• Korean Journal of Environment and Ecology
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• v.23 no.5
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• pp.431-438
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• 2009

The main purpose of this research is to prepare and provide basic materials for the propagational strategy of eelgrass by investigating on the morphological adaptation of Korean Zostera marina to ocean currents. An eelgrass plant mainly consists of rhizome, leaf sheath, leaves and roots. The rhizome is the horizontal stem of the plant that serves as the backbone from which the leaves and roots emerge. The leaf sheath is the bundle at the base of the leaves that holds the leaves together, protecting the meristem, the primary growth point of the shoot. Leaves originate from a meristem which is protected by a sheath at the actively growing end of the rhizome. As the shoot grows, the rhizome elongates, moving across or within the sediment, forming roots as it progresses. The aggregated leaves from the leaf sheath are found to have two cell layers on one side and multiple layers of airy tissues called aerenchyma on the other. The aerenchyma tissues are developed in multi-layered cell structures surrounding the veins which are formed in the leaf sheath. Generative shoots are made of rhizomes, which are circular or ovoidal, stem, and spathe and spadix. The transverse section of rhizome and the stem and central floral axis is found to be circular, ovoid and in the shape of convex respectively, and the vascular bundle, which is a part of transport system, has one large tube in the center and two small tubes on both sides. The layers of collenchyma cells numbered from 12 to 15 in the stem, and from 7 to 12 in the rhizome. The seed coat is composed of sclereids, small bundles of sclerenchyma tissues, which prevent the influx of sea water from the outside and help endure the environmental stress. In conclusion, alternative multi-layer structure in circular, convex type aggregated leaf base are interpreted to morphological adaption as doing tolerable elastic structure through movement of seawater. The generative shoots develop long slim stem and branches in circular or ovoidal shapes to minimize the adverse impacts of sea current, which can be interpreted as the plant's morphological adaptation to its environment.

• The Korean Journal of Nuclear Medicine
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• v.38 no.3
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• pp.233-240
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• 2004

Purpose: We developed a computer-aided classifier using artificial neural network (ANN) to discriminate the cerebral metabolic pattern of medial and lateral temporal lobe epilepsy (TLE). Materials and Methods: We studied brain F-18-FDG PET images of 113 epilepsy patients sugically and pathologically proven as medial TLE (left 41, right 42) or lateral TLE (left 14, right 16). PET images were spatially transformed onto a standard template and normalized to the mean counts of cortical regions. Asymmetry indices for predefined 17 mirrored regions to hemispheric midline and those for medial and lateral temporal lobes were used as input features for ANN. ANN classifier was composed of 3 independent multi-layered perceptrons (1 for left/right lateralization and 2 for medial/lateral discrimination) and trained to interpret metabolic patterns and produce one of 4 diagnoses (L/R medial TLE or L/R lateral TLE). Randomly selected 8 images from each group were used to train the ANN classifier and remaining 51 images were used as test sets. The accuracy of the diagnosis with ANN was estimated by averaging the agreement rates of independent 50 trials and compared to that of nuclear medicine experts. Results: The accuracy in lateralization was 89% by the human experts and 90% by the ANN classifier Overall accuracy in localization of epileptogenic zones by the ANN classifier was 69%, which was comparable to that by the human experts (72%). Conclusion: We conclude that ANN classifier performed as well as human experts and could be potentially useful supporting tool for the differential diagnosis of TLE.