contain a highly flexible compensation mechanism, accounting not just for delays but also variability in delays (e.g., those resulting from variations in luminance contrast, internal body temperature, muscle fatigue, etc.), visual mechanisms also contribute to compensation. Previous suggestions of this notion of "visual prediction" led to a lively debate producing re-examination of previous arguments, new analyses, and review of the experiments presented here. Understanding visual prediction will inform our theories of sensory processes and visual perception, and will impact our notion of visual awareness.

  1. Estimation of fuel cell operating time for predictive maintenance strategies

    Energy Technology Data Exchange (ETDEWEB)

    Onanena, R. [FC LAB, Techn' Hom, rue Thierry Mieg, 90010 Belfort Cedex (France); FEMTO-ST (UMR CNRS 6174), ENISYS department, University of Franche-Comte (France); INRETS - LTN, ' ' Le Descartes 2' ' , 2 rue de la butte verte, 93166 Noisy-le-Grand Cedex (France); Oukhellou, L. [INRETS - LTN, ' ' Le Descartes 2' ' , 2 rue de la butte verte, 93166 Noisy-le-Grand Cedex (France); CERTES Universite Paris 12, 61 avenue du Gal. de Gaulle, 94100 Creteil (France); Candusso, D. [FC LAB, Techn' Hom, rue Thierry Mieg, 90010 Belfort Cedex (France); INRETS - LTN, ' ' Le Descartes 2' ' , 2 rue de la butte verte, 93166 Noisy-le-Grand Cedex (France); Same, A.; Aknin, P. [INRETS - LTN, ' ' Le Descartes 2' ' , 2 rue de la butte verte, 93166 Noisy-le-Grand Cedex (France); Hissel, D. [FC LAB, Techn' Hom, rue Thierry Mieg, 90010 Belfort Cedex (France); FEMTO-ST (UMR CNRS 6174), ENISYS department, University of Franche-Comte (France)

    2010-08-15

    Durability is one of the limiting factors for spreading and commercialization of fuel cell technology. That is why research to extend fuel cell durability is being conducted world wide. A pattern-recognition approach aiming to estimate fuel cell operating time based on electrochemical impedance spectroscopy measurements is presented here. It is based on extracting the features from the impedance spectra. For that purpose, two approaches have been investigated. In the first one, particular points of the spectrum are empirically extracted as features. In the second approach, a parametric modeling is performed to extract features from both the real and the imaginary parts of the impedance spectrum. In particular, a latent regression model is used to automatically split the spectrum into several segments that are approximated by polynomials. The number of segments is adjusted taking into account the a priori knowledge about the physical behavior of the fuel cell components. Then, a linear regression model using different subsets of extracted features is employed for an estimate of the fuel cell operating time. The effectiveness of the proposed approach is evaluated on an experimental dataset. Allowing the estimation of the fuel cell operating time, and consequently its remaining duration life, these results could lead to interesting perspectives for predictive fuel cells maintenance policy. (author)

  2. Time Granularity Transformation of Time Series Data for Failure Prediction of Overhead Line

    Science.gov (United States)

    Ma, Yan; Zhu, Wenbing; Yao, Jinxia; Gu, Chao; Bai, Demeng; Wang, Kun

    2017-01-01

    In this paper, we give an approach of transforming time series data with different time granularities into the same plane, which is the basis of further association analysis. We focus on the application of overhead line tripping. First all the relative state variables with line tripping are collected into our big data platform. We collect line account, line fault, lightning, power load and meteorological data. Second we respectively pre-process the five kinds of data to guarantee the integrality of data and simplicity of analysis. We use a representation way combining the aggregated representation and trend extraction methods, which considers both short term variation and long term trend of time sequence. Last we use extensive experiments to demonstrate that the proposed time granularity transformation approach not only lets multiple variables analysed on the same plane, but also has a high prediction accuracy and low running time no matter for SVM or logistic regression algorithm.

  3. Application of Astronomic Time-latitude Residuals in Earthquake Prediction

    Science.gov (United States)

    Yanben, Han; Lihua, Ma; Hui, Hu; Rui, Wang; Youjin, Su

    2007-04-01

    After the earthquake (Ms = 6.1) occurred in Luquan county of Yunnan province on April 18, 1985, the relationship between major earthquakes and astronomical time-latitude residuals (ATLR) of a photoelectric astrolabe in Yunnan Observatory was analyzed. ATLR are the rest after deducting the effects of Earth’s whole motion from the observations of time and latitude. It was found that there appeared the anomalies of the ATLR before earthquakes which happened in and around Yunnan, a seismic active region. The reason of the anomalies is possibly from change of the plumb line due to the motion of the groundmass before earthquakes. Afterwards, using studies of the anomalous characters and laws of ATLR, we tried to provide the warning information prior to the occurrence of a few major earthquakes in the region. The significant synchronous anomalies of ATLR of the observatory appeared before the earthquake of magnitude 6.2 in Dayao county of Yunnan province, on July 21, 2003. It has been again verified that the anomalies possibly provide the prediction information for strong earthquakes around the observatory.

  4. Predicting armed conflict: Time to adjust our expectations?

    Science.gov (United States)

    Cederman, Lars-Erik; Weidmann, Nils B

    2017-02-03

    This Essay provides an introduction to the general challenges of predicting political violence, particularly compared with predicting other types of events (such as earthquakes). What is possible? What is less realistic? We aim to debunk myths about predicting violence, as well as to illustrate the substantial progress in this field. Copyright © 2017, American Association for the Advancement of Science.

  5. Prediction of shock arrival times from CME and flare data

    Science.gov (United States)

    Núñez, Marlon; Nieves-Chinchilla, Teresa; Pulkkinen, Antti

    2016-08-01

    This paper presents the Shock Arrival Model (SARM) for predicting shock arrival times for distances from 0.72 AU to 8.7 AU by using coronal mass ejections (CME) and flare data. SARM is an aerodynamic drag model described by a differential equation that has been calibrated with a data set of 120 shocks observed from 1997 to 2010 by minimizing the mean absolute error (MAE), normalized to 1 AU. SARM should be used with CME data (radial, earthward, or plane-of-sky speeds) and flare data (peak flux, duration, and location). In the case of 1 AU, the MAE and the median of absolute errors were 7.0 h and 5.0 h, respectively, using the available CME/flare data. The best results for 1 AU (an MAE of 5.8 h) were obtained using both CME data, either radial or cone model-estimated speeds, and flare data. For the prediction of shock arrivals at distances from 0.72 AU to 8.7 AU, the normalized MAE and the median were 7.1 h and 5.1 h, respectively, using the available CME/flare data. SARM was also calibrated to be used with CME data alone or flare data alone, obtaining normalized MAE errors of 8.9 h and 8.6 h, respectively, for all shock events. The model verification was carried out with an additional data set of 20 shocks observed from 2010 to 2012 with radial CME speeds to compare SARM with the empirical ESA model and the numerical MHD-based ENLIL model. The results show that the ENLIL's MAE was lower than the SARM's MAE, which was lower than the ESA's MAE. The SARM's best results were obtained when both flare and true CME speeds were used.

  6. Food pattern analysis over time: unhealthful eating trajectories predict obesity.

    Science.gov (United States)

    Pachucki, M A

    2012-05-01

    Analysis of dietary patterns is prominent in nutrition literatures, yet few studies have taken advantage of multiple repeated measurements to understand the nature of individual-level changes over time in food choice, or the relation between these changes and body mass index (BMI). To investigate changes in eating patterns at the individual level across three exam periods, and to prospectively examine the relation of eating trajectories to BMI at the cohort level. The study included 3418 participants at baseline. Clinically measured BMI and dietary intake were assessed during three exam periods between 1991 and 2001 using a validated food frequency questionnaire. An individual's eating trajectory across exam periods was analyzed using sequence analysis, and then used to estimate outcomes of continuous BMI and categorical obesity status. Ordinary least squares regression models with robust standard errors were adjusted for socio-economic and demographic confounders, baseline BMI and baseline eating. A total of 66.2% (n=1614) of participants change their diet pattern during the study period, 33.8% (n=823) remain stable. After accounting for potential confounders, an unhealthful trajectory is significantly associated with a 0.42 kg m(-2) increase in BMI (confidence interval (CI): 0.1, 0.7). Those with an unhealthful trajectory are 1.79 times more likely to be overweight (relative risk ratio, 95% CI: 1.1, 2.8) and 2.4 times more likely to be obese (relative risk ratio, 95% CI: 1.3, 4.4). Moreover, a number of specific diet transitions between exams are predictive of weight gain or loss. Contextualizing an individual's current eating behaviors with an eye towards diet history may be an important boon in the reduction of obesity. Although it may not be realistic for many people to shift from the least to most healthful diet, results from this study suggest that consistent movement in an overall healthier direction is associated with less weight gain.

  7. Deciphering elapsed time and predicting action timing from neuronal population signals

    Directory of Open Access Journals (Sweden)

    Shigeru eShinomoto

    2011-06-01

    Full Text Available The proper timing of actions is necessary for the survival of animals, whether in hunting prey or escaping predators. Researchers in the field of neuroscience have begun to explore neuronal signals correlated to behavioral interval timing. Here, we attempt to decode the lapse of time from neuronal population signals recorded from the frontal cortex of monkeys performing a multiple-interval timing task. We designed a Bayesian algorithm that deciphers temporal information hidden in noisy signals dispersed within the activity of individual neurons recorded from monkeys trained to determine the passage of time before initiating an action. With this decoder, we succeeded in estimating the elapsed time with a precision of approximately 1 sec throughout the relevant behavioral period from firing rates of 25 neurons in the pre-supplementary motor area. Further, an extended algorithm makes it possible to determine the total length of the time interval required to wait in each trial. This enables observers to predict the moment at which the subject will take action from the neuronal activity in the brain. A separate population analysis reveals that the neuronal ensemble represents the lapse of time in a manner scaled relative to the scheduled interval, rather than representing it as the real physical time.

  8. Time-Predictable Communication on a Time-Division Multiplexing Network-on-Chip Multicore

    DEFF Research Database (Denmark)

    Sørensen, Rasmus Bo

    This thesis presents time-predictable inter-core communication on a multicore platform with a time-division multiplexing (TDM) network-on-chip (NoC) for hard real-time systems. The thesis is structured as a collection of papers that contribute within the areas of: reconfigurable TDM NoCs, static...... of the Argo NoC network interface (NI) that supports instantaneous reconfiguration, a TDM traffic scheduler that generates virtual circuit (VC) configurations for the Argo NoC, and software functions for two types of intercore communication. The new generation of the Argo NoC adds the capability...... in terms of shortening the TDM period. The thesis identifies two types of inter-core communication that are commonly used in real-time systems: message passing and state-based communication. We implement message passing as a circular buffer with the data transfer through the NoC. The worst-case execution...

  9. Prevalence of acne in primary school children and the relationship of acne with pubertal maturation

    Directory of Open Access Journals (Sweden)

    Hilal Kaya Erdoğan

    2014-12-01

    Full Text Available Background and Design: Although acne vulgaris is generally regarded as a disease of adolescence period, it can occur in infancy, early childhood and prepubertal period. Acne may emerge as the first sign of pubertal maturation. In our study, we aimed to determine the acne prevalence in primary school children, then, evaluate the pubertal signs in those children; examine the correlation of the presence and severity of acne with pubertal signs, and finally, revise the concept of prepubertal acne. Materials and Methods: A thousand students from 2 schools in Istanbul were included in the study. Age, gender, and the presence, localization and severity of acne were recorded. Acne severity was evaluated using the Orfanos-Gollnick Acne Grading System while a validated self evaluation form which had been developed by Morris and Udry was used to evaluate pubertal stage. Data were evaluated statistically. Results: Five hundred and thirty-four male and 466 female primary school children, with an age range of 7 to 11, were included in the study. Acne was determined in 11.5% of the students. 20% of girls and 4% of boys had acne. Comparing acne presence and age, the average age was higher in group with acne than those with no acne. The mean age of children with grade 1 acne was lower than those with grade 2 acne. All the students with acne had mid-facial acne. Comparing acne presence and pubertal symptoms, the rate of the presence of acne was higher in pubertal girls. No acne was observed in prepubertal boys. Evaluating acne severity and pubertal signs, the difference between prepubertal and pubertal girls was not significant. Comparing acne and telarche stages, the group without acne had lower telarche rates. Comparing acne and pubertal stages, children with acne had advanced puberty. Conclusion: Our study denotes that acne prevalence is related to pubertal maturation and age; while it does not support the hypothesis that acne is the first sign of pubertal

  10. Giant pubertal prolactinoma: Complete resolution following short ...

    African Journals Online (AJOL)

    2016-04-06

    Apr 6, 2016 ... disappeared in a short time with cabergoline treatment. Key words: ... stature, and delayed development of his secondary sex characteristics. .... Leong KS, Foy PM, Swift AC, Atkin SL, Hadden DR, MacFarlane IA. CSF.

  11. Networked Control System Time-Delay Compensation Based on Time-Delay Prediction and Improved Implicit GPC

    OpenAIRE

    Zhong-Da Tian; Shu-Jiang Li; Yan-Hong Wang; Hong-Xia Yu

    2015-01-01

    The random time delay in a networked control system can usually deteriorate the control performance and stability of the networked control system. In order to solve this problem, this paper puts forward a networked control system random time-delay compensation method based on time-delay prediction and improved implicit generalized predictive control (GPC). The least squares support vector machine is used to predict the future time delay of network. The parameters of the least squares support...

  12. Navy Global Predictions for the Dynamo Time Period

    Science.gov (United States)

    Reynolds, C. A.; Ridout, J. A.; Flatau, M. K.; Chen, J.; Richman, J. G.; Jensen, T. G.; Shriver, J. F.

    2014-12-01

    The performance of 30-day simulations of the Navy Global Environmental Model (NAVGEM) is evaluated under several metrics. The time period of interest is the DYNAMO (Dynamics of Madden Julian Oscillation) field experiment period, starting late October 2011. The NAVGEM experiments are run at an effective 37-km resolution with several different SST configurations. The in the first set of experiments, the initial SST analysis, provided by the NCODA (Navy Coupled Ocean Data Assimilation) system, is either held fixed to the initial value (fixed SST) or updated every 6 hours. These forecasts are compared with forecasts in which the SST is updated with 3-h analyses from the Hybrid Coordinate Ocean Model (HYCOM), and forecasts in which NAVGEM is interactively coupled to HYCOM. Experiments are also performed with different physical parameterization options. The extended integrations are verified using observed OLR, TRMM precipitation estimates, and global analyses. The use of fixed SSTs is clearly sub-optimal. Biases in monthly mean fields are far more pronounced in the simulations where the SST is held fixed as compared to those in simulations where updated SST analyses are used. Biases in the monthly mean fields are further reduced when NAVGEM is coupled to HYCOM. Differences in SST can "migrate" to substantial changes in the time-mean land-surface temperatures, illustrating the substantial impact of SSTs over the full domain. Concerning the simulation of the MJO, some improvement is noted when the system is fully coupled, although the simulations still exhibit deficiencies such as eastward propagation that is too slow, and difficulty propagating over the maritime continent. Simulations that are started every 5 days indicate that the NAVGEM uncoupled system has difficulty predicting MJO initiation, but simulations started when the MJO is active in the Indian Ocean are able to capture eastward propagation characteristics. The coupled NAVGEM-HYCOM system shows ability to

  13. Osteoporosis-Related Mortality: Time-Trends and Predictive Factors

    Directory of Open Access Journals (Sweden)

    Nelly Ziadé

    2014-07-01

    Full Text Available Osteoporosis is one of the leading causes of handicap worldwide and a major contributor to the global burden of diseases. In particular, osteoporosis is associated with excess mortality. We reviewed the impact of osteoporosis on mortality in a population by defining three categories: mortality following hip fractures, mortality following other sites of fractures, and mortality associated with low bone mineral density (BMD. Hip fractures, as well as other fractures at major sites are all associated with excess mortality, except at the forearm site. This excess mortality is higher during the first 3-6 months after the fracture and then declines over time, but remains higher than the mortality of the normal population up to 22 years after the fracture. Low BMD is also associated with high mortality, with hazard ratios of around 1.3 for every decrease in 1 standard deviation of bone density at 5 years, independently of fractures, reflecting a more fragile population. Finally predictors of mortality were identified and categorised in demographic known factors (age and male gender and in factors reflecting a poor general health status such as the number of comorbidities, low mental status, or level of social dependence. Our results indicate that the management of a patient with osteoporosis should include a multivariate approach that could be based on predictive models in the future.

  14. Predictive active disturbance rejection control for processes with time delay.

    Science.gov (United States)

    Zheng, Qinling; Gao, Zhiqiang

    2014-07-01

    Active disturbance rejection control (ADRC) has been shown to be an effective tool in dealing with real world problems of dynamic uncertainties, disturbances, nonlinearities, etc. This paper addresses its existing limitations with plants that have a large transport delay. In particular, to overcome the delay, the extended state observer (ESO) in ADRC is modified to form a predictive ADRC, leading to significant improvements in the transient response and stability characteristics, as shown in extensive simulation studies and hardware-in-the-loop tests, as well as in the frequency response analysis. In this research, it is assumed that the amount of delay is approximately known, as is the approximated model of the plant. Even with such uncharacteristic assumptions for ADRC, the proposed method still exhibits significant improvements in both performance and robustness over the existing methods such as the dead-time compensator based on disturbance observer and the Filtered Smith Predictor, in the context of some well-known problems of chemical reactor and boiler control problems.

  15. Semen characteristics in pubertal boys. I. Semen quality after first ejaculation.

    Science.gov (United States)

    Janczewski, Z; Bablok, L

    1985-01-01

    Semen specimens from 134 pubertal boys were examined, and some 274 assays were made. An analysis of the biological quality of semen in relation to the period of time after first ejaculation brings high values of statistical dependence of the volume of semen, its liquefaction, spermatozoal concentration, percentage of morphologically normal forms of spermatozoa, and normal spermatozoal motility on the period of time after first ejaculation. Normal figures for semen volume, semen liquefaction, spermatozoal concentration, and morphology are observed 12-14 months after first ejaculation. The percentage of normally motile spermatozoa becomes standard 21-23 months after first ejaculation. There were changes in semen characteristics from azoospermia through cryptozoospermia, oligozoospermia, and asthenozoospermia to normospermia. Azoospermia dominates until the fifth month after the first ejaculation, oligozoospermia from the sixth to the eleventh month, asthenozoospermia from the twelfth to the twentieth month, and normospermia from the twenty-first month.

  16. Prenatal androgen excess programs metabolic derangements in pubertal female rats.

    Science.gov (United States)

    Yan, Xiaonan; Dai, Xiaonan; Wang, Jing; Zhao, Nannan; Cui, Yugui; Liu, Jiayin

    2013-04-01

    Owing to the heterogeneity in the clinical symptoms of polycystic ovary syndrome (PCOS), the early pathophysiological mechanisms of PCOS remain unclear. Clinical, experimental, and genetic evidence supports an interaction between genetic susceptibility and the influence of maternal environment in the pathogenesis of PCOS. To determine whether prenatal androgen exposure induced PCOS-related metabolic derangements during pubertal development, we administrated 5α-dihydrotestosterone (DHT) in pregnant rats and observed their female offspring from postnatal 4 to 8 weeks. The prenatally androgenized (PNA) rats exhibited more numerous total follicles, cystic follicles, and atretic follicles than the controls. Fasting glucose, insulin, leptin levels, and homeostatic model assessment for insulin resistance were elevated in the PNA rats at the age of 5-8 weeks. Following intraperitoneal glucose tolerance tests, glucose and insulin levels did not differ between two groups; however, the PNA rats showed significantly higher 30- and 60-min glucose levels than the controls after insulin stimulation during 5-8 weeks. In addition, prenatal DHT treatment significantly decreased insulin-stimulated phosphorylation of AKT in the skeletal muscles of 6-week-old PNA rats. The abundance of IR substrate 1 (IRS1) and IRS2 was decreased in the skeletal muscles and liver after stimulation with insulin in the PNA group, whereas phosphorylation of insulin-signaling proteins was unaltered in the adipose tissue. These findings validate the contribution of prenatal androgen excess to metabolic derangements in pubertal female rats, and the impaired insulin signaling through IRS and AKT may result in the peripheral insulin resistance during pubertal development.

  17. Predictions of urban volumes in single time series

    NARCIS (Netherlands)

    Thomas, Tom; Weijermars, Wendy; Berkum, van Eric

    2010-01-01

    Congestion is increasing in many urban areas. This has led to a growing awareness of the importance of accurate traffic-flow predictions. In this paper, we introduce a prediction scheme that is based on an extensive study of volume patterns that were collected at about 20 urban intersections in the

  18. Predicting Fluid Intelligence by Components of Reaction Time Distributions from Simple Choice Reaction Time Tasks

    Directory of Open Access Journals (Sweden)

    Yoanna Schulz-Zhecheva

    2016-07-01

    Full Text Available Mean reaction times (RT and the intra-subject variability of RT in simple RT tasks have been shown to predict higher-order cognitive abilities measured with psychometric intelligence tests. To further explore this relationship and to examine its generalizability to a sub-adult-aged sample, we administered different choice RT tasks and Cattell’s Culture Fair Intelligence Test (CFT 20-R to n = 362 participants aged eight to 18 years. The parameters derived from applying Ratcliff’s diffusion model and an ex-Gaussian model to age-residualized RT data were used to predict fluid intelligence using structural equation models. The drift rate parameter of the diffusion model, as well as σ of the ex-Gaussian model, showed substantial predictive validity regarding fluid intelligence. Our findings demonstrate that stability of performance, more than its mere speed, is relevant for fluid intelligence and we challenge the universality of the worst performance rule observed in adult samples.

  19. Granular Vulvovaginitis Syndrome in Nelore pubertal and post pubertal replacement heifers under tropical conditions: role of Mycoplasma spp., Ureaplasma diversum and BHV-1.

    Science.gov (United States)

    Gambarini, M L; Kunz, T L; Oliveira Filho, B D; Porto, R N G; Oliveira, C M G; Brito, W M E D; Viu, M A O

    2009-10-01

    In order to determine the role of Mycoplasma spp, Ureaplasma diversum and BHV-1 as causal agents of Granular Vulvovaginitis Syndrome in Nelore heifers raised under tropical conditions and based on the hypothesis that stressful conditions during puberty or breeding season would be a determinant factor for the infection, 340 heifers not vaccinated against BHV-1 were divided in Post-pubertal, in the beginning of the first breeding season, and Pubertal heifers. The vaginal lesion score (VLS) Grade 1 to 4 was giving according to lesion area and severity. Vaginal mucus was used to isolate Mycoplasma spp., Ureaplasma diversum and BHV-1. The predominant VLS was 2. No sample was positive for BHV-1; 48% were positive for Mycoplasma spp., Ureaplasma diversum, or both, with predominance of Ureaplasma diversum. Serum neutralization for BHV-1 showed more positive animals in pubertal group (23%); 3 of the paired sera demonstrated seroconversion. These data indicated that post-pubertal and pubertal Nelore heifers raised under extensive conditions are more susceptible to Mycoplasma spp. and Ureaplasma diversum. The hypothesis that the stress of pubertal period could lead to an acute vaginal infection by HBV-1 was not proofed.

  20. The organizational effects of pubertal testosterone on sexual proficiency in adult male Syrian hamsters.

    Science.gov (United States)

    De Lorme, Kayla C; Sisk, Cheryl L

    2016-10-15

    Social proficiency requires making appropriate behavioral adaptations as a result of social experience. For example, male rodents become sexually proficient with experience as demonstrated by a reduction in ectopic (misdirected) mounts, mount-to-intromission ratio, and latency to ejaculation. We previously found that over a series of timed tests with a receptive female, male hamsters deprived of testosterone specifically during puberty (NoT@P) have overall lower levels of sexual behavior and continue to display high levels of ectopic mounts, compared with males that experienced endogenous testosterone during puberty (T@P). These results suggested that pubertal testosterone programs sexual proficiency in adulthood, but because NoT@P males engaged in less sexual behavior than T@P males in these tests, the amount of sexual experience may have been insufficient to improve sexual proficiency. To more rigorously test the hypothesis that pubertal testosterone is necessary for social proficiency in adulthood, the present study compared the behavior of NoT@P and T@P males in a series of 4 trials with a 48-h interval between each trial. Sexual experience was equated by limiting each trial to 5 intromissions. Sexually-naïve males were either gonadectomized prepubertally (NoT@P) or in adulthood (T@P) and received subcutaneous testosterone capsules four weeks later. Two weeks after testosterone replacement, these groups and a group of adult gonad-intact controls began sexual behavior testing. We found that NoT@P males had more ectopic mounts/min across all four tests compared to gonad-intact and T@P males. Moreover, both gonad-intact and T@P males, but not NoT@P males, showed an increase in the number of mounts and intromissions/min between trials 1 and 3. Unexpectedly, both gonad-intact and T@P, but not NoT@P, males showed a decrease in sexual behaviors during trial 4. Thus, T@P males display multiple behavioral adaptations to sexual experience that are not observed in No

  1. Pubertal development in elite juvenile gymnasts. Effects of physical training.

    Science.gov (United States)

    Lindholm, C; Hagenfeldt, K; Ringertz, B M

    1994-03-01

    Twenty-two female teenagers engaged in elite gymnast training were prospectively studied during a five-year period and their pubertal development was recorded. Height and weight, as well as stage of development according to Tanner, were registered every six months. FSH, LH, TSH and prolactin were measured in girls who had not yet had their first menstrual period. Twenty-two healthy school girls in the same age group who were not actively engaged in physical exercise served as a control group. Pubertal development was completed during the observation period in all the gymnasts but one, who had primary amenorrhea at the age of eighteen. As a group, the gymnasts had a significantly delayed age of menarche compared to the control group and to normal Swedish girls. They also had significantly less body fat and were shorter and lighter than the control group. They grew much more slowly and did not have the distinct growth spurt seen in the controls. The final height of six of the gymnasts was less than the expected height. The frequency of injuries was high in the gymnasts, which might be a result of hard training combined with late menarche and low body fat.

  2. Evaluating the uncertainty of predicting future climate time series at the hourly time scale

    Science.gov (United States)

    Caporali, E.; Fatichi, S.; Ivanov, V. Y.

    2011-12-01

    A stochastic downscaling methodology is developed to generate hourly, point-scale time series for several meteorological variables, such as precipitation, cloud cover, shortwave radiation, air temperature, relative humidity, wind speed, and atmospheric pressure. The methodology uses multi-model General Circulation Model (GCM) realizations and an hourly weather generator, AWE-GEN. Probabilistic descriptions of factors of change (a measure of climate change with respect to historic conditions) are computed for several climate statistics and different aggregation times using a Bayesian approach that weights the individual GCM contributions. The Monte Carlo method is applied to sample the factors of change from their respective distributions thereby permitting the generation of time series in an ensemble fashion, which reflects the uncertainty of climate projections of future as well as the uncertainty of the downscaling procedure. Applications of the methodology and probabilistic expressions of certainty in reproducing future climates for the periods, 2000 - 2009, 2046 - 2065 and 2081 - 2100, using the 1962 - 1992 period as the baseline, are discussed for the location of Firenze (Italy). The climate predictions for the period of 2000 - 2009 are tested against observations permitting to assess the reliability and uncertainties of the methodology in reproducing statistics of meteorological variables at different time scales.

  3. Physical Stress may Result in Growth Suppression and Pubertal Delay in Working Boys

    Directory of Open Access Journals (Sweden)

    Muhammad Irfan

    2012-01-01

    Full Text Available Child labour is an immense problem in Pakistan. As labour boys are put under persistent/severe physical stress, we hypothesised, that it may result in higher levels of cortisol and exhaust glycogen, fats and protein. Depletion of fats may result in lower body weight, and insufficient leptin concentrations could excite gonadotropic releasing hormone (GnRH at normal time of puberty in working boys. Moreover, lower testosterone levels in working boys, due to delayed puberty, may result in suppression of somatotropic axis. Short/weak stature and failure of onset of puberty may cause poor performance, inferiority complex and psychological disorders. Therefore, the present study is designed to find out the timing of onset of puberty in working boys. The study will include 10–18 years of working boys as case and non-working boys of the same age group as control. Working boys will be labour boys, while the control group will not be involved in physical work. A questionnaire will be used to record socioeconomic status, major diseases, nutritional status, type and duration of work and family history of puberty, growth and obesity of subjects. Boys with familial history of pubertal delay, obesity, malnutrition, mental disorders, haematological diseases and severe/chronic diseases will be excluded. The intensity of physical working stress will be determined by a grading scale. The anthropometric data including height, weight, body mass index (BMI, bone age and tests of adiposity will be collected from subjects. The stages of pubertal onset will be determined by Tanner staging. Serum concentrations of hormones of growth, thyroid, adrenal, brain–gut and gonadal axis will be determined in non-working and working boys. Physical and hormonal tests of the working boys and the comparison with non-working boys are sufficient to test the idea

  4. Physical Stress May Result in Growth Suppression and Pubertal Delay in Working Boys

    Directory of Open Access Journals (Sweden)

    Mazhar Qayyum

    2011-01-01

    Full Text Available Child labor is an immense problem of Pakistan. As labor boys stay under persistent/severe physical stress, we hypothesized, that it may result in higher levels of cortisol and exhaust glycogen, fats and proteins. Depletion of fats may result in lower body weight, and insufficient leptin concentrations to excite gonadotropic releasing hormone (GnRH at the normal time of puberty in working boys. Moreover, lower testosterone levels in working boys, due to delayed puberty, may result in suppression of somatotropic axis. The Short/weak stature and failure of the onset of puberty may cause poor performance, the inferiority complex and psychological disorders. Therefore, present study is designed to find out timing of onset of the puberty in working boys. The study will include 10-18 years of working boys as a case and non-working boys of same age groups as control. Working boys will be labor boys while the control group will not be involved in physical work. A questionnaire will be used to record socioeconomic status, major diseases, nutritional status, type, and duration of work and family history of puberty, growth and obesity of subjects. Boys with familial history of pubertal delay, obesity, malnutrition, mental disorders, hematological diseases and severe/chronic diseases will be excluded. The intensity of physical working stress will be determined by a grading scale. The anthropometric data including height, weight, body mass index (BMI, bone age, tests of adiposity will be collected from subjects. The stages of pubertal onset will be determined by Tanner staging. Serum concentrations of hormones of growth, thyroid, adrenal, brain-gut and gonadal axis will be determined in nonworking and working boys. Physical and hormonal tests of the working boys and comparison with non-working boys are sufficient to test the idea.

  5. Climate predictability and prediction skill on seasonal time scales over South America from CHFP models

    Science.gov (United States)

    Osman, Marisol; Vera, C. S.

    2016-11-01

    This work presents an assessment of the predictability and skill of climate anomalies over South America. The study was made considering a multi-model ensemble of seasonal forecasts for surface air temperature, precipitation and regional circulation, from coupled global circulation models included in the Climate Historical Forecast Project. Predictability was evaluated through the estimation of the signal-to-total variance ratio while prediction skill was assessed computing anomaly correlation coefficients. Both indicators present over the continent higher values at the tropics than at the extratropics for both, surface air temperature and precipitation. Moreover, predictability and prediction skill for temperature are slightly higher in DJF than in JJA while for precipitation they exhibit similar levels in both seasons. The largest values of predictability and skill for both variables and seasons are found over northwestern South America while modest but still significant values for extratropical precipitation at southeastern South America and the extratropical Andes. The predictability levels in ENSO years of both variables are slightly higher, although with the same spatial distribution, than that obtained considering all years. Nevertheless, predictability at the tropics for both variables and seasons diminishes in both warm and cold ENSO years respect to that in all years. The latter can be attributed to changes in signal rather than in the noise. Predictability and prediction skill for low-level winds and upper-level zonal winds over South America was also assessed. Maximum levels of predictability for low-level winds were found were maximum mean values are observed, i.e. the regions associated with the equatorial trade winds, the midlatitudes westerlies and the South American Low-Level Jet. Predictability maxima for upper-level zonal winds locate where the subtropical jet peaks. Seasonal changes in wind predictability are observed that seem to be related to

  6. Prediction of antibiotic resistance: time for a new preclinical paradigm?

    DEFF Research Database (Denmark)

    Sommer, Morten Otto Alexander; Munck, Christian; Toft-Kehler, Rasmus Vendler

    2017-01-01

    Predicting the future is difficult, especially for evolutionary processes that are influenced by numerous unknown factors. Still, this is what is required of drug developers when they assess the risk of resistance arising against a new antibiotic candidate during preclinical development. In this ......Predicting the future is difficult, especially for evolutionary processes that are influenced by numerous unknown factors. Still, this is what is required of drug developers when they assess the risk of resistance arising against a new antibiotic candidate during preclinical development....... In this Opinion article, we argue that the traditional procedures that are used for the prediction of antibiotic resistance today could be markedly improved by including a broader analysis of bacterial fitness, infection dynamics, horizontal gene transfer and other factors. This will lead to more informed...

  7. Real-Time Optimization for Economic Model Predictive Control

    DEFF Research Database (Denmark)

    Sokoler, Leo Emil; Edlund, Kristian; Frison, Gianluca

    2012-01-01

    In this paper, we develop an efficient homogeneous and self-dual interior-point method for the linear programs arising in economic model predictive control. To exploit structure in the optimization problems, the algorithm employs a highly specialized Riccati iteration procedure. Simulations show...

  8. Predicting the Timing and Location of the next Hawaiian Volcano

    Science.gov (United States)

    Russo, Joseph; Mattox, Stephen; Kildau, Nicole

    2010-01-01

    The wealth of geologic data on Hawaiian volcanoes makes them ideal for study by middle school students. In this paper the authors use existing data on the age and location of Hawaiian volcanoes to predict the location of the next Hawaiian volcano and when it will begin to grow on the floor of the Pacific Ocean. An inquiry-based lesson is also…

  9. Generalized dualities in one-time physics as holographic predictions from two-time physics

    Science.gov (United States)

    Araya, Ignacio J.; Bars, Itzhak

    2014-03-01

    In the conventional formalism of physics, with one time, systems with different Hamiltonians or Lagrangians have different physical interpretations and are considered to be independent systems unrelated to each other. However, in this paper we construct explicitly canonical maps in one-time (1T) phase space (including timelike components, specifically the Hamiltonian) to show that it is appropriate to regard various 1T physics systems, with different Lagrangians or Hamiltonians, as being duals of each other. This concept is similar in spirit to dualities discovered in more complicated examples in field theory or string theory. Our approach makes it evident that such generalized dualities are widespread. This suggests that, as a general phenomenon, there are hidden relations and hidden symmetries that conventional 1T physics does not capture, implying the existence of a more unified formulation of physics that naturally supplies the hidden information. In fact, we show that two-time (2T) physics in (d +2) dimensions is the generator of these dualities in 1T physics in d dimensions by providing a holographic perspective that unifies all the dual 1T systems into one. The unifying ingredient is a gauge symmetry in phase space. Via such dualities it is then possible to gain new insights toward new physical predictions not suspected before, and suggest new methods of computation that yield results not obtained before. As an illustration, we will provide concrete examples of 1T systems in classical mechanics that are solved analytically for the first time via our dualities. These dualities in classical mechanics have counterparts in quantum mechanics and field theory, and in some simpler cases they have already been constructed in field theory. We comment on the impact of our approach on the meaning of space-time and on the development of new computational methods based on dualities.

  10. Climate Prediction Center (CPC) Global Precipitation Time Series

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global precipitation time series provides time series charts showing observations of daily precipitation as well as accumulated precipitation compared to normal...

  11. Climate Prediction Center (CPC) Global Temperature Time Series

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The global temperature time series provides time series charts using station based observations of daily temperature. These charts provide information about the...

  12. EFFECT OF GnRH AND PHOSPHORUS IN DELAYED PUBERTAL SURTI BUFFALO HEIFERS

    Directory of Open Access Journals (Sweden)

    H.B. Dhamsaniya

    2016-06-01

    Full Text Available The study was conducted on eighteen delayed pubertal Surti buffalo heifers, divided into three equal groups (6 in each to evaluate the efficacy of GnRH alone and in combination of phosphorus. The buffalo heifers in Group-I and Group-II were treated with Buserelin acetate (5 ml, IM. Buffalo heifers in Group-II also received additional injection of Toldimphos sodium (10 ml, IM at 3 day interval for 4 times, while buffalo heifers in Group-III served as control. The percentage of induced estrus was highest (83.33% in each treated groups as compared to control group (50%. The mean estrus induction intervals were significantly (P<0.05 shorter in Group-I (20.20 ± 2.18 days and Group-II (18.80 ± 2.32 days as compared to control group (30.24 ± 0.81 days. The conception rate at induced estrus was highest in Group-II (50% followed by Group-I (33.33%. The plasma progesterone levels being significantly lowest on the day of estrus (less than 0.5 ng/ml as compared to pre-treatment days in all groups. The mean total protein and triglycerides levels were differed significantly between the groups on the day of estrus and being significantly higher in Group-II as compared to Group-I and III on that day. A significantly higher level of cholesterol in both treatment groups as compared to the control group during different intervals and also being higher on the day of estrus as compared to pre-treatment days. The mean plasma glucose levels were differed nonsignificantly between and within the treatment and control groups. It is concluded that estrus can be successfully induced in delayed pubertal heifers with the use of GnRH alone and in combination with phosphorus.

  13. Estrus induction and fertility response in delayed pubertal Kankrej heifers treated with norgestomet ear implant

    Directory of Open Access Journals (Sweden)

    C. F. Chaudhari

    Full Text Available Aim: The study was undertaken to find out the estrus induction and fertility response in delayed pubertal Kankrej heifers treated with norgestomet ear implant. Materials and methods: Total eighteen anoestrus Kankrej heifers of delayed puberty weighed above 250 kg and attained between 30 to 36 months of age were selected and divided in to three groups of six animals each at random to conduct the experiment. Animals in group 1 were implanted Crestar ear implant for 9 days. In addition to this, group 2 received 500 IU of PMSG on the day of implant removal. In group 3, treatment protocol remained same as in group 2, but Inj. Receptal @ 2 ml was given additionally at the time of breeding. Results: All the animals exhibited estrus with average duration of 25.41+ 0.94, 21.95+ 0.20 and 22.68 + 1.46 hours between implant withdrawal and estrus induction in group 1, 2 and 3, respectively. The duration of estrus was significantly (P<0.05 longer (25.61+ 2.95 hours in group 2, followed by group 1 (18.88 + 1.45 hours and group 3 (13.48 + 1.92 hours. The pregnancy rate at induced estrus was 33.33 percent in group 2. In group 1 and group 3 none of the heifers found pregnant at induced estrus. The overall conception rate was maximum in group 2 (66.67 percent followed by group 3 (50 percent and group 1 (33.33 percent after the 3rd service. Conclusion: Although the conception rate at induced estrus was lower, norgestomet ear implant could be utilized to induced estrus in delayed pubertal cow heifers. [Vet. World 2012; 5(8.000: 453-458

  14. Pubertal Shifts in Adrenal Responsiveness to Stress and Adrenocorticotropic Hormone in Male Rats

    Science.gov (United States)

    Romeo, Russell D.; Minhas, Sumeet; Svirsky, Sarah E.; Hall, Baila S.; Savenkova, Marina; Karatsoreos, Ilia N.

    2014-01-01

    Summary Studies have indicated significant pubertal-related differences in hormonal stress reactivity. We report here that prepubertal (30d) male rats display a more protracted stress-induced corticosterone response than adults (70d), despite showing relatively similar levels of adrenocorticotropic hormone (ACTH). Additionally, we show that adrenal expression of the ACTH receptor, melanocortin 2 receptor (Mc2r), is higher in prepubertal compared to adult animals, and that expression of melanocortin receptor accessory protein (Mrap), a molecule that chaperones MC2R to the cell surface, is greater in prepubertal males following stress. Given that these data suggest a pubertal shift in adrenal sensitivity to ACTH, we directly tested this possibility by injecting prepubertal and adult males with 6.25 or 9.375 μg/kg of exogenous rat ACTH and measured their hormone levels 30 and 60 min post-injection. As these doses resulted in different circulating levels of ACTH at these two ages, we performed regression analyses to assess the relationship between circulating ACTH and corticosterone concentrations. We found no difference between the ages in the correlation between ACTH and corticosterone levels at the 30 min time point. However, 60 min following the ACTH injection, we found prepubertal rats had significantly higher corticosterone concentrations at lower levels of ACTH compared to adults. These data suggest that prolonged exposure to ACTH leads to greater corticosterone responsiveness prior to puberty, and indicate that changes in adrenal sensitivity to ACTH may, in part, contribute to the protracted hormonal stress response in prepubertal rats. PMID:24636511

  15. Effect of stress hormone antagonists on ovarian follicular development in pre-pubertal rat

    Directory of Open Access Journals (Sweden)

    Kalid Hamood Abdullah

    2012-08-01

    Full Text Available Effect of stress on pre-pubertal ovarian follicular development was studied. Fifteen day old female rats were administered under stress (exposed to maternal separation; 6 hours/day from post-natal day 15 to 21 for 7 days, and appropriate controls were maintained. The time of exposure was randomly changed every day during light phase (7AM to 7 PM of the day to avoid habituation. There was a significant decrease in serum estrogen levels on post-natal day 21 in stress group rats compared to controls indicating stress response in these rats. However, mean number of healthy follicles in all categories of follicles were significantly lower in stressed rats compared to controls. Concomitant with these changes, mean number of atreitic follicles showed an increase over control values in stressed rats. In contrast administration of Naltrexone (5μg NTX/rat/day, Mifepristone (1 μg MP/rat/day, FSH (10 IU FSH/rat/day with stressed the significant increases in the relative weight of ovary, uterus, fallopian tube, body weight and the mean number of healthy follicles in the ovary compared to the controls. In the ovary treatment of stressed did not affect primordial follicles. Primordial follicles were reduced in number significantly in the ovary of controls and treated groups when compared with the initial controls whereas there was no significant variation among the controls and the treated groups. The results indicate that stress dose not interfere with the progress of pre-pubertal follicular development. However, it causes increased loss of follicles by atretia.

  16. Tracking of anthropometric parameters and bioelectrical impedance in pubertal boys and girls.

    Science.gov (United States)

    Leppik, Aire; Jürimäe, Toivo; Jürimäe, Jaak

    2006-12-01

    The aim of this study was to investigate the anthropometric parameters and body impedance once per year during four years of the pubertal period in Estonian children. In total, 81 boys and 86 girls aged 10-11 years at the beginning of the study were investigated. Pubertal status was self-assessed by sexual maturation stages according to Tanner and physical activity index (PAI) according to Telama et al.. Body height and weight were measured and body mass index (BMI) calculated. In total, 9 skinfolds, 13 girths, 8 lengths and 8 breadths/lengths were measured according to the protocol of the International Society for the Advancement of Kinanthropometry. Somatotype components were estimated according to the method of Carter and Heath. Body impedance was measured using Multiscan 5000 (Bodystat, UK) and the impedance index (height/impedance) was calculated. The tracking of body height, weight, BMI, skinfolds, girths, lengths, breadth/lengths and body impedance was high (as a rule r> or =0.9). By increasing the time period, the correlation slightly decreased. In contrast, tracking correlations for PAI and Tanner stages were significant but quite low. Increase in mean body height was highest between 12-13 years of age (6.9 cm per year) in boys and in girls between 11-12 years of age (6.3 cm per year). In boys and girls, the peak increase in body weight was between 11 and 12 years of age, 5.7 kg and 5.2 kg, respectively. With the increasing age, body impedance decreased and impedance index increased. In conclusion, our results indicate that during puberty the detailed anthropometric parameters and body impedance tracked highly. However, the tracking of PAI and Tanner stages was significant but relatively low.

  17. Coping and coping effectiveness in relation to a competitive sport event: pubertal status, chronological age, and gender among adolescent athletes.

    Science.gov (United States)

    Nicholls, Adam; Polman, Remco; Morley, David; Taylor, Natalie J

    2009-06-01

    An aim of this paper was to discover whether athletes of different pubertal status, chronological age, and gender reported distinct coping strategies in response to stress during a competitive event in their sport. A secondary aim was to examine pubertal status group, chronological age, and gender differences in coping effectiveness. Participants were adolescent athletes (n = 527), classified as beginning-pubertal (n = 59), midpubertal (n = 189), advanced-pubertal (n = 237), and postpubertal (n = 22). Findings revealed that there were small, but significant differences in how athletes of different pubertal status and chronological age coped. There were also significant differences between how athletes of different pubertal status perceived the effectiveness of their coping strategies. Interestingly, our results suggested that the relationship between pubertal status and coping and coping effectiveness is different from the relationship between chronological age and coping and coping effectiveness.

  18. Pubertal maturation and sex steroids are related to alcohol use in adolescents.

    Science.gov (United States)

    de Water, Erik; Braams, Barbara R; Crone, Eveline A; Peper, Jiska S

    2013-02-01

    Adolescents often show risk-taking behavior, including experimentation with alcohol. Previous studies have shown that advanced pubertal maturation is related to increased alcohol use in adolescents, even when controlling for age. Little is known about the underlying mechanisms of this relation between pubertal maturation and alcohol use. The goal of the present study was twofold. In Experiment 1, we investigated whether advanced pubertal maturation is associated with higher levels of alcohol use, when controlling for age. To this end, questionnaires on pubertal development and alcohol use were administered to a large sample of 797 Dutch adolescents (405 boys) aged 11-16 years. In Experiment 2, we explored whether sex steroids contribute to this relation between pubertal maturation and alcohol use by examining the association between salivary sex steroid levels and alcohol use in 168 adolescents (86 boys). It was found that, when controlling for age, advanced pubertal maturation is related to increased alcohol use in adolescent boys and girls. Controlling for age, higher testosterone and estradiol levels correlated with the onset of alcohol use in boys. In addition, higher estradiol levels were associated with a larger quantity of alcohol use in boys. Correlations between sex steroids and alcohol use were not significant in girls. These findings show that advanced pubertal maturation is related to advanced alcohol use, and that higher sex steroid levels could be one of the underlying mechanisms of this relation in boys. Sex steroids might promote alcohol use by stimulating brain regions implicated in reward processing.

  19. Online Learning Solutions for Freeway Travel Time Prediction

    NARCIS (Netherlands)

    Van Lint, J.W.C.

    2008-01-01

    Providing travel time information to travelers on available route alternatives in traffic networks is widely believed to yield positive effects on individual drive behavior and (route/departure time) choice behavior, as well as on collective traffic operations in terms of, for example, overall time

  20. Online Learning Solutions for Freeway Travel Time Prediction

    NARCIS (Netherlands)

    Van Lint, J.W.C.

    2008-01-01

    Providing travel time information to travelers on available route alternatives in traffic networks is widely believed to yield positive effects on individual drive behavior and (route/departure time) choice behavior, as well as on collective traffic operations in terms of, for example, overall time

  1. T-CREST: Time-predictable multi-core architecture for embedded systems

    DEFF Research Database (Denmark)

    Schoeberl, Martin; Abbaspourseyedi, Sahar; Jordan, Alexander

    2015-01-01

    Real-time systems need time-predictable platforms to allow static analysis of the worst-case execution time (WCET). Standard multi-core processors are optimized for the average case and are hardly analyzable. Within the T-CREST project we propose novel solutions for time-predictable multi-core ar...

  2. Predictive modelling of running and dwell times in railway traffic

    NARCIS (Netherlands)

    Kecman, P.; Goverde, R.M.P.

    2015-01-01

    Accurate estimation of running and dwell times is important for all levels of planning and control of railway traffic. The availability of historical track occupation data with a high degree of granularity inspired a data-driven approach for estimating these process times. In this paper we present

  3. 'It is Time to Prepare the Next patient' Real-Time Prediction of Procedure Duration in Laparoscopic Cholecystectomies.

    Science.gov (United States)

    Guédon, Annetje C P; Paalvast, M; Meeuwsen, F C; Tax, D M J; van Dijke, A P; Wauben, L S G L; van der Elst, M; Dankelman, J; van den Dobbelsteen, J J

    2016-12-01

    Operating Room (OR) scheduling is crucial to allow efficient use of ORs. Currently, the predicted durations of surgical procedures are unreliable and the OR schedulers have to follow the progress of the procedures in order to update the daily planning accordingly. The OR schedulers often acquire the needed information through verbal communication with the OR staff, which causes undesired interruptions of the surgical process. The aim of this study was to develop a system that predicts in real-time the remaining procedure duration and to test this prediction system for reliability and usability in an OR. The prediction system was based on the activation pattern of one single piece of equipment, the electrosurgical device. The prediction system was tested during 21 laparoscopic cholecystectomies, in which the activation of the electrosurgical device was recorded and processed in real-time using pattern recognition methods. The remaining surgical procedure duration was estimated and the optimal timing to prepare the next patient for surgery was communicated to the OR staff. The mean absolute error was smaller for the prediction system (14 min) than for the OR staff (19 min). The OR staff doubted whether the prediction system could take all relevant factors into account but were positive about its potential to shorten waiting times for patients. The prediction system is a promising tool to automatically and objectively predict the remaining procedure duration, and thereby achieve optimal OR scheduling and streamline the patient flow from the nursing department to the OR.

  4. Networked Control System Time-Delay Compensation Based on Time-Delay Prediction and Improved Implicit GPC

    Directory of Open Access Journals (Sweden)

    Zhong-Da Tian

    2015-01-01

    Full Text Available The random time delay in a networked control system can usually deteriorate the control performance and stability of the networked control system. In order to solve this problem, this paper puts forward a networked control system random time-delay compensation method based on time-delay prediction and improved implicit generalized predictive control (GPC. The least squares support vector machine is used to predict the future time delay of network. The parameters of the least squares support vector machine time-delay prediction model are difficult to determine, and the genetic algorithm is used for least squares support vector machine optimal prediction parameter optimization. Then, an improved implicit generalized predictive control method is adopted to compensate for the time delay. The simulation results show that the method in this paper has high prediction accuracy and a good compensation effect for the random time delay of the networked control system, has a small amount of on-line calculation and that the output response and control stability of the system are improved.

  5. Increased reaction time predicts visual learning deficits in Parkinson's disease

    Science.gov (United States)

    Marinelli, Lucio; Perfetti, Bernardo; Moisello, Clara; Di Rocco, Alessandro; Eidelberg, David; Abbruzzese, Giovanni; Ghilardi, Maria Felice

    2010-01-01

    To determine whether the process involved in movement preparation of patients in the early stages of Parkinson's disease (PD) shares attentional resources with visual learning, we tested 23 patients with PD and 13 normal controls with two different tasks. The first was a motor task where subjects were required to move as soon as possible to randomly presented targets by minimizing reaction time. The second was a visual learning task where targets were presented in a preset order and subjects were asked to learn the sequence order by attending to the display without moving. PD patients showed higher reaction and movement times, while visual learning was reduced compared to controls. For PD patients, reaction times, but not movement times, displayed an inverse significant correlation with the scores of visual learning. We conclude that visual declarative learning and movement preparation might share similar attentional and working memory resources. PMID:20568090

  6. Pubertal bisphenol A exposure alters murine mammary stem cell function leading to early neoplasia in regenerated glands.

    Science.gov (United States)

    Wang, Danhan; Gao, Hui; Bandyopadhyay, Abhik; Wu, Anqi; Yeh, I-Tien; Chen, Yidong; Zou, Yi; Huang, Changjiang; Walter, Christi A; Dong, Qiaoxiang; Sun, Lu-Zhe

    2014-04-01

    Perinatal exposure to bisphenol A (BPA) has been shown to cause aberrant mammary gland morphogenesis and mammary neoplastic transformation. Yet, the underlying mechanism is poorly understood. We tested the hypothesis that mammary glands exposed to BPA during a susceptible window may lead to its susceptibility to tumorigenesis through a stem cell-mediated mechanism. We exposed 21-day-old Balb/c mice to BPA by gavage (25 μg/kg/d) during puberty for 3 weeks, and a subset of animals were further challenged with one oral dose (30 mg/kg) of 7,12-dimethylbenz(a)anthracene (DMBA) at 2 months of age. Primary mammary cells were isolated at 6 weeks, and 2 and 4 months of age for murine mammary stem cell (MaSC) quantification and function analysis. Pubertal exposure to the low-dose BPA increased lateral branches and hyperplasia in adult mammary glands and caused an acute increase of MaSC in 6-week-old glands and a delayed increase of luminal progenitors in 4-month-old adult gland. Most importantly, pubertal BPA exposure altered the function of MaSC from different age groups, causing early neoplastic lesions in their regenerated glands similar to those induced by DMBA exposure, which indicates that MaSCs are susceptible to BPA-induced transformation. Deep sequencing analysis on MaSC-enriched mammospheres identified a set of aberrantly expressed genes associated with early neoplastic lesions in patients with human breast cancer. Thus, our study for the first time shows that pubertal BPA exposure altered MaSC gene expression and function such that they induced early neoplastic transformation.

  7. Prediction of residence time distributions in food processing machinery

    DEFF Research Database (Denmark)

    Karlson, Torben; Friis, Alan; Szabo, Peter

    1996-01-01

    The velocity field in a co-rotating disc scraped surface heat exchanger (CDHE) is calculated using a finite element method. The residence time distribution for the CDHE is then obtained by tracing particles introduced in the inlet.......The velocity field in a co-rotating disc scraped surface heat exchanger (CDHE) is calculated using a finite element method. The residence time distribution for the CDHE is then obtained by tracing particles introduced in the inlet....

  8. Prediction of residence time distributions in food processing machinery

    DEFF Research Database (Denmark)

    Karlson, Torben; Friis, Alan; Szabo, Peter

    1996-01-01

    The velocity field in a co-rotating disc scraped surface heat exchanger (CDHE) is calculated using a finite element method. The residence time distribution for the CDHE is then obtained by tracing particles introduced in the inlet.......The velocity field in a co-rotating disc scraped surface heat exchanger (CDHE) is calculated using a finite element method. The residence time distribution for the CDHE is then obtained by tracing particles introduced in the inlet....

  9. Predictive Information Rate in Discrete-time Gaussian Processes

    CERN Document Server

    Abdallah, Samer A

    2012-01-01

    We derive expressions for the predicitive information rate (PIR) for the class of autoregressive Gaussian processes AR(N), both in terms of the prediction coefficients and in terms of the power spectral density. The latter result suggests a duality between the PIR and the multi-information rate for processes with mutually inverse power spectra (i.e. with poles and zeros of the transfer function exchanged). We investigate the behaviour of the PIR in relation to the multi-information rate for some simple examples, which suggest, somewhat counter-intuitively, that the PIR is maximised for very `smooth' AR processes whose power spectra have multiple poles at zero frequency. We also obtain results for moving average Gaussian processes which are consistent with the duality conjectured earlier. One consequence of this is that the PIR is unbounded for MA(N) processes.

  10. Time Series Prediction based on Hybrid Neural Networks

    Directory of Open Access Journals (Sweden)

    S. A. Yarushev

    2016-01-01

    Full Text Available In this paper, we suggest to use hybrid approach to time series forecasting problem. In first part of paper, we create a literature review of time series forecasting methods based on hybrid neural networks and neuro-fuzzy approaches. Hybrid neural networks especially effective for specific types of applications such as forecasting or classification problem, in contrast to traditional monolithic neural networks. These classes of problems include problems with different characteristics in different modules. The main part of paper create a detailed overview of hybrid networks benefits, its architectures and performance under traditional neural networks. Hybrid neural networks models for time series forecasting are discussed in the paper. Experiments with modular neural networks are given.

  11. A pre-pubertal girl with giant juvenile fibroadenoma: A rare case report

    Directory of Open Access Journals (Sweden)

    Kumar Gaurav

    2015-01-01

    Conclusion: Through this case we want to emphasize that these giant benign neoplasms should be suspected in any pre-pubertal girl with breast lump and should always be treated with breast conserving surgery.

  12. Insulin resistance in obese pre-pubertal children: Relation to body ...

    African Journals Online (AJOL)

    Heba Elsedfy

    2014-04-16

    Apr 16, 2014 ... sensitivity indices and investigate its relationship with abdominal fat distribution by Dual energy ... associated with negative metabolic predictors in pubertal ..... metabolic determinants of nonalcoholic fatty liver disease in.

  13. Maternal pre-pregnancy body mass index and pubertal development among sons

    DEFF Research Database (Denmark)

    Hounsgaard, M L; Håkonsen, L B; Vested, A

    2013-01-01

    Maternal overweight and obesity in pregnancy has been associated with earlier age of menarche in daughters as well as reduced semen quality in sons. We aimed at investigating pubertal development in sons born by mothers with a high body mass index (BMI). The study included 2522 sons of mothers...... that during pregnancy in 1984-1987 were enrolled in a mother-child cohort and gave information on their pre-pregnancy height and weight from which we calculated their BMI. Information on sons' pubertal development, assessed by age when starting regular shaving, voice break, acne and first nocturnal emission...... indicators of pubertal development, results also indicated earlier pubertal development among sons of obese mothers. After excluding sons of underweight mothers in a subanalysis, we observed an inverse trend between maternal pre-pregnancy BMI and age at regular shaving, acne and first nocturnal emission...

  14. Predicting the Timing of Women's Departure from Abusive Relationships

    Science.gov (United States)

    Panchanadeswaran, Subadra; McCloskey, Laura A.

    2007-01-01

    The aim of this study was to investigate forces that affect the timing of women's exit from violent relationships with men. Abused women were recruited from posters in the community and battered women's shelters, interviewed, and followed up for 10 years. Data for this study are based on 100 women and were analyzed using event history analysis.…

  15. Predicting seed dormancy loss and germination timing for Bromus tectorum in a semi-arid environment using hydrothermal time models

    Science.gov (United States)

    Susan E. Meyer; Phil S. Allen

    2009-01-01

    A principal goal of seed germination modelling for wild species is to predict germination timing under fluctuating field conditions. We coupled our previously developed hydrothermal time, thermal and hydrothermal afterripening time, and hydration-dehydration models for dormancy loss and germination with field seed zone temperature and water potential measurements from...

  16. Meditation-induced states predict attentional control over time.

    Science.gov (United States)

    Colzato, Lorenza S; Sellaro, Roberta; Samara, Iliana; Baas, Matthijs; Hommel, Bernhard

    2015-12-01

    Meditation is becoming an increasingly popular topic for scientific research and various effects of extensive meditation practice (ranging from weeks to several years) on cognitive processes have been demonstrated. Here we show that extensive practice may not be necessary to achieve those effects. Healthy adult non-meditators underwent a brief single session of either focused attention meditation (FAM), which is assumed to increase top-down control, or open monitoring meditation (OMM), which is assumed to weaken top-down control, before performing an Attentional Blink (AB) task - which assesses the efficiency of allocating attention over time. The size of the AB was considerably smaller after OMM than after FAM, which suggests that engaging in meditation immediately creates a cognitive-control state that has a specific impact on how people allocate their attention over time.

  17. Prediction of dynamic expected time to system failure

    Energy Technology Data Exchange (ETDEWEB)

    Oh, Deog Yeon; Lee, Chong Chul [Korea Nuclear Fuel Co., Ltd., Taejon (Korea, Republic of)

    1997-12-31

    The mean time to failure (MTTF) expressing the mean value of the system life is a measure of system effectiveness. To estimate the remaining life of component and/or system, the dynamic mean time to failure concept is suggested. It is the time-dependent property depending on the status of components. The Kalman filter is used to estimate the reliability of components using the on-line information (directly measured sensor output or device-specific diagnostics in the intelligent sensor) in form of the numerical value (state factor). This factor considers the persistency of the fault condition and confidence level in measurement. If there is a complex system with many components, each calculated reliability`s of components are combined, which results in the dynamic MTTF of system. The illustrative examples are discussed. The results show that the dynamic MTTF can well express the component and system failure behaviour whether any kinds of failure are occurred or not. 9 refs., 6 figs. (Author)

  18. [Consumptions of Meat and Dairy Products, Zinc Intake and Pubertal Development in Adolescents in Chengdu].

    Science.gov (United States)

    Luo, Jiao; Yang, Ming-zhe; Duan, Ruo-nan; Tian, Guo; Bao, Yu-xin; Chen, Yan-rong; Xue, Hong-mei; Liu, Yan; Cheng, Guo

    2015-09-01

    To determine the associations between meat, dairy and zinc intake and pubertal development in adolescents in Chengdu. A total of 1320 children and adolescents aged 9-15 years in Chengdu were recruited using a stratified cluster sampling strategy. Dietary intake was assessed by the food frequency questionnaire (FFQ) and 3-day 24-hour dietary recall. Pubertal development was evaluated through physical examinations. Consumptions of meat and dairy, and zinc intake were compared between groups with different levels of pubertal development according to the Tanner criteria. The median age of spermarche was 13. 00 years. The boys who had had spermarche consumed more meat (including red meat) and dairy products than those who had not yet (Pmeat was positively correlated with the level of pubertal development (Pmeat and less diiry products than those who had not yet (Pproducts was negatively associated with breast development and the level of pubertal development (P meat, red meat and dairy products are associated with pubertal development in adolescents in Chengdu. However, the differences between boys and girls warrant further studies.

  19. PRE-PUBERTAL CHILDREN AND EXERCISE IN HOT AND HUMID ENVIRONMENTS: A BRIEF REVIEW

    Directory of Open Access Journals (Sweden)

    Wade H. Sinclair

    2007-12-01

    Full Text Available The ability of pre-pubertal children to regulate their body temperature under thermoneutral environments is similar to that of an adult albeit via differing routes. However, this ability is challenged when exposed to extreme environments. Thermoregulatory responses of pre-pubertal children differ from adults via adaptations that occur during growth and maturation and disadvantage children when exercising in hot and humid environments. When ambient temperatures exceed that of the skin, an influx of thermal energy from the environment increases thermal stress. When coupled with exercise, the increased thermal stress results in reduced physical performance and an increased risk of developing heat-related illness. Evidence suggesting the severity of heat-related illness is greater in pre-pubertal children than adults is inconclusive because age-related differences in thermoregulatory responses are attributed to either morphologic or functional changes. Additionally, the majority of research on pre-pubertal children exercising in the heat has been maturational or comparative studies with adults conducted in the near absence of convective cooling, complicating extrapolation to field-based environments. However, current consensus is that pre-pubertal children are disadvantaged when exercising in extreme temperatures and that care should be taken in preparing for and conducting sporting activities in hot and humid environments for pre-pubertal children

  20. Time-dependent Integrated Predictive Modeling of ITER Plasmas

    Institute of Scientific and Technical Information of China (English)

    R.V. Budny

    2007-01-01

    @@ Introduction Modeling burning plasmas is important for speeding progress toward practical Tokamak energy production. Examples of issues that can be elucidated by modelinginclude requirements for heating, fueling, torque, and current drive systems, design of diagnostics, and estimates of the plasma performance (e.g., fusion power production) in various plasma scenarios. The modeling should be time-dependent to demonstrate that burning plasmas can be created, maintained (controlled), and terminated successfully. The modeling also should be integrated to treat self-consistently the nonlinearities and strong coupling between the plasma, heating, current drive, confinement, and control systems.

  1. Nonlinear Time Series Prediction Using Chaotic Neural Networks

    Institute of Scientific and Technical Information of China (English)

    LI KePing; CHEN TianLun

    2001-01-01

    A nonlinear feedback term is introduced into the evaluation equation of weights of the backpropagation algorithm for neural network, the network becomes a chaotic one. For the purpose of that we can investigate how the different feedback terms affect the process of learning and forecasting, we use the model to forecast the nonlinear time series which is produced by Makey-Glass equation. By selecting the suitable feedback term, the system can escape from the local minima and converge to the global minimum or its approximate solutions, and the forecasting results are better than those of backpropagation algorithm.``

  2. Improving predictability of time series using maximum entropy methods

    Science.gov (United States)

    Chliamovitch, G.; Dupuis, A.; Golub, A.; Chopard, B.

    2015-04-01

    We discuss how maximum entropy methods may be applied to the reconstruction of Markov processes underlying empirical time series and compare this approach to usual frequency sampling. It is shown that, in low dimension, there exists a subset of the space of stochastic matrices for which the MaxEnt method is more efficient than sampling, in the sense that shorter historical samples have to be considered to reach the same accuracy. Considering short samples is of particular interest when modelling smoothly non-stationary processes, which provides, under some conditions, a powerful forecasting tool. The method is illustrated for a discretized empirical series of exchange rates.

  3. Airport noise predicts song timing of European birds.

    Science.gov (United States)

    Dominoni, Davide M; Greif, Stefan; Nemeth, Erwin; Brumm, Henrik

    2016-09-01

    Anthropogenic noise is of increasing concern to biologists and medical scientists. Its detrimental effects on human health have been well studied, with the high noise levels from air traffic being of particular concern. However, less is known about the effects of airport noise pollution on signal masking in wild animals. Here, we report a relationship between aircraft noise and two major features of the singing behavior of birds. We found that five of ten songbird species began singing significantly earlier in the morning in the vicinity of a major European airport than their conspecifics at a quieter control site. As birds at both sites started singing before the onset of air traffic in the morning, this suggests that the birds in the vicinity of the airport advanced their activity to gain more time for unimpaired singing before the massive plane noise set in. In addition, we found that during the day, chaffinches avoided singing during airplane takeoffs, but only when the noise exceeded a certain threshold, further suggesting that the massive noise caused by the airport can impair acoustic communication in birds. Overall, our study indicates that birds may be adjusting their mating signals and time budgets in response to aircraft noise.

  4. Nonlinear Time Series Prediction Using LS-SVM with Chaotic Mutation Evolutionary Programming for Parameter Optimization

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Nonlinear time series prediction is studied by using an improved least squares support vector machine (LSSVM) regression based on chaotic mutation evolutionary programming (CMEP) approach for parameter optimization.We analyze how the prediction error varies with different parameters (σ, γ) in LS-SVM. In order to select appropriate parameters for the prediction model, we employ CMEP algorithm. Finally, Nasdaq stock data are predicted by using this LS-SVM regression based on CMEP, and satisfactory results are obtained.

  5. Predicting heartbeat arrival time for failure detection over internet using auto-regressive exogenous model

    Institute of Scientific and Technical Information of China (English)

    Zhao Haijun; Ma Yan; Huang Xiaohong; Su Yujie

    2008-01-01

    Predicting heartbeat message arrival time is crucial for the quality of failure detection service over internet. However, internet dynamic characteristics make it very difficult to understand message behavior and accurately predict heartbeat arrival time. To solve this problem, a novel black-box model is proposed to predict the next heartbeat arrival time. Heartbeat arrival time is modeled as auto-regressive process, heartbeat sending time is modeled as exogenous variable, the model's coefficients are estimated based on the sliding window of observations and this result is used to predict the next heartbeat arrival time. Simulation shows that this adaptive auto-regressive exogenous (ARX) model can accurately capture heartbeat arrival dynamics and minimize prediction error in different network environments.

  6. Prediction and analysis of chaotic time series on the basis of support vector

    Institute of Scientific and Technical Information of China (English)

    Li Tianliang; He Liming; Li Haipeng

    2008-01-01

    Based on discussion on the theories of support vector machines(SVM),an one-step prediction model for time series prediction is presented,wherein the chaos theory is incorporated.Chaotic character of the time series is taken into account in the prediction procedure;parameters of reconstruction-delay and embedding-dimension for phase-space reconstruction are calculated in light of mutual-information and false-nearest-neighbor method,respectively.Precision and functionality have been demonstrated by the experimental results on the basis of the prediction of Lorenz chaotic time series.

  7. Near Real Time MISR Wind Observations for Numerical Weather Prediction

    Science.gov (United States)

    Mueller, K. J.; Protack, S.; Rheingans, B. E.; Hansen, E. G.; Jovanovic, V. M.; Baker, N.; Liu, J.; Val, S.

    2014-12-01

    The Multi-angle Imaging SpectroRadiometer (MISR) project, in association with the NASA Langley Atmospheric Science Data Center (ASDC), has this year adapted its original production software to generate near-real time (NRT) cloud-motion winds as well as radiance imagery from all nine MISR cameras. These products are made publicly available at the ASDC with a latency of less than 3 hours. Launched aboard the sun-synchronous Terra platform in 1999, the MISR instrument continues to acquire near-global, 275 m resolution, multi-angle imagery. During a single 7 minute overpass of any given area, MISR retrieves the stereoscopic height and horizontal motion of clouds from the multi-angle data, yielding meso-scale near-instantaneous wind vectors. The ongoing 15-year record of MISR height-resolved winds at 17.6 km resolution has been validated against independent data sources. Low-level winds dominate the sampling, and agree to within ±3 ms-1 of collocated GOES and other observations. Low-level wind observations are of particular interest to weather forecasting, where there is a dearth of observations suitable for assimilation, in part due to reliability concerns associated with winds whose heights are assigned by the infrared brightness temperature technique. MISR cloud heights, on the other hand, are generated from stereophotogrammetric pattern matching of visible radiances. MISR winds also address data gaps in the latitude bands between geostationary satellite coverage and polar orbiting instruments that obtain winds from multiple overpasses (e.g. MODIS). Observational impact studies conducted by the Naval Research Laboratory (NRL) and by the German Weather Service (Deutscher Wetterdienst) have both demonstrated forecast improvements when assimilating MISR winds. An impact assessment using the GEOS-5 system is currently in progress. To benefit air quality forecasts, the MISR project is currently investigating the feasibility of generating near-real time aerosol products.

  8. Real Time Volcanic Cloud Products and Predictions for Aviation Alerts

    Science.gov (United States)

    Krotkov, Nickolay A.; Habib, Shahid; da Silva, Arlindo; Hughes, Eric; Yang, Kai; Brentzel, Kelvin; Seftor, Colin; Li, Jason Y.; Schneider, David; Guffanti, Marianne; Hoffman, Robert L.; Myers, Tim; Tamminen, Johanna; Hassinen, Seppo

    2014-01-01

    Volcanic eruptions can inject significant amounts of sulfur dioxide (SO2) and volcanic ash into the atmosphere, posing a substantial risk to aviation safety. Ingesting near-real time and Direct Readout satellite volcanic cloud data is vital for improving reliability of volcanic ash forecasts and mitigating the effects of volcanic eruptions on aviation and the economy. NASA volcanic products from the Ozone Monitoring Insrument (OMI) aboard the Aura satellite have been incorporated into Decision Support Systems of many operational agencies. With the Aura mission approaching its 10th anniversary, there is an urgent need to replace OMI data with those from the next generation operational NASA/NOAA Suomi National Polar Partnership (SNPP) satellite. The data provided from these instruments are being incorporated into forecasting models to provide quantitative ash forecasts for air traffic management. This study demonstrates the feasibility of the volcanic near-real time and Direct Readout data products from the new Ozone Monitoring and Profiling Suite (OMPS) ultraviolet sensor onboard SNPP for monitoring and forecasting volcanic clouds. The transition of NASA data production to our operational partners is outlined. Satellite observations are used to constrain volcanic cloud simulations and improve estimates of eruption parameters, resulting in more accurate forecasts. This is demonstrated for the 2012 eruption of Copahue. Volcanic eruptions are modeled using the Goddard Earth Observing System, Version 5 (GEOS-5) and the Goddard Chemistry Aerosol and Radiation Transport (GOCART) model. A hindcast of the disruptive eruption from Iceland's Eyjafjallajokull is used to estimate aviation re-routing costs using Metron Aviation's ATM Tools.

  9. Stress induced alterations in pre-pubertal ovarian follicular development in rat

    Directory of Open Access Journals (Sweden)

    Yajurvedi H.N.

    2011-12-01

    Full Text Available The objective of the study was to find out whether stress experienced during neo-natal period alters the timing of formation of pre-antral and antral follicles and if so, whether pre-treatment with CRH receptor antagonist prevents these effects in rats. New born rat pups (n= 15 were exposed to maternal separation (6 hours/ day from post-natal day (PND 1 to 7 and were killed on PND 8, 11 and 15. The time of exposure was randomly changed every day during light phase (7Am to 7Pm of the day to avoid habituation. There was a significant increase in serum corticosterone levels on PND 8 and 11 in stress group rats compared to controls indicating stress response in these pups. The ovary of both control and stressed rats contained oocytes and primary follicles on PND 8 and 11 and in showed progress of follicular development upto to pre-antral and early antral follicle formation on PND 11 and 15. However, mean number of healthy oocytes and all categories of follicles at all ages studied were significantly lower in stressed rats compared to controls. Concomitant with these changes, number of atreatic follicles showed an increase over control values in stressed rats. The increase in atresia of follicles was due to apoptosis as shown by increase in the percentage of granulosa cells showing TUNEL positive staining and caspase 3 activity. On the other hand, pre-treatment with CRH- receptor antagonist (CRH 9-41 2ng/ 0.1 ml/ rat prior to undergoing stress regime on PND 1 to 7, prevented alterations in pre- pubertal follicular development thereby indicating that the ovarian changes were due to effects of stress induced activation of HPA axis. The results indicate that, stress during neonatal phase, though does not affect timing of formation of pre-antral and antral follicles, it does enhance atresia of follicles of all categories, including follicular reserve, which may affect the reproductive potential of adults. The results, for the first time reveal that CRF

  10. The Time and Cost Prediction of Tunnel Boring Machine in Tunnelling

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Making use of microsoft visual studio. net platform, the assistant decision-making system of tunnel boring machine in tunnelling has been built to predict the time and cost. Computation methods of the performance parameters have been discussed. New time and cost prediction models have been depicted. The multivariate linear regression has been used to make the parameters more precise, which are the key factor to affect the prediction near to the reality.

  11. Discussion of Some Problems About Nonlinear Time Series Prediction Using v-Support Vector Machine

    Institute of Scientific and Technical Information of China (English)

    GAO Cheng-Feng; CHEN Tian-Lun; NAN Tian-Shi

    2007-01-01

    Some problems in using v-support vector machine (v-SVM) for the prediction of nonlinear time series are discussed. The problems include selection of various net parameters, which affect the performance of prediction, mixture of kernels, and decomposition cooperation linear programming v-SVM regression, which result in improvements of the algorithm. Computer simulations in the prediction of nonlinear time series produced by Mackey-Glass equation and Lorenz equation provide some improved results.

  12. Neural Underpinnings of Impaired Predictive Motor Timing in Children with Developmental Coordination Disorder

    Science.gov (United States)

    Debrabant, Julie; Gheysen, Freja; Caeyenberghs, Karen; Van Waelvelde, Hilde; Vingerhoets, Guy

    2013-01-01

    A dysfunction in predictive motor timing is put forward to underlie DCD-related motor problems. Predictive timing allows for the pre-selection of motor programmes (except "program" in computers) in order to decrease processing load and facilitate reactions. Using functional magnetic resonance imaging (fMRI), this study investigated the neural…

  13. Theoretical Prediction and Experimental Determination of Heating Time During High-Temperature Heat Treatment of Wood

    Directory of Open Access Journals (Sweden)

    LIU Xin-you

    2011-06-01

    Full Text Available Theoretical prediction provides basic understanding and guidance to correctly implement a certaintechnology in the production process. The present study uses a differential equation to predict the heattransfer time between the surface and core layer of wood during the heat treatment, with applicability inestimating the duration of heat treatments at high temperatures. The obtained prediction was compared withthe result of an experimental study performed on Chinese poplar wood with various thicknesses (20, 40 and60mm. During this experiment, the time necessary for the core of wood to reach a temperature of 100°C,130°C and finally 180°C was monitored and the recorded values were compared with the predicted ones.The result of this comparison proved that the experimental values matched the theoretically predicted times,validating thus the applicability of the proposed equation as prediction tool.

  14. Maternal swimming exercise during pregnancy attenuates anxiety/depressive-like behaviors and voluntary morphine consumption in the pubertal male and female rat offspring born from morphine dependent mothers.

    Science.gov (United States)

    Torabi, Masoumeh; Pooriamehr, Alireza; Bigdeli, Imanollah; Miladi-Gorji, Hossein

    2017-09-01

    This study was designed to examine whether maternal swimming exercise during pregnancy would attenuate prenatally morphine-induced anxiety, depression and voluntary consumption of morphine in the pubertal male and female rat offspring. Pregnant rats during the development of morphine dependence were allowed to swim (30-45min/d, 3days per a week) on gestational days 11-18. Then, the pubertal male and female rat offspring were tested for the elevated plus-maze (EPM), sucrose preference test (SPT) and voluntary morphine consumption using a two-bottle choice (TBC) paradigm. The results showed that male and female rat offspring born of the swimmer morphine-dependent mothers exhibited an increase in EPM open arm time and entries, higher levels of sucrose preference than their sedentary control mothers. Voluntary consumption of morphine was less in the male and female rat offspring born of the swimmer morphine-dependent mothers as compared with their sedentary control mothers during three periods of the intake of drug. Thus, swimming exercise in pregnant morphine dependent mothers decreased anxiety, depressive-like behavior and also the voluntary morphine consumption in the pubertal male and female offspring, which may prevent prenatally morphine-induced behavioral sensitization in offspring. Copyright © 2017 Elsevier B.V. All rights reserved.

  15. Effects on steroid hormones secretion resulting from the acute stimulation of sectioning the superior ovarian nerve to pre-pubertal rats

    Directory of Open Access Journals (Sweden)

    Morales-Ledesma Leticia

    2012-10-01

    Full Text Available Abstract In the adult rat, neural signals arriving to the ovary via the superior ovarian nerve (SON modulate progesterone (P4, testosterone (T and estradiol (E2 secretion. The aims of the present study were to analyze if the SON in the pre-pubertal rat also modulates ovarian hormone secretion and the release of follicle stimulating hormone (FSH and luteinizing (LH hormone. P4, T, E2, FSH and LH serum levels were measured 30 or 60 minutes after sectioning the SON of pre-pubertal female rats. Our results indicate that the effects on hormone levels resulting from unilaterally or bilaterally sectioning the SON depends on the analyzed hormone, and the time lapse between surgery and autopsy, and that the treatment yielded asymmetric results. The results also suggest that in the pre-pubertal rat the neural signals arriving to the ovaries via the SON regulate the enzymes participating in P4, T and E2 synthesis in a non-parallel way, indicating that the mechanisms regulating the synthesis of each hormone are not regulated by the same signals. Also, that the changes in the steroids hormones are not explained exclusively by the modifications in gonadotropins secretion. The observed differences in hormone levels between rats sacrificed 30 and 60 min after surgery reflect the onset of the compensatory systems regulating hormones secretion.

  16. A wavelet-based approach to assessing timing errors in hydrologic predictions

    Science.gov (United States)

    Liu, Yuqiong; Brown, James; Demargne, Julie; Seo, Dong-Jun

    2011-02-01

    SummaryStreamflow predictions typically contain errors in both the timing and the magnitude of peak flows. These two types of error often originate from different sources (e.g. rainfall-runoff modeling vs. routing) and hence may have different implications and ramifications for both model diagnosis and decision support. Thus, where possible and relevant, they should be distinguished and separated in model evaluation and forecast verification applications. Distinct information on timing errors in hydrologic prediction could lead to more targeted model improvements in a diagnostic evaluation context, as well as better-informed decisions in many practical applications, such as flood prediction, water supply forecasting, river regulation, navigation, and engineering design. However, information on timing errors in hydrologic predictions is rarely evaluated or provided. In this paper, we discuss the importance of assessing and quantifying timing error in hydrologic predictions and present a new approach, which is based on the cross wavelet transform (XWT) technique. The XWT technique transforms the time series of predictions and corresponding observations into a two-dimensional time-scale space and provides information on scale- and time-dependent timing differences between the two time series. The results for synthetic timing errors (both constant and time-varying) indicate that the XWT-based approach can estimate timing errors in streamflow predictions with reasonable reliability. The approach is then employed to analyze the timing errors in real streamflow simulations for a number of headwater basins in the US state of Texas. The resulting timing error estimates were consistent with the physiographic and climatic characteristics of these basins. A simple post-factum timing adjustment based on these estimates led to considerably improved agreement between streamflow observations and simulations, further illustrating the potential for using the XWT-based approach for

  17. A Vehicle Traveling Time Prediction Method Based on Grey Theory and Linear Regression Analysis

    Institute of Scientific and Technical Information of China (English)

    TU Jun; LI Yan-ming; LIU Cheng-liang

    2009-01-01

    Vehicle traveling time prediction is an important part of the research of intelligent transportation system. By now, there have been various kinds of methods for vehicle traveling time prediction. But few consider both aspects of time and space. In this paper, a vehicle traveling time prediction method based on grey theory (GT) and linear regression analysis (LRA) is presented. In aspects of time, we use the history data sequence of bus speed on a certain road to predict the future bus speed on that road by GT. And in aspects of space, we calculate the traffic affecting factors between various roads by LRA. Using these factors we can predict the vehicle's speed at the lower road if the vehicle's speed at the current road is known. Finally we use time factor and space factor as the weighting factors of the two results predicted by GT and LRA respectively to find the fina0l result, thus calculating the vehicle's travehng time. The method also considers such factors as dwell time, thus making the prediction more accurate.

  18. Efficient Worst-Case Execution Time Analysis of Dynamic Branch Prediction

    DEFF Research Database (Denmark)

    Puffitsch, Wolfgang

    2016-01-01

    Dynamic branch prediction is commonly found in modern processors, but notoriously difficult to model for worst-case execution time analysis. This is particularly true for global dynamic branch predictors, where predictions are influenced by the global branch history. Prior research in this area has...... concluded that modeling of global branch prediction is too costly for practical use. This paper presents an approach to model global branch prediction while keeping the analysis effort reasonably low. The approach separates the branch history analysis from the integer linear programming formulation...... of the worst-case execution time problem. Consequently, the proposed approach scales to longer branch history lengths than previous approaches....

  19. Prediction of chaotic time series based on modified minimax probability machine regression

    Institute of Scientific and Technical Information of China (English)

    Sun Jian-Cheng

    2007-01-01

    Long-term prediction of chaotic time series is very difficult, for the chaos restricts predictability. In thie paper a new method is studied to model and predict chaotic time series based on minimax probability machine regression (MPMR). Since the positive global Lyapunov exponents lead the errors to increase exponentially in modelling the chaotic time series, a weighted term is introduced to compensate a cost function. Using mean square error (MSE) and absolute error (AE) as a criterion, simulation results show that the proposed method is more effective and accurate for multistep prediction. It can identify the system characteristics quite well and provide a new way to make long-term predictions of the chaotic time series.

  20. Attachment, parenting styles and bullying during pubertal years.

    Science.gov (United States)

    van der Watt, Ronél

    2014-01-01

    Research that focuses on combining attachment, parenting styles, bullying and the reciprocal nature thereof in the parent-adolescent and peer relationships is limited. The bio-psychosocial changes that adolescents experience open up broader social realities and are perceived differently by parents and adolescents. Attachment processes and parenting styles may elicit dissimilar perceptions. These processes are also associated with the multifaceted dynamics of bullying. The aim of the article is to advocate for research on the possible link between the implications of attachment, parenting styles and bullying. Exploring the association between attachment, parenting styles and bullying can deepen the understanding of the developmental challenges within the parent-adolescent relationship, add insight to the different perceptions of adolescents and parents, and complement intervention programmes accordingly. Firstly, this article outlines bio-psychosocial changes in the pubertal years as related to the social realities of the adolescent. Secondly, a discussion on the concepts 'attachment', 'parenting styles', 'bullying', and the potential link between these concepts will follow. Thirdly, an outline of the clinical implications of the apparent association between these concepts is given. The article concludes with recommendations that researchers can consider while exploring the relationship between attachment, parenting styles, and bullying and the delineation thereof in the parent-adolescent relationship.

  1. Which measures of time preference best predict outcomes? Evidence from a large-scale field experiment

    OpenAIRE

    Burks, Stephen V.; Carpenter, Jeffrey P.; Goette, Lorenz; Rustichini, Aldo

    2011-01-01

    Economists and psychologists have devised numerous instruments to measure time preferences and have generated a rich literature examining the extent to which time preferences predict important outcomes; however, we still do not know which measures work best. With the help of a large sample of non-student participants (truck driver trainees) and administrative data on outcomes, we gather four different time preference measures and test the extent to which they predict both on their own and whe...

  2. A real-time algorithm for predicting core temperature in humans.

    Science.gov (United States)

    Gribok, Andrei V; Buller, Mark J; Hoyt, Reed W; Reifman, Jaques

    2010-07-01

    In this paper, we present a real-time implementation of a previously developed offline algorithm for predicting core temperature in humans. The real-time algorithm uses a zero-phase Butterworth digital filter to smooth the data and an autoregressive (AR) model to predict core temperature. The performance of the algorithm is assessed in terms of its prediction accuracy, quantified by the root mean squared error (RMSE), and in terms of prediction uncertainty, quantified by statistically based prediction intervals (PIs). To evaluate the performance of the algorithm, we simulated real-time implementation using core-temperature data collected during two different field studies, involving ten different individuals. One of the studies includes a case of heat illness suffered by one of the participants. The results indicate that although the real-time predictions yielded RMSEs that are larger than those of the offline algorithm, the real-time algorithm does produce sufficiently accurate predictions for practically meaningful prediction horizons (approximately 20 min). The algorithm reached alert (39 degrees C) and alarm (39.5 degrees C) thresholds for the heat-ill individual but did not even attain the alert threshold for the other individuals, demonstrating the algorithm's good sensitivity and specificity. The PIs reflected, in an intuitively expected manner, the uncertainty associated with real-time forecast as a function of prediction horizon and core-temperature variability. The results also corroborate the feasibility of "universal" AR models, where an offline-developed model based on one individual's data could be used to predict any other individual in real time. We conclude that the real-time implementation of the algorithm confirms the attributes observed in the offline version and, hence, could be considered as a warning tool for impending heat illnesses.

  3. Error criteria for cross validation in the context of chaotic time series prediction.

    Science.gov (United States)

    Lim, Teck Por; Puthusserypady, Sadasivan

    2006-03-01

    The prediction of a chaotic time series over a long horizon is commonly done by iterating one-step-ahead prediction. Prediction can be implemented using machine learning methods, such as radial basis function networks. Typically, cross validation is used to select prediction models based on mean squared error. The bias-variance dilemma dictates that there is an inevitable tradeoff between bias and variance. However, invariants of chaotic systems are unchanged by linear transformations; thus, the bias component may be irrelevant to model selection in the context of chaotic time series prediction. Hence, the use of error variance for model selection, instead of mean squared error, is examined. Clipping is introduced, as a simple way to stabilize iterated predictions. It is shown that using the error variance for model selection, in combination with clipping, may result in better models.

  4. Application of uncertainty reasoning based on cloud model in time series prediction

    Institute of Scientific and Technical Information of China (English)

    张锦春; 胡谷雨

    2003-01-01

    Time series prediction has been successfully used in several application areas, such as meteoro-logical forecasting, market prediction, network traffic forecasting, etc. , and a number of techniques have been developed for modeling and predicting time series. In the traditional exponential smoothing method, a fixed weight is assigned to data history, and the trend changes of time series are ignored. In this paper, an uncertainty reasoning method, based on cloud model, is employed in time series prediction, which uses cloud logic controller to adjust the smoothing coefficient of the simple exponential smoothing method dynamically to fit the current trend of the time series. The validity of this solution was proved by experiments on various data sets.

  5. Application of uncertainty reasoning based on cloud model in time series prediction

    Institute of Scientific and Technical Information of China (English)

    张锦春; 胡谷雨

    2003-01-01

    Time series prediction has been successfully used in several application areas, such as meteorological forecasting, market prediction, network traffic forecasting, etc., and a number of techniques have been developed for modeling and predicting time series. In the traditional exponential smoothing method, a fixed weight is assigned to data history, and the trend changes of time series are ignored. In this paper, an uncertainty reasoning method, based on cloud model, is employed in time series prediction, which uses cloud logic controller to adjust the smoothing coefficient of the simple exponential smoothing method dynamically to fit the current trend of the time series. The validity of this solution was proved by experiments on various data sets.

  6. Influence of Memory Hierarchies on Predictability for Time Constrained Embedded Software

    CERN Document Server

    Wehmeyer, Lars

    2011-01-01

    Safety-critical embedded systems having to meet real-time constraints are expected to be highly predictable in order to guarantee at design time that certain timing deadlines will always be met. This requirement usually prevents designers from utilizing caches due to their highly dynamic, thus hardly predictable behavior. The integration of scratchpad memories represents an alternative approach which allows the system to benefit from a performance gain comparable to that of caches while at the same time maintaining predictability. In this work, we compare the impact of scratchpad memories and caches on worst case execution time (WCET) analysis results. We show that caches, despite requiring complex techniques, can have a negative impact on the predicted WCET, while the estimated WCET for scratchpad memories scales with the achieved Performance gain at no extra analysis cost.

  7. Temporal Prediction Errors Affect Short-Term Memory Scanning Response Time.

    Science.gov (United States)

    Limongi, Roberto; Silva, Angélica M

    2016-11-01

    The Sternberg short-term memory scanning task has been used to unveil cognitive operations involved in time perception. Participants produce time intervals during the task, and the researcher explores how task performance affects interval production - where time estimation error is the dependent variable of interest. The perspective of predictive behavior regards time estimation error as a temporal prediction error (PE), an independent variable that controls cognition, behavior, and learning. Based on this perspective, we investigated whether temporal PEs affect short-term memory scanning. Participants performed temporal predictions while they maintained information in memory. Model inference revealed that PEs affected memory scanning response time independently of the memory-set size effect. We discuss the results within the context of formal and mechanistic models of short-term memory scanning and predictive coding, a Bayes-based theory of brain function. We state the hypothesis that our finding could be associated with weak frontostriatal connections and weak striatal activity.

  8. Comparison of time series models for predicting campylobacteriosis risk in New Zealand.

    Science.gov (United States)

    Al-Sakkaf, A; Jones, G

    2014-05-01

    Predicting campylobacteriosis cases is a matter of considerable concern in New Zealand, after the number of the notified cases was the highest among the developed countries in 2006. Thus, there is a need to develop a model or a tool to predict accurately the number of campylobacteriosis cases as the Microbial Risk Assessment Model used to predict the number of campylobacteriosis cases failed to predict accurately the number of actual cases. We explore the appropriateness of classical time series modelling approaches for predicting campylobacteriosis. Finding the most appropriate time series model for New Zealand data has additional practical considerations given a possible structural change, that is, a specific and sudden change in response to the implemented interventions. A univariate methodological approach was used to predict monthly disease cases using New Zealand surveillance data of campylobacteriosis incidence from 1998 to 2009. The data from the years 1998 to 2008 were used to model the time series with the year 2009 held out of the data set for model validation. The best two models were then fitted to the full 1998-2009 data and used to predict for each month of 2010. The Holt-Winters (multiplicative) and ARIMA (additive) intervention models were considered the best models for predicting campylobacteriosis in New Zealand. It was noticed that the prediction by an additive ARIMA with intervention was slightly better than the prediction by a Holt-Winter multiplicative method for the annual total in year 2010, the former predicting only 23 cases less than the actual reported cases. It is confirmed that classical time series techniques such as ARIMA with intervention and Holt-Winters can provide a good prediction performance for campylobacteriosis risk in New Zealand. The results reported by this study are useful to the New Zealand Health and Safety Authority's efforts in addressing the problem of the campylobacteriosis epidemic. © 2013 Blackwell Verlag GmbH.

  9. Uncertainty in Bus Arrival Time Predictions: Treating Heteroscedasticity With a Metamodel Approach

    DEFF Research Database (Denmark)

    O'Sullivan, Aidan; Pereira, Francisco Camara; Zhao, Jinhua

    2016-01-01

    Arrival time predictions for the next available bus or train are a key component of modern traveler information systems (TISs). A great deal of research has been conducted within the intelligent transportation system community in developing an assortment of different algorithms that seek to incre......Arrival time predictions for the next available bus or train are a key component of modern traveler information systems (TISs). A great deal of research has been conducted within the intelligent transportation system community in developing an assortment of different algorithms that seek...... sources. In this paper, we tackle the issue of uncertainty in bus arrival time predictions using an alternative approach. Rather than endeavor to develop a superior method for prediction, we take existing predictions from a TIS and treat the algorithm generating them as a black box. The presence...

  10. Small-time scale network traffic prediction based on a local support vector machine regression model

    Institute of Scientific and Technical Information of China (English)

    Meng Qing-Fang; Chen Yue-Hui; Peng Yu-Hua

    2009-01-01

    In this paper we apply the nonlinear time series analysis method to small-time scale traffic measurement data. The prediction-based method is used to determine the embedding dimension of the traffic data. Based on the reconstructed phase space, the local support vector machine prediction method is used to predict the traffic measurement data, and the BIC-based neighbouring point selection method is used to choose the number of the nearest neighbouring points for the local support vector machine regression model. The experimental results show that the local support vector machine prediction method whose neighbouring points are optimized can effectively predict the small-time scale traffic measurement data and can reproduce the statistical features of real traffic measurements.

  11. Essays on the predictability of oil shocks and yield curves for real-time output growth

    Science.gov (United States)

    Carlton, Amelie B.

    This dissertation is a collection of three essays that revisits the long-standing puzzle of the apparently disproportionate effect of oil prices in the economy by examining output growth predictability with real-time data. Each study of the predictive content of oil shocks is from a different perspective by using newly developed real-time datasets, which allows for replicating the economic environment faced by policymakers in real time. The first study extends the conventional set of models of output growth determination by investigating predictability of models that incorporate various functional forms of oil prices and real-time data. The results are supportive of the relationship of GDP and oil in the context of Granger causality with real-time data. In the second essay, I use oil shocks to predict the economy is changing direction earlier than would be predicted by solely using initial GDP releases. The model provides compelling evidence of negative GDP growth predictability in response to oil price shocks, which could shorten the "recognition lag" for successful implementation of discretionary counter-cyclical policies. In the third essay, I evaluate short-horizon output growth predictability using real-time data for different sample periods. I find strong evidence of predictability at the one-quarter and four-quarter horizon for the United States. The major result of the paper is that we reject the null hypothesis of no predictability against an alternative hypothesis of predictability with oil shocks that include yield curves in the forecasting regression. This relationship suggests the combination of monetary policy and oil shocks are important for subsequent GDP growth.

  12. Differences in Motor Imagery Time when Predicting Task Duration in Alpine Skiers and Equestrian Riders

    Science.gov (United States)

    Louis, Magali; Collet, Christian; Champely, Stephane; Guillot, Aymeric

    2012-01-01

    Athletes' ability to use motor imagery (MI) to predict the speed at which they could perform a motor sequence has received little attention. In this study, 21 alpine skiers and 16 equestrian riders performed MI based on a prediction of actual performance time (a) after the course inspection, (b) before the start, and (c) after the actual…

  13. Using ERS spaceborne microwave soil moisture observations to predict groundwater head in space and time

    NARCIS (Netherlands)

    Sutanudjaja, E.H.; De Jong, S.M.; Van Geer, F.C.; Bierkens, M.F.P.

    2013-01-01

    The study presented in this paper is to investigate the possibility of using spaceborne remote sensing data for groundwater head prediction. Remotely-sensed soil moisture time series of SWI (Soil Water Index) derived from ERS (European Remote Sensing) scatterometers are used to predict groundwater

  14. Using ERS spaceborne microwave soil moisture observations to predict groundwater heads in space and time

    NARCIS (Netherlands)

    Sutanudjaja, E.H.; Jong, S.M. de; Bierkens, M.F.P.; Geer, F.C. van

    2013-01-01

    The study presented in this paper is to investigate the possibility of using spaceborne remote sensing data for groundwater head prediction. Remotely-sensed soil moisture time series of SWI (Soil Water Index) derived from ERS (European Remote Sensing) scatterometers are used to predict groundwater

  15. A framework for predicting three-dimensional prostate deformation in real time

    NARCIS (Netherlands)

    Jahya, Alex; Herink, Mark; Misra, Sarthak

    2013-01-01

    Background Surgical simulation systems can be used to estimate soft tissue deformation during pre- and intra-operative planning. Such systems require a model that can accurately predict the deformation in real time. In this study, we present a back-propagation neural network for predicting

  16. "Personal best times in an olympic distance triathlon and a marathon predict an ironman race time for recreational female triathletes".

    Science.gov (United States)

    Rüst, Christoph Alexander; Knechtle, Beat; Wirth, Andrea; Knechtle, Patrizia; Ellenrieder, Birte; Rosemann, Thomas; Lepers, Romuald

    2012-06-30

    "The aim of this study was to investigate whether the characteristics of anthropometry, training or previous performance were related to an Ironman race time in recreational female Ironman triathletes. These characteristics were correlated to an Ironman race time for 53 recreational female triathletes in order to determine the predictor variables, and so be able to predict an Ironman race time for future novice triathletes. In the bi-variate analysis, no anthropometric characteristic was related to race time. The weekly cycling kilometers (r = -0.35) and hours (r = -0.32), as well as the personal best time in an Olympic distance triathlon (r = 0.49) and in a marathon (r = 0.74) were related to an Ironman race time (triathlon ( P = 0.0453) and in a marathon (P = 0.0030) were the best predictors for the Ironman race time (n = 28, r² = 0.53). The race time in an Ironman triathlon might be partially predicted by the following equation (r² = 0.53, n = 28): Race time (min) = 186.3 + 1.595 × (personal best time in an Olympic distance triathlon, min) + 1.318 × (personal best time in a marathon, min) for recreational female Ironman triathletes."

  17. Prediction of altimetric sea level anomalies using time series models based on spatial correlation

    Science.gov (United States)

    Miziński, Bartłomiej; Niedzielski, Tomasz

    2014-05-01

    Sea level anomaly (SLA) times series, which are time-varying gridded data, can be modelled and predicted using time series methods. This approach has been shown to provide accurate forecasts within the Prognocean system, the novel infrastructure for anticipating sea level change designed and built at the University of Wrocław (Poland) which utilizes the real-time SLA data from Archiving, Validation and Interpretation of Satellite Oceanographic data (AVISO). The system runs a few models concurrently, and our ocean prediction experiment includes both uni- and multivariate time series methods. The univariate ones are: extrapolation of polynomial-harmonic model (PH), extrapolation of polynomial-harmonic model and autoregressive prediction (PH+AR), extrapolation of polynomial-harmonic model and self-exciting threshold autoregressive prediction (PH+SETAR). The following multivariate methods are used: extrapolation of polynomial-harmonic model and vector autoregressive prediction (PH+VAR), extrapolation of polynomial-harmonic model and generalized space-time autoregressive prediction (PH+GSTAR). As the aforementioned models and the corresponding forecasts are computed in real time, hence independently and in the same computational setting, we are allowed to compare the accuracies offered by the models. The objective of this work is to verify the hypothesis that the multivariate prediction techniques, which make use of cross-correlation and spatial correlation, perform better than the univariate ones. The analysis is based on the daily-fitted and updated time series models predicting the SLA data (lead time of two weeks) over several months when El Niño/Southern Oscillation (ENSO) was in its neutral state.

  18. Improved Short-Term Clock Prediction Method for Real-Time Positioning

    Directory of Open Access Journals (Sweden)

    Yifei Lv

    2017-06-01

    Full Text Available The application of real-time precise point positioning (PPP requires real-time precise orbit and clock products that should be predicted within a short time to compensate for the communication delay or data gap. Unlike orbit correction, clock correction is difficult to model and predict. The widely used linear model hardly fits long periodic trends with a small data set and exhibits significant accuracy degradation in real-time prediction when a large data set is used. This study proposes a new prediction model for maintaining short-term satellite clocks to meet the high-precision requirements of real-time clocks and provide clock extrapolation without interrupting the real-time data stream. Fast Fourier transform (FFT is used to analyze the linear prediction residuals of real-time clocks. The periodic terms obtained through FFT are adopted in the sliding window prediction to achieve a significant improvement in short-term prediction accuracy. This study also analyzes and compares the accuracy of short-term forecasts (less than 3 h by using different length observations. Experimental results obtained from International GNSS Service (IGS final products and our own real-time clocks show that the 3-h prediction accuracy is better than 0.85 ns. The new model can replace IGS ultra-rapid products in the application of real-time PPP. It is also found that there is a positive correlation between the prediction accuracy and the short-term stability of on-board clocks. Compared with the accuracy of the traditional linear model, the accuracy of the static PPP using the new model of the 2-h prediction clock in N, E, and U directions is improved by about 50%. Furthermore, the static PPP accuracy of 2-h clock products is better than 0.1 m. When an interruption occurs in the real-time model, the accuracy of the kinematic PPP solution using 1-h clock prediction product is better than 0.2 m, without significant accuracy degradation. This model is of practical

  19. Predicting Homework Time Management at the Secondary School Level: A Multilevel Analysis

    Science.gov (United States)

    Xu, Jianzhong

    2010-01-01

    The purpose of this study is to test empirical models of variables posited to predict homework time management at the secondary school level. Student- and class-level predictors of homework time management were analyzed in a survey of 1895 students from 111 classes. Most of the variance in homework time management occurred at the student level,…

  20. Predicting Homework Time Management at the Secondary School Level: A Multilevel Analysis

    Science.gov (United States)

    Xu, Jianzhong

    2010-01-01

    The purpose of this study is to test empirical models of variables posited to predict homework time management at the secondary school level. Student- and class-level predictors of homework time management were analyzed in a survey of 1895 students from 111 classes. Most of the variance in homework time management occurred at the student level,…

  1. Novel technique for prediction of time points for scheduling of multipurpose batch plants

    CSIR Research Space (South Africa)

    Seid, R

    2012-01-01

    Full Text Available and it is active for most of the time points when it is compared to other units. A linear model is used to predict how many times the critical unit is used. In conjunction with knowledge of recipe, this information is used to determine the optimal number of time...

  2. Modeling and Simulation of Time Series Prediction Based on Dynic Neural Network

    Institute of Scientific and Technical Information of China (English)

    王雪松; 程玉虎; 彭光正

    2004-01-01

    Molding and simulation of time series prediction based on dynic neural network(NN) are studied. Prediction model for non-linear and time-varying system is proposed based on dynic Jordan NN. Aiming at the intrinsic defects of back-propagation (BP) algorithm that cannot update network weights incrementally, a hybrid algorithm combining the temporal difference (TD) method with BP algorithm to train Jordan NN is put forward. The proposed method is applied to predict the ash content of clean coal in jigging production real-time and multi-step. A practical exple is also given and its application results indicate that the method has better performance than others and also offers a beneficial reference to the prediction of nonlinear time series.

  3. Real-Time, Maneuvering Flight Noise Prediction for Rotorcraft Flight Simulations Project

    Data.gov (United States)

    National Aeronautics and Space Administration — This proposal outlines a plan for developing new technology to provide accurate real-time noise prediction for rotorcraft in steady and maneuvering flight. Main...

  4. Predict or classify: The deceptive role of time-locking in brain signal classification

    CERN Document Server

    Rusconi, Marco

    2016-01-01

    Several experimental studies claim to be able to predict the outcome of simple decisions from brain signals measured before subjects are aware of their decision. Often, these studies use multivariate pattern recognition methods with the underlying assumption that the ability to classify the brain signal is equivalent to predict the decision itself. Here we show instead that it is possible to correctly classify a signal even if it does not contain any predictive information about the decision. We first define a simple stochastic model that mimics the random decision process between two equivalent alternatives, and generate a large number of independent trials that contain no choice-predictive information. The trials are first time-locked to the time point of the final event and then classified using standard machine-learning techniques. The resulting classification accuracy is above chance level long before the time point of time-locking. We then analyze the same trials using information theory. We demonstrate...

  5. Real-Time Noise Prediction of V/STOL Aircraft in Maneuvering Flight Project

    Data.gov (United States)

    National Aeronautics and Space Administration — This proposal outlines a plan for enhancing and integrating new breakthrough technologies to provide accurate real-time noise prediction of V/STOL aircraft in...

  6. Evaluation of the predictability of real-time crash risk models.

    Science.gov (United States)

    Xu, Chengcheng; Liu, Pan; Wang, Wei

    2016-09-01

    The primary objective of the present study was to investigate the predictability of crash risk models that were developed using high-resolution real-time traffic data. More specifically the present study sought answers to the following questions: (a) how to evaluate the predictability of a real-time crash risk model; and (b) how to improve the predictability of a real-time crash risk model. The predictability is defined as the crash probability given the crash precursor identified by the crash risk model. An equation was derived based on the Bayes' theorem for estimating approximately the predictability of crash risk models. The estimated predictability was then used to quantitatively evaluate the effects of the threshold of crash precursors, the matched and unmatched case-control design, and the control-to-case ratio on the predictability of crash risk models. It was found that: (a) the predictability of a crash risk model can be measured as the product of prior crash probability and the ratio between sensitivity and false alarm rate; (b) there is a trade-off between the predictability and sensitivity of a real-time crash risk model; (c) for a given level of sensitivity, the predictability of the crash risk model that is developed using the unmatched case-controlled sample is always better than that of the model developed using the matched case-controlled sample; and (d) when the control-to-case ratio is beyond 4:1, the increase in control-to-case ratio does not lead to clear improvements in predictability.

  7. Queuing Time Prediction Using WiFi Positioning Data in an Indoor Scenario.

    Science.gov (United States)

    Shu, Hua; Song, Ci; Pei, Tao; Xu, Lianming; Ou, Yang; Zhang, Libin; Li, Tao

    2016-11-22

    Queuing is common in urban public places. Automatically monitoring and predicting queuing time can not only help individuals to reduce their wait time and alleviate anxiety but also help managers to allocate resources more efficiently and enhance their ability to address emergencies. This paper proposes a novel method to estimate and predict queuing time in indoor environments based on WiFi positioning data. First, we use a series of parameters to identify the trajectories that can be used as representatives of queuing time. Next, we divide the day into equal time slices and estimate individuals' average queuing time during specific time slices. Finally, we build a nonstandard autoregressive (NAR) model trained using the previous day's WiFi estimation results and actual queuing time to predict the queuing time in the upcoming time slice. A case study comparing two other time series analysis models shows that the NAR model has better precision. Random topological errors caused by the drift phenomenon of WiFi positioning technology (locations determined by a WiFi positioning system may drift accidently) and systematic topological errors caused by the positioning system are the main factors that affect the estimation precision. Therefore, we optimize the deployment strategy during the positioning system deployment phase and propose a drift ratio parameter pertaining to the trajectory screening phase to alleviate the impact of topological errors and improve estimates. The WiFi positioning data from an eight-day case study conducted at the T3-C entrance of Beijing Capital International Airport show that the mean absolute estimation error is 147 s, which is approximately 26.92% of the actual queuing time. For predictions using the NAR model, the proportion is approximately 27.49%. The theoretical predictions and the empirical case study indicate that the NAR model is an effective method to estimate and predict queuing time in indoor public areas.

  8. Trip-oriented travel time prediction (TOTTP) with historical vehicle trajectories

    Science.gov (United States)

    Xu, Tao; Li, Xiang; Claramunt, Christophe

    2017-03-01

    Accurate travel time prediction is undoubtedly of importance to both traffic managers and travelers. In highly-urbanized areas, trip-oriented travel time prediction (TOTTP) is valuable to travelers rather than traffic managers as the former usually expect to know the travel time of a trip which may cross over multiple road sections. There are two obstacles to the development of TOTTP, including traffic complexity and traffic data coverage.With large scale historical vehicle trajectory data and meteorology data, this research develops a BPNN-based approach through integrating multiple factors affecting trip travel time into a BPNN model to predict trip-oriented travel time for OD pairs in urban network. Results of experiments demonstrate that it helps discover the dominate trends of travel time changes daily and weekly, and the impact of weather conditions is non-trivial.

  9. MULTISTAGE ADAPTIVE HIGHER-ORDER NONLINEAR FINITE IMPULSE RESPONSE FILTERS FOR CHAOTIC TIME SERIES PREDICTIONS

    Institute of Scientific and Technical Information of China (English)

    ZHANG JIA-SHU; XIAO XIAN-CI

    2001-01-01

    A multistage adaptive higher-order nonlinear finite impulse response (MAHONFIR) filter is proposed to predict chaotic time series. Using this approach, we may readily derive the decoupled parallel algorithm for the adaptation of the coefficients of the MAHONFIR filter, to guarantee a more rapid convergence of the adaptive weights to their optimal values. Numerical simulation results show that the MAHONFIR filters proposed here illustrate a very good performance for making an adaptive prediction of chaotic time series.

  10. Use of a multistage model to predict time trends in smoking induced lung cancer.

    OpenAIRE

    Swartz, J B

    1992-01-01

    STUDY OBJECTIVE--The aims were to use a mathematical model to predict the time course of smoking induced lung cancer, and to investigate to what extent the most recent increases in lung cancer mortality are due to cigarette smoking. DESIGN--A mathematical model was developed and solved by simulation to construct detailed smoking histories of the US white male population given available prevalence data by age and cohort. A multistage carcinogenesis model was used to predict the time course of ...

  11. Xenoestrogens diethylstilbestrol and zearalenone negatively influence pubertal rat's testis.

    Directory of Open Access Journals (Sweden)

    Katarzyna Marchlewska

    2010-01-01

    Full Text Available The aim of this study was to assess the impact of xenoestrogens: diethylstilbestrol (DES and zearalenone (ZEA on rat's pubertal testis and to compare it with the effect of natural estrogen - 17beta-estradiol (E. Male Wistar rats were daily, subcutaneously injected at 5th-15th postnatal days (p.d. with E (1.25 or 12.5 mug or DES (1.25 or 12.5 mug or ZEA (4 or 40 mug or vehicle. At 16th p.d. testes were dissected, weighted, and paraffin embedded. Following parameters were assessed: diameter and length of seminiferous tubule, numbers of spermatogonia A+intermediate+B (A/In/B, preleptotene spermatocytes (PL, leptotene+zygotene+pachytene spermatocytes (L/Z/PA and Sertoli cells per testis. Testes weight, seminiferous tubule diameter and length were decreased by both doses of E, DES and ZEA. DES effect was the strongest, but its influence on testis weight and seminiferous tubule length, on the contrary to E and ZEA, was not dose-dependent. Similarly, DES in both doses had the most severe negative impact on the number of germ and Sertoli cells. The negative influence of E on germ cells was less pronounced. The negative effect of ZEA was seen only after administration of the higher dose on spermatogonia number, while DES and E decreased A/In/B number more evidently. Sertoli cell number were decreased after both doses of E. ZEA40 decreased Sertoli cell number while ZEA4 had no effect. Conclusion: exposure of prepubertal male rat to DES has the strongest detrimental effect on the developing testis in comparison to E and ZEA. Both, E and DES, decreased number of germ and Sertoli cells, diminished seminiferous tubule diameter, length and testis weight. ZEA had much more weaker effect than the potent estrogens.

  12. Time series online prediction algorithm based on least squares support vector machine

    Institute of Scientific and Technical Information of China (English)

    WU Qiong; LIU Wen-ying; YANG Yi-han

    2007-01-01

    Deficiencies of applying the traditional least squares support vector machine (LS-SVM) to time series online prediction were specified. According to the kernel function matrix's property and using the recursive calculation of block matrix, a new time series online prediction algorithm based on improved LS-SVM was proposed. The historical training results were fully utilized and the computing speed of LS-SVM was enhanced. Then, the improved algorithm was applied to time series online prediction. Based on the operational data provided by the Northwest Power Grid of China, the method was used in the transient stability prediction of electric power system. The results show that, compared with the calculation time of the traditional LS-SVM(75-1 600 ms), that of the proposed method in different time windows is 40-60 ms, and the prediction accuracy(normalized root mean squared error) of the proposed method is above 0.8. So the improved method is better than the traditional LS-SVM and more suitable for time series online prediction.

  13. Real-time reliability prediction for dynamic systems with both deteriorating and unreliable components

    Institute of Scientific and Technical Information of China (English)

    XU ZhengGuo; JI YinDong; ZHOU DongHua

    2009-01-01

    As an important technology for predictive maintenance,failure prognosis has attracted more and more attentions in recent years.Real-time reliability prediction is one effective solution to failure prognosis.Considering a dynamic system that is composed of normal,deteriorating and unreliable components,this paper proposes an integrated approach to perform real-time reliability prediction for such a class of systems.For s deteriorating component,the degradation is modeled by a time-varying fault process which is a linear or approximately linear function of time.The behavior of an unreliable component is described by a random variable which has two possible values corresponding to the operating and malfunction conditions of this component.The whole proposed approach contains three algorithms.A modified interacting multiple model particle filter is adopted to estimate the dynamic system's state variables and the unmeasurable time-varying fault.An exponential smoothing algorithm named the Holt's method is used to predict the fault process.In the end,the system's reliability is predicted in real time by use of the Monte Carlo strategy.The proposed approach can effectively predict the impending failure of a dynamic system,which is verified by computer simulations based on a three-vessel water tank system.

  14. Cortical delta activity reflects reward prediction error and related behavioral adjustments, but at different times.

    Science.gov (United States)

    Cavanagh, James F

    2015-04-15

    Recent work has suggested that reward prediction errors elicit a positive voltage deflection in the scalp-recorded electroencephalogram (EEG); an event sometimes termed a reward positivity. However, a strong test of this proposed relationship remains to be defined. Other important questions remain unaddressed: such as the role of the reward positivity in predicting future behavioral adjustments that maximize reward. To answer these questions, a three-armed bandit task was used to investigate the role of positive prediction errors during trial-by-trial exploration and task-set based exploitation. The feedback-locked reward positivity was characterized by delta band activities, and these related EEG features scaled with the degree of a computationally derived positive prediction error. However, these phenomena were also dissociated: the computational model predicted exploitative action selection and related response time speeding whereas the feedback-locked EEG features did not. Compellingly, delta band dynamics time-locked to the subsequent bandit (the P3) successfully predicted these behaviors. These bandit-locked findings included an enhanced parietal to motor cortex delta phase lag that correlated with the degree of response time speeding, suggesting a mechanistic role for delta band activities in motivating action selection. This dissociation in feedback vs. bandit locked EEG signals is interpreted as a differentiation in hierarchically distinct types of prediction error, yielding novel predictions about these dissociable delta band phenomena during reinforcement learning and decision making.

  15. Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes.

    Science.gov (United States)

    Bai, Cong; Peng, Zhong-Ren; Lu, Qing-Chang; Sun, Jian

    2015-01-01

    Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes.

  16. Predictive fuzzy reasoning method for time series stock market data mining

    Science.gov (United States)

    Khokhar, Rashid H.; Md Sap, Mohd Noor

    2005-03-01

    Data mining is able to uncover hidden patterns and predict future trends and behaviors in financial markets. In this research we approach quantitative time series stock selection as a data mining problem. We present another modification of extraction of weighted fuzzy production rules (WFPRs) from fuzzy decision tree by using proposed similarity-based fuzzy reasoning method called predictive reasoning (PR) method. In proposed predictive reasoning method weight parameter can be assigned to each proposition in the antecedent of a fuzzy production rule (FPR) and certainty factor (CF) to each rule. Certainty factors are calculated by using some important variables like effect of other companies, effect of other local stock market, effect of overall world situation, and effect of political situation from stock market. The predictive FDT has been tested using three data sets including KLSE, NYSE and LSE. The experimental results show that WFPRs rules have high learning accuracy and also better predictive accuracy of stock market time series data.

  17. Variable structure control with sliding mode prediction for discrete-time nonlinear systems

    Institute of Scientific and Technical Information of China (English)

    Lingfei XIAO; Hongye SU; Xiaoyu ZHANG; Jian CHU

    2006-01-01

    A new variable structure control algorithm based on sliding mode prediction for a class of discrete-time nonlinear systems is presented. By employing a special model to predict future sliding mode value, and combining feedback correction and receding horizon optimization methods which are extensively applied on predictive control strategy, a discrete-time variable structure control law is constructed. The closed-loop systems are proved to have robustness to uncertainties with unspecified boundaries. Numerical simulation and pendulum experiment results illustrate that the closed-loop systems possess desired performance, such as strong robustness, fast convergence and chattering elimination.

  18. Time – Delay Simulated Artificial Neural Network Models for Predicting Shelf Life of Processed Cheese

    Directory of Open Access Journals (Sweden)

    Sumit Goyal

    2012-05-01

    Full Text Available This paper highlights the significance of Time-Delay ANN models for predicting shelf life of processed cheese stored at 7-8o^C. Bayesian regularization algorithm was selected as training function. Number of neurons in single and multiple hidden layers varied from 1 to 20. The network was trained with up to 100 epochs. Mean square error, root mean square error, coefficient of determination and nash - Sutcliffe coefficient were used for calculating the prediction capability of the developed models. Time-Delay ANN models with multilayer are quite efficient in predicting the shelf life of processed cheese stored at 7-8o^C.

  19. New prediction of chaotic time series based on local Lyapunov exponent

    Institute of Scientific and Technical Information of China (English)

    Zhang Yong

    2013-01-01

    A new method of predicting chaotic time series is presented based on a local Lyapunov exponent,by quantitatively measuring the exponential rate of separation or attraction of two infinitely close trajectories in state space.After reconstructing state space from one-dimensional chaotic time series,neighboring multiple-state vectors of the predicting point are selected to deduce the prediction formula by using the definition of the local Lyapunov exponent.Numerical simulations are carried out to test its effectiveness and verify its higher precision over two older methods.The effects of the number of referential state vectors and added noise on forecasting accuracy are also studied numerically.

  20. Application of retrospective time integration scheme to the prediction of torrential rain

    Institute of Scientific and Technical Information of China (English)

    Feng Guo-Lin; Dong Wen-Jie; Jia Xiao-Jing

    2004-01-01

    The retrospective time integration scheme presented on the principle of the self-memory of the atmosphere is applied to the mesoscale grid model MM5, constructing a mesoscale self-memorial model SMM5, and then the shortrange prediction experiments of torrential rain are performed in this paper. Results show that in comparison with MM5 the prediction accuracy of SMM5 is obviously improved due to its utilization of multiple time level past observations,and the precipitation area and intensity predicted by SMM5 are closer to observational fields than those by MM5.

  1. Lazy Spilling for a Time-Predictable Stack Cache: Implementation and Analysis

    DEFF Research Database (Denmark)

    Abbaspourseyedi, Sahar; Jordan, Alexander; Brandner, Florian

    2014-01-01

    The growing complexity of modern computer architectures increasingly complicates the prediction of the run-time behavior of software. For real-time systems, where a safe estimation of the program's worst-case execution time is needed, time-predictable computer architectures promise to resolve...... this problem. A stack cache, for instance, allows the compiler to efficiently cache a program's stack, while static analysis of its behavior remains easy. Likewise, its implementation requires little hardware overhead. This work introduces an optimization of the standard stack cache to avoid redundant spilling...

  2. Imprecise Computation Based Real-time Fault Tolerant Implementation for Model Predictive Control

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Model predictive control (MPC) could not be deployed in real-time control systems for its computation time is not well defined. A real-time fault tolerant implementation algorithm based on imprecise computation is proposed for MPC,according to the solving process of quadratic programming (QP) problem. In this algorithm, system stability is guaranteed even when computation resource is not enough to finish optimization completely. By this kind of graceful degradation, the behavior of real-time control systems is still predictable and determinate. The algorithm is demonstrated by experiments on servomotor, and the simulation results show its effectiveness.

  3. Impact of Pubertal Development and Physical Activity on Heart Rate Variability in Overweight and Obese Children in Taiwan

    Science.gov (United States)

    Chen, Su-Ru; Chiu, Hung-Wen; Lee, Yann-Jinn; Sheen, Tzong-Chi; Jeng, Chii

    2012-01-01

    Child obesity is frequently associated with dysfunction of autonomic nervous system. Children in pubertal development were suggested to be vulnerable to autonomic nervous system problems such as decrease of heart rate variability from dysregulation of metabolic control. This study explored the influence of pubertal development on autonomic nervous…

  4. Adolescents' Increasing Stress Response to Social Evaluation: Pubertal Effects on Cortisol and Alpha-Amylase during Public Speaking

    Science.gov (United States)

    van den Bos, Esther; de Rooij, Mark; Miers, Anne C.; Bokhorst, Caroline L.; Westenberg, P. Michiel

    2014-01-01

    Stress responses to social evaluation are thought to increase during adolescence, which may be due to pubertal maturation. However, empirical evidence is scarce. This study is the first to investigate the relation between pubertal development and biological responses to a social-evaluative stressor longitudinally. Participants performed the Leiden…

  5. Adolescents' Increasing Stress Response to Social Evaluation: Pubertal Effects on Cortisol and Alpha-Amylase during Public Speaking

    Science.gov (United States)

    van den Bos, Esther; de Rooij, Mark; Miers, Anne C.; Bokhorst, Caroline L.; Westenberg, P. Michiel

    2014-01-01

    Stress responses to social evaluation are thought to increase during adolescence, which may be due to pubertal maturation. However, empirical evidence is scarce. This study is the first to investigate the relation between pubertal development and biological responses to a social-evaluative stressor longitudinally. Participants performed the Leiden…

  6. Impact of Pubertal Development and Physical Activity on Heart Rate Variability in Overweight and Obese Children in Taiwan

    Science.gov (United States)

    Chen, Su-Ru; Chiu, Hung-Wen; Lee, Yann-Jinn; Sheen, Tzong-Chi; Jeng, Chii

    2012-01-01

    Child obesity is frequently associated with dysfunction of autonomic nervous system. Children in pubertal development were suggested to be vulnerable to autonomic nervous system problems such as decrease of heart rate variability from dysregulation of metabolic control. This study explored the influence of pubertal development on autonomic nervous…

  7. Travel Time Estimation and Prediction using Mobile Phones: A Cost Effective Method for Developing Countries

    Directory of Open Access Journals (Sweden)

    Satyakumar, M.

    2014-01-01

    Full Text Available Conventional data collection methods lack real time information and involve excessive cost of installation and maintenance. A real-time, low cost travel time data collection system can be developed using mobile phones. This project examines the use of mobile phones for travel time prediction of public transit vehicles and develops a dynamic travel time prediction model. Personnel were employed in public transit vehicles with mobile phones and these mobile phones were tracked continuously. Space information of the mobile phones represents the position of the buses and movement pattern of these mobile phones in turn represents the movement pattern of the public buses. The starting and arrival time at sections obtained from the cellular database were used to get the travel time and speed. Results obtained were statistically significant and it shows that use of mobile phone for travel time data collection is a low cost data collection technique for Indian cities.

  8. STUDY ON PREDICTION METHODS FOR DYNAMIC SYSTEMS OF NONLINEAR CHAOTIC TIME SERIES

    Institute of Scientific and Technical Information of China (English)

    马军海; 陈予恕; 辛宝贵

    2004-01-01

    The prediction methods for nonlinear dynamic systems which are decided by chaotic time series are mainly studied as well as structures of nonlinear self-related chaotic models and their dimensions.By combining neural networks and wavelet theories,the structures of wavelet transform neural networks were studied and also a wavelet neural networks learning method was given.Based on wavelet networks,a new method for parameter identification was suggested,which can be used selectively to extract different scales of frequency and time in time series in order to realize prediction of tendencies or details of original time series.Through pre-treatment and comparison of results before and after the treatment,several useful conclusions are reached:High accurate identification can be guaranteed by applying wavelet networks to identify parameters of self-related chaotic models and more valid prediction of the chaotic time series including noise can be achieved accordingly.

  9. Nonlinear continuous-time generalized predictive control of solar power plant

    Directory of Open Access Journals (Sweden)

    Khoukhi Billal

    2015-01-01

    Full Text Available This paper presents an application of nonlinear continuous-time generalized predictive control (GPC to the distributed collector field of a solar power plant. The major characteristic of a solar power plant is that the primary energy source, solar radiation, cannot be manipulated. Solar radiation varies throughout the day, causing changes in plant dynamics and strong perturbations in the process. A brief description of the solar power plant and its simulator is given. After that, basic concepts of predictive control and continuous-time generalized predictive control are introduced. A new control strategy, named nonlinear continuous-time generalized predictive control (NCGPC, is then derived to control the process. The simulation results show that the NCGPC gives a greater flexibility to achieve performance goals and better perturbation rejection than classical control.

  10. Predicting respiratory motion for real-time tumour tracking in radiotherapy

    CERN Document Server

    Krilavicius, Tomas; Simonavicius, Henrikas; Jarusevicius, Laimonas

    2015-01-01

    Purpose. Radiation therapy is a local treatment aimed at cells in and around a tumor. The goal of this study is to develop an algorithmic solution for predicting the position of a target in 3D in real time, aiming for the short fixed calibration time for each patient at the beginning of the procedure. Accurate predictions of lung tumor motion are expected to improve the precision of radiation treatment by controlling the position of a couch or a beam in order to compensate for respiratory motion during radiation treatment. Methods. For developing the algorithmic solution, data mining techniques are used. A model form from the family of exponential smoothing is assumed, and the model parameters are fitted by minimizing the absolute disposition error, and the fluctuations of the prediction signal (jitter). The predictive performance is evaluated retrospectively on clinical datasets capturing different behavior (being quiet, talking, laughing), and validated in real-time on a prototype system with respiratory mo...

  11. Food freezing with simultaneous surface dehydration: approximate prediction of freezing time

    Energy Technology Data Exchange (ETDEWEB)

    Campanone, Laura A.; Salvadori, Viviana O.; Mascheroni, Rodolfo H. [Centro de Investigacion Desarollo en Criotecnologia de Alimentos (CIDCA), Facultad de Ciencias Exactas, La Plata (Argentina); MODIAL, Facultad de Ingenieria, La Plata (Argentina)

    2005-03-01

    Freezing of unpackaged foods induces mass transfer in the form of surface ice sublimation, which in turn modifies heat transfer conditions. At present there are no simplified methods for predicting freezing times when surface dehydration occurs. This paper uses a previously developed model for the simulation of simultaneous heat and mass transfer during food freezing and storage to generate a complete set of predicted freezing times when dehydration occurs. Based on these data a simplified analytical method for the prediction of freezing time during freezing of unpackaged frozen foods was developed. The method accounts for product characteristics (shape, size and composition) and operating conditions (initial and refrigerant temperature, heat transfer coefficient, relative humidity). The prediction equation is very simple and results of its use - simulating usual freezing conditions for different products - shows very good accuracy when tested against the previously cited numerical model and all the available experimental data. (Author)

  12. Endothelial function in pre-pubertal children at risk of developing cardiomyopathy: a new frontier

    Directory of Open Access Journals (Sweden)

    Aline Cristina Tavares

    2012-01-01

    Full Text Available Although it is known that obesity, diabetes, and Kawasaki's disease play important roles in systemic inflammation and in the development of both endothelial dysfunction and cardiomyopathy, there is a lack of data regarding the endothelial function of pre-pubertal children suffering from cardiomyopathy. In this study, we performed a systematic review of the literature on pre-pubertal children at risk of developing cardiomyopathy to assess the endothelial function of pre-pubertal children at risk of developing cardiomyopathy. We searched the published literature indexed in PubMed, Bireme and SciELO using the keywords 'endothelial', 'children', 'pediatric' and 'infant' and then compiled a systematic review. The end points were age, the pubertal stage, sex differences, the method used for the endothelial evaluation and the endothelial values themselves. No studies on children with cardiomyopathy were found. Only 11 papers were selected for our complete analysis, where these included reports on the flow-mediated percentage dilatation, the values of which were 9.80±1.80, 5.90±1.29, 4.50±0.70, and 7.10±1.27 for healthy, obese, diabetic and pre-pubertal children with Kawasaki's disease, respectively. There was no significant difference in the dilatation, independent of the endothelium, either among the groups or between the genders for both of the measurements in children; similar results have been found in adolescents and adults. The endothelial function in cardiomyopathic children remains unclear because of the lack of data; nevertheless, the known dysfunctions in children with obesity, type 1 diabetes and Kawasaki's disease may influence the severity of the cardiovascular symptoms, the prognosis, and the mortality rate. The results of this study encourage future research into the consequences of endothelial dysfunction in pre-pubertal children.

  13. Effects of Di-(2-ethylhexyl) Phthalate on the Hypothalamus-Uterus in Pubertal Female Rats.

    Science.gov (United States)

    Liu, Te; Jia, Yiyang; Zhou, Liting; Wang, Qi; Sun, Di; Xu, Jin; Wu, Juan; Chen, Huaiji; Xu, Feng; Ye, Lin

    2016-11-12

    The pollution of endocrine disruptors and its impact on human reproductive system have attracted much attention. Di-(2-ethylhexyl) phthalate (DEHP), an environmental endocrine disruptor, is widely used in food packages, containers, medical supplies and children's toys. It can cause diseases such as infertility, sexual precocity and uterine bleeding and thus arouse concerns from the society and scholars. The effect of DEHP on pubertal female reproductive system is still not well-studied. This study was to investigate the effects of DEHP on the hypothalamus-uterus in pubertal female rats, reveal the reproductive toxicity of DEHP on pubertal female rats and its mechanism, and provide scientific evidence for the evaluation of toxicity and toxic mechanism of DEHP on reproductive system. Forty-eight pubertal female rats were randomly divided into four groups and respectively administered via oral gavage 0, 250, 500, or 1000 mg/kg/d DEHP in 0.1 mL corn oil/20 g body weight for up to four weeks. Compared with control rats, the DEHP-treated rats showed: (1) higher gonadotropin-releasing hormone (GnRH) level in the hypothalamus; (2) higher protein levels of GnRH in the hypothalamus; and (3) higher mRNA and protein levels of GnRH receptor (GnRHR) in the uterus. Our data reveal that DEHP exposure may lead to a disruption in pubertal female rats and an imbalance of hypothalamus-uterus. Meanwhile, DEHP may, through the GnRH in the hypothalamus and its receptor on the uterus, lead to diseases of the uterus. DEHP may impose a negative influence on the development and functioning of the reproductive system in pubertal female rats.

  14. [Dietary Fiber and Pubertal Development among Children and Adolescents--a Cross-sectional Study in Chengdu, Sichuan].

    Science.gov (United States)

    Tian, Guo; Liu, Yan; Xue, Hong-mei; Luo, Jiao; Chen, Yan-rong; Bao, Yu-xin; Duan, Ruo-nan; Yang, Ming-zhe; Cheng, Guo

    2016-03-01

    To determine the association between intake of dietary fiber and pubertal development among children and adolescents in Chengdu. A cross-sectional survey was undertaken in 1 340 children and adolescents aged 9-15 years. Data about dietary intake were collected through 24-h dietary self-recall. Pubertal development was measured by trained investigators using Tanner criteria. Consumptions of total fiber and fiber from different sources were compared among the participants with different stages of pubertal development. Data from 1 328 children and adolescents were analyzed. Boys (n = 667) at a later stage of pubertal development consumed less total fiber and fruit fiber than those at an earlier stage (P fiber than those at an earlier stage (P Dietary fiber intake, especially fruit fiber, is lower in children and adolescents with early commencement of puberty development. Further studies are needed to establish the relationship between dietary fiber and pubertal development.

  15. Predict or classify: The deceptive role of time-locking in brain signal classification

    Science.gov (United States)

    Rusconi, Marco; Valleriani, Angelo

    2016-06-01

    Several experimental studies claim to be able to predict the outcome of simple decisions from brain signals measured before subjects are aware of their decision. Often, these studies use multivariate pattern recognition methods with the underlying assumption that the ability to classify the brain signal is equivalent to predict the decision itself. Here we show instead that it is possible to correctly classify a signal even if it does not contain any predictive information about the decision. We first define a simple stochastic model that mimics the random decision process between two equivalent alternatives, and generate a large number of independent trials that contain no choice-predictive information. The trials are first time-locked to the time point of the final event and then classified using standard machine-learning techniques. The resulting classification accuracy is above chance level long before the time point of time-locking. We then analyze the same trials using information theory. We demonstrate that the high classification accuracy is a consequence of time-locking and that its time behavior is simply related to the large relaxation time of the process. We conclude that when time-locking is a crucial step in the analysis of neural activity patterns, both the emergence and the timing of the classification accuracy are affected by structural properties of the network that generates the signal.

  16. Time Score: A New Feature for Link Prediction in Social Networks

    Science.gov (United States)

    Munasinghe, Lankeshwara; Ichise, Ryutaro

    Link prediction in social networks, such as friendship networks and coauthorship networks, has recently attracted a great deal of attention. There have been numerous attempts to address the problem of link prediction through diverse approaches. In the present paper, we focus on the temporal behavior of the link strength, particularly the relationship between the time stamps of interactions or links and the temporal behavior of link strength and how link strength affects future link evolution. Most previous studies have not sufficiently discussed either the impact of time stamps of the interactions or time stamps of the links on link evolution. The gap between the current time and the time stamps of the interactions or links is also important to link evolution. In the present paper, we introduce a new time-aware feature, referred to as time score, that captures the important aspects of time stamps of interactions and the temporality of the link strengths. We also analyze the effectiveness of time score with different parameter settings for different network data sets. The results of the analysis revealed that the time score was sensitive to different networks and different time measures. We applied time score to two social network data sets, namely, Facebook friendship network data set and a coauthorship network data set. The results revealed a significant improvement in predicting future links.

  17. Remaining dischargeable time prediction for lithium-ion batteries using unscented Kalman filter

    Science.gov (United States)

    Dong, Guangzhong; Wei, Jingwen; Chen, Zonghai; Sun, Han; Yu, Xiaowei

    2017-10-01

    To overcome the range anxiety, one of the important strategies is to accurately predict the range or dischargeable time of the battery system. To accurately predict the remaining dischargeable time (RDT) of a battery, a RDT prediction framework based on accurate battery modeling and state estimation is presented in this paper. Firstly, a simplified linearized equivalent-circuit-model is developed to simulate the dynamic characteristics of a battery. Then, an online recursive least-square-algorithm method and unscented-Kalman-filter are employed to estimate the system matrices and SOC at every prediction point. Besides, a discrete wavelet transform technique is employed to capture the statistical information of past dynamics of input currents, which are utilized to predict the future battery currents. Finally, the RDT can be predicted based on the battery model, SOC estimation results and predicted future battery currents. The performance of the proposed methodology has been verified by a lithium-ion battery cell. Experimental results indicate that the proposed method can provide an accurate SOC and parameter estimation and the predicted RDT can solve the range anxiety issues.

  18. Serum levels of INSL3, AMH, Inhibin B and Testosterone during pubertal transition in healthy boys

    DEFF Research Database (Denmark)

    Lindhardt Johansen, Marie; Anand-Ivell, Ravinder; Mouritsen, Annette;

    2014-01-01

    to luteinizing hormone (LH), follicle-stimulating hormone (FSH), testosterone, inhibin B, and anti-Müllerian hormone (AMH) during puberty in healthy boys.MethodsTen boys were included from the longitudinal part of the COPENHAGEN Puberty Study. Pubertal evaluation, including testicular volume, was performed......IntroductionInsulin-like factor 3 (INSL3) is a promising marker of Leydig cell function with potentially high clinical relevance. Limited data of INSL3 levels in relation to other reproductive hormones in healthy pubertal boys exist.AimTo evaluate longitudinal serum changes in INSL3 compared...

  19. Electro convulsive therapy in a pre-pubertal child with severe depression.

    Directory of Open Access Journals (Sweden)

    Russell P

    2002-10-01

    Full Text Available Electro Convulsive Therapy (ECT in pre-pubertal children is a controversial and underreported treatment. Even though the effectiveness and side effects of ECT in adolescents are comparable with those in adults, there is a pervasive reluctance to use ECT in children and adolescents. We report the case of a pre-pubertal child in an episode of severe depression with catatonic features, where a protracted course of ECT proved life-saving in spite of prolonged duration of seizures and delayed response to treatment. The case illustrates the safety and efficacy of ECT in children. Relevant literature is also reviewed along with the case report.

  20. Pubertal development and fertility in survivors of childhood acute myeloid leukemia treated with chemotherapy only

    DEFF Research Database (Denmark)

    Molgaard-Hansen, Lene; Skou, Anne-Sofie; Juul, Anders

    2013-01-01

    More than 60% of children with acute myeloid leukemia (AML) become long-term survivors. Most are cured using chemotherapy without hematopoietic stem cell transplantation (HSCT). We report on pubertal development and compare self-reported parenthood among AML survivors and their siblings.......More than 60% of children with acute myeloid leukemia (AML) become long-term survivors. Most are cured using chemotherapy without hematopoietic stem cell transplantation (HSCT). We report on pubertal development and compare self-reported parenthood among AML survivors and their siblings....

  1. Mutation analysis of cathepsin C gene in a Chinese patient with pre-pubertal periodontitis

    Institute of Scientific and Technical Information of China (English)

    YANG Yuan; BAI Xiao-wen; SONG Shu-juan; GE Li-hong; CAO Cai-fang

    2005-01-01

    @@ Pre-pubertal periodontitis (PPP) is a rare and rapidly progressive form of early onset periodontitis resulting in premature tooth loss of primary and permanent dentitions. Mutations in cathepsin C (CTSC) gene have been found in patients with pre-pubertal periodontitis and Papillon-Lefevre syndrome which also characterized with severe periodontitis and palmoplantar hyperkera-tosis.1-3 To date, more than 40 mutations of CTSC gene have been identified in ethnically diverse people worldwide.4 However, there is no such genetic analysis in China. In the present study, we report the mutation analysis of a Chinese patient with PPP.

  2. Real-time seismic intensity prediction using frequency-dependent site amplification factors

    Science.gov (United States)

    Ogiso, Masashi; Aoki, Shigeki; Hoshiba, Mitsuyuki

    2016-05-01

    A promising approach for the next generation of earthquake early warning system is based on predicting ground motion directly from observed ground motion, without any information of hypocenter. In this study, we predicted seismic intensity at the target stations from the observed ground motion at adjacent stations, employing two different methods of correction for site amplification factors. The first method was frequency-dependent correction prediction, in which we used a digital causal filter to correct the site amplification for the observed waveform in the time domain. The second method was scalar correction, in which we used average differences in seismic intensity between two stations for the site amplification correction. Results from thousands of station pairs that covered almost all of Japan showed that seismic intensity prediction with frequency-dependent correction prediction was more accurate than prediction with scalar correction. Frequency-dependent correction for site amplification in the time domain may lead to more accurate prediction of ground motion in real time.

  3. Accuracy of the Timed Up and Go test for predicting sarcopenia in elderly hospitalized patients.

    Science.gov (United States)

    Martinez, Bruno Prata; Gomes, Isabela Barboza; Oliveira, Carolina Santana de; Ramos, Isis Resende; Rocha, Mônica Diniz Marques; Forgiarini Júnior, Luiz Alberto; Camelier, Fernanda Warken Rosa; Camelier, Aquiles Assunção

    2015-05-01

    The ability of the Timed Up and Go test to predict sarcopenia has not been evaluated previously. The objective of this study was to evaluate the accuracy of the Timed Up and Go test for predicting sarcopenia in elderly hospitalized patients. This cross-sectional study analyzed 68 elderly patients (≥60 years of age) in a private hospital in the city of Salvador-BA, Brazil, between the 1st and 5th day of hospitalization. The predictive variable was the Timed Up and Go test score, and the outcome of interest was the presence of sarcopenia (reduced muscle mass associated with a reduction in handgrip strength and/or weak physical performance in a 6-m gait-speed test). After the descriptive data analyses, the sensitivity, specificity and accuracy of a test using the predictive variable to predict the presence of sarcopenia were calculated. In total, 68 elderly individuals, with a mean age 70.4±7.7 years, were evaluated. The subjects had a Charlson Comorbidity Index score of 5.35±1.97. Most (64.7%) of the subjects had a clinical admission profile; the main reasons for hospitalization were cardiovascular disorders (22.1%), pneumonia (19.1%) and abdominal disorders (10.2%). The frequency of sarcopenia in the sample was 22.1%, and the mean length of time spent performing the Timed Up and Go test was 10.02±5.38 s. A time longer than or equal to a cutoff of 10.85 s on the Timed Up and Go test predicted sarcopenia with a sensitivity of 67% and a specificity of 88.7%. The accuracy of this cutoff for the Timed Up and Go test was good (0.80; IC=0.66-0.94; p=0.002). The Timed Up and Go test was shown to be a predictor of sarcopenia in elderly hospitalized patients.

  4. A maintenance time prediction method considering ergonomics through virtual reality simulation.

    Science.gov (United States)

    Zhou, Dong; Zhou, Xin-Xin; Guo, Zi-Yue; Lv, Chuan

    2016-01-01

    Maintenance time is a critical quantitative index in maintainability prediction. An efficient maintenance time measurement methodology plays an important role in early stage of the maintainability design. While traditional way to measure the maintenance time ignores the differences between line production and maintenance action. This paper proposes a corrective MOD method considering several important ergonomics factors to predict the maintenance time. With the help of the DELMIA analysis tools, the influence coefficient of several factors are discussed to correct the MOD value and the designers can measure maintenance time by calculating the sum of the corrective MOD time of each maintenance therbligs. Finally a case study is introduced, by maintaining the virtual prototype of APU motor starter in DELMIA, designer obtains the actual maintenance time by the proposed method, and the result verifies the effectiveness and accuracy of the proposed method.

  5. LPTA: Location Predictive and Time Adaptive Data Gathering Scheme with Mobile Sink for Wireless Sensor Networks

    Directory of Open Access Journals (Sweden)

    Chuan Zhu

    2014-01-01

    Full Text Available This paper exploits sink mobility to prolong the lifetime of sensor networks while maintaining the data transmission delay relatively low. A location predictive and time adaptive data gathering scheme is proposed. In this paper, we introduce a sink location prediction principle based on loose time synchronization and deduce the time-location formulas of the mobile sink. According to local clocks and the time-location formulas of the mobile sink, nodes in the network are able to calculate the current location of the mobile sink accurately and route data packets timely toward the mobile sink by multihop relay. Considering that data packets generating from different areas may be different greatly, an adaptive dwelling time adjustment method is also proposed to balance energy consumption among nodes in the network. Simulation results show that our data gathering scheme enables data routing with less data transmission time delay and balance energy consumption among nodes.

  6. Driver Vision Based Perception-Response Time Prediction and Assistance Model on Mountain Highway Curve

    Science.gov (United States)

    Li, Yi; Chen, Yuren

    2016-01-01

    To make driving assistance system more humanized, this study focused on the prediction and assistance of drivers’ perception-response time on mountain highway curves. Field tests were conducted to collect real-time driving data and driver vision information. A driver-vision lane model quantified curve elements in drivers’ vision. A multinomial log-linear model was established to predict perception-response time with traffic/road environment information, driver-vision lane model, and mechanical status (last second). A corresponding assistance model showed a positive impact on drivers’ perception-response times on mountain highway curves. Model results revealed that the driver-vision lane model and visual elements did have important influence on drivers’ perception-response time. Compared with roadside passive road safety infrastructure, proper visual geometry design, timely visual guidance, and visual information integrality of a curve are significant factors for drivers’ perception-response time. PMID:28042851

  7. Driver Vision Based Perception-Response Time Prediction and Assistance Model on Mountain Highway Curve

    Directory of Open Access Journals (Sweden)

    Yi Li

    2016-12-01

    Full Text Available To make driving assistance system more humanized, this study focused on the prediction and assistance of drivers’ perception-response time on mountain highway curves. Field tests were conducted to collect real-time driving data and driver vision information. A driver-vision lane model quantified curve elements in drivers’ vision. A multinomial log-linear model was established to predict perception-response time with traffic/road environment information, driver-vision lane model, and mechanical status (last second. A corresponding assistance model showed a positive impact on drivers’ perception-response times on mountain highway curves. Model results revealed that the driver-vision lane model and visual elements did have important influence on drivers’ perception-response time. Compared with roadside passive road safety infrastructure, proper visual geometry design, timely visual guidance, and visual information integrality of a curve are significant factors for drivers’ perception-response time.

  8. Driver Vision Based Perception-Response Time Prediction and Assistance Model on Mountain Highway Curve.

    Science.gov (United States)

    Li, Yi; Chen, Yuren

    2016-12-30

    To make driving assistance system more humanized, this study focused on the prediction and assistance of drivers' perception-response time on mountain highway curves. Field tests were conducted to collect real-time driving data and driver vision information. A driver-vision lane model quantified curve elements in drivers' vision. A multinomial log-linear model was established to predict perception-response time with traffic/road environment information, driver-vision lane model, and mechanical status (last second). A corresponding assistance model showed a positive impact on drivers' perception-response times on mountain highway curves. Model results revealed that the driver-vision lane model and visual elements did have important influence on drivers' perception-response time. Compared with roadside passive road safety infrastructure, proper visual geometry design, timely visual guidance, and visual information integrality of a curve are significant factors for drivers' perception-response time.

  9. Improving the Prediction of Total Surgical Procedure Time Using Linear Regression Modeling.

    Science.gov (United States)

    Edelman, Eric R; van Kuijk, Sander M J; Hamaekers, Ankie E W; de Korte, Marcel J M; van Merode, Godefridus G; Buhre, Wolfgang F F A

    2017-01-01

    For efficient utilization of operating rooms (ORs), accurate schedules of assigned block time and sequences of patient cases need to be made. The quality of these planning tools is dependent on the accurate prediction of total procedure time (TPT) per case. In this paper, we attempt to improve the accuracy of TPT predictions by using linear regression models based on estimated surgeon-controlled time (eSCT) and other variables relevant to TPT. We extracted data from a Dutch benchmarking database of all surgeries performed in six academic hospitals in The Netherlands from 2012 till 2016. The final dataset consisted of 79,983 records, describing 199,772 h of total OR time. Potential predictors of TPT that were included in the subsequent analysis were eSCT, patient age, type of operation, American Society of Anesthesiologists (ASA) physical status classification, and type of anesthesia used. First, we computed the predicted TPT based on a previously described fixed ratio model for each record, multiplying eSCT by 1.33. This number is based on the research performed by van Veen-Berkx et al., which showed that 33% of SCT is generally a good approximation of anesthesia-controlled time (ACT). We then systematically tested all possible linear regression models to predict TPT using eSCT in combination with the other available independent variables. In addition, all regression models were again tested without eSCT as a predictor to predict ACT separately (which leads to TPT by adding SCT). TPT was most accurately predicted using a linear regression model based on the independent variables eSCT, type of operation, ASA classification, and type of anesthesia. This model performed significantly better than the fixed ratio model and the method of predicting ACT separately. Making use of these more accurate predictions in planning and sequencing algorithms may enable an increase in utilization of ORs, leading to significant financial and productivity related benefits.

  10. Improving the Prediction of Total Surgical Procedure Time Using Linear Regression Modeling

    Directory of Open Access Journals (Sweden)

    Eric R. Edelman

    2017-06-01

    Full Text Available For efficient utilization of operating rooms (ORs, accurate schedules of assigned block time and sequences of patient cases need to be made. The quality of these planning tools is dependent on the accurate prediction of total procedure time (TPT per case. In this paper, we attempt to improve the accuracy of TPT predictions by using linear regression models based on estimated surgeon-controlled time (eSCT and other variables relevant to TPT. We extracted data from a Dutch benchmarking database of all surgeries performed in six academic hospitals in The Netherlands from 2012 till 2016. The final dataset consisted of 79,983 records, describing 199,772 h of total OR time. Potential predictors of TPT that were included in the subsequent analysis were eSCT, patient age, type of operation, American Society of Anesthesiologists (ASA physical status classification, and type of anesthesia used. First, we computed the predicted TPT based on a previously described fixed ratio model for each record, multiplying eSCT by 1.33. This number is based on the research performed by van Veen-Berkx et al., which showed that 33% of SCT is generally a good approximation of anesthesia-controlled time (ACT. We then systematically tested all possible linear regression models to predict TPT using eSCT in combination with the other available independent variables. In addition, all regression models were again tested without eSCT as a predictor to predict ACT separately (which leads to TPT by adding SCT. TPT was most accurately predicted using a linear regression model based on the independent variables eSCT, type of operation, ASA classification, and type of anesthesia. This model performed significantly better than the fixed ratio model and the method of predicting ACT separately. Making use of these more accurate predictions in planning and sequencing algorithms may enable an increase in utilization of ORs, leading to significant financial and productivity related

  11. Time series analysis as input for clinical predictive modeling: Modeling cardiac arrest in a pediatric ICU

    Directory of Open Access Journals (Sweden)

    Kennedy Curtis E

    2011-10-01

    Full Text Available Abstract Background Thousands of children experience cardiac arrest events every year in pediatric intensive care units. Most of these children die. Cardiac arrest prediction tools are used as part of medical emergency team evaluations to identify patients in standard hospital beds that are at high risk for cardiac arrest. There are no models to predict cardiac arrest in pediatric intensive care units though, where the risk of an arrest is 10 times higher than for standard hospital beds. Current tools are based on a multivariable approach that does not characterize deterioration, which often precedes cardiac arrests. Characterizing deterioration requires a time series approach. The purpose of this study is to propose a method that will allow for time series data to be used in clinical prediction models. Successful implementation of these methods has the potential to bring arrest prediction to the pediatric intensive care environment, possibly allowing for interventions that can save lives and prevent disabilities. Methods We reviewed prediction models from nonclinical domains that employ time series data, and identified the steps that are necessary for building predictive models using time series clinical data. We illustrate the method by applying it to the specific case of building a predictive model for cardiac arrest in a pediatric intensive care unit. Results Time course analysis studies from genomic analysis provided a modeling template that was compatible with the steps required to develop a model from clinical time series data. The steps include: 1 selecting candidate variables; 2 specifying measurement parameters; 3 defining data format; 4 defining time window duration and resolution; 5 calculating latent variables for candidate variables not directly measured; 6 calculating time series features as latent variables; 7 creating data subsets to measure model performance effects attributable to various classes of candidate variables; 8

  12. Molecular Dynamics Simulations and Kinetic Measurements to Estimate and Predict Protein-Ligand Residence Times.

    Science.gov (United States)

    Mollica, Luca; Theret, Isabelle; Antoine, Mathias; Perron-Sierra, Françoise; Charton, Yves; Fourquez, Jean-Marie; Wierzbicki, Michel; Boutin, Jean A; Ferry, Gilles; Decherchi, Sergio; Bottegoni, Giovanni; Ducrot, Pierre; Cavalli, Andrea

    2016-08-11

    Ligand-target residence time is emerging as a key drug discovery parameter because it can reliably predict drug efficacy in vivo. Experimental approaches to binding and unbinding kinetics are nowadays available, but we still lack reliable computational tools for predicting kinetics and residence time. Most attempts have been based on brute-force molecular dynamics (MD) simulations, which are CPU-demanding and not yet particularly accurate. We recently reported a new scaled-MD-based protocol, which showed potential for residence time prediction in drug discovery. Here, we further challenged our procedure's predictive ability by applying our methodology to a series of glucokinase activators that could be useful for treating type 2 diabetes mellitus. We combined scaled MD with experimental kinetics measurements and X-ray crystallography, promptly checking the protocol's reliability by directly comparing computational predictions and experimental measures. The good agreement highlights the potential of our scaled-MD-based approach as an innovative method for computationally estimating and predicting drug residence times.

  13. Predictive analytics for truck arrival time estimation : a field study at a European distribution center

    NARCIS (Netherlands)

    van der Spoel, Sjoerd; Amrit, Chintan Amrit; van Hillegersberg, Jos

    2017-01-01

    Distribution centres (DCs) are the hubs connecting transport streams in the supply chain. The synchronisation of coming and going cargo at a DC requires reliable arrival times. To achieve this, a reliable method to predict arrival times is needed. A literature review was performed to find the factor

  14. Predictive analytics for truck arrival time estimation: a field study at a European distribution center

    NARCIS (Netherlands)

    Spoel, van der Sjoerd; Amrit, Chintan; Hillegersberg, van Jos

    2015-01-01

    Distribution centres (DCs) are the hubs connecting transport streams in the supply chain. The synchronisation of coming and going cargo at a DC requires reliable arrival times. To achieve this, a reliable method to predict arrival times is needed. A literature review was performed to find the factor

  15. A novel trajectory prediction control for proximate time-optimal digital control DC—DC converters

    Science.gov (United States)

    Qing, Wang; Ning, Chen; Shen, Xu; Weifeng, Sun; Longxing, Shi

    2014-09-01

    The purpose of this paper is to present a novel trajectory prediction method for proximate time-optimal digital control DC—DC converters. The control method provides pre-estimations of the duty ratio in the next several switching cycles, so as to compensate the computational time delay of the control loop and increase the control loop bandwidth, thereby improving the response speed. The experiment results show that the fastest transient response time of the digital DC—DC with the proposed prediction is about 8 μs when the load current changes from 0.6 to 0.1 A.

  16. A PSO-SVM Model for Short-Term Travel Time Prediction Based on Bluetooth Technology

    Institute of Scientific and Technical Information of China (English)

    Qun Wang; Zhuyun Liu; Zhongren Peng

    2015-01-01

    The accurate prediction of travel time along roadway provides valuable traffic information for travelers and traffic managers. Aiming at short⁃term travel time forecasting on urban arterials, a prediction model ( PSO⁃SVM) combining support vector machine ( SVM) and particle swarm optimization ( PSO) is developed. Travel time data collected with Bluetooth devices are used to calibrate the proposed model. Field experiments show that the PSO⁃SVM model ’ s error indicators are lower than the single SVM model and the BP neural network (BPNN)model. Particularly, the mean⁃absolute percentage error (MAPE) of PSO⁃SVM is only 9�453 4 %which is less than that of the single SVM model ( 12�230 2 %) and the BPNN model ( 15�314 7 %) . The results indicate that the proposed PSO⁃SVM model is feasible and more effective than other models for short⁃term travel time prediction on urban arterials.

  17. PREDICTION TECHNIQUES OF CHAOTIC TIME SERIES AND ITS APPLICATIONS AT LOW NOISE LEVEL

    Institute of Scientific and Technical Information of China (English)

    MA Jun-hai; WANG Zhi-qiang; CHEN Yu-shu

    2006-01-01

    The paper not only studies the noise reduction methods of chaotic time series with noise and its reconstruction techniques, but also discusses prediction techniques of chaotic time series and its applications based on chaotic data noise reduction. In the paper, we first decompose the phase space of chaotic time series to range space and null noise space. Secondly we restructure original chaotic time series in range space. Lastly on the basis of the above, we establish order of the nonlinear model and make use of the nonlinear model to predict some research. The result indicates that the nonlinear modelhas very strong ability of approximation function, and Chaos predict method has certain tutorial significance to the practical problems.

  18. The Coupled Model Predictability of the Western North Pacific Summer Monsoon with Different Leading Times

    Institute of Scientific and Technical Information of China (English)

    LU Ri-Yu; LI Chao-Fan; Se-Hwan YANG; Buwen DONG

    2012-01-01

    Leading time length is an important issue for modeling seasonal forecasts. In this study, a comparison of the interannual predictability of the Western North Pacific (WNP) summer monsoon between different leading months was performed by using one-, four-, and sevenmonth lead retrospective forecasts (hindcasts) of four coupled models from Ensembles-Based Predictions of Climate Changes and Their Impacts (ENSEMBLES) for the period of 1960 2005. It is found that the WNP summer anomalies, including lower-tropospheric circulation and precipitation anomalies, can be well predicted for all these leading months. The accuracy of the four-month lead prediction is only slightly weaker than that of the one-month lead prediction, although the skill decreases with the increase of leading months.

  19. Body trunk fat and insulin resistance in post-pubertal obese adolescents

    Directory of Open Access Journals (Sweden)

    Luana Caroline dos Santos

    Full Text Available CONTEXT AND OBJECTIVE: Insulin resistance is a metabolic disorder commonly associated with excess body fat accumulation that may increase chronic disease risk. The present study was undertaken to evaluate the relationship between body composition and insulin resistance among obese adolescents. DESIGN AND SETTING: Cross-sectional study, at the Adolescence Center, Pediatric Department, Universidade Federal de São Paulo. METHODS: Body composition was assessed using dual-energy X-ray absorptiometry. Dietary intake was evaluated using a three-day dietary record. The biochemical evaluation comprised glucose, insulin, serum lipid, leptin and ghrelin measurements. Insulin resistance was calculated by means of the homeostasis model assessment of insulin resistance (HOMA-IR. RESULTS: Forty-nine post-pubertal obese adolescents participated in the study: 12 boys and 37 girls of mean age 16.6 (1.4 years and mean body mass index (BMI of 35.0 (3.9 kg/m². The mean glucose, insulin and HOMA values were 90.3 (6.4 mg/dl, 16.6 (8.1 µIU/ml and 3.7 (1.9, respectively. Hyperinsulinemia and insulin resistance were observed in 40.2% and 57.1% of the subjects, respectively. Adolescents with insulin resistance had higher BMI and body trunk fat. There was a trend towards higher leptin concentration in obese individuals with insulin resistance. Insulin resistance was positively correlated with body trunk fat, BMI, body fat mass (kg, leptin and body fat percentage. Furthermore, there was a negative correlation between HOMA-IR and lean body mass. The body composition predicted 30% of the HOMA-IR levels, according to linear regression models. CONCLUSION: Body trunk fat was significantly associated with insulin resistance, demonstrating the clinical importance of abdominal obesity during adolescence.

  20. Review of methods for predicting in situ volume change movement of expansive soil over time

    Directory of Open Access Journals (Sweden)

    Hana H. Adem

    2015-02-01

    Full Text Available The soil movement information over time is required for the design of foundations placed in expansive soils. This information is also helpful for the assessment of pre-wetting and controlled wetting mitigation alternatives for expansive soils. Several researchers during the past fifteen years have proposed different methods for the prediction of the soil movements over time. The available methods can be categorized into (i consolidation theory-based methods, (ii water content-based methods, and (iii suction-based methods. In this paper, a state-of-the-art of the prediction methods is succinctly summarized. The methods are critically reviewed in terms of their predictive capacity along with their strengths and limitations. The review highlights the need for prediction methods that are conceptually simple yet efficient for use in conventional engineering practice for different types of expansive soils.

  1. Review of methods for predicting in situ volume change movement of expansive soil over time

    Institute of Scientific and Technical Information of China (English)

    Hana H. Adem; Sai K. Vanapalli

    2015-01-01

    The soil movement information over time is required for the design of foundations placed in expansive soils. This information is also helpful for the assessment of pre-wetting and controlled wetting mitigation alternatives for expansive soils. Several researchers during the past fifteen years have proposed different methods for the prediction of the soil movements over time. The available methods can be categorized into (i) consolidation theory-based methods, (ii) water content-based methods, and (iii) suction-based methods. In this paper, a state-of-the-art of the prediction methods is succinctly summarized. The methods are critically reviewed in terms of their predictive capacity along with their strengths and limitations. The review highlights the need for prediction methods that are conceptually simple yet efficient for use in conventional engineering practice for different types of expansive soils.

  2. Predicting Time Series from Short-Term High-Dimensional Data

    Science.gov (United States)

    Ma, Huanfei; Zhou, Tianshou; Aihara, Kazuyuki; Chen, Luonan

    The prediction of future values of time series is a challenging task in many fields. In particular, making prediction based on short-term data is believed to be difficult. Here, we propose a method to predict systems' low-dimensional dynamics from high-dimensional but short-term data. Intuitively, it can be considered as a transformation from the inter-variable information of the observed high-dimensional data into the corresponding low-dimensional but long-term data, thereby equivalent to prediction of time series data. Technically, this method can be viewed as an inverse implementation of delayed embedding reconstruction. Both methods and algorithms are developed. To demonstrate the effectiveness of the theoretical result, benchmark examples and real-world problems from various fields are studied.

  3. Prediction of Gas Emission Based on Information Fusion and Chaotic Time Series

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    In order to make more exact predictions of gas emissions, information fusion and chaos time series are combined to predict the amount of gas emission in pits. First, a multi-sensor information fusion frame is established. The frame includes a data level, a character level and a decision level. Functions at every level are interpreted in detail in this paper. Then, the process of information fusion for gas emission is introduced. On the basis of those data processed at the data and character levels, the chaos time series and neural network are combined to predict the amount of gas emission at the decision level. The weights of the neural network are gained by training not by manual setting, in order to avoid subjectivity introduced by human intervention. Finally, the experimental results were analyzed in Matlab 6.0 and prove that the method is more accurate in the prediction of the amount of gas emission than the traditional method.

  4. Accuracy of patient's turnover time prediction using RFID technology in an academic ambulatory surgery center.

    Science.gov (United States)

    Marchand-Maillet, Florence; Debes, Claire; Garnier, Fanny; Dufeu, Nicolas; Sciard, Didier; Beaussier, Marc

    2015-02-01

    Patients flow in outpatient surgical unit is a major issue with regards to resource utilization, overall case load and patient satisfaction. An electronic Radio Frequency Identification Device (RFID) was used to document the overall time spent by the patients between their admission and discharge from the unit. The objective of this study was to evaluate how a RFID-based data collection system could provide an accurate prediction of the actual time for the patient to be discharged from the ambulatory surgical unit after surgery. This is an observational prospective evaluation carried out in an academic ambulatory surgery center (ASC). Data on length of stay at each step of the patient care, from admission to discharge, were recorded by a RFID device and analyzed according to the type of surgical procedure, the surgeon and the anesthetic technique. Based on these initial data (n = 1520), patients were scheduled in a sequential manner according to the expected duration of the previous case. The primary endpoint was the difference between actual and predicted time of discharge from the unit. A total of 414 consecutive patients were prospectively evaluated. One hundred seventy four patients (42%) were discharged at the predicted time ± 30 min. Only 24% were discharged behind predicted schedule. Using an automatic record of patient's length of stay would allow an accurate prediction of the discharge time according to the type of surgery, the surgeon and the anesthetic procedure.

  5. Neighbourhood selection for local modelling and prediction of hydrological time series

    Science.gov (United States)

    Jayawardena, A. W.; Li, W. K.; Xu, P.

    2002-02-01

    The prediction of a time series using the dynamical systems approach requires the knowledge of three parameters; the time delay, the embedding dimension and the number of nearest neighbours. In this paper, a new criterion, based on the generalized degrees of freedom, for the selection of the number of nearest neighbours needed for a better local model for time series prediction is presented. The validity of the proposed method is examined using time series, which are known to be chaotic under certain initial conditions (Lorenz map, Henon map and Logistic map), and real hydro meteorological time series (discharge data from Chao Phraya river in Thailand, Mekong river in Thailand and Laos, and sea surface temperature anomaly data). The predicted results are compared with observations, and with similar predictions obtained by using arbitrarily fixed numbers of neighbours. The results indicate superior predictive capability as measured by the mean square errors and coefficients of variation by the proposed approach when compared with the traditional approach of using a fixed number of neighbours.

  6. Longitudinal changes in adolescent risk-taking: a comprehensive study of neural responses to rewards, pubertal development, and risk-taking behavior.

    Science.gov (United States)

    Braams, Barbara R; van Duijvenvoorde, Anna C K; Peper, Jiska S; Crone, Eveline A

    2015-05-01

    Prior studies have highlighted adolescence as a period of increased risk-taking, which is postulated to result from an overactive reward system in the brain. Longitudinal studies are pivotal for testing these brain-behavior relations because individual slopes are more sensitive for detecting change. The aim of the current study was twofold: (1) to test patterns of age-related change (i.e., linear, quadratic, and cubic) in activity in the nucleus accumbens, a key reward region in the brain, in relation to change in puberty (self-report and testosterone levels), laboratory risk-taking and self-reported risk-taking tendency; and (2) to test whether individual differences in pubertal development and risk-taking behavior were contributors to longitudinal change in nucleus accumbens activity. We included 299 human participants at the first time point and 254 participants at the second time point, ranging between ages 8-27 years, time points were separated by a 2 year interval. Neural responses to rewards, pubertal development (self-report and testosterone levels), laboratory risk-taking (balloon analog risk task; BART), and self-reported risk-taking tendency (Behavior Inhibition System/Behavior Activation System questionnaire) were collected at both time points. The longitudinal analyses confirmed the quadratic age pattern for nucleus accumbens activity to rewards (peaking in adolescence), and the same quadratic pattern was found for laboratory risk-taking (BART). Nucleus accumbens activity change was further related to change in testosterone and self-reported reward-sensitivity (BAS Drive). Thus, this longitudinal analysis provides new insight in risk-taking and reward sensitivity in adolescence: (1) confirming an adolescent peak in nucleus accumbens activity, and (2) underlining a critical role for pubertal hormones and individual differences in risk-taking tendency.

  7. The effect of a complex training and detraining programme on selected strength and power variables in early pubertal boys.

    Science.gov (United States)

    Ingle, Lee; Sleap, Mike; Tolfrey, Keith

    2006-09-01

    Complex training, a combination of resistance training and plyometrics is growing in popularity, despite limited support for its efficacy. In pre- and early pubertal children, the study of complex training has been limited, and to our knowledge an examination of its effect on anaerobic performance characteristics of the upper and lower body has not been undertaken. Furthermore, the effect of detraining after complex training requires clarification. The physical characteristics (mean+/-s) of the 54 male participants in the present study were as follows: age 12.3 +/- 0.3 years, height 1.57 +/- 0.07 m, body mass 50.3 +/- 11.0 kg. Participants were randomly assigned to an experimental (n = 33) or control group (n = 21). The training, which was performed three times a week for 12 weeks, included a combination of dynamic constant external resistance and plyometrics. After training, participants completed 12 weeks of detraining. At baseline, after training and after detraining, peak and mean anaerobic power, dynamic strength and athletic performance were assessed. Twenty-six participants completed the training and none reported any training-related injury. Complex training was associated with small increases ( 0.05). In the experimental group, dynamic strength was increased by 24.3 - 71.4% (dependent on muscle group; P 0.05). For 40-m sprint running, basketball chest pass and vertical jump test performance, the experimental group saw a small improvement ( 0.05). In conclusion, in pre- and early pubertal boys, upper and lower body complex training is a time-effective and safe training modality that confers small improvements in anaerobic power and jumping, throwing and sprinting performance, and marked improvements in dynamic strength. However, after detraining, the benefits of complex training are lost at similar rates to other training modalities.

  8. Prediction of oil expression by uniaxial compression using time-varying oilseed properties

    DEFF Research Database (Denmark)

    Bargale, P. C.; Wulfsohn, Dvoralai; Irudayaraj, J.

    2000-01-01

    recovery for extruded soybean very well, the predictions were not satisfactory for sunflower seed samples. The higher error was attributed to material non-homogeneity and the presence of hulls in the sunflower seeds, which increased errors in measurement of the medium permeability function. The lack...... of experimental permeability data in the very early stages of pressing (t properties in the simulations resulted in substantially more accurate predictions of quantities and trends in oil recovery with time, when compared...

  9. Discussion About Nonlinear Time Series Prediction Using Least Squares Support Vector Machine

    Institute of Scientific and Technical Information of China (English)

    XU Rui-Rui; BIAN Guo-Xing; GAO Chen-Feng; CHEN Tian-Lun

    2005-01-01

    The least squares support vector machine (LS-SVM) is used to study the nonlinear time series prediction.First, the parameter γ and multi-step prediction capabilities of the LS-SVM network are discussed. Then we employ clustering method in the model to prune the number of the support values. The learning rate and the capabilities of filtering noise for LS-SVM are all greatly improved.

  10. Two Machine Learning Approaches for Short-Term Wind Speed Time-Series Prediction.

    Science.gov (United States)

    Ak, Ronay; Fink, Olga; Zio, Enrico

    2016-08-01

    The increasing liberalization of European electricity markets, the growing proportion of intermittent renewable energy being fed into the energy grids, and also new challenges in the patterns of energy consumption (such as electric mobility) require flexible and intelligent power grids capable of providing efficient, reliable, economical, and sustainable energy production and distribution. From the supplier side, particularly, the integration of renewable energy sources (e.g., wind and solar) into the grid imposes an engineering and economic challenge because of the limited ability to control and dispatch these energy sources due to their intermittent characteristics. Time-series prediction of wind speed for wind power production is a particularly important and challenging task, wherein prediction intervals (PIs) are preferable results of the prediction, rather than point estimates, because they provide information on the confidence in the prediction. In this paper, two different machine learning approaches to assess PIs of time-series predictions are considered and compared: 1) multilayer perceptron neural networks trained with a multiobjective genetic algorithm and 2) extreme learning machines combined with the nearest neighbors approach. The proposed approaches are applied for short-term wind speed prediction from a real data set of hourly wind speed measurements for the region of Regina in Saskatchewan, Canada. Both approaches demonstrate good prediction precision and provide complementary advantages with respect to different evaluation criteria.

  11. Ship motion extreme short time prediction of ship pitch based on diagonal recurrent neural network

    Institute of Scientific and Technical Information of China (English)

    SHEN Yan; XIE Mei-ping

    2005-01-01

    A DRNN (diagonal recurrent neural network) and its RPE (recurrent prediction error) learning algorithm are proposed in this paper .Using of the simple structure of DRNN can reduce the capacity of calculation. The principle of RPE learning algorithm is to adjust weights along the direction of Gauss-Newton. Meanwhile, it is unnecessary to calculate the second local derivative and the inverse matrixes, whose unbiasedness is proved. With application to the extremely short time prediction of large ship pitch, satisfactory results are obtained. Prediction effect of this algorithm is compared with that of auto-regression and periodical diagram method, and comparison results show that the proposed algorithm is feasible.

  12. Short Term Prediction of PM10 Concentrations Using Seasonal Time Series Analysis

    OpenAIRE

    Hamid Hazrul Abdul; Yahaya Ahmad Shukri; Ramli Nor Azam; Ul-Saufie Ahmad Zia; Yasin Mohd Norazam

    2016-01-01

    Air pollution modelling is one of an important tool that usually used to make short term and long term prediction. Since air pollution gives a big impact especially to human health, prediction of air pollutants concentration is needed to help the local authorities to give an early warning to people who are in risk of acute and chronic health effects from air pollution. Finding the best time series model would allow prediction to be made accurately. This research was carried out to find the be...

  13. Predicting Natural and Chaotic Time Series with a Swarm-Optimized Neural Network

    Institute of Scientific and Technical Information of China (English)

    Juan A. Lazzús

    2011-01-01

    Natural and chaotic time series are predicted using an artificial neural network (ANN) based on particle swarm optimization (PSO).Firstly,the hybrid ANN+PSO algorithm is applied on Mackey-Glass series in the short-term prediction x(t + 6),using the current value x(t) and the past values:x(t - 6),x(t - 12),x(t - 18).Then,this method is applied on solar radiation data using the values of the past years:x(t - 1),...,x(t - 4).The results show that the ANN+PSO method is a very powerful tool for making predictions of natural and chaotic time series.Chaotic time series is an important research and application area.Several models for time series data can have many forms and represent different stochastic processes.Time series contain much information about dynamic systems.[1] These systems are usually modeled by delay-differential equations.[2]%Natural and chaotic time series are predicted using an artificial neural network (ANN) based on particle swarm optimization (PSO). Firstly, the hybrid ANN+PSO algorithm is applied on Mackey-Glass series in the short-term prediction x(t + 6), using the current value x(t) and the past values: x(t - 6), x(t - 12), x(t - 18). Then, this method is applied on solar radiation data using the values of the past years: x(t - 1), ..., x(t - 4). The results show that the ANN+PSO method is a very powerful tool for making predictions of natural and chaotic time series.

  14. Multivariable time series prediction for the icing process on overhead power transmission line.

    Science.gov (United States)

    Li, Peng; Zhao, Na; Zhou, Donghua; Cao, Min; Li, Jingjie; Shi, Xinling

    2014-01-01

    The design of monitoring and predictive alarm systems is necessary for successful overhead power transmission line icing. Given the characteristics of complexity, nonlinearity, and fitfulness in the line icing process, a model based on a multivariable time series is presented here to predict the icing load of a transmission line. In this model, the time effects of micrometeorology parameters for the icing process have been analyzed. The phase-space reconstruction theory and machine learning method were then applied to establish the prediction model, which fully utilized the history of multivariable time series data in local monitoring systems to represent the mapping relationship between icing load and micrometeorology factors. Relevant to the characteristic of fitfulness in line icing, the simulations were carried out during the same icing process or different process to test the model's prediction precision and robustness. According to the simulation results for the Tao-Luo-Xiong Transmission Line, this model demonstrates a good accuracy of prediction in different process, if the prediction length is less than two hours, and would be helpful for power grid departments when deciding to take action in advance to address potential icing disasters.

  15. Leave-one-out prediction error of systolic arterial pressure time series under paced breathing

    CERN Document Server

    Ancona, N; Marinazzo, D; Nitti, L; Pellicoro, M; Pinna, G D; Stramaglia, S

    2004-01-01

    In this paper we show that different physiological states and pathological conditions may be characterized in terms of predictability of time series signals from the underlying biological system. In particular we consider systolic arterial pressure time series from healthy subjects and Chronic Heart Failure patients, undergoing paced respiration. We model time series by the regularized least squares approach and quantify predictability by the leave-one-out error. We find that the entrainment mechanism connected to paced breath, that renders the arterial blood pressure signal more regular, thus more predictable, is less effective in patients, and this effect correlates with the seriousness of the heart failure. The leave-one-out error separates controls from patients and, when all orders of nonlinearity are taken into account, alive patients from patients for which cardiac death occurred.

  16. Real-time mobile robot teleoperation via Internet based on predictive control

    Institute of Scientific and Technical Information of China (English)

    Shihua WANG; Bugong XU; YunHui LIU; Yeming ZHOU

    2008-01-01

    A remote control system that can control a mobile robot in real time via the internet is proposed. To compensate for the network delay and counteract its impact on the teleoperation system, a predictive control scheme based on the modified Smith predictor proposed is selected. To ensure the stability and transparency of the system, a dynamic model manager is designed based on the information exchange between the sensors at the mas-ter and slave sides. To precisely predict the time delay, a new timer synchronization algorithm is proposed. To decrease delay- jitter, a new data buffer scheme is per-formed. Force feedback and a virtual predictive display are introduced to enhance the real-time efficiency of tele-operation. The usefulness and effectiveness of the pro-posed method and system are proven by teleoperation experiments via the internet over a long distance.

  17. Time history prediction of direct-drive implosions on the Omega facility

    Science.gov (United States)

    Laffite, S.; Bourgade, J. L.; Caillaud, T.; Delettrez, J. A.; Frenje, J. A.; Girard, F.; Glebov, V. Yu.; Joshi, T.; Landoas, O.; Legay, G.; Lemaire, S.; Mancini, R. C.; Marshall, F. J.; Masse, L.; Masson-Laborde, P. E.; Michel, D. T.; Philippe, F.; Reverdin, C.; Seka, W.; Tassin, V.

    2016-01-01

    We present in this article direct-drive experiments that were carried out on the Omega facility [T. R. Boehly et al., Opt. Commun. 133, 495 (1997)]. Two different pulse shapes were tested in order to vary the implosion stability of the same target whose parameters, dimensions and composition, remained the same. The direct-drive configuration on the Omega facility allows the accurate time-resolved measurement of the scattered light. We show that, provided the laser coupling is well controlled, the implosion time history, assessed by the "bang-time" and the shell trajectory measurements, can be predicted. This conclusion is independent on the pulse shape. In contrast, we show that the pulse shape affects the implosion stability, assessed by comparing the target performances between prediction and measurement. For the 1-ns square pulse, the measured neutron number is about 80% of the prediction. For the 2-step 2-ns pulse, we test here that this ratio falls to about 20%.

  18. Models to Predict Flowering Time in the Main Saffron Production Regions of Khorasan Province

    Science.gov (United States)

    Behdani, M. A.; Koocheki, A.; Nassiri, M.; Rezvani, P.

    The objective of this study was to develop a thermal model that can be used for prediction of saffron flowering time. For this purpose, existing data on saffron flower emergence time were collected in a wide range of temperature regimes over the saffron production regions of Khorasan province, Iran. Linear second-order polynomial and 5-parameter beta models were used and statistically compared for their ability in predicting saffron flowering time as a function of temperature. The results showed a significant delay in flowering date across the temperature gradient. While beta model had a better statistical performance but the simple linear model also showed a good predicting ability and therefore, can be used as a reliable model.

  19. Real time remaining useful life prediction based on nonlinear Wiener based degradation processes with measurement errors

    Institute of Scientific and Technical Information of China (English)

    唐圣金; 郭晓松; 于传强; 周志杰; 周召发; 张邦成

    2014-01-01

    Real time remaining useful life (RUL) prediction based on condition monitoring is an essential part in condition based maintenance (CBM). In the current methods about the real time RUL prediction of the nonlinear degradation process, the measurement error is not considered and forecasting uncertainty is large. Therefore, an approximate analytical RUL distribution in a closed-form of a nonlinear Wiener based degradation process with measurement errors was proposed. The maximum likelihood estimation approach was used to estimate the unknown fixed parameters in the proposed model. When the newly observed data are available, the random parameter is updated by the Bayesian method to make the estimation adapt to the item’s individual characteristic and reduce the uncertainty of the estimation. The simulation results show that considering measurement errors in the degradation process can significantly improve the accuracy of real time RUL prediction.

  20. Research on power grid loss prediction model based on Granger causality property of time series

    Energy Technology Data Exchange (ETDEWEB)

    Wang, J. [North China Electric Power Univ., Beijing (China); State Grid Corp., Beijing (China); Yan, W.P.; Yuan, J. [North China Electric Power Univ., Beijing (China); Xu, H.M.; Wang, X.L. [State Grid Information and Telecommunications Corp., Beijing (China)

    2009-03-11

    This paper described a method of predicting power transmission line losses using the Granger causality property of time series. The stable property of the time series was investigated using unit root tests. The Granger causality relationship between line losses and other variables was then determined. Granger-caused time series were then used to create the following 3 prediction models: (1) a model based on line loss binomials that used electricity sales to predict variables, (2) a model that considered both power sales and grid capacity, and (3) a model based on autoregressive distributed lag (ARDL) approaches that incorporated both power sales and the square of power sales as variables. A case study of data from China's electric power grid between 1980 and 2008 was used to evaluate model performance. Results of the study showed that the model error rates ranged between 2.7 and 3.9 percent. 6 refs., 3 tabs., 1 fig.

  1. Iterative prediction of chaotic time series using a recurrent neural network

    Energy Technology Data Exchange (ETDEWEB)

    Essawy, M.A.; Bodruzzaman, M. [Tennessee State Univ., Nashville, TN (United States). Dept. of Electrical and Computer Engineering; Shamsi, A.; Noel, S. [USDOE Morgantown Energy Technology Center, WV (United States)

    1996-12-31

    Chaotic systems are known for their unpredictability due to their sensitive dependence on initial conditions. When only time series measurements from such systems are available, neural network based models are preferred due to their simplicity, availability, and robustness. However, the type of neutral network used should be capable of modeling the highly non-linear behavior and the multi-attractor nature of such systems. In this paper the authors use a special type of recurrent neural network called the ``Dynamic System Imitator (DSI)``, that has been proven to be capable of modeling very complex dynamic behaviors. The DSI is a fully recurrent neural network that is specially designed to model a wide variety of dynamic systems. The prediction method presented in this paper is based upon predicting one step ahead in the time series, and using that predicted value to iteratively predict the following steps. This method was applied to chaotic time series generated from the logistic, Henon, and the cubic equations, in addition to experimental pressure drop time series measured from a Fluidized Bed Reactor (FBR), which is known to exhibit chaotic behavior. The time behavior and state space attractor of the actual and network synthetic chaotic time series were analyzed and compared. The correlation dimension and the Kolmogorov entropy for both the original and network synthetic data were computed. They were found to resemble each other, confirming the success of the DSI based chaotic system modeling.

  2. Prediction of peptide drift time in ion mobility mass spectrometry from sequence-based features

    KAUST Repository

    Wang, Bing

    2013-05-09

    Background: Ion mobility-mass spectrometry (IMMS), an analytical technique which combines the features of ion mobility spectrometry (IMS) and mass spectrometry (MS), can rapidly separates ions on a millisecond time-scale. IMMS becomes a powerful tool to analyzing complex mixtures, especially for the analysis of peptides in proteomics. The high-throughput nature of this technique provides a challenge for the identification of peptides in complex biological samples. As an important parameter, peptide drift time can be used for enhancing downstream data analysis in IMMS-based proteomics.Results: In this paper, a model is presented based on least square support vectors regression (LS-SVR) method to predict peptide ion drift time in IMMS from the sequence-based features of peptide. Four descriptors were extracted from peptide sequence to represent peptide ions by a 34-component vector. The parameters of LS-SVR were selected by a grid searching strategy, and a 10-fold cross-validation approach was employed for the model training and testing. Our proposed method was tested on three datasets with different charge states. The high prediction performance achieve demonstrate the effectiveness and efficiency of the prediction model.Conclusions: Our proposed LS-SVR model can predict peptide drift time from sequence information in relative high prediction accuracy by a test on a dataset of 595 peptides. This work can enhance the confidence of protein identification by combining with current protein searching techniques. 2013 Wang et al.; licensee BioMed Central Ltd.

  3. Personal best times in an Olympic distance triathlon and in a marathon predict Ironman race time in recreational male triathletes

    Directory of Open Access Journals (Sweden)

    Knechtle P

    2011-08-01

    Full Text Available Christoph Alexander Rüst1, Beat Knechtle1,2, Patrizia Knechtle2, Thomas Rosemann1, Romuald Lepers31Institute of General Practice and Health Services Research, University of Zurich, Zurich, Switzerland; 2Gesundheitszentrum St Gallen, St Gallen, Switzerland; 3INSERM U887, University of Burgundy, Faculty of Sport Sciences, Dijon, FranceBackground: The purpose of this study was to define predictor variables for recreational male Ironman triathletes, using age and basic measurements of anthropometry, training, and previous performance to establish an equation for the prediction of an Ironman race time for future recreational male Ironman triathletes.Methods: Age and anthropometry, training, and previous experience variables were related to Ironman race time using bivariate and multivariate analysis.Results: A total of 184 recreational male triathletes, of mean age 40.9 ± 8.4 years, height 1.80 ± 0.06 m, and weight 76.3 ± 8.4 kg completed the Ironman within 691 ± 83 minutes. They spent 13.9 ± 5.0 hours per week in training, covering 6.3 ± 3.1 km of swimming, 194.4 ± 76.6 km of cycling, and 45.0 ± 15.9 km of running. In total, 149 triathletes had completed at least one marathon, and 150 athletes had finished at least one Olympic distance triathlon. They had a personal best time of 130.4 ± 44.2 minutes in an Olympic distance triathlon and of 193.9 ± 31.9 minutes in marathon running. In total, 126 finishers had completed both an Olympic distance triathlon and a marathon. After multivariate analysis, both a personal best time in a marathon (P < 0.0001 and in an Olympic distance triathlon (P < 0.0001 were the best variables related to Ironman race time. Ironman race time (minutes might be partially predicted by the following equation: (r2 = 0.65, standard error of estimate = 56.8 = 152.1 + 1.332 × (personal best time in a marathon, minutes + 1.964 × (personal best time in an Olympic distance triathlon, minutes.Conclusion: These results suggest

  4. Prediction of maximum magnitude and original time of reservoir induced seismicity

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    This paper deals with the prediction of potentially maximum magnitude and origin time for reservoir induced seismicity (RIS). The factor and sign of seismology and geology of RIS has been studied, and the information quantity for magnitude of induced seismicity provided by them has been calculated. In terms of information quan-tity the biggest possible magnitude of RIS is determined. The changes of seismic frequency with time are studied using grey model method, and the time of the biggest change rate is taken as original time of the main shock. The feasibility of methods for predicting magnitude and time has been tested for the reservoir induced seismicity in the Xinfengjiang reservoir, China and the Koyna reservoir, India.

  5. Determining the input dimension of a neural network for nonlinear time series prediction

    Institute of Scientific and Technical Information of China (English)

    张胜; 刘红星; 高敦堂; 都思丹

    2003-01-01

    Determining the input dimension of a feed-forward neural network for nonlinear time series prediction plays an important role in the modelling.The paper first summarizes the current methods for determining the input dimension of the neural network.Then inspired by the fact that the correlation dimension of a nonlinear dynamic system is the mostimportant feature of it,the paper presents a new idea that the input dimension of the neural network for nonlinear time series prediction can be taken as an integer just greater than or equal to the correlation dimension.Finally,some wlidation examples and results are given.

  6. Arthrospira (Spirulina) platensis supplementation affects folliculogenesis, progesterone and ghrelin levels in fattening pre-pubertal gilts

    NARCIS (Netherlands)

    Abadjieva, Desislava; Nedeva, Radka; Marchev, Yordan; Jordanova, Gergana; Chervenkov, Mihail; Dineva, Julieta; Shimkus, Almantas; Shimkiene, Aldona; Teerds, Katja; Kistanova, Elena

    2017-01-01

    The aim of the present investigation was to study the effect of Arthrospira (Spirulina) platensis supplemented diet on follicular development and related endocrine parameters, such as estradiol and progesterone levels as well as ghrelin levels in pre-pubertal gilts. Twenty-one 60-day-old Danube

  7. Sex Variations in Youth Anxiety Symptoms: Effects of Pubertal Development and Gender Role Orientation

    Science.gov (United States)

    Carter, Rona; Silverman, Wendy K.; Jaccard, James

    2011-01-01

    This study evaluated whether pubertal development and gender role orientation (i.e., masculinity and femininity) can partially explain sex variations in youth anxiety symptoms among clinic-referred anxious youth (N = 175; ages 9-13 years; 74% Hispanic; 48% female). Using youth and parent ratings of youth anxiety symptoms, structural equation…

  8. Pubertal Development, Choice of Friends, and Smoking Initiation among Adolescent Males

    Science.gov (United States)

    Drapela, Laurie A.; Gebelt, Janet L.; McRee, Nick

    2006-01-01

    Prior research has indicated that pubertal development and peer associations are important determinants of adolescent smoking behavior. However, more remains to be learned about "why" these variables matter or how they may be related to one another in ways that lead to the initiation of smoking. Using contractual data from the National…

  9. Sex Variations in Youth Anxiety Symptoms: Effects of Pubertal Development and Gender Role Orientation

    Science.gov (United States)

    Carter, Rona; Silverman, Wendy K.; Jaccard, James

    2011-01-01

    This study evaluated whether pubertal development and gender role orientation (i.e., masculinity and femininity) can partially explain sex variations in youth anxiety symptoms among clinic-referred anxious youth (N = 175; ages 9-13 years; 74% Hispanic; 48% female). Using youth and parent ratings of youth anxiety symptoms, structural equation…

  10. Effect of high and low antral follicle count in pubertal beef heifers on IVF

    Science.gov (United States)

    Pubertal heifers can be classified between those with high (n = 25) or low (n = 15) antral follicle counts (AFC). The objective of this study was to determine oocyte development and maturation (e.g. fertility) in an IVF system for high- and low-AFC heifers. From a pool of 120 heifers, 10 high- and 1...

  11. Insulin resistance in obese pre-pubertal children: Relation to body composition

    Directory of Open Access Journals (Sweden)

    Heba Elsedfy

    2014-07-01

    Conclusion: Dysglycaemia and dyslipidaemia are common among pre-pubertal obese children. Insulin sensitivity indices based on OGTT are superior to fasting indices in identifying at risk children. OGTT should be included in assessing obese children with BMI > 2 SDS. DXA scanning has limited value for this purpose in clinical settings.

  12. Serum inhibin B concentrations in pubertal boys conceived by ICSI: first results

    NARCIS (Netherlands)

    F. Belva; M. Bonduelle; R.C. Painter; J. Schiettecatte; P. Devroey; J. de Schepper

    2010-01-01

    Currently, no published data exist about the gonadal function of children born after ICSI. To evaluate potential risk of testicular seminal dysfunction in boys born to fathers with compromised spermatogenesis, serum inhibin B (as a marker for spermatogenesis) was assessed. We recruited 50 pubertal a

  13. Salivary testosterone concentrations in pubertal ICSI boys compared with spontaneously conceived boys

    NARCIS (Netherlands)

    F. Belva; M. Bonduelle; J. Schiettecatte; H. Tournaye; R.C. Painter; P. Devroey; J. de Schepper

    2011-01-01

    BACKGROUND: To date, no data exist about Leydig cell function of pubertal boys born after ICSI. To evaluate a potential risk of gonadal dysfunction in children born from fathers with compromised fertility, testicular function was assessed by the measurement of salivary testosterone. METHODS: Morning

  14. Identification of various testicular cell populations in pubertal and adult cockerels

    Science.gov (United States)

    Precise identification of the male germinal stem cell population is important for their practical use in programs dedicated to the integration of exogenous genetic material in testicular tissues. In the present study, our aim was to identify germinal cell populations in the testes of pubertal and ad...

  15. Elevated serum IGF-I, but unaltered sex steroid levels, in healthy boys with pubertal gynaecomastia

    DEFF Research Database (Denmark)

    Mieritz, Mikkel G; Sorensen, Kaspar; Aksglaede, Lise

    2014-01-01

    of 501 healthy Danish school boys (aged 6·1-19·8 year) from the COPENHAGEN Puberty Study. MEASUREMENTS: Anthropometry and pubertal stages (PH1-6 and G1-5) were evaluated, and the presence of gynaecomastia was assessed. Body fat percentage was calculated by means of four skin folds and impedance...

  16. Serum AMH levels are lower in healthy boys who develop pubertal gynaecomastia

    DEFF Research Database (Denmark)

    Mieritz, Mikkel G.; Hagen, Casper P.; Almstrup, Kristian

    2015-01-01

    Background: Pubertal gynaecomastia is thought to be a clinical sign of an oestrogen-androgen imbalance, affecting up to 60% of boys. In most cases no underlying endocrinopathy can be identified. In boys, Anti-mullerian hormone (AMH) is produced by immature Sertoli cells and circulating level decr...

  17. Dynamic Travel Time Prediction Models for Buses Using Only GPS Data

    Directory of Open Access Journals (Sweden)

    Wei Fan

    2015-01-01

    Full Text Available Providing real-time and accurate travel time information of transit vehicles can be very helpful as it assists passengers in planning their trips to minimize waiting times. The purpose of this research is to develop and compare dynamic travel time prediction models which can provide accurate prediction of bus travel time in order to give real-time information at a given downstream bus stop using only global positioning system (GPS data. Historical Average (HA, Kalman Filtering (KF and Artificial Neural Network (ANN models are considered and developed in this paper. A case has been studied by making use of the three models. Promising results are obtained from the case study, indicating that the models can be used to implement an Advanced Public Transport System. The implementation of this system could assist transit operators in improving the reliability of bus services, thus attracting more travelers to transit vehicles and helping relieve congestion. The performances of the three models were assessed and compared with each other under two criteria: overall prediction accuracy and robustness. It was shown that the ANN outperformed the other two models in both aspects. In conclusion, it is shown that bus travel time information can be reasonably provided using only arrival and departure time information at stops even in the absence of traffic-stream data.

  18. MO-G-18C-05: Real-Time Prediction in Free-Breathing Perfusion MRI

    Energy Technology Data Exchange (ETDEWEB)

    Song, H [Department of Radiology, University of Pittsburgh, Pittsburgh, PA (United States); Liu, W [Department of Bioengineering, UCLA, Los Angeles, CA (United States); Ruan, D [Department of Bioengineering, UCLA, Los Angeles, CA (United States); Department of Radiation Oncology, UCLA, Los Angeles, CA (United States); Jung, S [Department of Statistics, University of Pittsburgh, Pittsburgh, PA (United States); Gach, M [Department of Radiology, University of Pittsburgh, Pittsburgh, PA (United States); Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA (United States)

    2014-06-15

    Purpose: The aim is to minimize frame-wise difference errors caused by respiratory motion and eliminate the need for breath-holds in magnetic resonance imaging (MRI) sequences with long acquisitions and repeat times (TRs). The technique is being applied to perfusion MRI using arterial spin labeling (ASL). Methods: Respiratory motion prediction (RMP) using navigator echoes was implemented in ASL. A least-square method was used to extract the respiratory motion information from the 1D navigator. A generalized artificial neutral network (ANN) with three layers was developed to simultaneously predict 10 time points forward in time and correct for respiratory motion during MRI acquisition. During the training phase, the parameters of the ANN were optimized to minimize the aggregated prediction error based on acquired navigator data. During realtime prediction, the trained ANN was applied to the most recent estimated displacement trajectory to determine in real-time the amount of spatial Results: The respiratory motion information extracted from the least-square method can accurately represent the navigator profiles, with a normalized chi-square value of 0.037±0.015 across the training phase. During the 60-second training phase, the ANN successfully learned the respiratory motion pattern from the navigator training data. During real-time prediction, the ANN received displacement estimates and predicted the motion in the continuum of a 1.0 s prediction window. The ANN prediction was able to provide corrections for different respiratory states (i.e., inhalation/exhalation) during real-time scanning with a mean absolute error of < 1.8 mm. Conclusion: A new technique enabling free-breathing acquisition during MRI is being developed. A generalized ANN development has demonstrated its efficacy in predicting a continuum of motion profile for volumetric imaging based on navigator inputs. Future work will enhance the robustness of ANN and verify its effectiveness with human

  19. Effects of vitamin A on in vitro maturation of pre-pubertal mouse spermatogonial stem cells.

    Directory of Open Access Journals (Sweden)

    Albanne Travers

    Full Text Available Testicular tissue cryopreservation is the only potential option for fertility preservation in pre-pubertal boys exposed to gonadotoxic treatment. Completion of spermatogenesis after in vitro maturation is one of the future uses of harvested testicular tissue. The purpose of the current study was to evaluate the effects of vitamin A on in vitro maturation of fresh and frozen-thawed mouse pre-pubertal spermatogonial stem cells in an organ culture system. Pre-pubertal CD1 mouse fresh testes were cultured for 7 (D7, 9 (D9 and 11 (D11 days using an organ culture system. Basal medium was supplemented with different concentrations of retinol (Re or retinoic acid (RA alone or in combination. Seminiferous tubule morphology (tubule diameter, intra-tubular cell type, intra-tubular cell death and proliferation (PCNA antibody and testosterone level were assessed at D7, D9 and D11. Pre-pubertal mouse testicular tissue were frozen after a soaking temperature performed at -7 °C, -8 °C or -9 °C and after thawing, were cultured for 9 days, using the culture medium preserving the best fresh tissue functionality. Retinoic acid at 10(-6M and retinol at 3.3.10(-7M, as well as retinol 10(-6M are favourable for seminiferous tubule growth, maintenance of intra-tubular cell proliferation and germ cell differentiation of fresh pre-pubertal mouse spermatogonia. Structural and functional integrity of frozen-thawed testicular tissue appeared to be well-preserved after soaking temperature at -8 °C, after 9 days of organotypic culture using 10(-6M retinol. RA and Re can control in vitro germ cell proliferation and differentiation. Re at a concentration of 10(-6M maintains intra-tubular cell proliferation and the ability of spermatogonia to initiate spermatogenesis in fresh and frozen pre-pubertal mouse testicular tissue using a soaking temperature at -8 °C. Our data suggested a possible human application for in vitro maturation of cryopreserved pre-pubertal testicular

  20. Detecting determinism with improved sensitivity in time series: Rank-based nonlinear predictability score

    Science.gov (United States)

    Naro, Daniel; Rummel, Christian; Schindler, Kaspar; Andrzejak, Ralph G.

    2014-09-01

    The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

  1. Jump neural network for real-time prediction of glucose concentration.

    Science.gov (United States)

    Zecchin, Chiara; Facchinetti, Andrea; Sparacino, Giovanni; Cobelli, Claudio

    2015-01-01

    Prediction of the future value of a variable is of central importance in a wide variety of fields, including economy and finance, meteorology, informatics, and, last but not least important, medicine. For example, in the therapy of Type 1 Diabetes (T1D), in which, for patient safety, glucose concentration in the blood should be maintained in a defined normoglycemic range, the ability to forecast glucose concentration in the short-term (with a prediction horizon of around 30 min) might be sufficient to reduce the incidence of hypoglycemic and hyperglycemic events. Neural Network (NN) approaches are suitable for prediction purposes because of their ability to model nonlinear dynamics and handle in their inputs signals coming from different domains. In this chapter we illustrate the design of a jump NN glucose prediction algorithm that exploits past glucose concentration data, measured in real-time by a minimally invasive continuous glucose monitoring (CGM) sensor, and information on ingested carbohydrates, supplied by the patient himself or herself. The methodology is assessed by tuning the NN on data of ten T1D individuals and then testing it on a dataset of ten different subjects. Results with a prediction horizon of 30 min show that prediction of glucose concentration in T1D via NN is feasible and sufficiently accurate. The average time anticipation obtained is compatible with the generation of preventive hypoglycemic and hyperglycemic alerts and the improvement of artificial pancreas performance.

  2. Time-series prediction of shellfish farm closure: A comparison of alternatives

    Directory of Open Access Journals (Sweden)

    Ashfaqur Rahman

    2014-08-01

    Full Text Available Shellfish farms are closed for harvest when microbial pollutants are present. Such pollutants are typically present in rainfall runoff from various land uses in catchments. Experts currently use a number of observable parameters (river flow, rainfall, salinity as proxies to determine when to close farms. We have proposed using the short term historical rainfall data as a time-series prediction problem where we aim to predict the closure of shellfish farms based only on rainfall. Time-series event prediction consists of two steps: (i feature extraction, and (ii prediction. A number of data mining challenges exist for these scenarios: (i which feature extraction method best captures the rainfall pattern over successive days that leads to opening or closure of the farms?, (ii The farm closure events occur infrequently and this leads to a class imbalance problem; the question is what is the best way to deal with this problem? In this paper we have analysed and compared different combinations of balancing methods (under-sampling and over-sampling, feature extraction methods (cluster profile, curve fitting, Fourier Transform, Piecewise Aggregate Approximation, and Wavelet Transform and learning algorithms (neural network, support vector machine, k-nearest neighbour, decision tree, and Bayesian Network to predict closure events accurately considering the above data mining challenges. We have identified the best combination of techniques to accurately predict shellfish farm closure from rainfall, given the above data mining challenges.

  3. Short Term Prediction of PM10 Concentrations Using Seasonal Time Series Analysis

    Directory of Open Access Journals (Sweden)

    Hamid Hazrul Abdul

    2016-01-01

    Full Text Available Air pollution modelling is one of an important tool that usually used to make short term and long term prediction. Since air pollution gives a big impact especially to human health, prediction of air pollutants concentration is needed to help the local authorities to give an early warning to people who are in risk of acute and chronic health effects from air pollution. Finding the best time series model would allow prediction to be made accurately. This research was carried out to find the best time series model to predict the PM10 concentrations in Nilai, Negeri Sembilan, Malaysia. By considering two seasons which is wet season (north east monsoon and dry season (south west monsoon, seasonal autoregressive integrated moving average model were used to find the most suitable model to predict the PM10 concentrations in Nilai, Negeri Sembilan by using three error measures. Based on AIC statistics, results show that ARIMA (1, 1, 1 × (1, 0, 012 is the most suitable model to predict PM10 concentrations in Nilai, Negeri Sembilan.

  4. Artificial neural networks for the prediction of peptide drift time in ion mobility mass spectrometry

    Directory of Open Access Journals (Sweden)

    Plasencia Manolo

    2010-04-01

    Full Text Available Abstract Background There is an increasing usage of ion mobility-mass spectrometry (IMMS in proteomics. IMMS combines the features of ion mobility spectrometry (IMS and mass spectrometry (MS. It separates and detects peptide ions on a millisecond time-scale. IMS separates peptide ions based on drift time that is determined by the collision cross-section of each peptide ion in a given experiment condition. A peptide ion's collision cross-section is related to the ion size and shape resulted from the peptide amino acid sequence and their modifications. This inherent relation between the drift time of peptide ion and peptide sequence indicates that the drift time of peptide ions can be used to infer peptide sequence and therefore, for peptide identification. Results This paper describes an artificial neural networks (ANNs regression model for the prediction of peptide ion drift time in IMMS. Each peptide in this work was represented using three descriptors (i.e., molecular weight, sequence length and a two-dimensional sequence index. An ANN predictor consisting of four input nodes, three hidden nodes and one output node was constructed for peptide ion drift time prediction. For the model training and testing, a 10-fold cross-validation strategy was employed for three datasets each containing different charge states. Dataset one contains 212 singly-charged peptide ions, dataset two has 306 doubly-charged peptide ions, and dataset three has 77 triply-charged peptide ions. Our proposed method achieved 94.4%, 93.6% and 74.2% prediction accuracy for singly-, doubly- and triply-charged peptide ions, respectively. Conclusions An ANN-based method has been developed for predicting the drift time of peptide ions in IMMS. The results achieved here demonstrate the effectiveness and efficiency of the prediction model. This work can enhance the confidence of protein identification by combining with current database search approaches for protein identification.

  5. Associations between socio-demographic characteristics and pubertal status with disordered eating among primary school children in Selangor, Malaysia.

    Science.gov (United States)

    Chong, Lin Siew; Chin, Yit Siew; Gan, Wan Ying; Nasir, Mohd Taib Mohd

    2017-03-01

    To determine the associations between socio-demographic characteristics and pubertal status with disordered eating among primary school children. Using a stratified multi-stage sampling, a total of 816 children (282 boys and 534 girls) aged 10 to 11 years from 12 selected primary schools in the state of Selangor, participated in this study. Data were collected on socio-demographic characteristics, pubertal status and disordered eating behaviors. The Pubertal Development Scale and the Children's Eating Attitudes Test (ChEAT) were used to assess pubertal status and disordered eating, respectively. Logistic regression analysis was conducted to determine the risk factors of disordered eating. The prevalence of disordered eating was 30.8% (32.8% in boys and 29.7% in girls). However, the sex difference in the prevalence was not statistically significant. Age, ethnicity and pubertal status were significantly associated with disordered eating in univariate logistic regression analysis. Multivariate logistic regression analysis showed that among boys, being either in an advanced or post-pubertal stage (adjusted OR=8.64) and older age group (adjusted OR=2.03) were risk factors of disordered eating. However, among girls, being a Malay (adjusted OR=3.79) or Indian (adjusted OR=5.04) in an advanced or post-pubertal stage (adjusted OR=2.34) and older age group (adjusted OR=1.53) were risk factors of disordered eating. This study found one in three children had disordered eating. Since ethnicity and pubertal status were identified as risk factors, ethnicity-specific intervention programs on the prevention of disordered eating among children should take into consideration their pubertal status.

  6. Strategic influence on the time course of predictive inferences in reading.

    Science.gov (United States)

    Calvo, Manuel G; Castillo, M Dolores; Schmalhofer, Franz

    2006-01-01

    In the present study, we investigated how reading strategies affect the time course of online predictive inferences. Participants read sentences under instructions either to anticipate the outcomes of described events or to understand the sentences. These were followed by a target word to be named, with stimulus onset asynchronies (SOAs) of 500 or 1,000 msec (50- or 550-msec interstimulus interval, respectively). Sentences either were predictive of events or were lexically matched control sentences. There was facilitation in naming latencies for predictable target words in the strategic-anticipation condition at both SOAs, but not in the read-to-understand condition, with a significant improvement in the former condition in comparison with the latter. This suggests that predictive inferences, which are typically considered to be resource demanding, can be speeded up by specific goals in reading. Moreover, this can occur at no cost to comprehension of explicit information, as was revealed by a comprehension test.

  7. A First-order Prediction-Correction Algorithm for Time-varying (Constrained) Optimization: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-07-25

    This paper focuses on the design of online algorithms based on prediction-correction steps to track the optimal solution of a time-varying constrained problem. Existing prediction-correction methods have been shown to work well for unconstrained convex problems and for settings where obtaining the inverse of the Hessian of the cost function can be computationally affordable. The prediction-correction algorithm proposed in this paper addresses the limitations of existing methods by tackling constrained problems and by designing a first-order prediction step that relies on the Hessian of the cost function (and do not require the computation of its inverse). Analytical results are established to quantify the tracking error. Numerical simulations corroborate the analytical results and showcase performance and benefits of the algorithms.

  8. Time-dependent prediction degredation assessment of neural-networks-based TEC forecasting models

    Directory of Open Access Journals (Sweden)

    Th. D. Xenos

    2003-01-01

    Full Text Available An estimation of the difference in TEC prediction accuracy achieved when the prediction varies from 1 h to 7 days in advance is described using classical neural networks. Hourly-daily Faraday-rotation derived TEC measurements from Florence are used. It is shown that the prediction accuracy for the examined dataset, though degrading when time span increases, is always high. In fact, when a relative prediction error margin of ± 10% is considered, the population percentage included therein is almost always well above the 55%. It is found that the results are highly dependent on season and the dataset wealth, whereas they highly depend on the foF2 - TEC variability difference and on hysteresis-like effect between these two ionospheric characteristics.

  9. A multi-time scale approach to remaining useful life prediction in rolling bearing

    Science.gov (United States)

    Qian, Yuning; Yan, Ruqiang; Gao, Robert X.

    2017-01-01

    This paper presents a novel multi-time scale approach to bearing defect tracking and remaining useful life (RUL) prediction, which integrates enhanced phase space warping (PSW) with a modified Paris crack growth model. As a data-driven method, PSW describes the dynamical behavior of the bearing being tested on a fast-time scale, whereas the Paris crack growth model, as a physics-based model, characterizes the bearing's defect propagation on a slow-time scale. Theoretically, PSW constructs a tracking metric by evaluating the phase space trajectory warping of the bearing vibration data, and establishes a correlation between measurement on a fast-time scale and defect growth variables on a slow-time scale. Furthermore, PSW is enhanced by a multi-dimensional auto-regression (AR) model for improved accuracy in defect tracking. Also, the Paris crack growth model is modified by a time-piecewise algorithm for real-time RUL prediction. Case studies performed on two run-to-failure experiments indicate that the developed technique is effective in tracking the evolution of bearing defects and accurately predict the bearing RUL, thus contributing to the literature of bearing prognosis .

  10. Effect of pubertal development and physical activity on plasma ghrelin concentration in boys.

    Science.gov (United States)

    Jürimäe, J; Cicchella, A; Tillmann, V; Lätt, E; Haljaste, K; Purge, P; Pomerants, T; Jürimäe, T

    2009-01-01

    The aim of the present study was to assess the influence of regular physical activity on plasma ghrelin concentration in pre-pubertal and pubertal boys. In addition, the impact of ghrelin concentration on bone mineral density (BMD) was examined. In total, 56 healthy schoolboys aged between 10 and 16 yr were divided into the swimming (no.=28) and the control (no.=28) groups. The subjects were matched by age and body mass index (BMI), generating 9 matched pairs in pubertal group I (Tanner stage 1), 11 pairs in group II (Tanner stages 2 and 3), and 8 pairs in group III (Tanner stages 4 and 5). Swimmers in pubertal groups II and III had significantly (both pghrelin levels than the controls (group II: 1126.8+/-406.0 vs 868.3+/-411.2 pg/ml; group III: 1105.5+/-337.5 vs 850.8+/-306.0 pg/ml, respectively), whereas no difference was seen in the pubertal group I (1230.8+/-386.0 vs 1272.7+/-424.4 pg/ml). Ghrelin was the most important hormonal determinant for total BMD and lumbar apparent volumetric BMD (BMAD) (R2=27.2% and R2=19.8%, respectively) in swimmers, whereas in control boys, plasma IGF-I was the most important hormonal predictor accounting for 41.8% of the variability of total BMD and 20.4% of the variability of lumbar BMAD. In conclusion, ghrelin concentration decreased during puberty in physically inactive boys, while in regularly physically active boys it remained relatively unchanged. Ghrelin appears to be an important hormonal predictor for BMD in physically active boys, while BMD is mostly determined by IGF-I in physically inactive boys.

  11. Parathyroid hormone levels in pubertal uremic adolescents treated with growth hormone.

    Science.gov (United States)

    Picca, Stefano; Cappa, Marco; Martinez, Chiara; Moges, Seyoum Ido; Osborn, John; Perfumo, Francesco; Ardissino, Gianluigi; Bonaudo, Roberto; Montini, Giovanni; Rizzoni, Gianfranco

    2004-01-01

    We have previously described severe hyperparathyroidism during the pubertal growth spurt in three uremic adolescents treated with recombinant human growth hormone (rhGH). Here we investigate the possible role of puberty in the genesis of hyperparathyroidism during rhGH treatment of a large cohort of patients. Data from 67 uremic patients treated with rhGH from five Italian pediatric nephrology centers were retrospectively recorded every 3 months starting 1 year before rhGH administration. The mean (+/-SD) rhGH treatment observation period was 19.9+/-5.9 months. The mean age at the start of rhGH treatment was 8.3+/-3.6 years. Of the 67 patients, 15 reached pubertal stage 2 during the 1st year of rhGH treatment and 12 of these 15 progressed to pubertal stage 3. The relative increase in parathyroid hormone (PTH) levels after rhGH initiation was greater in pubertal [1.95, 95% confidence interval (CI) 1.43-2.66] than in prepubertal patients (1.19, 95% CI 1.01-1.40). Increases in PTH levels were significantly different between the two groups (Delta=1.64, 95% CI 1.16-3.19, P=0.007). Multiple regression analysis showed an inverse correlation between PTH and calcium levels and a positive correlation between PTH and pubertal stage 3. There was no correlation with phosphate levels and calcitriol dosage. In conclusion, these results suggest that in uremic adolescents treated with rhGH puberty may influence PTH levels.

  12. Time Perspectives Predict Mood States and Satisfaction with Life over and above Personality.

    Science.gov (United States)

    Stolarski, Maciej; Matthews, Gerald

    2016-01-01

    The present study aimed to test the incremental validity of Time Perspective (TP) scales in predicting satisfaction with life and mood, over and above the Big Five personality traits. It also investigated whether the new TP construct of Future Negative perspective contributed to prediction of these outcomes. Participants (N = 265) completed four measures: Satisfaction With Life Scale (SWLS), UWIST Mood Adjective Checklist (UMACL), a modified Zimbardo Time Perspective Inventory (ZTPI), and NEO-Five Factor Inventory (NEO-FFI). Results confirmed the incremental validity of TP, although Big Five dimensions were independently predictive of life satisfaction and certain mood scales. Past Negative TP was the strongest single predictor of life satisfaction. However, Future Negative TP was be the strongest mood predictor from the TP universe, after controlling for the Big Five and remaining TP dimensions. Findings suggest that TP is an important aspect of personality for understanding individual differences in well-being.

  13. Least squares support vector machine for short-term prediction of meteorological time series

    Science.gov (United States)

    Mellit, A.; Pavan, A. Massi; Benghanem, M.

    2013-01-01

    The prediction of meteorological time series plays very important role in several fields. In this paper, an application of least squares support vector machine (LS-SVM) for short-term prediction of meteorological time series (e.g. solar irradiation, air temperature, relative humidity, wind speed, wind direction and pressure) is presented. In order to check the generalization capability of the LS-SVM approach, a K-fold cross-validation and Kolmogorov-Smirnov test have been carried out. A comparison between LS-SVM and different artificial neural network (ANN) architectures (recurrent neural network, multi-layered perceptron, radial basis function and probabilistic neural network) is presented and discussed. The comparison showed that the LS-SVM produced significantly better results than ANN architectures. It also indicates that LS-SVM provides promising results for short-term prediction of meteorological data.

  14. A simple model for predicting sprint-race times accounting for energy loss on the curve

    Science.gov (United States)

    Mureika, J. R.

    1997-11-01

    The mathematical model of J. Keller for predicting World Record race times, based on a simple differential equation of motion, predicted quite well the records of the day. One of its shortcoming is that it neglects to account for a sprinter's energy loss around a curve, a most important consideration particularly in the 200m--400m. An extension to Keller's work is considered, modeling the aforementioned energy loss as a simple function of the centrifugal force acting on the runner around the curve. Theoretical World Record performances for indoor and outdoor 200m are discussed, and the use of the model at 300m is investigated. Some predictions are made for possible 200m outdoor and indoor times as run by Canadian 100m WR holder Donovan Bailey, based on his 100m final performance at the 1996 Olympic Games in Atlanta.

  15. A Simple Model for Predicting Sprint Race Times Accounting for Energy Loss on the Curve

    CERN Document Server

    Mureika, J R

    1997-01-01

    The mathematical model of J. Keller for predicting World Record race times, based on a simple differential equation of motion, predicted quite well the records of the day. One of its shortcoming is that it neglects to account for a sprinter's energy loss around a curve, a most important consideration particularly in the 200m--400m. An extension to Keller's work is considered, modeling the aforementioned energy loss as a simple function of the centrifugal force acting on the runner around the curve. Theoretical World Record performances for indoor and outdoor 200m are discussed, and the use of the model at 300m is investigated. Some predictions are made for possible 200m outdoor and indoor times as run by Canadian 100m WR holder Donovan Bailey, based on his 100m final performance at the 1996 Olympic Games in Atlanta.

  16. Ecological prediction with nonlinear multivariate time-frequency functional data models

    Science.gov (United States)

    Yang, Wen-Hsi; Wikle, Christopher K.; Holan, Scott H.; Wildhaber, Mark L.

    2013-01-01

    Time-frequency analysis has become a fundamental component of many scientific inquiries. Due to improvements in technology, the amount of high-frequency signals that are collected for ecological and other scientific processes is increasing at a dramatic rate. In order to facilitate the use of these data in ecological prediction, we introduce a class of nonlinear multivariate time-frequency functional models that can identify important features of each signal as well as the interaction of signals corresponding to the response variable of interest. Our methodology is of independent interest and utilizes stochastic search variable selection to improve model selection and performs model averaging to enhance prediction. We illustrate the effectiveness of our approach through simulation and by application to predicting spawning success of shovelnose sturgeon in the Lower Missouri River.

  17. Measuring Complexity and Predictability of Time Series with Flexible Multiscale Entropy for Sensor Networks.

    Science.gov (United States)

    Zhou, Renjie; Yang, Chen; Wan, Jian; Zhang, Wei; Guan, Bo; Xiong, Naixue

    2017-04-06

    Measurement of time series complexity and predictability is sometimes the cornerstone for proposing solutions to topology and congestion control problems in sensor networks. As a method of measuring time series complexity and predictability, multiscale entropy (MSE) has been widely applied in many fields. However, sample entropy, which is the fundamental component of MSE, measures the similarity of two subsequences of a time series with either zero or one, but without in-between values, which causes sudden changes of entropy values even if the time series embraces small changes. This problem becomes especially severe when the length of time series is getting short. For solving such the problem, we propose flexible multiscale entropy (FMSE), which introduces a novel similarity function measuring the similarity of two subsequences with full-range values from zero to one, and thus increases the reliability and stability of measuring time series complexity. The proposed method is evaluated on both synthetic and real time series, including white noise, 1/f noise and real vibration signals. The evaluation results demonstrate that FMSE has a significant improvement in reliability and stability of measuring complexity of time series, especially when the length of time series is short, compared to MSE and composite multiscale entropy (CMSE). The proposed method FMSE is capable of improving the performance of time series analysis based topology and traffic congestion control techniques.

  18. Coefficient of retardation time found out by polynomial fitting to predict creep behaviour of polystyrene

    Institute of Scientific and Technical Information of China (English)

    XIE Gang

    2005-01-01

    The universal creep function is successful in relating the creep (ε) to the ageing time (ta ), coefficient of retardation time (β), and intrinsic time (t0). The relation was used to treat the creep experimental data for polystyrene (PS) specimens at a given aged time and different stress levels. Comparing with "middle-point"method reported in the literatures,β is found out by another method "polynomial fitting" in this work. Then unified master lines were constructed with the treated data and curves according to the universal equation. The master lines can be used to predict the long-term creep behaviour and lifetime by extrapolating to a required ultimate strain.

  19. Similarity-Based Prediction of Travel Times for Vehicles Traveling on Known Routes

    DEFF Research Database (Denmark)

    Tiesyte, Dalia; Jensen, Christian Søndergaard

    2008-01-01

    , historical data in combination with real-time data may be used to predict the future travel times of vehicles more accurately, thus improving the experience of the users who rely on such information. We propose a Nearest-Neighbor Trajectory (NNT) technique that identifies the historical trajectory......The use of centralized, real-time position tracking is proliferating in the areas of logistics and public transportation. Real-time positions can be used to provide up-to-date information to a variety of users, and they can also be accumulated for uses in subsequent data analyses. In particular...... of vehicles that travel along known routes. In empirical studies with real data from buses, we evaluate how well the proposed distance functions are capable of predicting future vehicle movements. Second, we propose a main-memory index structure that enables incremental similarity search and that is capable...

  20. Comparison of Taxi Time Prediction Performance Using Different Taxi Speed Decision Trees

    Science.gov (United States)

    Lee, Hanbong

    2017-01-01

    In the STBO modeler and tactical surface scheduler for ATD-2 project, taxi speed decision trees are used to calculate the unimpeded taxi times of flights taxiing on the airport surface. The initial taxi speed values in these decision trees did not show good prediction accuracy of taxi times. Using the more recent, reliable surveillance data, new taxi speed values in ramp area and movement area were computed. Before integrating these values into the STBO system, we performed test runs using live data from Charlotte airport, with different taxi speed settings: 1) initial taxi speed values and 2) new ones. Taxi time prediction performance was evaluated by comparing various metrics. The results show that the new taxi speed decision trees can calculate the unimpeded taxi-out times more accurately.

  1. LES prediction of space-time correlations in turbulent shear flows

    Institute of Scientific and Technical Information of China (English)

    Li Guo; Dong Li; Xing Zhang; Guo-Wei He

    2012-01-01

    We compare the space-time correlations calculated from direct numerical simulation (DNS) and large-eddy simulation (LES) of turbulent channel flows.It is found from the comparisons that the LES with an eddy-viscosity subgrid scale (SGS) model over-predicts the space-time correlations than the DNS.The overpredictions are further quantified by the integral scales of directional correlations and convection velocities.A physical argument for the overprediction is provided that the eddy-viscosity SGS model alone does not includes the backscatter effects although it correctly represents the energy dissipations of SGS motions.This argument is confirmed by the recently developed elliptic model for space-time correlations in turbulent shear flows.It suggests that enstrophy is crucial to the LES prediction of spacetime correlations.The random forcing models and stochastic SGS models are proposed to overcome the overpredictions on space-time correlations.

  2. A comparison of actual versus predicted emergency ambulance journey times using generic Geographic Information System software.

    Science.gov (United States)

    McMeekin, Peter; Gray, Jo; Ford, Gary A; Duckett, Jay; Price, Christopher I

    2014-09-01

    The planning of regional emergency medical services is aided by accurate prediction of urgent ambulance journey times, but it is unclear whether it is appropriate to use Geographical Information System (GIS) products designed for general traffic. We examined the accuracy of a commercially available generic GIS package when predicting emergency ambulance journey times under different population and temporal conditions. We undertook a retrospective cohort study of emergency ambulance admissions to three emergency departments (ED) serving differing population distributions in northeast England (urban/suburban/rural). The transport time from scene to ED for all the highest priority dispatches between 1 October 2009 and 30 September 2010 was compared with predictions made by generic GIS software. For 10,156 emergency ambulance journeys, the mean prediction discrepancy between actual and predicted journey times across all EDs was an underprediction of 1.6 min (SD 4.9). Underprediction was statistically significant at all population densities, but unlikely to be of clinical significance. Ambulances in urban areas were able to exceed general traffic speed, whereas, the opposite effect was seen in suburban and rural road networks. There were minor effects due to travel outside the busiest traffic times (mean overprediction 0.8 min) and during winter months (mean underprediction 0.4 min). It is reasonable to estimate emergency ambulance journey times using generic GIS software, but in order to avoid insufficient regional ambulance provision it would be necessary to make small adjustments because of the tendency towards systematic underprediction. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  3. Review of methods for predicting in situ volume change movement of expansive soil over time

    OpenAIRE

    Hana H. Adem; Sai K. Vanapalli

    2015-01-01

    The soil movement information over time is required for the design of foundations placed in expansive soils. This information is also helpful for the assessment of pre-wetting and controlled wetting mitigation alternatives for expansive soils. Several researchers during the past fifteen years have proposed different methods for the prediction of the soil movements over time. The available methods can be categorized into (i) consolidation theory-based methods, (ii) water content-based methods,...

  4. An Analytical Prediction Model of Time Diversity Performance for Earth-Space Fade Mitigation

    Directory of Open Access Journals (Sweden)

    Pantelis-Daniel M. Arapoglou

    2008-01-01

    Full Text Available Time diversity (TD has recently attracted attention as a promising and cost-efficient solution for high-frequency broadcast satellite applications. The present work proposes a general prediction model for the application of TD by approximating the time dynamics of rain attenuation through the use of the joint lognormal distribution. The proposed method is tested against experimental data and its performance is investigated with respect to the basic parameters of a satellite link.

  5. Semiparametric models of time-dependent predictive values of prognostic biomarkers.

    Science.gov (United States)

    Zheng, Yingye; Cai, Tianxi; Stanford, Janet L; Feng, Ziding

    2010-03-01

    Rigorous statistical evaluation of the predictive values of novel biomarkers is critical prior to applying novel biomarkers into routine standard care. It is important to identify factors that influence the performance of a biomarker in order to determine the optimal conditions for test performance. We propose a covariate-specific time-dependent positive predictive values curve to quantify the predictive accuracy of a prognostic marker measured on a continuous scale and with censored failure time outcome. The covariate effect is accommodated with a semiparametric regression model framework. In particular, we adopt a smoothed survival time regression technique (Dabrowska, 1997, The Annals of Statistics 25, 1510-1540) to account for the situation where risk for the disease occurrence and progression is likely to change over time. In addition, we provide asymptotic distribution theory and resampling-based procedures for making statistical inference on the covariate-specific positive predictive values. We illustrate our approach with numerical studies and a dataset from a prostate cancer study.

  6. Neural network incorporating meal information improves accuracy of short-time prediction of glucose concentration.

    Science.gov (United States)

    Zecchin, Chiara; Facchinetti, Andrea; Sparacino, Giovanni; De Nicolao, Giuseppe; Cobelli, Claudio

    2012-06-01

    Diabetes mellitus is one of the most common chronic diseases, and a clinically important task in its management is the prevention of hypo/hyperglycemic events. This can be achieved by exploiting continuous glucose monitoring (CGM) devices and suitable short-term prediction algorithms able to infer future glycemia in real time. In the literature, several methods for short-time glucose prediction have been proposed, most of which do not exploit information on meals, and use past CGM readings only. In this paper, we propose an algorithm for short-time glucose prediction using past CGM sensor readings and information on carbohydrate intake. The predictor combines a neural network (NN) model and a first-order polynomial extrapolation algorithm, used in parallel to describe, respectively, the nonlinear and the linear components of glucose dynamics. Information on the glucose rate of appearance after a meal is described by a previously published physiological model. The method is assessed on 20 simulated datasets and on 9 real Abbott FreeStyle Navigator datasets, and its performance is successfully compared with that of a recently proposed NN glucose predictor. Results suggest that exploiting meal information improves the accuracy of short-time glucose prediction.

  7. Delay Prediction for Real-Time Video Adaptive Transmisson over TCP

    Directory of Open Access Journals (Sweden)

    Yonghua Xiong

    2010-06-01

    Full Text Available Real-time multimedia streaming applications are increasingly using TCP instead of UCP as underlying transport protocol, however the great end-to-end delays are the major factor to influence the quality of streaming across the Internet using TCP. In this paper, we point the requirement for transmitting real-time video with acceptable playing performance via TCP and present a stochastic prediction model which can predict the sending-delays of video frames.  Based on the prediction model, we propose a real-time video adaptive transmission scheme which can dynamically adjust video frame rate and playout buffer size according to available network bandwidth. The scheme does not require any modifications to the network infrastructure or TCP protocol stack and only wants to measure some parameters including video frame size, loss ratio, congestion windows size, RTT and RTO time before video frames are sent. The performance of proposed prediction model and adaptive scheme are evaluated through extensive simulations using the NS-2 simulator.

  8. Predicting High Risk Adolescents' Substance Use over Time: The Role of Parental Monitoring

    Science.gov (United States)

    Clark, Heddy Kovach; Shamblen, Stephen R.; Ringwalt, Chris L.; Hanley, Sean

    2012-01-01

    We examined whether parental monitoring at baseline predicted subsequent substance use in a high-risk youth population. Students in 14 alternative high schools in Washington State completed self-report surveys at three time points over the course of 2 years. Primary analyses included 1,423 students aged 14-20 who lived with at least one parent or…

  9. Incorporating Retention Time to Refine Models Predicting Thermal Regimes of Stream Networks Across New England

    Science.gov (United States)

    Thermal regimes are a critical factor in models predicting effects of watershed management activities on fish habitat suitability. We have assembled a database of lotic temperature time series across New England (> 7000 station-year combinations) from state and Federal data s...

  10. Predicting High Risk Adolescents' Substance Use over Time: The Role of Parental Monitoring

    Science.gov (United States)

    Clark, Heddy Kovach; Shamblen, Stephen R.; Ringwalt, Chris L.; Hanley, Sean

    2012-01-01

    We examined whether parental monitoring at baseline predicted subsequent substance use in a high-risk youth population. Students in 14 alternative high schools in Washington State completed self-report surveys at three time points over the course of 2 years. Primary analyses included 1,423 students aged 14-20 who lived with at least one parent or…

  11. Advanced Time Approach of FW-H Equations for Predicting Noise

    DEFF Research Database (Denmark)

    Haiqing, Si; Yan, Shi; Shen, Wen Zhong

    2013-01-01

    approach, on the other hand, computational cost can be saved using the approach due to no demand of pre-storing lots of aerodynamic data. To further validate the efficiency of the advanced time approach for predicting noise, unsteady flow fields are firstly simulated for air around square cylinder and NACA...

  12. What Time Is Sunrise? Revisiting the Refraction Component of Sunrise/set Prediction Models

    Science.gov (United States)

    Wilson, Teresa; Bartlett, Jennifer L.; Hilton, James Lindsay

    2017-01-01

    Algorithms that predict sunrise and sunset times currently have an error of one to four minutes at mid-latitudes (0° - 55° N/S) due to limitations in the atmospheric models they incorporate. At higher latitudes, slight changes in refraction can cause significant discrepancies, even including difficulties determining when the Sun appears to rise or set. While different components of refraction are known, how they affect predictions of sunrise/set has not yet been quantified. A better understanding of the contributions from temperature profile, pressure, humidity, and aerosols could significantly improve the standard prediction. We present a sunrise/set calculator that interchanges the refraction component by varying the refraction model. We then compare these predictions with data sets of observed rise/set times to create a better model. Sunrise/set times and meteorological data from multiple locations will be necessary for a thorough investigation of the problem. While there are a few data sets available, we will also begin collecting this data using smartphones as part of a citizen science project. The mobile application for this project will be available in the Google Play store. Data analysis will lead to more complete models that will provide more accurate rise/set times for the benefit of astronomers, navigators, and outdoorsmen everywhere.

  13. Prediction problem for target events based on the inter-event waiting time

    Science.gov (United States)

    Shapoval, A.

    2010-11-01

    In this paper we address the problem of forecasting the target events of a time series given the distribution ξ of time gaps between target events. Strong earthquakes and stock market crashes are the two types of such events that we are focusing on. In the series of earthquakes, as McCann et al. show [W.R. Mc Cann, S.P. Nishenko, L.R. Sykes, J. Krause, Seismic gaps and plate tectonics: seismic potential for major boundaries, Pure and Applied Geophysics 117 (1979) 1082-1147], there are well-defined gaps (called seismic gaps) between strong earthquakes. On the other hand, usually there are no regular gaps in the series of stock market crashes [M. Raberto, E. Scalas, F. Mainardi, Waiting-times and returns in high-frequency financial data: an empirical study, Physica A 314 (2002) 749-755]. For the case of seismic gaps, we analytically derive an upper bound of prediction efficiency given the coefficient of variation of the distribution ξ. For the case of stock market crashes, we develop an algorithm that predicts the next crash within a certain time interval after the previous one. We show that this algorithm outperforms random prediction. The efficiency of our algorithm sets up a lower bound of efficiency for effective prediction of stock market crashes.

  14. Time-of-day-dependent adaptation of the HPA axis to predictable social defeat stress.

    Science.gov (United States)

    Koch, C E; Bartlang, M S; Kiehn, J T; Lucke, L; Naujokat, N; Helfrich-Förster, C; Reber, S O; Oster, H

    2016-12-01

    In modern societies, the risk of developing a whole array of affective and somatic disorders is associated with the prevalence of frequent psychosocial stress. Therefore, a better understanding of adaptive stress responses and their underlying molecular mechanisms is of high clinical interest. In response to an acute stressor, each organism can either show passive freezing or active fight-or-flight behaviour, with activation of sympathetic nervous system and the hypothalamus-pituitary-adrenal (HPA) axis providing the necessary energy for the latter by releasing catecholamines and glucocorticoids (GC). Recent data suggest that stress responses are also regulated by the endogenous circadian clock. In consequence, the timing of stress may critically affect adaptive responses to and/or pathological effects of repetitive stressor exposure. In this article, we characterize the impact of predictable social defeat stress during daytime versus nighttime on bodyweight development and HPA axis activity in mice. While 19 days of social daytime stress led to a transient reduction in bodyweight without altering HPA axis activity at the predicted time of stressor exposure, more detrimental effects were seen in anticipation of nighttime stress. Repeated nighttime stressor exposure led to alterations in food metabolization and reduced HPA axis activity with lower circulating adrenocorticotropic hormone (ACTH) and GC concentrations at the time of predicted stressor exposure. Our data reveal a circadian gating of stress adaptation to predictable social defeat stress at the level of the HPA axis with impact on metabolic homeostasis underpinning the importance of timing for the body's adaptability to repetitive stress.

  15. Comparative analysis of Recurrent and Finite Impulse Response Neural Networks in Time Series Prediction

    Directory of Open Access Journals (Sweden)

    Milos Miljanovic

    2012-02-01

    Full Text Available The purpose of this paper is to perform evaluation of two different neural network architectures used for solving temporal problems, i.e. time series prediction. The data sets in this project include Mackey-Glass,Sunspots, and Standard & Poor's 500, the stock market index. The study also presents a comparison study on the two networks and their performance.

  16. Multi-Scale Gaussian Processes: a Novel Model for Chaotic Time Series Prediction

    Institute of Scientific and Technical Information of China (English)

    ZHOU Ya-Tong; ZHANG Tai-Yi; SUN Jian-Cheng

    2007-01-01

    @@ Based on the classical Gaussian process (GP) model, we propose a multi-scale Gaussian process (MGP) model to predict the existence of chaotic time series. The MGP employs a covariance function that is constructed by a scaling function with its different dilations and translations, ensuring that the optimal hyperparameter is easy to determine.

  17. Compensation for the distortion in satellite laser range predictions due to varying pulse travel times

    Science.gov (United States)

    Paunonen, Matti

    1993-01-01

    A method for compensating for the effect of the varying travel time of a transmitted laser pulse to a satellite is described. The 'observed minus predicted' range differences then appear to be linear, which makes data screening or use in range gating more effective.

  18. Factors that Predict Full-Time Community College Faculty Engagement in Online Instruction

    Science.gov (United States)

    Akroyd, Duane; Patton, Bess; Bracken, Susan

    2013-01-01

    This study is a secondary quantitative analysis of the 2004 National Study of Postsecondary Faculty (NSOPF) data. It examines the ability of human capital, intrinsic rewards, extrinsic rewards, and gender/race demographics to predict full-time community college faculty teaching on-line courses. Findings indicate that those faculty with higher…

  19. Factors that Predict Full-Time Community College Faculty Engagement in Online Instruction

    Science.gov (United States)

    Akroyd, Duane; Patton, Bess; Bracken, Susan

    2013-01-01

    This study is a secondary quantitative analysis of the 2004 National Study of Postsecondary Faculty (NSOPF) data. It examines the ability of human capital, intrinsic rewards, extrinsic rewards, and gender/race demographics to predict full-time community college faculty teaching on-line courses. Findings indicate that those faculty with higher…

  20. Deleterious effects of obesity on physical fitness in pre-pubertal children.

    Science.gov (United States)

    Ceschia, Arianna; Giacomini, Stefano; Santarossa, Simone; Rugo, Miriam; Salvadego, Desy; Da Ponte, Alessandro; Driussi, Caterina; Mihaleje, Martina; Poser, Stefano; Lazzer, Stefano

    2016-01-01

    The prevalence of obesity in children has increased dramatically during the past decades in Europe and understanding physical fitness and its components in children is critical to design and implement effective interventions. The objective of the present study was to analyse the association between physical fitness (aerobic, speed, agility, power, flexibility and balance) and body mass index (BMI) in pre-pubertal children. A total of 2411 healthy schoolchildren (7-11 years) participated in this study. Anthropometric characteristics and body composition were assessed by skinfold thickness. Physical fitness was measured by nine physical fitness tests: endurance running, 20 m running speed, agility, handgrip strength, standing long jump and squat jump, sit and reach, medicine ball forward throw and static balance. No relevant differences were observed between boys and girls regarding anthropometric characteristics, body composition and physical fitness. However, overweight and obese children showed significantly lower physical fitness levels in endurance running, speed and agility (mean: +18.8, +5.5 and +14.5% of time to complete tasks, respectively), lower limb power normalised to body mass (-23.3%) and balance tests (number of falls: +165.5%) than their normal weight counterparts. On the other hand, obesity did not affect handgrip, throwing and flexibility. In conclusion, increased BMI was associated with lower performance capabilities limiting proper motor skill development, which directly affects the ability of children to take on sports skills. Actions undertaken to promote children's wellness and fitness should be prioritised and introduced early in life with the aim of enhancing physical fitness as well as preventing overweight and obesity.

  1. Period, epoch and prediction errors of ephemeris from continuous sets of timing measurements

    CERN Document Server

    Deeg, Hans J

    2015-01-01

    Space missions such as Kepler and CoRoT have led to large numbers of eclipse or transit measurements in nearly continuous time series. This paper shows how to obtain the period error in such measurements from a basic linear least-squares fit, and how to correctly derive the timing error in the prediction of future transit or eclipse events. Assuming strict periodicity, a formula for the period error of such time series is derived: sigma_P = sigma_T (12/( N^3-N))^0.5, where sigma_P is the period error; sigma_T the timing error of a single measurement and N the number of measurements. Relative to the iterative method for period error estimation by Mighell & Plavchan (2013), this much simpler formula leads to smaller period errors, whose correctness has been verified through simulations. For the prediction of times of future periodic events, the usual linear ephemeris where epoch errors are quoted for the first time measurement, are prone to overestimation of the error of that prediction. This may be avoided...

  2. Support vector echo-state machine for chaotic time-series prediction.

    Science.gov (United States)

    Shi, Zhiwei; Han, Min

    2007-03-01

    A novel chaotic time-series prediction method based on support vector machines (SVMs) and echo-state mechanisms is proposed. The basic idea is replacing "kernel trick" with "reservoir trick" in dealing with nonlinearity, that is, performing linear support vector regression (SVR) in the high-dimension "reservoir" state space, and the solution benefits from the advantages from structural risk minimization principle, and we call it support vector echo-state machines (SVESMs). SVESMs belong to a special kind of recurrent neural networks (RNNs) with convex objective function, and their solution is global, optimal, and unique. SVESMs are especially efficient in dealing with real life nonlinear time series, and its generalization ability and robustness are obtained by regularization operator and robust loss function. The method is tested on the benchmark prediction problem of Mackey-Glass time series and applied to some real life time series such as monthly sunspots time series and runoff time series of the Yellow River, and the prediction results are promising.

  3. Accuracy of the Timed Up and Go test for predicting sarcopenia in elderly hospitalized patients

    Science.gov (United States)

    Martinez, Bruno Prata; Gomes, Isabela Barboza; de Oliveira, Carolina Santana; Ramos, Isis Resende; Rocha, Mônica Diniz Marques; Júnior, Luiz Alberto Forgiarini; Camelier, Fernanda Warken Rosa; Camelier, Aquiles Assunção

    2015-01-01

    OBJECTIVES: The ability of the Timed Up and Go test to predict sarcopenia has not been evaluated previously. The objective of this study was to evaluate the accuracy of the Timed Up and Go test for predicting sarcopenia in elderly hospitalized patients. METHODS: This cross-sectional study analyzed 68 elderly patients (≥60 years of age) in a private hospital in the city of Salvador-BA, Brazil, between the 1st and 5th day of hospitalization. The predictive variable was the Timed Up and Go test score, and the outcome of interest was the presence of sarcopenia (reduced muscle mass associated with a reduction in handgrip strength and/or weak physical performance in a 6-m gait-speed test). After the descriptive data analyses, the sensitivity, specificity and accuracy of a test using the predictive variable to predict the presence of sarcopenia were calculated. RESULTS: In total, 68 elderly individuals, with a mean age 70.4±7.7 years, were evaluated. The subjects had a Charlson Comorbidity Index score of 5.35±1.97. Most (64.7%) of the subjects had a clinical admission profile; the main reasons for hospitalization were cardiovascular disorders (22.1%), pneumonia (19.1%) and abdominal disorders (10.2%). The frequency of sarcopenia in the sample was 22.1%, and the mean length of time spent performing the Timed Up and Go test was 10.02±5.38 s. A time longer than or equal to a cutoff of 10.85 s on the Timed Up and Go test predicted sarcopenia with a sensitivity of 67% and a specificity of 88.7%. The accuracy of this cutoff for the Timed Up and Go test was good (0.80; IC=0.66-0.94; p=0.002). CONCLUSION: The Timed Up and Go test was shown to be a predictor of sarcopenia in elderly hospitalized patients. PMID:26039955

  4. Accuracy of the Timed Up and Go test for predicting sarcopenia in elderly hospitalized patients

    Directory of Open Access Journals (Sweden)

    Bruno Prata Martinez

    2015-05-01

    Full Text Available OBJECTIVES: The ability of the Timed Up and Go test to predict sarcopenia has not been evaluated previously. The objective of this study was to evaluate the accuracy of the Timed Up and Go test for predicting sarcopenia in elderly hospitalized patients. METHODS: This cross-sectional study analyzed 68 elderly patients (≥60 years of age in a private hospital in the city of Salvador-BA, Brazil, between the 1st and 5th day of hospitalization. The predictive variable was the Timed Up and Go test score, and the outcome of interest was the presence of sarcopenia (reduced muscle mass associated with a reduction in handgrip strength and/or weak physical performance in a 6-m gait-speed test. After the descriptive data analyses, the sensitivity, specificity and accuracy of a test using the predictive variable to predict the presence of sarcopenia were calculated. RESULTS: In total, 68 elderly individuals, with a mean age 70.4±7.7 years, were evaluated. The subjects had a Charlson Comorbidity Index score of 5.35±1.97. Most (64.7% of the subjects had a clinical admission profile; the main reasons for hospitalization were cardiovascular disorders (22.1%, pneumonia (19.1% and abdominal disorders (10.2%. The frequency of sarcopenia in the sample was 22.1%, and the mean length of time spent performing the Timed Up and Go test was 10.02±5.38 s. A time longer than or equal to a cutoff of 10.85 s on the Timed Up and Go test predicted sarcopenia with a sensitivity of 67% and a specificity of 88.7%. The accuracy of this cutoff for the Timed Up and Go test was good (0.80; IC=0.66-0.94; p=0.002. CONCLUSION: The Timed Up and Go test was shown to be a predictor of sarcopenia in elderly hospitalized patients.

  5. Software Design Challenges in Time Series Prediction Systems Using Parallel Implementation of Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    Narayanan Manikandan

    2016-01-01

    Full Text Available Software development life cycle has been characterized by destructive disconnects between activities like planning, analysis, design, and programming. Particularly software developed with prediction based results is always a big challenge for designers. Time series data forecasting like currency exchange, stock prices, and weather report are some of the areas where an extensive research is going on for the last three decades. In the initial days, the problems with financial analysis and prediction were solved by statistical models and methods. For the last two decades, a large number of Artificial Neural Networks based learning models have been proposed to solve the problems of financial data and get accurate results in prediction of the future trends and prices. This paper addressed some architectural design related issues for performance improvement through vectorising the strengths of multivariate econometric time series models and Artificial Neural Networks. It provides an adaptive approach for predicting exchange rates and it can be called hybrid methodology for predicting exchange rates. This framework is tested for finding the accuracy and performance of parallel algorithms used.

  6. Software Design Challenges in Time Series Prediction Systems Using Parallel Implementation of Artificial Neural Networks

    Science.gov (United States)

    Manikandan, Narayanan; Subha, Srinivasan

    2016-01-01

    Software development life cycle has been characterized by destructive disconnects between activities like planning, analysis, design, and programming. Particularly software developed with prediction based results is always a big challenge for designers. Time series data forecasting like currency exchange, stock prices, and weather report are some of the areas where an extensive research is going on for the last three decades. In the initial days, the problems with financial analysis and prediction were solved by statistical models and methods. For the last two decades, a large number of Artificial Neural Networks based learning models have been proposed to solve the problems of financial data and get accurate results in prediction of the future trends and prices. This paper addressed some architectural design related issues for performance improvement through vectorising the strengths of multivariate econometric time series models and Artificial Neural Networks. It provides an adaptive approach for predicting exchange rates and it can be called hybrid methodology for predicting exchange rates. This framework is tested for finding the accuracy and performance of parallel algorithms used. PMID:26881271

  7. Software Design Challenges in Time Series Prediction Systems Using Parallel Implementation of Artificial Neural Networks.

    Science.gov (United States)

    Manikandan, Narayanan; Subha, Srinivasan

    2016-01-01

    Software development life cycle has been characterized by destructive disconnects between activities like planning, analysis, design, and programming. Particularly software developed with prediction based results is always a big challenge for designers. Time series data forecasting like currency exchange, stock prices, and weather report are some of the areas where an extensive research is going on for the last three decades. In the initial days, the problems with financial analysis and prediction were solved by statistical models and methods. For the last two decades, a large number of Artificial Neural Networks based learning models have been proposed to solve the problems of financial data and get accurate results in prediction of the future trends and prices. This paper addressed some architectural design related issues for performance improvement through vectorising the strengths of multivariate econometric time series models and Artificial Neural Networks. It provides an adaptive approach for predicting exchange rates and it can be called hybrid methodology for predicting exchange rates. This framework is tested for finding the accuracy and performance of parallel algorithms used.

  8. Autoregressive Prediction with Rolling Mechanism for Time Series Forecasting with Small Sample Size

    Directory of Open Access Journals (Sweden)

    Zhihua Wang

    2014-01-01

    Full Text Available Reasonable prediction makes significant practical sense to stochastic and unstable time series analysis with small or limited sample size. Motivated by the rolling idea in grey theory and the practical relevance of very short-term forecasting or 1-step-ahead prediction, a novel autoregressive (AR prediction approach with rolling mechanism is proposed. In the modeling procedure, a new developed AR equation, which can be used to model nonstationary time series, is constructed in each prediction step. Meanwhile, the data window, for the next step ahead forecasting, rolls on by adding the most recent derived prediction result while deleting the first value of the former used sample data set. This rolling mechanism is an efficient technique for its advantages of improved forecasting accuracy, applicability in the case of limited and unstable data situations, and requirement of little computational effort. The general performance, influence of sample size, nonlinearity dynamic mechanism, and significance of the observed trends, as well as innovation variance, are illustrated and verified with Monte Carlo simulations. The proposed methodology is then applied to several practical data sets, including multiple building settlement sequences and two economic series.

  9. Predictive motor timing performance dissociates between early diseases of the cerebellum and Parkinson's disease.

    Science.gov (United States)

    Bares, Martin; Lungu, Ovidiu V; Husárová, Ivica; Gescheidt, Tomás

    2010-03-01

    There is evidence that both the basal ganglia and the cerebellum play a role in the neural representation of time in a variety of behaviours, but whether one of them is more important is not yet clear. To address this question in the context of predictive motor timing, we tested patients with various movement disorders implicating these two structures in a motor-timing task. Specifically, we investigated four different groups: (1) patients with early Parkinson's disease (PD); (2) patients with sporadic spinocerebellar ataxia (SCA); (3) patients with familial essential tremor (ET); and (4) matched healthy controls. We used a predictive motor-timing task that involved mediated interception of a moving target, and we assessed the effect of movement type (acceleration, deceleration and constant), speed (slow, medium and fast) and angle (0 degrees , 15 degrees and 30 degrees) on performance (hit, early error and late error). The main results showed that PD group and arm ET subgroup did not significantly differ from the control group. SCA and head ET subjects (severe and mild cerebellar damage, respectively) were significantly worse at interception than the other two groups. Our findings support the idea that the basal ganglia play a less significant role in predictive motor timing than the cerebellum. The fact that SCA and ET subjects seemed to have a fundamental problem with predictive motor timing suggests that the cerebellum plays an essential role in integrating incoming visual information with the motor output in a timely manner, and that ET is a heterogeneous entity that deserves increased attention from clinicians.

  10. Space can substitute for time in predicting climate-change effects on biodiversity

    Science.gov (United States)

    Blois, Jessica L.; Williams, John W.; Fitzpatrick, Matthew C.; Jackson, Stephen T.; Ferrier, Simon

    2013-06-01

    "Space-for-time" substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption-that drivers of spatial gradients of species composition also drive temporal changes in diversity-rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as "time-for-time" predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change.

  11. Working Memory and Auditory Imagery Predict Sensorimotor Synchronization with Expressively Timed Music.

    Science.gov (United States)

    Colley, Ian D; Keller, Peter E; Halpern, Andrea R

    2017-08-11

    Sensorimotor synchronization (SMS) is prevalent and readily studied in musical settings, as most people are able to perceive and synchronize with a beat (e.g. by finger tapping). We took an individual differences approach to understanding SMS to real music characterized by expressive timing (i.e. fluctuating beat regularity). Given the dynamic nature of SMS, we hypothesized that individual differences in working memory and auditory imagery-both fluid cognitive processes-would predict SMS at two levels: 1) mean absolute asynchrony (a measure of synchronization error), and 2) anticipatory timing (i.e. predicting, rather than reacting to beat intervals). In Experiment 1, participants completed two working memory tasks, four auditory imagery tasks, and an SMS-tapping task. Hierarchical regression models were used to predict SMS performance, with results showing dissociations among imagery types in relation to mean absolute asynchrony, and evidence of a role for working memory in anticipatory timing. In Experiment 2, a new sample of participants completed an expressive timing perception task to examine the role of imagery in perception without action. Results suggest that imagery vividness is important for perceiving and control is important for synchronizing with, irregular but ecologically valid musical time series. Working memory is implicated in synchronizing by anticipating events in the series.

  12. The Evolutionary Modeling and Short-range Climatic Prediction for Meteorological Element Time Series

    Institute of Scientific and Technical Information of China (English)

    YU Kangqing; ZHOU Yuehua; YANG Jing'an; KANG Zhuo

    2005-01-01

    The time series of precipitation in flood season (May-September) at Wuhan Station, which is set as an example of the kind of time series with chaos characters, is split into two parts: One includes macro climatic timescale period waves that are affected by some relatively steady climatic factors such as astronomical factors (sunspot, etc.), some other known and/or unknown factors, and the other includes micro climatic timescale period waves superimposed on the macro one. The evolutionary modeling (EM), which develops from genetic programming (GP), is supposed to be adept at simulating the former part because it creates the nonlinear ordinary differential equation (NODE) based upon the data series. The natural fractals (NF)are used to simulate the latter part. The final prediction is the sum of results from both methods, thus the model can reflect multi-time scale effects of forcing factors in the climate system. The results of this example for 2002 and 2003 are satisfactory for climatic prediction operation. The NODE can suggest that the data vary with time, which is beneficial to think over short-range climatic analysis and prediction. Comparison in principle between evolutionary modeling and linear modeling indicates that the evolutionary one is a better way to simulate the complex time series with nonlinear characteristics.

  13. TIME-FREQUENCY 2-D LMS BASED LONG-RANGE CHANNEL PREDICTION FOR WIRELESS OFDM SYSTEMS

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Adaptive modulation can optimize the spectrum efficiency and system performance with the channel state information achieved by the long-range channel prediction. To avoid re-estimating channel correlation function as the channel stationarity varies and to track the channel adaptively,LMS (Least-Mean-Square) based long-range channel prediction is discussed in the existing literature,but it needs long observation interval to reach the convergence. Given that all OFDM (Orthogonal Frequency Division Multiplexing) subcarriers have the identical time-domain correlation and stationarity during the same time interval, this paper proposed a 2-D LMS based predictor which updates the filter weights in both time and frequency domain. The proposed scheme can effectively decrease the observation intervals and significantly speed up the convergence than the conventional LMS and Parallel LMS (PLMS). Complexity analysis and simulation results prove that the proposed scheme can improve the BER (Bit Error Rate) performance and spectrum efficiency with negligible complexity increase.

  14. Geostatistical Spatio-Time model of crime in el Salvador: Structural and Predictive Analysis

    Directory of Open Access Journals (Sweden)

    Welman Rosa Alvarado

    2011-07-01

    Full Text Available Today, to study a geospatial and spatio-temporal phenomena requires searching statistical tools that enable the analysis of the dependency of space, time and interactions. The science that studies this kind of subjects is the Geoestatics which the goal is to predict spatial phenomenon. This science is considered the base for modeling phenomena that involves interactions between space and time. In the past 10 years, the Geostatistic had seen a great development in areas like the geology, soils, remote sensing, epidemiology, agriculture, ecology, economy, etc. In this research, the geostatistic had been apply to build a predictive map about crime in El Salvador; for that the variability of space and time together is studied to generate crime scenarios: crime hot spots are determined, crime vulnerable groups are identified, to improve political decisions and facilitate to decision makers about the insecurity in the country.

  15. Prediction of Ready Queue Processing Time in Multiprocessor Environment Using Lottery Scheduling (ULS

    Directory of Open Access Journals (Sweden)

    Amita CHOUDHARY

    2011-01-01

    Full Text Available While in multi-user environment, CPU has to manage lot of requests generated over the same time. Waiting queue of processes generates a problem of scheduling for processors. Designers and hardware architects have suggested system of multiprocessors to overcome the queue length. Lottery scheduling is one such method where processes in waiting queue are selected through a chance manner. This opens a way to use probability models to get estimates of system parameters. This paper is an application where the processing time of jobs in ready queue is predicted using the sampling method under the k-processors environment (k>1.The random selection of one process by each of k processors through without replacement method is a sample data set which helps in the prediction of possible ready queue processing time. Some theorems are established and proved to get desired results in terms of confidence intervals.

  16. FREEZING AND THAWING TIME PREDICTION METHODS OF FOODS II: NUMARICAL METHODS

    Directory of Open Access Journals (Sweden)

    Yahya TÜLEK

    1999-03-01

    Full Text Available Freezing is one of the excellent methods for the preservation of foods. If freezing and thawing processes and frozen storage method are carried out correctly, the original characteristics of the foods can remain almost unchanged over an extended periods of time. It is very important to determine the freezing and thawing time period of the foods, as they strongly influence the both quality of food material and process productivity and the economy. For developing a simple and effectively usable mathematical model, less amount of process parameters and physical properties should be enrolled in calculations. But it is a difficult to have all of these in one prediction method. For this reason, various freezing and thawing time prediction methods were proposed in literature and research studies have been going on.

  17. Multi-step-prediction of chaotic time series based on co-evolutionary recurrent neural network

    Institute of Scientific and Technical Information of China (English)

    Ma Qian-Li; Zheng Qi-Lun; Peng Hong; Zhong Tan-Wei; Qin Jiang-Wei

    2008-01-01

    This paper proposes a co-evolutionary recurrent neural network (CERNN) for the multi-step-prediction of chaotic time series,it estimates the proper parameters of phase space reconstruction and optimizes the structure of recurrent neural networks by co-evolutionary strategy.The searching space was separated into two subspaces and the individuals are trained in a parallel computational procedure.It can dynamically combine the embedding method with the capability of recurrent neural network to incorporate past experience due to internal recurrence.The effectiveness of CERNN is evaluated by using three benchmark chaotic time series data sets:the Lorenz series,Mackey-Glass series and real-world sun spot series.The simulation results show that CERNN improves the performances of multi-step-prediction of chaotic time series.

  18. Chaotic time series prediction using mean-field theory for support vector machine

    Institute of Scientific and Technical Information of China (English)

    Cui Wan-Zhao; Zhu Chang-Chun; Bao Wen-Xing; Liu Jun-Hua

    2005-01-01

    This paper presents a novel method for predicting chaotic time series which is based on the support vector machines approach, and it uses the mean-field theory for developing an easy and efficient learning procedure for the support vector machine. The proposed method approximates the distribution of the support vector machine parameters to a Gaussian process and uses the mean-field theory to estimate these parameters easily, and select the weights of the mixture of kernels used in the support vector machine estimation more accurately and faster than traditional quadratic programming-based algorithms. Finally, relationships between the embedding dimension and the predicting performance of this method are discussed, and the Mackey-Glass equation is applied to test this method. The stimulations show that the mean-field theory for support vector machine can predict chaotic time series accurately, and even if the embedding dimension is unknown, the predicted results are still satisfactory. This result implies that the mean-field theory for support vector machine is a good tool for studying chaotic time series.

  19. Time-Delay Artificial Neural Network Computing Models for Predicting Shelf Life of Processed Cheese

    Directory of Open Access Journals (Sweden)

    Sumit Goyal

    2012-04-01

    Full Text Available This paper presents the capability of Time–delay artificial neural network models for predicting shelf life of processed cheese. Datasets were divided into two subsets (30 for training and 6 for validation. Models with single and multi layers were developed and compared with each other. Mean Square Error, Root Mean Square Error, Coefficient of Determination and Nash -
    Sutcliffo Coefficient were used as performance evaluators, Time- delay model predicted the shelf life of processed cheese as 28.25 days, which is very close to experimental shelf life of 30 days.

  20. On the best learning algorithm for web services response time prediction

    DEFF Research Database (Denmark)

    Madsen, Henrik; Albu, Razvan-Daniel; Popentiu-Vladicescu, Florin

    2013-01-01

    an application is. A Web service is better imagined as an application "segment," or better as a program enabler. Performance is an important quality aspect of Web services because of their distributed nature. Predicting the response of web services during their operation is very important.......In this article we will examine the effect of different learning algorithms, while training the MLP (Multilayer Perceptron) with the intention of predicting web services response time. Web services do not necessitate a user interface. This may seem contradictory to most people's concept of what...