This report provides a comprehensive view of drug lag in the three regions. More detailed analyses are necessary in order for a more in-depth discussion of the background factors, impacts and measures for the drug lag,which is especially noticeable in Japan.

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a) Input CT image of an object (b) Distance field on the inside of the object (c) Distance field on the outside of the object Figure 1: The result of the OoCDT algorithm for an "Cylinder-Head" model (size: 850 × 800 × 1059 ≈ 700M cells). Note that the data size of the distance field is about 3GB (4 bytes/cell), which is too large to allocate to the RAM. Our algorithm can compute such large distance fields on common 32-bit computers.. AbstractThis paper presents a method for computing distance fields from large volumetric models. Conventional methods have strict limits in terms of the amount of memory space available, as all volumetric models must be allocated to the random access memory (RAM) to compute distance fields. We resolve this problem through an outof-core strategy. Our algorithm starts by decomposing volumetric models into small regions known as clusters, and distance fields are then computed by Local Distance Transform (LDT) and InterCluster Propagation (ICP). LDT computes the distance transform for each cluster, and since it is independent, other clusters can also be saved to the storage medium. ICP propagates the distance at the boundary of the cluster to neighboring clusters to remove inconsistency in distance fields. In addition, we propose an efficient ordering algorithm based on the propagated distance to reduce LDT and ICP. This paper also demonstrates the results of distance transform from volumetric models with over a billion cells.

A substantial number of unapproved drugs were being imported to Japan. A formal system for monitoring the use of those drugs should be established.