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Abstract Essential to life on Earth, assessment of marine photosynthesis is of paramount importance. Photosynthesis occurs in spatially discrete microscopic entities at various levels of biological organization, from subcellular chloroplasts to symbiotic microalgae and macroalgae, and is influenced by the surrounding conditions.As such, in situ photosynthetic efficiency mapping on appropriate scales holds great promise for learning about these processes.To achieve this goal, we designed, fabricated, and tested an underwater microscope that incorporates standard colour, epifluorescence, and variable chlorophyllafluorescence imaging with nearly micron spatial resolution that resolves the structure and photosynthetic efficiency of benthic organisms.Our results highlight coral observations with high‐resolution photosynthetic spatial variability and detailed morphology. Our imaging system therefore enables research never before possible on the health and physiology of benthic aquatic organisms in situ, placing it in the context of their physical and biological environment. 

Our subjective visual experiences involve complex interaction between our eyes, our brain, and the surrounding world. It gives us the sense of sight, color, stereopsis, distance, pattern recognition, motor coordination, and more. The increasing ubiquity of gaze-aware technology brings with it the ability to track gaze and pupil measures with varying degrees of fidelity. With this in mind, a review that considers the various gaze measures becomes increasingly relevant, especially considering our ability to make sense of these signals given different spatio-temporal sampling capacities. In this paper, we selectively review prior work on eye movements and pupil measures. We first describe the main oculomotor events studied in the literature, and their characteristics exploited by different measures. Next, we review various eye movement and pupil measures from prior literature. Finally, we discuss our observations based on applications of these measures, the benefits and practical challenges involving these measures, and our recommendations on future eye-tracking research directions. 

Objective We measured how long distraction by a smartphone affects simulated driving behaviors after the tasks are completed (i.e., the distraction hangover). Background Most drivers know that smartphones distract. Trying to limit distraction, drivers can use hands-free devices, where they only briefly glance at the smartphone. However, the cognitive cost of switching tasks from driving to communicating and back to driving adds an underappreciated, potentially long period to the total distraction time. Method Ninety-seven 21- to 78-year-old individuals who self-identified as active drivers and smartphone users engaged in a simulated driving scenario that included smartphone distractions. Peripheral-cue and car-following tasks were used to assess driving behavior, along with synchronized eye tracking. Results The participants’ lateral speed was larger than baseline for 15 s after the end of a voice distraction and for up to 25 s after a text distraction. Correct identification of peripheral cues dropped about 5% per decade of age, and participants from the 71+ age group missed seeing about 50% of peripheral cues within 4 s of the distraction. During distraction, coherence with the lead car in a following task dropped from 0.54 to 0.045, and seven participants rear-ended the lead car. Breadth of scanning contracted by 50% after distraction. Conclusion Simulated driving performance drops dramatically after smartphone distraction for all ages and for both voice and texting. Application Public education should include the dangers of any smartphone use during driving, including hands-free. 

Numerous types of biological branching networks, with varying shapes and sizes, are used to acquire and distribute resources. Here, we show that plant root and shoot architectures share a fundamental design property. We studied the spatial density function of plant architectures, which specifies the probability of finding a branch at each location in the 3-dimensional volume occupied by the plant. We analyzed 1645 root architectures from four species and discovered that the spatial density functions of all architectures are population-similar. This means that despite their apparent visual diversity, all of the roots studied share the same basic shape, aside from stretching and compression along orthogonal directions. Moreover, the spatial density of all architectures can be described as variations on a single underlying function: a Gaussian density truncated at a boundary of roughly three standard deviations. Thus, the root density of any architecture requires only four parameters to specify: the total mass of the architecture and the standard deviations of the Gaussian in the three x , y , z growth directions. Plant shoot architectures also follow this design form, suggesting that two basic plant transport systems may use similar growth strategies. 

For someone with Autism Spectrum Disorder, performance on tasks that require coordinated motor and cognitive activities, such as walking while talking (or texting) on our phones, can take substantially more effort to accomplish. While it is more common to isolate and examine motor and cognitive skill in separate experiments, we propose a dual task experiment to allow us to examine performance in people with autism more realistically. We designed a system composed of three task types and accompanying hardware to simultaneously quantify balance, fine motor skill, and cognitive ability. We hypothesized that the additional demands of the balance and speeded finger-tapping tasks would degrade motor performance in the simultaneous conditions, but not impact cognitive (N-Back task) performance. Movement data were evaluated by comparing the change of each group across 3 levels of cognitive load (0-, 1-, and 2-back). We tested the task on a small sample of young adults with autism spectrum disorder (ASD; n=4) and matched controls (n=4). We observed a trend largely consistent with our hypotheses. The system's temporal precision and modular design also allow for the incorporation of other sensors as needed, like EEG or heart rate variability. We propose that a version of this system be tested as a putative outcome measure for interventions involving attention, cognitive load or certain types of motor skill training.