23 research outputs found
Numerical study of effect of elastomeric stress absorbers on stress reduction in bone-dental implant interface
Objective This paper focused on optimal stress distribution in the mandibular bone surrounding a dental implant and is devoted to the development of a modified Osteoplant® implant type in order to minimize stress concentration in the bone-implant interface. Material and Methods This study investigated 0.4 mm thick layers of two elastomeric stress barriers incorporated into the dental implant using 3-D finite element analysis. Results Overall, this proposed implant provoked lower load transfer in bone-implant interface due to the effect of the elastomers as stress absorbers. The stress level in the bone was reduced between 28% and 42% for three load cases: 75 N, 60 N and 27 N in corono-apical, linguo-buccal and disto-mesial direction, respectively. Conclusion The proposed model provided an acceptable solution for load transfer reduction to the mandible. This investigation also permitted to choose how to incorporate two elastomers into the Osteoplant® implant system
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Pomalidomide, bortezomib and low-dose dexamethasone in lenalidomide-refractory and proteasome inhibitor-exposed myeloma
This phase 1 dose-escalation study evaluated pomalidomide, bortezomib (subcutaneous (SC) or intravenous (IV)) and low-dose dexamethasone (LoDEX) in lenalidomide-refractory and proteasome inhibitor-exposed relapsed or relapsed and refractory multiple myeloma (RRMM). In 21-day cycles, patients received pomalidomide (1–4 mg days 1–14), bortezomib (1–1.3 mg/m2 days 1, 4, 8 and 11 for cycles 1–8; days 1 and 8 for cycle ⩾9) and LoDEX. Primary endpoint was to determine the maximum tolerated dose (MTD). Thirty-four patients enrolled: 12 during escalation, 10 in the MTD IV bortezomib cohort and 12 in the MTD SC bortezomib cohort. Patients received a median of 2 prior lines of therapy; 97% bortezomib exposed. With no dose-limiting toxicities, MTD was defined as the maximum planned dose: pomalidomide 4 mg, bortezomib 1.3 mg/m2 and LoDEX. All patients discontinued treatment by data cutoff (2 April 2015). The most common grade 3/4 treatment-emergent adverse events were neutropenia (44%) and thrombocytopenia (26%), which occurred more frequently with IV than SC bortezomib. No grade 3/4 peripheral neuropathy or deep vein thrombosis was reported. Overall response rate was 65%. Median duration of response was 7.4 months. Pomalidomide, bortezomib and LoDEX was well tolerated and effective in lenalidomide-refractory and bortezomib-exposed patients with RRMM
Process Plan Generation for Reconfigurable Manufacturing Systems: Exact Versus Evolutionary-Based Multi-objective Approaches
International audienceFuture productions are facing an increasingly complex environments, customized, flexible and high-quality production. Moreover, low costs, high reactivity and high quality products are necessary criteria for industries to achieve competitiveness in nowadays market. In this context, reconfigurable manufacturing systems (RMSs) have emerged to fulfill these requirements. This chapter addresses the multi-objective process plan generation problem in RMS environment. Three approaches are proposed and compared: an iterative multi-objective integer linear program (I-MOILP) and adapted versions of the well-known evolutionary algorithms, respectively, archived multi-objective simulated annealing (AMOSA) and the non-dominated sorting genetic algorithm (NSGA-II). Moreover, in addition to the minimization of the classical total production cost and the total completion time, the minimization of the maximum machines exploitation time is considered as a novel optimization criterion, in order to have high quality products. To illustrate the applicability of the three approaches, an example is presented and the obtained numerical results are analysed
Management of reconfigurable production networks in order-based production
High market volatility as well as increasing global competition in manufacturing lead to a growing demand for flexible and agile production networks. Advanced production systems in turn conduct high capital expenditure along with high investment risks. However, the latest developments of information and communication technology in production environments carry promising optimization opportunities. The approach of this paper is to apply reconfigurable production networks for scalable capacity and low capital expenditure by adapting “Production planning as a service”. Therefore, a genetic algorithm was applied to solve a complex optimization problem. At the end of this work, a prototypical application of the discussed subject is shown on a world-leading household appliance manufacturer