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Abstract I developed a simple crystal growth process to obtain a single Ga crystal. The crystal orientation of a Ga plate could be controlled by a crystal growth process using a seed Ga crystal. By anodizing a [100]-direction highly oriented Ga plate, I realized the formation of a highly ordered array of high-aspect-ratio straight nanoholes. It was observed that the nanohole growth direction depends on the crystal orientation of a Ga plate. To date, this dependence has yet to be observed in materials other than porous Ga oxide obtained by an anodization process. The present fabrication process is expected to be applied to the fabrication of various functional devices requiring a porous Ga oxide with high-aspect-ratio straight nanoholes, such as hydrogen formation devices and functional filters.

A gait is a walking pattern that can help identify a person. Recently, gait analysis employed a vision-based pose estimation for further feature extraction. This research aims to identify a person by analyzing their walking pattern. Moreover, the authors intend to expand gait analysis for other tasks, e.g., the analysis of clinical, psychological, and emotional tasks. The vision-based human pose estimation method is used in this study to extract the joint angles and rank correlation between them. We deploy the multi-view gait databases for the experiment, i.e., CASIA-B and OUMVLP-Pose. The features are separated into three parts, i.e., whole, upper, and lower body features, to study the effect of the human body part features on an analysis of the gait. For person identity matching, a minimum Dynamic Time Warping (DTW) distance is determined. Additionally, we apply a majority voting algorithm to integrate the separated matching results from multiple cameras to enhance accuracy, and it improved up to approximately 30% compared to matching without majority voting.

Climatic factors have commonly been attributed as the trigger of general flowering, a unique community-level mass flowering phenomenon involving most dipterocarp species that forms the foundation of Southeast Asian tropical rainforests. This intriguing flowering event is often succeeded by mast fruiting, which provides a temporary yet substantial burst of food resources for animals, particularly frugivores. However, the physiological mechanism that triggers general flowering, particularly in dipterocarp species, is not well understood largely due to its irregular and unpredictable occurrences in the tall and dense forests. To shed light on this mechanism, we employed ecological transcriptomic analyses on an RNA-seq dataset of a general flowering species, Shorea curtisii (Dipterocarpaceae), sequenced from leaves and buds collected at multiple vegetative and flowering phenological stages. We assembled 64,219 unigenes from the transcriptome of which 1,730 and 3,559 were differentially expressed in the leaf and the bud, respectively. Differentially expressed unigene clusters were found to be enriched with homologs of Arabidopsis thaliana genes associated with response to biotic and abiotic stresses, nutrient level, and hormonal treatments. When combined with rainfall data, our transcriptome data reveals that the trees were responding to a brief period of drought prior to the elevated expression of key floral promoters and followed by differential expression of unigenes that indicates physiological changes associated with the transition from vegetative to reproductive stages. Our study is timely for a representative general flowering dipterocarp species that occurs in forests that are under the constant threat of deforestation and climate change as it pinpoints important climate sensitive and flowering-related homologs and offers a glimpse into the cascade of gene expression before and after the onset of floral initiation.

In this research, we proposed a two-stage pipeline for segmenting urinary stones. The first stage U-Net generated the map localizing the urinary organs in full abdominal x-ray images. Then, this map was used for creating partitioned images input to the second stage U-Net to reduce class imbalance and was also used in stone-embedding augmentation to increase a number of training data. The U-Net model was trained with the combination of real stone-contained images and synthesized stone-embedded images to segment urinary stones on the partitioned input images. In addition, we proposed to use an inverse weighting method in the focal Tversky loss function in order to rebalance lesion size. The U-Net model using our proposed pipeline produced a 71.28% pixel-wise $F_{2}$ score and a 69.82% region-wise $F_{2}$ score, which were 2.88% and 7.63%, respectively, higher than those of a baseline method. Experimental results showed that the proposed method improved urinary stone segmentation results, especially for small stones and stones in uncommon locations.

Global warming-induced climate change causes significant agricultural problems by increasing the incidence of drought and flooding events. Waterlogging is an inevitable consequence of these changes but its effects on oil palms have received little attention and are poorly understood. Recent waterlogging studies have focused on oil palm seedlings, with particular emphasis on phenology. However, the transcriptomic waterlogging response of mature oil palms remains elusive in real environments. We therefore investigated transcriptomic changes over time in adult oil palms at plantations over a two-year period with pronounced seasonal variation in precipitation. A significant transcriptional waterlogging response was observed in the oil palm stem core but not in leaf samples when gene expression was correlated with cumulative precipitation over two-day periods. Pathways and processes upregulated or enriched in the stem core response included hypoxia, ethylene signaling, and carbon metabolism. Post-waterlogging recovery in oil palms was found to be associated with responses to heat stress and carotenoid biosynthesis. Nineteen transcription factors (TFs) potentially involved in the waterlogging response of mature oil palms were also identified. These data provide new insights into the transcriptomic responses of planted oil palms to waterlogging and offer valuable guidance on the sensitivity of oil palm plantations to future climate changes.

A urinary stone is a type of abnormality that occurs frequently in the urinary system. An automated segmentation of urinary stones is important for assisting medical doctors in early diagnosis and further treatment. While deep learning techniques are effective for image segmentation, they require a large number of datasets to achieve high accuracy. We proposed a GAN-based augmentation technique for creating synthetic images based on stone and non-stone mask inputs in order to improve the segmentation network’s performance by increasing the number and diversity of training data. The synthetic training images were generated from stone-contained images and stone-free images using existing stone ground truth and corresponding stone location maps, respectively. To segment urinary stones from full abdominal x-ray images, we trained the MultiResUnet model using both original stone-contained and our proposed synthetic samples. The proposed method obtained a 69.59% pixel-wise $F_{1}$ score and a 68.14% region-wise $F_{1}$ score, which achieved an improvement of 2.12% and 2.13%, respectively, over a model trained with only the original stone-contained dataset.

Herein, we give an overview of several less explored structural and optical characterization techniques useful for biomaterials. New insights into the structure of natural fibers such as spider silk can be gained with minimal sample preparation. Electromagnetic radiation (EMR) over a broad range of wavelengths (from X-ray to THz) provides information of the structure of the material at correspondingly different length scales (nm-to-mm). When the sample features, such as the alignment of certain fibers, cannot be characterized optically, polarization analysis of the optical images can provide further information on feature alignment. The 3D complexity of biological samples necessitates that there be feature measurements and characterization over a large range of length scales. We discuss the issue of characterizing complex shapes by analysis of the link between the color and structure of spider scales and silk. For example, it is shown that the green-blue color of a spider scale is dominated by the chitin slab’s Fabry–Pérot-type reflectivity rather than the surface nanostructure. The use of a chromaticity plot simplifies complex spectra and enables quantification of the apparent colors. All the experimental data presented herein are used to support the discussion on the structure–color link in the characterization of materials.

This paper presents a real-time hand segmentation method that is based on background subtraction and color information. A hand, as foreground, is extracted from an image by background subtraction where unit gradient vectors (UGVs) are used instead of image intensities. The UGV-based method is more stable under dynamic lighting conditions because the UGVs are invariant to changes in illumination. Meanwhile, the hand is also detected using color information. These two method results lead into the final hand segmentation. Experimental results show that the proposed method can segment a hand in an image robustly under various lighting conditions. We have implemented the proposed method using a low-cost embedded board Raspberry Pi.

In this study, highly ordered anodic porous metal oxides of transition metals (W, Fe, Co, and Nb) were prepared by anodization combined with a pretexturing process. The formation of an array of dimples on the metal surface was achieved by dry etching using ordered anodic porous alumina as a mask. Subsequent anodization of the pretextured metals generated metal oxides (WO3, Fe2O3, Co3O4, and Nb2O4) with an ordered hole array structure because each dimple acted as a starting point for hole development. The hole periodicity of the resulting ordered anodic porous metal oxide could be controlled by changing the periodicity of the dimples formed on the substrate. Ordered anodic porous films obtained by this process could be used in various functional devices that require ordered hole array structures.

Multilayered porous hollow spheres were obtained by the periodic anodization of small Al particles in different electrolytes and subsequent selective etching. The periodic anodization of small Al particles in concentrated H2SO4 and oxalic acid generated oxide layers on their surface with a periodically modulated solubility in the thickness direction. Hollow spheres composed of multilayered porous alumina shells were prepared by the subsequent etching of residual Al and the oxide layers formed in concentrated H2SO4. The resulting multilayered hollow spheres had a large specific surface area originating from their unique geometrical structure and are expected to find use in various applications such as catalysts, sensors, and drug carriers.

This paper presents a drowsiness detection method for drivers based on visual features in a video sequence. Image intensities are traditionally visual features. However, it is known that they are directly influenced by lighting conditions. We propose a human eye detection method using the normalized cross-correlation between displacement vectors and gradient vectors. Gradient vectors are dependent on lighting conditions but the normalization step makes them independent of illuminations. In this way, the proposed method can detect human eyes regardless of various lighting conditions. We have also found that normalized cross-correlation can be useful, not only for detecting eyes, but also for recognizing open and closed eye states. To overcome poor lighting conditions, we used infrared auxiliary illumination in order to make the proposed method work every moment. The computation speed of the proposed method is fast enough to perform at video rates.

Crowd counting is a challenging task dealing with the variation of an object scale and a crowd density. Existing works have emphasized on skip connections by integrating shallower layers with deeper layers, where each layer extracts features in a different object scale and crowd density. However, only high-level features are emphasized while ignoring low-level features. This paper proposes an estimation network by passing high-level features to shallow layers and emphasizing its low-level feature. Since an estimation network is a hierarchical network, a high-level feature is also emphasized by an improved low-level feature. Our estimation network consists of two identical networks for extracting a high-level feature and estimating the final result. To preserve semantic information, dilated convolution is employed without resizing the feature map. Our method was tested in three datasets for counting humans and vehicles in a crowd image. The counting performance is evaluated by mean absolute error and root mean squared error indicating the accuracy and robustness of an estimation network, respectively. The experimental result shows that our network outperforms other related works in a high crowd density and is effective for reducing over-counting error in the overall case.

Pollinator syndrome is one of the most important determinants regulating pollen dispersal in tropical tree species. It has been widely accepted that the reproduction of tropical forest species, especially dipterocarps that rely on insects with weak flight for their pollination, is positively density-dependent. However differences in pollinator syndrome should affect pollen dispersal patterns and, consequently, influence genetic diversity via the mating process. We examined the pollen dispersal pattern and mating system of Shorea maxwelliana, the flowers of which are larger than those of Shorea species belonging to section Mutica which are thought to be pollinated by thrips (weak flyers). A Bayesian mating model based on the paternity of seeds collected from mother trees during sporadic and mass flowering events revealed that the estimated pollen dispersal kernel and average pollen dispersal distance were similar for both flowering events. This evidence suggests that the putative pollinators - small beetles and weevils - effectively contribute to pollen dispersal and help to maintain a high outcrossing rate even during sporadic flowering events. However, the reduction in pollen donors during a sporadic event results in a reduction in effective pollen donors, which should lead to lower genetic diversity in the next generation derived from seeds produced during such an event. Although sporadic flowering has been considered less effective for outcrossing in Shorea species that depend on thrips for their pollination, effective pollen dispersal by the small beetles and weevils ensures outcrossing during periods of low flowering tree density, as occurs in a sporadic flowering event.

Climatic factors have commonly been attributed as the trigger of general flowering, a unique community-level mass flowering phenomenon involving most dipterocarp species that forms the foundation of Southeast Asian tropical rainforests. This intriguing flowering event is often succeeded by mast fruiting, which provides a temporary yet substantial burst of food resources for animals, particularly frugivores. However, the physiological mechanism that triggers general flowering, particularly in dipterocarp species, is not well understood largely due to its irregular and unpredictable occurrences in the tall and dense forests. To shed light on this mechanism, we employed ecological transcriptomic analyses on an RNA-seq dataset of a general flowering species, Shorea curtisii (Dipterocarpaceae), sequenced from leaves and buds collected at multiple vegetative and flowering phenological stages. We assembled 64,219 unigenes from the transcriptome of which 1,730 and 3,559 were differentially expressed in the leaf and the bud, respectively. Differentially expressed unigene clusters were found to be enriched with homologs of Arabidopsis thaliana genes associated with response to biotic and abiotic stresses, nutrient level, and hormonal treatments. When combined with rainfall data, our transcriptome data reveals that the trees were responding to a brief period of drought prior to the elevated expression of key floral promoters and followed by differential expression of unigenes that indicates physiological changes associated with the transition from vegetative to reproductive stages. Our study is timely for a representative general flowering dipterocarp species that occurs in forests that are under the constant threat of deforestation and climate change as it pinpoints important climate sensitive and flowering-related homologs and offers a glimpse into the cascade of gene expression before and after the onset of floral initiation. [ABSTRACT FROM AUTHOR]

A STEM/EDS study of a porous Ga oxide film formed by an anodization process was conducted in this study to examine the crystalline structure of the film and the elemental distribution in the oxide film before and after heat treatment. The as-formed anodic film with a morphology resembling the well-known porous anodic Al oxide film was amorphous, crystallizing after heat treatment at 600 °C without changing the morphology and elemental distribution. The EDS elemental maps disclosed the duplex nature of the pore wall oxide; the phosphate anion was contaminated in the outer oxide layer next to the pores, and the inner layer consisted of relatively pure Ga oxide, practically free from phosphate. The similarity of morphology and elemental distributions between the porous anodic Al and Ga oxides suggests that the growth of both anodic oxide films proceeds under the same mechanism. In addition, crystallized porous Ga oxides are expected to be applied to fabricate various functional devices requiring geometrically controlled semiconductor nanohole arrays, such as devices for hydrogen formation. [ABSTRACT FROM AUTHOR]