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This paper aims to propose a simulation model integrated with an empirical regression analysis to provide a new mathematical formulation for automated storage and retrieval system (AS/RS) travel time estimation under class-based storage and different input/output (I/O) point vertical levels.

A simulation approach is adopted to compute the travel time under different warehouse scenarios. Simulation runs with several I/O point levels and multiple shape factor values.

The proposed model is extremely precise for both single command (SC) and dual command (DC) cycles and very well fitted for a reliable computation of travel times.

The proposed mathematical formulation for estimating the AS/RS travel time advances widely applied methodologies existing in literature. As well as, it provides a practical implication by supporting faster and more accurate travel time computations for both SC and DC cycles. However, the regression analysis is conducted based on simulated data and can be refined by numerical values coming from real warehouses.

This work provides a new simulation model and a refined mathematical equation to estimate AS/RS travel time.

The objective of this paper is to propose an approach to comparatively analyze the performance of drugs and consumable products warehouses belonging to different healthcare institutions.

A Cluster Analysis is completed in order to classify warehouses and identify common patterns based on similar organizational characteristics. The variables taken into account are associated with inventory levels, the number of SKUs, and incoming and outgoing flows.

The outcomes of the empirical analysis are confirmed by additional indicators reflecting the demand level and the associated logistics flows faced by the warehouses at issue. Also, the warehouses belonging to the same cluster show similar behaviors for all the indicators considered, meaning that the performed Cluster Analysis can be considered as coherent.

The study proposes an approach aimed at grouping healthcare warehouses based on relevant logistics aspects. Thus, it can foster the application of statistical analysis in the healthcare Supply Chain Management. The present work is associated with only one regional healthcare system.

The approach might support healthcare agencies in comparing the performance of their warehouses more accurately. Consequently, it could facilitate comprehensive investigations of the managerial similarities and differences that could be a first step toward warehouse aggregation in homogeneous logistics units.

This analysis puts forward an approach based on a consolidated statistical tool, to assess the logistics performances in a set of warehouses and, in turn to deepen the related understanding as well as the factors determining them.

This study was conducted to find out the association between estrogen exposure and systemic lupus erythematosus (SLE) in Bangladeshi women.

A case-control study was carried out from January to December 2015 among 128 intervention cases and 128 age-matched control group participants to find out the association with estrogen exposure and development of SLE.

Case group participants were five times (OR 5.14, 95% CI 2.14–12.33), three times (OR 3.40, 95% CI 1.25–9.21) and four times (OR 4.00, 95% CI 1.45–11.00) more likely to receive different higher levels of education compared to the control group. Exposure to estrogen showed a positive association with the development of SLE. The case group (12.63 ± 1.61 years) had a lower age at menarche than that of the control group (13.31 ± 1.47 years; p < 0.001) and their proportion (62.6%) of using oral contraceptive pills were more than that of the control group (45.6%; p < 0.01). After controlling the effect of the positively associated variables, SLE patients were found two times (adjusted OR 2.26; 95% CI 1.29–3.95) more likely to use oral contraceptive pills than the control group. The case group was more (adjusted OR 0.771; 95% CI 0.642–0.927) prone to have an earlier age at menarche compared to the control group.

This study identified the association between estrogen exposure and SLE. Contraceptive pills should be used cautiously and both consumers and service providers need to be aware of their effects.