Thermal Design and Experimental Verification of the 3D-printed Registojet

A 3D-printed resistojet, wherein the heater and flow path were united, was produced. The heater consists of multi-layer shells and is difficult to break down. In this paper, the thermal design and the results of the thrust measurement are reported. The measured electrical resistance matched with the predicted one. Both the heater and the thrust reached 70 percent efficiency when paired with a nitrogen propellant at a mass flow rate of 0.2 g/s.AIAA 2018-4907 Session: Micropropulsion I

Classification of multiple emotional states from facial expressions in head-fixed mice using a deep learning-based image analysis

Facial expressions are widely recognized as universal indicators of underlying internal states in most species of animals, thereby presenting as a non-invasive measure for assessing physical and mental conditions. Despite the advancement of artificial intelligence-assisted tools for automated analysis of voluminous facial expression data in human subjects, the corresponding tools for mice still remain limited so far. Considering that mice are the most prevalent model animals for studying human health and diseases, a comprehensive characterization of emotion-dependent patterns of facial expressions in mice could extend our knowledge on the basis of emotions and the related disorders. Here, we present a framework for the development of a deep learning-powered tool for classifying facial expressions in head-fixed mouse. We demonstrate that our machine vision was capable of accurately classifying three different emotional states from lateral facial images in head-fixed mouse. Moreover, we objectively determined how our classifier characterized the differences among the facial images through the use of an interpretation technique called Gradient-weighted Class Activation Mapping. Importantly, our machine vision presumably discerned the data by leveraging multiple facial features. Our approach is likely to facilitate the non-invasive decoding of a variety of emotions from facial images in head-fixed mice.Tanaka Y., Nakata T., Hibino H., et al. Classification of multiple emotional states from facial expressions in head-fixed mice using a deep learning-based image analysis. PLoS ONE 18, e0288930 (2023); https://doi.org/10.1371/journal.pone.0288930

Polyunsaturated fatty acids-enriched lipid from reduced sugar alcohol mannitol by marine yeast Rhodosporidiobolus fluvialis Y2

Brown macroalgae is a promising marine biomass for the production of bioethanol and biodiesel fuels. Here we investigate the biochemical processes used by marine oleaginous yeast for assimilating the major carbohydrate found in brown macroalgae. Briefly, yeast Rhodosporidiobolus fluvialis strain Y2 was isolated from seawater and grown in minimal medium containing reduced sugar alcohol mannitol as the sole carbon source with a salinity comparable to seawater. Conditions limiting nitrogen were used to facilitate lipid synthesis. R. fluvialis Y2 yielded 55.1% (w/w) and 39.1% (w/w) of lipids, per dry cell weight, from mannitol in the absence and presence of salinity, respectively. Furthermore, mannitol, as a sugar source, led to an increase in the composition of polyunsaturated fatty acids, linoleic acid (C18:2) and linolenic acid (C18:3), compared to glucose. This suggests that oxidation of mannitol leads to the activation of NADH-dependent fatty acid desaturases in R. fluvialis Y2. Such fatty acid composition may contribute to the cold-flow properties of biodiesel fuels. Our results identified a salt-tolerant oleaginous yeast species with unique metabolic traits, demonstrating a key role as a decomposer in the global carbon cycle through marine ecosystems. This is the first study on mannitol-induced synthesis of lipids enriched with polyunsaturated fatty acids by marine yeast

Identification of Surface Antigens That Define Human Pluripotent Stem Cell-Derived PRRX1+Limb-Bud-like Mesenchymal Cells

Stem cell-based therapies and experimental methods rely on efficient induction of human pluripotent stem cells (hPSCs). During limb development, the lateral plate mesoderm (LPM) produces limb-bud mesenchymal (LBM) cells that differentiate into osteochondroprogenitor cells and form cartilage tissues in the appendicular skeleton. Previously, we generated PRRX1-tdTomato reporter hPSCs to establish the protocol for inducing the hPSC-derived PRRX1(+) LBM-like cells. However, surface antigens that assess the induction efficiency of hPSC-derived PRRX1(+) LBM-like cells from LPM have not been identified. Here, we used PRRX1-tdTomato reporter hPSCs and found that high pluripotent cell density suppressed the expression of PRRX1 mRNA and tdTomato after LBM-like induction. RNA sequencing and flow cytometry suggested that PRRX1-tdTomato(+) LBM-like cells are defined as CD44(high) CD140B(high) CD49f(-). Importantly, other hPSC lines, including four human induced pluripotent stem cell lines (414C2, 1383D2, HPS1042, HPS1043) and two human embryonic stem cell lines (SEES4, SEES7), showed the same results. Thus, an appropriate cell density of hPSCs before differentiation is a prerequisite for inducing the CD44(high) CD140B(high) CD49f(-) PRRX1(+) LBM-like cells

Revisiting a kNN-based Image Classification System with High-capacity Storage

In existing image classification systems that use deep neural networks, the knowledge needed for image classification is implicitly stored in model parameters. If users want to update this knowledge, then they need to fine-tune the model parameters. Moreover, users cannot verify the validity of inference results or evaluate the contribution of knowledge to the results. In this paper, we investigate a system that stores knowledge for image classification, such as image feature maps, labels, and original images, not in model parameters but in external high-capacity storage. Our system refers to the storage like a database when classifying input images. To increase knowledge, our system updates the database instead of fine-tuning model parameters, which avoids catastrophic forgetting in incremental learning scenarios. We revisit a kNN (k-Nearest Neighbor) classifier and employ it in our system. By analyzing the neighborhood samples referred by the kNN algorithm, we can interpret how knowledge learned in the past is used for inference results. Our system achieves 79.8% top-1 accuracy on the ImageNet dataset without fine-tuning model parameters after pretraining, and 90.8% accuracy on the Split CIFAR-100 dataset in the task incremental learning setting.Comment: 16 pages, 7 figures, 6 table

Pathological Role of Tonsillar B Cells in IgA Nephropathy

Although impaired immune regulation along the mucosa-bone marrow axis has been postulated to play an important role, the pathogenesis of IgA nephropathy (IgAN) is unknown; thus, no disease-specific therapy for this disease exists. The therapeutic efficacy of tonsillectomy or tonsillectomy in combination with steroid pulse therapy for IgAN has been discussed. Although randomized control trials for these therapies are ongoing in Japan, the scientific rationale for these therapies remains obscure. It is now widely accepted that abnormally glycosylated IgA1 and its related immune complex (IC) are probably key molecules for the pathogenesis, and are thus considered possible noninvasive biomarkers for this disease. Emerging evidence indicates that B cells in mucosal infections, particularly in tonsillitis, may produce the nephritogenic IgA. In this paper, we briefly summarize characteristics of the nephritogenic IgA/IgA IC, responsible B cells, and underlying mechanisms. This clinical and experimental information may provide important clues for a therapeutic rationale

Cellular DBP and E4BP4 proteins are critical for determining the period length of the circadian oscillator

AbstractThe phenotypes of mice carrying clock gene mutations have been critical to understanding the mammalian clock function. However, behavior does not necessarily reflect cell-autonomous clock phenotypes, because of the hierarchical dominance of the central clock. We performed cell-based siRNA knockdown and cDNA overexpression and monitored rhythm using bioluminescent reporters of clock genes. We found that knockdown of DBP, D-box positive regulator, in our model led to a short-period phenotype, whereas overexpressing of DBP produced a long-period rhythm when compared to controls. Furthermore, knockdown and overexpressing of E4BP4, D-box negative regulator, led to an opposite effect of DBP. Our experiments demonstrated that D-box regulators play a crucial role in determining the period length of Per1 and Per2 promoter-driven circadian rhythms in Rat-1 fibroblasts

Propulsive Performance and Heating Environment of Rotating Detonation Engine with Various Nozzles

Geometric throats are commonly applied to rocket combustors to increase pressure and specific impulse. This paper presents the results from thrust measurements of an ethylene/gas-oxygen rotating detonation engine with various throat geometries in a vacuum chamber to simulate varied backpressure conditions in a range of 1.1–104 kPa. For the throatless case, the detonation channel area was regarded to be equivalent the throat area, and three throat-contraction ratios were tested: 1, 2.5, and 8. Results revealed that combustor pressure was approximately proportional to equivalent throat mass flux for all test cases. Specific impulse was measured for a wide range of pressure ratios, defined as the ratio of the combustor pressure to the backpressure in the vacuum chamber. The rotating detonation engine could achieve almost the same level of optimum specific impulse for each backpressure, whether or not flow was squeezed by a geometric throat. In addition, heat-flux measurements using heat-resistant material are summarized. Temporally and spatially averaged heat flux in the engine were roughly proportional to channel mass flux. Heat-resistant material wall compatibility with two injector shapes of doublet and triplet injection is also discussed