In automated laboratories consisting of multiple different types of instruments, scheduling algorithms are useful for determining the optimal allocations of instruments to minimize the time required to complete experimental procedures. However, previous studies on scheduling algorithms for laboratory automation have not emphasized the time constraints by mutual boundaries (TCMBs) among operations, which is important in procedures involving live cells or unstable biomolecules. Here, we define the “scheduling for laboratory automation in biology” (S-LAB) problem as a scheduling problem for automated laboratories in which operations with TCMBs are performed by multiple different instruments. We formulate an S-LAB problem as a mixed-integer programming (MIP) problem and propose a scheduling method using the branch-and-bound algorithm. Simulations show that our method can find the optimal schedules of S-LAB problems that minimize overall execution time while satisfying the TCMBs. Furthermore, we propose the use of our scheduling method for the simulation-based design of job definitions and laboratory configurations.

Spatial and temporal adaptation of predictive saccades based on motion trajectories. Three macaque monkeys were trained in the predictive saccade task (Fig. 1a, Methods). Each trial began with the appearance of a red fixation point (FP, 0.5° square) presented below a gray rectangle (10° height, 'occluder'). During eye fixation, a white target spot (0.5° circle) appeared above the occluder and moved obliquely at 20°/s. After a 500-ms excursion, the target reached the upper side of the rectangle and was occluded for 580-710 ms. For each trial, the target path was randomly selected among 28 combinations of initial target location and trajectory

The understanding of brain activity during program comprehension have advanced thanks to noninvasive neuroimaging techniques, such as functional magnetic resonance imaging (fMRI). However, individual neuroimaging studies of program comprehension often provided inconsistent results and made it difficult to identify the neural bases. To identify the essential brain regions, this study performed a small meta-analysis on recent fMRI studies of program comprehension using multilevel kernel density analysis (MKDA). Our analysis identified a set of brain regions consistently activated in various program comprehension tasks. These regions consisted of three clusters, each of which centered at the left inferior frontal gyrus pars triangularis (IFG Tri), posterior part of middle temporal gyrus (pMTG), and right middle frontal gyrus (MFG). Additionally, subsequent analyses revealed relationships among the activation patterns in the previous studies and multiple cognitive functions. These findings suggest that program comprehension mainly recycles the language-related networks and partially employs other domain-general resources in the human brain.

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