Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
Filter
  • Hindawi Limited  (2)
Type of Medium
Publisher
  • Hindawi Limited  (2)
Language
Years
  • 1
    In: International Journal of Endocrinology, Hindawi Limited, Vol. 2018 ( 2018), p. 1-11
    Abstract: Background . Recently, several studies have reported that dedifferentiation occurs in fatal well-differentiated thyroid cancer (WDTC) cases. This study aimed at investigating the clinicopathological characteristics of WDTC undergoing dedifferentiation. Methods . A total of 63 WDTC patients harboring dedifferentiated phenotype were enrolled in the study. The Kaplan-Meier method and Cox regression analysis were used to perform survival analyses. Harrell index of concordance (C-index) and Akaike information criterion (AIC) were calculated to compare the predictive value for prognosis among several prognostic classification systems. Results . The median cause-specific survival (CSS) of patients was 138 months, with the CSS rate of 64.0% and 53.3% at 5 and 10 years, respectively. Presence of the anaplastic thyroid cancer (ATC) phenotype significantly increased the risk of poor CSS ( P = 0.033 ), and age was the only independent risk factor for disease progression ( P = 0.015 ). The C-index and AIC of the age, grade, extent, size (AGES) prognostic classification system for the CSS were 0.723 and 59.937, respectively. Conclusions . The presence of dedifferentiated phenotypes can be responsible for the poor outcomes in WDTC patients. The AGES system demonstrates to be an optimal prognostic system for WDTC undergoing dedifferentiation.
    Type of Medium: Online Resource
    ISSN: 1687-8337 , 1687-8345
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2018
    detail.hit.zdb_id: 2502951-4
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
  • 2
    Online Resource
    Online Resource
    Hindawi Limited ; 2020
    In:  Mathematical Problems in Engineering Vol. 2020 ( 2020-04-21), p. 1-11
    In: Mathematical Problems in Engineering, Hindawi Limited, Vol. 2020 ( 2020-04-21), p. 1-11
    Abstract: Energy storage systems (ESSs) are promising solutions for the mitigation of power fluctuations and the management of load demands in distribution networks (DNs). However, the uncertainty of load demands and wind generations (WGs) may have a significant impact on the capacity allocation of ESSs. To solve the problem, a novel optimal ESS capacity allocation scheme for ESSs is proposed to reduce the influence of uncertainty of both WG and load demands. First, an optimal capacity allocation model is established to minimize the ESS investment costs and the network power loss under constraints of DN and ESS operating points and power balance. Then, the proposed method reduces the uncertainty of load through a comprehensive demand response system based on time-of-use (TOU) and incentives. To predict the output of WGs, we combined particle swarm optimization (PSO) and backpropagation neural network to create a prediction model of the wind power. An improved simulated annealing PSO algorithm (ISAPSO) is used to solve the optimization problem. Numerical studies are carried out in a modified IEEE 33-node distribution system. Simulation results demonstrate that the proposed model can provide the optimal capacity allocation and investment cost of ESSs with minimal power losses.
    Type of Medium: Online Resource
    ISSN: 1024-123X , 1563-5147
    Language: English
    Publisher: Hindawi Limited
    Publication Date: 2020
    detail.hit.zdb_id: 2014442-8
    SSG: 11
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. Further information can be found on the KOBV privacy pages