This paper studies a single machine scheduling problem with time-dependent learning and setup times. Time-dependent learning means that the actual processing time of a job is a function of the sum of the normal proces...This paper studies a single machine scheduling problem with time-dependent learning and setup times. Time-dependent learning means that the actual processing time of a job is a function of the sum of the normal processing times of the jobs already scheduled. The setup time of a job is proportional to the length of the already processed jobs, that is, past-sequence-dependent (psd) setup time. We show that the addressed problem remains polynomially solvable for the objectives, i.e., minimization of the total completion time and minimization of the total weighted completion time. We also show that the smallest processing time (SPT) rule provides the optimum sequence for the addressed problem.展开更多
Mean platelet volume （MPV） is an early marker ofplatelet activation. Larger platelets, compared to small ones, increase platelet adhesion and aggregation, and present a higher thrombotic activity. Some studies have ...Mean platelet volume （MPV） is an early marker ofplatelet activation. Larger platelets, compared to small ones, increase platelet adhesion and aggregation, and present a higher thrombotic activity. Some studies have explored the association between MPV and the morbidity of portal vein thrombosis （PVT）. The aim of this study was to evaluate the predictive effect of MPV in patients with PVT by a meta-analysis. We searched Pubmed, Web of Science, SCOPUS, OVID, CNKI and CBMD from database inception to September 13, 2017. Seven studies in accordance with selection criteria were included. The extraction of basic data was independently conducted by two reviewers. The mean difference in MPV between PVT patients and controls were pooled with weighted mean difference （WMD） and 95% confidence interval of 0.88 fl （95% CI： 0.61-1.15）. A random-effect model was chosen for an obvious heterogeneity in the pooling （Chi-square=27.12, df=6, P〈0.0001, F=77.9%）. The sources of heterogeneity were from the difference of primary disease of participants and portal vein diameter. Taken together, our results reveal that MPV is a predictive indicator in patients with PVT.展开更多
文摘This paper studies a single machine scheduling problem with time-dependent learning and setup times. Time-dependent learning means that the actual processing time of a job is a function of the sum of the normal processing times of the jobs already scheduled. The setup time of a job is proportional to the length of the already processed jobs, that is, past-sequence-dependent (psd) setup time. We show that the addressed problem remains polynomially solvable for the objectives, i.e., minimization of the total completion time and minimization of the total weighted completion time. We also show that the smallest processing time (SPT) rule provides the optimum sequence for the addressed problem.
基金This work was supported by the National Natural Science Foundation of China （No. 81500109）.
文摘Mean platelet volume （MPV） is an early marker ofplatelet activation. Larger platelets, compared to small ones, increase platelet adhesion and aggregation, and present a higher thrombotic activity. Some studies have explored the association between MPV and the morbidity of portal vein thrombosis （PVT）. The aim of this study was to evaluate the predictive effect of MPV in patients with PVT by a meta-analysis. We searched Pubmed, Web of Science, SCOPUS, OVID, CNKI and CBMD from database inception to September 13, 2017. Seven studies in accordance with selection criteria were included. The extraction of basic data was independently conducted by two reviewers. The mean difference in MPV between PVT patients and controls were pooled with weighted mean difference （WMD） and 95% confidence interval of 0.88 fl （95% CI： 0.61-1.15）. A random-effect model was chosen for an obvious heterogeneity in the pooling （Chi-square=27.12, df=6, P〈0.0001, F=77.9%）. The sources of heterogeneity were from the difference of primary disease of participants and portal vein diameter. Taken together, our results reveal that MPV is a predictive indicator in patients with PVT.
