Relevant bibliographies by topics / Cumulative structure function

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Academic literature on the topic 'Cumulative structure function'

Author: Grafiati
Published: 13 April 2024

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Journal articles on the topic "Cumulative structure function"

1

Tolentino, Dante, and Sonia E. Ruiz. "Time-Dependent Confidence Factor for Structures with Cumulative Damage." Earthquake Spectra 31, no. 1 (2015): 441–61. http://dx.doi.org/10.1193/010912eqs008m.

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An approach is proposed to evaluate the confidence factor implicit in structures over an interval of time, considering that the structural capacity and structural demand vary simultaneously over time. A new closed-form mathematical expression of the confidence factor over a time interval is used, assuming that the structural capacity degradation is represented by a second degree polynomial function in the total interval. This formulation is made in accordance with the demand and capacity factor design format. Confidence factors at the ends of different time intervals are evaluated for an old ten-story building. The confidence factors and their confidence levels, calculated under the assumption that the structural capacity degradation follows a linear function, and alternatively, a polynomial function, are compared. The maximum difference between confidence factors assuming both types of functions is 5% after 100 years of structure construction, which represents a small difference for the engineering practice.
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2

Cox, Angela M., Yong Gao, Anne-Karina T. Perl, Robert S. Tepper, and Shawn K. Ahlfeld. "Cumulative effects of neonatal hyperoxia on murine alveolar structure and function." Pediatric Pulmonology 52, no. 5 (2017): 616–24. http://dx.doi.org/10.1002/ppul.23654.

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3

Iyit, Neslihan. "Modelling world energy security data from multinomial distribution by generalized linear model under different cumulative link functions." Open Chemistry 16, no. 1 (2018): 377–85. http://dx.doi.org/10.1515/chem-2018-0053.

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AbstractEnergy securityis one of the major components of energy sustainability in the world’s energy performance. In this study,energy securityis taken as an ordinal response variable coming from the multinomial distribution with the energy grade levelsA,B,C, andD. Thereafter, the worldenergy securitydata is tried to be statistically modelled by usinggeneralized linear model (GLM)approach for the ordinal response variable under different cumulative link functions. The cumulative link functions comparatively used in this study are cumulative logit, cumulative probit, cumulative complementary log-log, cumulative Cauchit, and cumulative negative log-log. In order to avoid a multicollinearity problem in the data structure, principal component analysis (PCA) technique is integrated with theGLMapproach for the ordinal response variable. In this study, statistically, the importance of determining the best cumulative link function on the accuracy of parameter estimates, confidence intervals, and hypothesis tests in theGLMfor the multinomially distributed response variable is highlighted. In terms of energy evaluation, by usingcumulative logitas the best cumulative link function,energy sources consumptions,electricity productions from nuclear energy,natural gas,oil,coal,and hydroelectric,energy use per capita and energy importsare found to have statistically significant effects onenergy securityin the world’s energy performance.
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4

Terek, Milan. "Regional Incomes Structure Analysis in Slovak Republic On the Basis of EU-SILC Data." Scientific Annals of Economics and Business 64, no. 2 (2017): 171–85. http://dx.doi.org/10.1515/saeb-2017-0011.

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Abstract The paper deals with the regional incomes structure analysis in Slovak republic on the basis of European Union statistics on income and living conditions in Slovak republic data. The empirical probability mass function and empirical cumulative distribution function is constructed with aid of given sampling weights. On the basis of these functions the median, medial, standard deviation and population histogram of the whole gross household incomes for the whole Slovak republic and separately for eight Slovak regions are estimated and compared.
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5

Ndlovu, Bonginkosi D., Sileshi F. Melesse, Temesgen Zewotir, and Temesgen Zewotir. "A mixture model with application to discrete competing risks data." South African Statistical Journal 53, no. 2 (2019): 73–86. http://dx.doi.org/10.37920/sasj.2019.53.2.2.

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In this paper, we modify the continuous time mixture competing risks model (Larson and Dinse, 1985) to handle discrete competing risks data. The main result of the model is an alternate regression expression for the cumulative incidence function. The structure of the regression expression for the cumulative incidence function under this model, and the proportional hazards assumption for the conditional hazard rates with piece-wise constant baseline conditional hazards, combine to allow for another means to assess the covariate effects on the cumulative incidence function. This benefit comes at some computational costs because the parameters are estimated via an EM algorithm. The proposed model is applied to real data and it is found that it improves the exercise of evaluating the covariate effects on the cumulative incidence function compared to other discrete competing risks models.
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6

Teramoto, Kanako, Wilson Nadruz Junior, Kunihiro Matsushita, et al. "Mid- to Late-Life Time-Averaged Cumulative Blood Pressure and Late-Life Cardiac Structure, Function, and Heart Failure." Hypertension 76, no. 3 (2020): 808–18. http://dx.doi.org/10.1161/hypertensionaha.120.14833.

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Limited data exist regarding systolic blood pressure (SBP) through mid- to late-life and late-life cardiac function and heart failure (HF) risk. Among 4578 HF-free participants in the ARIC study (Atherosclerosis Risk in Communities) attending the fifth visit (2011–2013; age 75±5 years), time-averaged cumulative SBP was calculated as the sum of averaged SBPs from adjacent consecutive visits (visits 1–5) indexed to total observation time (24±1 years). Calculations were performed using measured SBPs and also incorporating antihypertensive medication specific effect constants (underlying SBP). Outcomes included comprehensive echocardiography at visit 5 and post-visit 5 incident HF, HF with preserved ejection fraction, and reduced ejection fraction. Higher cumulative SBP was associated with greater left ventricular mass and worse diastolic measures (all P <0.001), associations that were stronger with underlying compared with cumulative SBP (all P <0.05). At 5.6±1.2 years follow-up post-visit 5, higher cumulative measured and underlying SBP were associated with incident HF (hazard ratio per 10 mm Hg for measured: 1.12 [1.01–1.24]; underlying: 1.19 [95% CI, 1.10–1.30]) and HF with preserved ejection fraction (measured: 1.15 [1.00–1.33]; underlying: 1.28 [1.14–1.45]), but not HF with reduced ejection fraction (measured: 1.11 [0.94–1.32]; underlying: 1.11 [0.96–1.24]). Associations with HF and HF with preserved ejection fraction were more robust with cumulative underlying compared with measured SBP (all P <0.05). Time-averaged cumulative SBP in mid to late life is associated with worse cardiac function and risk of incident HF, especially HF with preserved ejection fraction, in late life. These associations were stronger considering underlying as opposed to measured SBP, highlighting the importance of prevention and effective treatment of hypertension to prevent late-life cardiac dysfunction and HF.
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7

Jenkins, Lisanne M., Chaney R. Garner, Shawn Kurian, et al. "Cumulative Blood Pressure Exposure, Basal Ganglia, and Thalamic Morphology in Midlife." Hypertension 75, no. 5 (2020): 1289–95. http://dx.doi.org/10.1161/hypertensionaha.120.14678.

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High blood pressure (BP) negatively affects brain structure and function. Hypertension is associated with white matter hyperintensities, cognitive and mobility impairment in late-life. However, the impact of BP exposure from young adulthood on brain structure and function in mid-life is unclear. Identifying early brain structural changes associated with BP exposure, before clinical onset of cognitive dysfunction and mobility impairment, is essential for understanding mechanisms and developing interventions. We examined the effect of cumulative BP exposure from young adulthood on brain structure in a substudy of 144 (61 female) individuals from the CARDIA (Coronary Artery Risk Development in Young Adults) study. At year 30 (Y 30 , ninth visit), participants (56±4 years old) completed brain magnetic resonance imaging and gait measures (pace, rhythm, and postural control). Cumulative systolic and diastolic BP (cumulative systolic blood pressure, cDBP) over 9 visits were calculated, multiplying mean values between 2 consecutive visits by years between visits. Surface-based analysis of basal ganglia and thalamus was achieved using FreeSurfer-initiated Large Deformation Diffeomorphic Metric Mapping. Morphometric changes were regressed onto cumulative BP to localize regions of shape variation. Y 30 white matter hyperintensity volumes were small and positively correlated with cumulative BP but not gait. Negative morphometric associations with cumulative systolic blood pressure were seen in the caudate, putamen, nucleus accumbens, pallidum, and thalamus. A concave right medial putamen shape mediated the relationship between cumulative systolic blood pressure and stride width. Basal ganglia and thalamic morphometric changes, rather than volumes, may be earlier manifestation of gray matter structural signatures of BP exposure that impact midlife gait.
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8

Aslam, Muhammad, Muhammad Riaz, Tabassum Naz Sindhu, and Zaheer Ahmed. "A Study of Cumulative Quantity Control Chart for a Mixture of Rayleigh Model under a Bayesian Framework." Revista Colombiana de Estadística 39, no. 2 (2016): 185. http://dx.doi.org/10.15446/rce.v39n2.58915.

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<p>This study deals with the cumulative charting technique based on a simple and a mixture of Rayleigh models. The respective charting schemes are referred as the SRCQC-chart and the MRCQC-chart. These are stimulated from existing statistical control charts in this direction i.e. the cumulative quantity control (CQC) chart, based on exponential and Weibull models, and the cumulative count control (CCC) chart, based on the simple geometricmodel. Another motivation for this study is the mixture cumulative count control (MCCC) chart based on the two component geometric model. The use of mixture cumulative quantity is an attractive approach for process monitoring. The design structure of the proposed control chart is derived by using the cumulative distribution function of simple, and two components of mixture distribution(s). We observed that the proposed charting structure is efficient in detecting the changes in process parameters. The application of the proposed scheme is illustrated using a real dataset.</p>
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9

Nie, Cong, Xiaoming Liu, and Serge B. Provost. "An Objective Measure of Distributional Estimability as Applied to the Phase-Type Aging Model." Risks 12, no. 2 (2024): 37. http://dx.doi.org/10.3390/risks12020037.

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The phase-type aging model (PTAM) is a class of Coxian-type Markovian models that can provide a quantitative description of the effects of various aging characteristics. Owing to the unique structure of the PTAM, parametric inference on the model is affected by a significant estimability issue, its profile likelihood functions being flat. While existing methods for assessing distributional non-estimability require the subjective specification of thresholds, this paper objectively quantifies estimability in the context of general statistical models. More specifically, this is achieved via a carefully designed cumulative distribution function sensitivity measure, under which the threshold is tailored to the empirical cumulative distribution function, thus becoming an experiment-based quantity. The proposed definition, which is validated to be innately sound, is then employed to determine and enhance the estimability of the PTAM.
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10

Bow, Eric W., and John M. Rimoldi. "The Structure–Function Relationships of Classical Cannabinoids: CB1/CB2 Modulation." Perspectives in Medicinal Chemistry 8 (January 2016): PMC.S32171. http://dx.doi.org/10.4137/pmc.s32171.

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The cannabinoids are members of a deceptively simple class of terpenophenolic secondary metabolites isolated from Cannabis sativa highlighted by (-)-Δ 9 -tetrahydrocannabinol (THC), eliciting distinct pharmacological effects mediated largely by cannabinoid receptor (CB1 or CB2) signaling. Since the initial discovery of THC and related cannabinoids, synthetic and semisynthetic classical cannabinoid analogs have been evaluated to help define receptor binding modes and structure–CB1/CB2 functional activity relationships. This perspective will examine the classical cannabinoids, with particular emphasis on the structure–activity relationship of five regions: C3 side chain, phenolic hydroxyl, aromatic A-ring, pyran B-ring, and cyclohexenyl C-ring. Cumulative structure–activity relationship studies to date have helped define the critical structural elements required for potency and selectivity toward CB1 and CB2 and, more importantly, ushered the discovery and development of contemporary nonclassical cannabinoid modulators with enhanced physicochemical and pharmacological profiles.
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