Flexible Modeling of a Long Reach Articulated Carrier: Geometric and Elastic Error Calibration

Author(s):  
J. Chalfoun ◽  
C. Bidard ◽  
D. Keller ◽  
Y. Perrot ◽  
G. Piolain
2021 ◽  
Vol 10 (8) ◽  
pp. 1657
Author(s):  
Morgane Mounier ◽  
Gaëlle Romain ◽  
Mary Callanan ◽  
Akoua Alla ◽  
Olayidé Boussari ◽  
...  

With improvements in acute myeloid leukemia (AML) diagnosis and treatment, more patients are surviving for longer periods. A French population of 9453 AML patients aged ≥15 years diagnosed from 1995 to 2015 was studied to quantify the proportion cured (P), time to cure (TTC) and median survival of patients who are not cured (MedS). Net survival (NS) was estimated using a flexible model adjusted for age and sex in sixteen AML subtypes. When cure assumption was acceptable, the flexible cure model was used to estimate P, TTC and MedS for the uncured patients. The 5-year NS varied from 68% to 9% in men and from 77% to 11% in women in acute promyelocytic leukemia (AML-APL) and in therapy-related AML (t-AML), respectively. Major age-differenced survival was observed for patients with a diagnosis of AML with recurrent cytogenetic abnormalities. A poorer survival in younger patients was found in t-AML and AML with minimal differentiation. An atypical survival profile was found for acute myelomonocytic leukemia and AML without maturation in both sexes and for AML not otherwise specified (only for men) according to age, with a better prognosis for middle-aged compared to younger patients. Sex disparity regarding survival was observed in younger patients with t-AML diagnosed at 25 years of age (+28% at 5 years in men compared to women) and in AML with minimal differentiation (+23% at 5 years in women compared to men). All AML subtypes included an age group for which the assumption of cure was acceptable, although P varied from 90% in younger women with AML-APL to 3% in older men with acute monoblastic and monocytic leukemia. Increased P was associated with shorter TTC. A sizeable proportion of AML patients do not achieve cure, and MedS for these did not exceed 23 months. We identify AML subsets where cure assumption is negative, thus pointing to priority areas for future research efforts.


Author(s):  
Xu-dong Huang ◽  
Chen-hua Wang ◽  
Jing-run Pan ◽  
Jia-bin Chen ◽  
Chun-lei Song ◽  
...  

2014 ◽  
Vol 33 (29) ◽  
pp. 5111-5125 ◽  
Author(s):  
Baoguang Han ◽  
Menggang Yu ◽  
James J. Dignam ◽  
Paul J. Rathouz

2015 ◽  
Vol 22 (3) ◽  
pp. 363-381 ◽  
Author(s):  
Candida Geerdens ◽  
Gerda Claeskens ◽  
Paul Janssen

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ben Lopman ◽  
Carol Y. Liu ◽  
Adrien Le Guillou ◽  
Andreas Handel ◽  
Timothy L. Lash ◽  
...  

AbstractUniversity administrators face decisions about how to safely return and maintain students, staff and faculty on campus throughout the 2020–21 school year. We developed a susceptible-exposed-infectious-recovered (SEIR) deterministic compartmental transmission model of SARS-CoV-2 among university students, staff, and faculty. Our goals were to inform planning at our own university, Emory University, a medium-sized university with around 15,000 students and 15,000 faculty and staff, and to provide a flexible modeling framework to inform the planning efforts at similar academic institutions. Control strategies of isolation and quarantine are initiated by screening (regardless of symptoms) or testing (of symptomatic individuals). We explored a range of screening and testing frequencies and performed a probabilistic sensitivity analysis. We found that among students, monthly and weekly screening can reduce cumulative incidence by 59% and 87%, respectively, while testing with a 2-, 4- and 7-day delay between onset of infectiousness and testing results in an 84%, 74% and 55% reduction in cumulative incidence. Smaller reductions were observed among staff and faculty. Community-introduction of SARS-CoV-2 onto campus may be controlled with testing, isolation, contract tracing and quarantine. Screening would need to be performed at least weekly to have substantial reductions beyond disease surveillance. This model can also inform resource requirements of diagnostic capacity and isolation/quarantine facilities associated with different strategies.


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