In this study, we investigated the feasibility of automatic emotion classification by applying the machine learning algorithm Random Forest to time-series brain activity data measured using functional near-infrared spectroscopy (fNIRS). fNIRS is a noninvasive neuroimaging technique capable of monitoring cerebral hemodynamics by detecting changes in oxygenated and deoxygenated hemoglobin concentrations in the cortical surface. It offers practical advantages such as portability, safety, and ease of use, making it suitable for real-world emotion research. Fifteen healthy male participants were presented with emotionally valenced visual stimuli, consisting of pleasant, unpleasant, and neutral images that had been pre-classified based on previous subjective ratings. During the task, changes in blood flow in the prefrontal cortex were recorded using 22 fNIRS channels. After preprocessing the fNIRS signals to reduce drift and physiological noise, we applied statistical analyses and machine learning techniques to evaluate emotional responses. Specifically, we conducted paired t-tests to assess significant differences in hemoglobin levels before and during stimulus presentation, and used the feature importance metric from Random Forest to identify which brain regions contributed most to emotion classification. The classification model achieved a remarkably high accuracy of 99.48 % using all channels and maintained strong performance (96.04 %) even when restricted to the top five most informative channels. These results indicate that the integration of fNIRS and machine learning is a promising approach for developing objective, reliable, and noninvasive methods for emotion recognition, with potential applications in fields such as affective computing, mental health assessment, and brain-computer interfaces.

Food texture, which includes properties such as viscosity and elasticity, considerably affects swallowing ease and sensory perception. This study aims to objectively evaluate the physiological responses when swallowing jelly drinks with varying physical properties by analyzing electroencephalogram (EEG) signals. EEG data were collected while participants swallowed four different commercially available jelly drinks. Spectrograms obtained after preprocessing and time-frequency conversion using the short-time Fourier transform were input into the EfficientNetB7 deep learning model for classifying the jelly types based on the EEG patterns. This model achieved high classification accuracy on the training data; however, its performance on validation data was notably lower, suggesting potential overfitting. Jelly1 and Jelly3 were frequently misclassified because of their similar textures, while Jelly4 showed relatively higher classification accuracy, which can be attributed to its distinct physical characteristics. These findings suggest that EEG signals recorded during swallowing contain texture-related neural signatures, and deep learning models can be used to partially capture these differences. This study contributes to the development of neurophysiological methods for food texture evaluation and lays the foundation for applications in dysphagia assessment and food engineering.

Single-cell spatial omics analysis requires consideration of biological functions and mechanisms in a microenvironment. However, microenvironment analysis using bioinformatic methods is limited by the need to detect histological morphology and extend it to the surrounding area. In this study, we developed SpatialKNifeY (SKNY), an image-processing-based toolkit that detects spatial domains that potentially reflect histology and extends these domains to the microenvironment. Using spatial transcriptomic data from breast cancer, we applied the SKNY algorithm to identify tumor spatial domains, followed by clustering of the domains, trajectory estimation, and spatial extension to the tumor microenvironment (TME). The results of the trajectory estimation were consistent with the known mechanisms of cancer progression. We observed tumor vascularization and immunodeficiency at mid- and late-stage progression in TME. Furthermore, we applied the SKNY to integrate and cluster the spatial domains of 14 patients with metastatic colorectal cancer, and the clusters were divided based on the TME characteristics. In conclusion, the SKNY facilitates the determination of the functions and mechanisms in the microenvironment and cataloguing of the features.

Conventional methods of assessing swallowing function are invasive and burdensome to the patient. Although swallowing function assessment can be performed non-invasively using an ultrasound system, one issue must be overcome: the position of the probe is not fixed. Therefore, deep learning-based object detection was used to detect the esophageal wall so that a more stable and accurate examination can be performed. As a result,. Although the detection rate was high enough and false positive rate was low enough for practical use, we believe that the detection rate can be further increased in the future by learning ultrasound images taken from various angles from a larger number of subjects.

The alterations in the electroencephalogram (EEG) activity of healthy adult males during the ingestion of carbonated beverages were investigated. The primary objective was to explore how carbonation levels affect brain activity, with a focus on the P300 component, which is associated with stimulus evaluation. Brain function was measured using an electroencephalograph placed on the scalp. The participants were provided with water, mildly carbonated water, and strongly carbonated water as the experimental stimuli. We analyzed time-series signals to identify and characterize P300 waves and conducted spectral analysis to observe changes in the power spectral density across different frequency bands. The findings indicated significant variations in the EEG signals corresponding to different carbonation levels of the beverages. Specifically, there was an observable increase in the beta-band power and a decrease in the alpha-band power as the carbonation level increased. These changes were most prominent for the electrodes near the frontal lobe. The results suggest that carbonated beverages elicit different neural responses from water, which can be accurately captured through EEG measurements. This study provides valuable insights into the functional activity of the brain during swallowing and highlights the potential of electroencephalography for studying sensory stimuli and motor control mechanisms.

The demand for SAR - Synthetic Aperture Radar satellites that can observe a target area through clouds and during nighttime - is emerging, particularly in Asia, where frequent cloud cover inhibits the satellite monitoring capabilities of optical sensors. Our goal is to build a constellation of small SAR satellites to achieve short-term revisits (less than one day), to make the best use of SAR sensors that can acquire data regardless of weather or time of day. We expect that the development of this constellation will expand the scope of SAR data to business and private decision making, and develop a market for commercial use. We have launched our first demonstrative satellite - StriX-$\alpha$- at the end of 2020, are already preparing to build our second satellite, and will go on to make a six-satellite constellation by 2022. Our ultimate goal is to build a constellation - StriX - consisting of 30 satellites. The name StriX was given based on the scientific name for the genus of owls - an allusion to its ability to ‘see’.

BACKGROUND: Genome graph is an emerging approach for representing structural variants on genomes with branches. For example, representing structural variants of cancer genomes as a genome graph is more natural than representing such genomes as differences from the linear reference genome. While more and more structural variants are being identified by long-read sequencing, many of them are difficult to visualize using existing structural variants visualization tools. To this end, visualization method for large genome graphs such as human cancer genome graphs is demanded. RESULTS: We developed MOdular Multi-scale Integrated Genome graph browser, MoMI-G, a web-based genome graph browser that can visualize genome graphs with structural variants and supporting evidences such as read alignments, read depth, and annotations. This browser allows more intuitive recognition of large, nested, and potentially more complex structural variations. MoMI-G has view modules for different scales, which allow users to view the whole genome down to nucleotide-level alignments of long reads. Alignments spanning reference alleles and those spanning alternative alleles are shown in the same view. Users can customize the view, if they are not satisfied with the preset views. In addition, MoMI-G has Interval Card Deck, a feature for rapid manual inspection of hundreds of structural variants. Herein, we describe the utility of MoMI-G by using representative examples of large and nested structural variations found in two cell lines, LC-2/ad and CHM1. CONCLUSIONS: Users can inspect complex and large structural variations found by long-read analysis in large genomes such as human genomes more smoothly and more intuitively. In addition, users can easily filter out false positives by manually inspecting hundreds of identified structural variants with supporting long-read alignments and annotations in a short time. SOFTWARE AVAILABILITY: MoMI-G is freely available at https://github.com/MoMI-G/MoMI-G under the MIT license.

Increasing the export of fruit is vital for the Japanese economy. In this study, we focused on the peach trade as it is the third most transported fruit in Japan. The peach is a very sensitive fruit; therefore, proper packaging is important. We proposed a special packing sheet that we named the “concavo-convex sheet” developed through a simple mechanism. However, there were some problems in creating this sheet. This study describes the new mechanism for creating the concavo-convex sheet, and a real machine using the installed mechanism was developed. As a result, it was confirmed that the sheet can be realized by the new machine.

An important goal for the Japanese economy involves increasing the export of fruits. Especially, the export of peaches to Taiwan is an important part of trade for Japan. However, the peach fruit moth poses a serious problem. The moth is not native to Taiwan. Therefore, the moths that are exported with peaches may cause ecological damage in Taiwan. We are in the process of developing a peach fruit inspection system involving the use of X-rays. A handling unit that is a part of the inspection system is required to softly hold the peach without damaging it. This study describes a concavo-convex sheet developed by two nonwoven fabric clothes that is adapted for the inspection system. There are two important factors involved for incorporating the sheet in the inspection system, namely, the friction coefficient of the sheet and damage protection for the peaches. These factors are investigated by performing experiments that use several real, fresh peaches. The results confirm that the concavo-convex sheet satisfies the important properties necessary to employ the system for peach fruit inspection.

This paper describes an unique sheet developed from non-woven fabric that can be used to reduce transportation shock experienced by fruits that are easily damaged, such as peaches or strawberries, when transporting to foreign countries where there is a significant demand for these fruits. The proposed sheet comprises two non-woven fabric cloths suitable for packing these types of fruit. The non-woven cloth has useful characteristics such as air permeability, sealing properties, and X-ray transmission properties that make it suitable for transporting easily damaged fruit. In this paper, the application of the proposed sheet is applied for the packing of the fruits, however, the sheet that has the air permeability and shock resistance property is useful for the assistive robot and human interaction robot. And, the sheet is made manually, since the method to produce it is not constructed. The task of the human is reduced, if the mechanism for making the sheet can be realized. This paper describes that the properties of the sheet are introduced, and that the performance is investigated by experimental methods. Finally, the mechanism for producing the sheet is described and investigated using an experimental prototype.

The innate immune response is primarily mediated by the Toll-like receptors functioning through the MyD88-dependent and TRIF-dependent pathways. Despite being widely studied, it is not yet completely understood and systems-level analyses have been lacking. In this study, we identified a high-probability network of genes activated during the innate immune response using a novel approach to analyze time-course gene expression profiles of activated immune cells in combination with a large gene regulatory and protein-protein interaction network. We classified the immune response into three consecutive time-dependent stages and identified the most probable paths between genes showing a significant change in expression at each stage. The resultant network contained several novel and known regulators of the innate immune response, many of which did not show any observable change in expression at the sampled time points. The response network shows the dominance of genes from specific functional classes during different stages of the immune response. It also suggests a role for the protein phosphatase 2a catalytic subunit α in the regulation of the immunoproteasome during the late phase of the response. In order to clarify the differences between the MyD88-dependent and TRIF-dependent pathways in the innate immune response, time-course gene expression profiles from MyD88-knockout and TRIF-knockout dendritic cells were analyzed. Their response networks suggest the dominance of the MyD88-dependent pathway in the innate immune response, and an association of the circadian regulators and immunoproteasomal degradation with the TRIF-dependent pathway. The response network presented here provides the most probable associations between genes expressed in the early and the late phases of the innate immune response, while taking into account the intermediate regulators. We propose that the method described here can also be used in the identification of time-dependent gene sub-networks in other biological systems.

The architecture of a single-chip video DSP capable of attaining a maximum performance of 300-MOPS (mega operations per second) using 0.8- mu m CMOS technology is described. The DSP is designed for the many applications regarding p*64 kb/s single-board video codecs based on DSPs that have roughly ten times the performance of conventional DSPs. Highly parallel architectures that allow four pipelined processing units to be integrated into one chip are studied extensively. The authors consider data path configurations, program sequencing control, and microinstructions that effectively support multiple pipeline processing. A prototype DSP is fabricated using 0.8- mu m CMOS technology, and some performance evaluations are presented.>

A single board video codec for ISDN B/2B channel transmission, which depends on a CCITT standardization p*64 video coding algorithm and communication protocol, has been developed. The video codec is constructed with newly designed DSPs, four kinds of NTSC-CIF (Common Intermediate Format) mutual conversion LSIs, a transmission codec LSI and an AD/DA hybrid IC. The video codec codes and decodes a full CIF signal at a frame rate of 10 frames/s and communicates over either an ISDN 64 kb/s or 2*6 64 kb/s channel. The codec is fabricated on a single small board with a size of 280 mm*280 mm. Furthermore, a desk-top prototype visual telephone terminal which uses the video codec, voice codec and NCU has been developed.>

The architecture of a newly developed highly parallel pipeline DSP that achieves over 300 MOPS/LSI programming capability is presented. This programmable single-chip DSP is designed for application to a variety of different single-board moving image codecs, which require a DSP with roughly 10 times the power of conventional single pipeline unit architecture DSPs. Assuming 0.8- mu m CMOS technology, a single-chip DSP architecture integrating four sets of pipeline processing units was extensively studied. The DSP configuration and noble techniques enabling efficient operation of plural pipeline processing units are described. Evaluation of the performance of the DSP is also presented.>

This paper describes custom designed VLSI coder and decoder, which transmit time division multiplexed (TDM) color signals at 32 Mbit/sec. Two-dimensional intraframe DPCM prediction, variable word length coding, and data buffer to smooth the data rate are devised on one coder chip. Reverse function are devised on one decoder chip. Test sequence is investigated for logic design purposes. Several techniques, e.g., double phased clock and prediction loop modification are employed to simplify the configuration and to ensure the operation rate of video processing.