Three-Dimensional Image Visualization under Photon-Starved Conditions Using N Observations and Statistical Estimation.

In this paper, we propose a method for the three-dimensional (3D) image visualization of objects under photon-starved conditions using multiple observations and statistical estimation. To visualize 3D objects under these conditions, photon counting integral imaging was used, which can extract photons from 3D objects using the Poisson random process. However, this process may not reconstruct 3D images under severely photon-starved conditions due to a lack of photons. Therefore, to solve this problem, in this paper, we propose N-observation photon-counting integral imaging with statistical estimation. Since photons are extracted randomly using the Poisson distribution, increasing the samples of photons can improve the accuracy of photon extraction. In addition, by using a statistical estimation method, such as maximum likelihood estimation, 3D images can be reconstructed. To prove our proposed method, we implemented the optical experiment and calculated its performance metrics, which included the peak signal-to-noise ratio (PSNR), structural similarity (SSIM), peak-to-correlation energy (PCE), and the peak sidelobe ratio (PSR).

Image Processing Techniques for Improving Quality of 3D Profile in Digital Holographic Microscopy Using Deep Learning Algorithm.

Digital Holographic Microscopy (DHM) is a 3D imaging technology widely applied in biology, microelectronics, and medical research. However, the noise generated during the 3D imaging process can affect the accuracy of medical diagnoses. To solve this problem, we proposed several frequency domain filtering algorithms. However, the filtering algorithms we proposed have a limitation in that they can only be applied when the distance between the direct current (DC) spectrum and sidebands are sufficiently far. To address these limitations, among the proposed filtering algorithms, the HiVA algorithm and deep learning algorithm, which effectively filter by distinguishing between noise and detailed information of the object, are used to enable filtering regardless of the distance between the DC spectrum and sidebands. In this paper, a combination of deep learning technology and traditional image processing methods is proposed, aiming to reduce noise in 3D profile imaging using the Improved Denoising Diffusion Probabilistic Models (IDDPM) algorithm.

Three-Dimensional (3D) Visualization under Extremely Low Light Conditions Using Kalman Filter.

In recent years, research on three-dimensional (3D) reconstruction under low illumination environment has been reported. Photon-counting integral imaging is one of the techniques for visualizing 3D images under low light conditions. However, conventional photon-counting integral imaging has the problem that results are random because Poisson random numbers are temporally and spatially independent. Therefore, in this paper, we apply a technique called Kalman filter to photon-counting integral imaging, which corrects data groups with errors, to improve the visual quality of results. The purpose of this paper is to reduce randomness and improve the accuracy of visualization for results by incorporating the Kalman filter into 3D reconstruction images under extremely low light conditions. Since the proposed method has better structure similarity (SSIM), peak signal-to-noise ratio (PSNR) and cross-correlation values than the conventional method, it can be said that the visualization of low illuminated images can be accurate. In addition, the proposed method is expected to accelerate the development of autonomous driving technology and security camera technology.

Proposal for Detection of the 0

The competition between the Kondo correlation and superconductivity in quantum-dot Josephson junctions (QDJJs) has been known to drive a quantum phase transition between 0 and π junctions. Theoretical studies so far have predicted that under strong Coulomb correlations the 0-π transition should go through intermediate states, 0^{'} and π^{'} phases. By combining a nonperturbative numerical method and the resistively shunted junction model, we investigated the magnetic-field-driven phase transition of the QDJJs in the Kondo regime and found that the low-field magnetotransport exhibits a unique feature which can be used to distinguish the intermediate phases. In particular, the magnetic-field driven π^{'}-π transition is found to lead to the enhancement of the supercurrent which is strongly related to the Kondo effect.

High-intensity Intermittent Training Enhances Spatial Memory and Hippocampal Neurogenesis Associated with BDNF Signaling in Rats.

High-intensity intermittent (or interval) training (HIIT) has started to gain popularity as a time-effective approach to providing beneficial effects to the brain and to peripheral organs. However, it still remains uncertain whether HIIT enhances hippocampal functions in terms of neurogenesis and spatial memory due to unconsidered HIIT protocol for rodents. Here, we established the HIIT regimen for rats with reference to human study. Adult male Wistar rats were assigned randomly to Control, moderate-intensity continuous training (MICT; 20 m/min, 30 min/day, 5 times/week), and HIIT (60 m/min, 10 30-s bouts of exercise, interspaced with 2.5 min of recovery, 5 times/week) groups. The ratios of exercise time and volume between MICT and HIIT were set as 6:1 and 2:1-4:1, respectively. After 4 weeks of training, all-out time in the incremental exercise test was prolonged for exercise training. In skeletal muscle, the plantaris citrate synthase activity significantly increased only in the HIIT group. Simultaneously, both HIIT and MICT led to enhanced spatial memory and adult hippocampal neurogenesis (AHN) as well as enhanced protein levels of hippocampal brain-derived neurotrophic factor (BDNF) signaling. Collectively, we suggest that HIIT could be a time-efficient exercise protocol that enhances hippocampal memory and neurogenesis in rats and is associated with hippocampal BDNF signaling.

3D photon counting integral imaging by using multi-level decomposition.

In this paper, we propose three-dimensional (3D) photon counting integral imaging by using multi-level decomposition such as discrete wavelet transform to improve the visual quality and measurement accuracy under photon-starved conditions. Conventional 3D integral imaging can visualize 3D objects and acquire their depth information. However, the amount of irradiated light on the object causes the degradation of visual quality for 3D images under photon-starved conditions. To visualize 3D objects, photon counting integral imaging has been utilized. It can detect photons from 3D scenes by using a computational photon counting model, which is modelled by the Poisson random process. However, photons occur not only from objects but also in areas where objects do not exist. Moreover, photon fluctuation may occur in the scene through shot noise. Since these noise photons are measurement errors, it may decrease the image quality and accuracy. In contrast, our proposed method uses 2D discrete wavelet transform, which can emphasize the object photons effectively. Finally, our proposed method can enhance the visual quality of 3D images and provide more accurate depth information under photon-starved conditions. To prove the feasibility of our proposed method, we implement the optical experiment and calculate various image quality metrics.

Noise Filtering Method of Digital Holographic Microscopy for Obtaining an Accurate Three-Dimensional Profile of Object Using a Windowed Sideband Array (WiSA).

In the image processing method of digital holographic microscopy (DHM), we can obtain a phase information of an object by windowing a sideband in Fourier domain and taking inverse Fourier transform. In this method, it is necessary to window a wide sideband to obtain detailed information on the object. However, since the information of the DC spectrum is widely distributed over the entire range from the center of Fourier domain, the window sideband includes not only phase information but also DC information. For this reason, research on acquiring only the phase information of an object without noise in digital holography is a challenging issue for many researchers. Therefore, in this paper, we propose the use of a windowed sideband array (WiSA) as an image processing method to obtain an accurate three-dimensional (3D) profile of an object without noise in DHM. The proposed method does not affect the neighbor pixels of the filtered pixel but removes noise while maintaining the detail of the object. Thus, a more accurate 3D profile can be obtained compared with the conventional filter. In this paper, we create an ideal comparison target i.e., microspheres for comparison, and verify the effect of the filter through additional experiments using red blood cells.

Vehicle Trajectory Prediction Using Hierarchical Graph Neural Network for Considering Interaction among Multimodal Maneuvers.

Predicting the trajectories of surrounding vehicles by considering their interactions is an essential ability for the functioning of autonomous vehicles. The subsequent movement of a vehicle is decided based on the multiple maneuvers of surrounding vehicles. Therefore, to predict the trajectories of surrounding vehicles, interactions among multiple maneuvers should be considered. Recent research has taken into account interactions that are difficult to express mathematically using data-driven deep learning methods. However, previous studies have only considered the interactions among observed trajectories due to subsequent maneuvers that are unobservable and numerous maneuver combinations. Thus, to consider the interaction among multiple maneuvers, this paper proposes a hierarchical graph neural network. The proposed hierarchical model approximately predicts the multiple maneuvers of vehicles and considers the interaction among the maneuvers by representing their relationships in a graph structure. The proposed method was evaluated using a publicly available dataset and a real driving dataset. Compared with previous methods, the results of the proposed method exhibited better prediction performance in highly interactive situations.

Exercise-induced changes of gene expression in the cerebellum of aged mice.

PURPOSE: Exercise has been prescribed to the elderly based on its effect on increasing muscle strength and protein synthesis that prevent sense of balance and/or cognitive functions. However, a few molecular mechanism researches has been conducted on how the vestibular organs, cerebellum, and hippocampus, which are responsible for the deterioration and balance of spatial learning memory due to aging, are affected by exercise. METHODS: The 9-week old and 84-week old C57Bl/6 were assigned randomly to Young-Control (YC), Young-Exercise (YE), Old-Control (OC) and Old-Exercise (OE) groups for 4 -week treadmill running. A Rotarod test was used to evaluate motor coordination function. Moreover, a high-throughput whole transcript expression RNA array approach was applied to the cerebellum of aged mice to explain the novel molecular mechanism of beneficial effect of exercise. RESULTS: As results, the motor coordination function was significantly improved in exercise-aged mice. The RNA sequencing analysis showed that the expression of cerebellar genes was significantly changed by aging rather than exercise. Especially, Cers1 was up-regulated in sedentary aged mice and down-regulated in exercise aged mice. Fumonisin B1, inhibition of Cers1, mitigates neuronal cell death induced by doxorubicin. CONCLUSION: These results provide unraveling specific transcripts and understanding of the exercise-related cerebellum transcriptome in aged mice. Well-designed exercise program might prevent the motor coordination defect in aged model, which development of the exercise protocol for elderly population based on these markers.

Effects of low temperature on longevity and lipid metabolism in the marine rotifer Brachionus koreanus.

Low-temperature exposure prolongs lifespans and changes lipid metabolism but the relationship between longevity and lipids is largely unknown. Here, we examine the relationship between longevity and lipid metabolism at low temperatures (20 °C and 15 °C) compared with a 25 °C control. Life parameters, fatty acid composition, and transcriptome changes were analyzed in the monogonont rotifer Brachionus koreanus. In vivo life-parameter data indicate that lifespan and fecundity exhibit opposite correlations at low temperatures. The amount of total fatty acids decreased significantly at low temperatures but areas stained with Nile red increased at 15 °C compared with the control. From RNA-seq-based transcriptional analysis, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway-enrichment analysis were conducted. GO analysis shows that telomeres were positively regulated at low temperatures. KEGG pathway-enrichment results indicate that gene expression involved in lipid metabolism was activated with increased glycerol and/or choline synthesis at low temperatures. We suggest that reduced reproductive rates are associated with a decrease of lecithin, which is involved in the conversion of glycerol to triacylglycerol in response to low temperatures by lowering the temperature of body fluid.

Exercise-induced AMPK activation is involved in delay of skeletal muscle senescence.

Accumulation of senescent cells leads to aging related phenotypes in various organs. Sarcopenia is a frequently observed aging-related disease, which is associated with the loss of muscle mass and functional disability. Physical activity represents the most critical treatment method for preventing decreased muscle size, mass and strength. However, the underlying mechanism as to how physical activity provides this beneficial effect on muscle function has not yet been fully understood. In particular, one unresolved question about aging is how the boost in catabolism induced by aerobic exercise affects skeletal muscle atrophy and other senescence phenotypes. Here we show that pre-activation of AMPK with the AMPK activator, AICAR can mitigate the diminished cellular viability of skeletal muscle cells induced by doxorubicin, which accelerates senescence through free radical production. Pre-incubation for 3 h with AICAR decreased doxorubicin-induced phosphorylation of AMPK in a differentiated skeletal muscle cell line. Accordingly, cellular viability of skeletal muscle cells was recovered in the cells pre-treated with AICAR then administered doxorubicin as compared to that of doxorubicin-only treatment. In accordance with the results of cellular experiments, we verified that 4 weeks of treadmill exercise decreased the senescence marker, p16 and p21 in 19-month-old mice compared to sedentary mice. In this study, we provide new evidence that prior activation of AMPK can reduce doxorubicin induced cell senescence phenotypes. The evidence in this paper suggest that aerobic exercise-activated catabolism in the skeletal muscle may prevent cellular senescence, partially through the cell cycle regulation.

Tributyltin Affects Retinoid X Receptor-Mediated Lipid Metabolism in the Marine Rotifer Brachionus koreanus.

To examine how tributyltin (TBT), a model obesogen, affects the lipid metabolism in the marine rotifer Brachionus koreanus, we carried out life-cycle studies and determined the in vitro and in silico interactions of retinoid X receptor (RXR) with TBT, the transcriptional levels of RXR and lipid metabolic genes, and the fatty acid content. The lethal concentration 10% (LC10) was determined to be 5.12 µg/L TBT, and negative effects on ecologically relevant end points (e.g., decreased lifespan and fecundity) were detected at 5 µg/L TBT. On the basis of these findings, subsequent experiments were conducted below 1 µg/L TBT, which did not show any negative effects on ecologically relevant end points in B. koreanus. Nile red staining analysis showed that after exposure to 1 µg/L TBT, B. koreanus stored neutral lipids and had significantly increased transcriptional levels of RXR and lipid metabolism-related genes compared to the control. However, the content of total fatty acids did not significantly change at any exposure level. In the single fatty acids profile, a significant increase in saturated fatty acids (SFAs) 14:0 and 20:0 was observed, but the contents of omega-3 and omega-6 fatty acids were significantly decreased. Also, a transactivation assay of TBT with RXR showed that TBT is an agonist of Bk-RXR with a similar fold-induction to the positive control. Taken together, these results demonstrate that TBT-modulated RXR signaling leads to increase in transcriptional levels of lipid metabolism-related genes and the synthesis of SFAs but decreases the content of polyunsaturated fatty acids (PUFAs). Our findings support a wider taxonomic scope of lipid perturbation due to xenobiotic exposure that occurs via NRs in aquatic animals.

Fast Online Coordinate Correction of a Multi-Sensor for Object Identification in Autonomous Vehicles.

Multi-sensor perception systems may have mismatched coordinates between each sensor even if the sensor coordinates are converted to a common coordinate. This discrepancy can be due to the sensor noise, deformation of the sensor mount, and other factors. These mismatched coordinates can seriously affect the estimation of a distant object's position and this error can result in problems with object identification. To overcome these problems, numerous coordinate correction methods have been studied to minimize coordinate mismatching, such as off-line sensor error modeling and real-time error estimation methods. The first approach, off-line sensor error modeling, cannot cope with the occurrence of a mismatched coordinate in real-time. The second approach, using real-time error estimation methods, has high computational complexity due to the singular value decomposition. Therefore, we present a fast online coordinate correction method based on a reduced sensor position error model with dominant parameters and estimate the parameters by using rapid math operations. By applying the fast coordinate correction method, we can reduce the computational effort within the necessary tolerance of the estimation error. By experiments, the computational effort was improved by up to 99.7% compared to the previous study, and regarding the object's radar the identification problems were improved by 94.8%. We conclude that the proposed method provides sufficient correcting performance for autonomous driving applications when the multi-sensor coordinates are mismatched.

Interrelationship of salinity shift with oxidative stress and lipid metabolism in the monogonont rotifer Brachionus koreanus.

Salinity is a critical key abiotic factor affecting biological processes such as lipid metabolism, yet the relationship between salinity and lipid metabolism has not been studied in the rotifer. To understand the effects of salinity on the monogonont rotifer B. koreanus, we examined high saline (25 and 35psu) conditions compared to the control (15psu). In vivo life cycle parameters (e.g. cumulative offspring and life span) were observed in response to 25 and 35psu compared to 15psu. In addition, to investigate whether high salinity induces oxidative stress, the level of reactive oxygen species (ROS) and glutathione S-transferase activity (GST) were measured in a salinity- (15, 25, and 35psu; 24h) and time-dependent manner (3, 6, 12, 24h; 35psu). Furthermore composition of fatty acid (FA) and lipid metabolism-related genes (e.g. elongases and desaturases) were examined in response to different salinity conditions. As a result, retardation in cumulative offspring and significant increase in life span were demonstrated in the 35psu treatment group compared to the control (15psu). Furthermore, ROS level and GST activity have both demonstrated a significant increase (P<0.05) in the 35psu treatment. In general, the quantity of FA and mRNA expression of the lipid metabolism-related genes was significantly decreased (P<0.05) in response to high saline condition with exceptions for both GST-S4 and S5 demonstrated a significant increase in their mRNA expression. This study demonstrates that high salinity induces oxidative stress, leading to a negative impact on lipid metabolism in the monogonont rotifer, B. koreanus.

Microplastic Size-Dependent Toxicity, Oxidative Stress Induction, and p-JNK and p-p38 Activation in the Monogonont Rotifer (Brachionus koreanus).

In this study, we evaluated accumulation and adverse effects of ingestion of microplastics in the monogonont rotifer (Brachionus koreanus). The dependence of microplastic toxicity on particle size was investigated by measuring several in vivo end points and studying the ingestion and egestion using 0.05-, 0.5-, and 6-µm nonfunctionalized polystyrene microbeads. To identify the defense mechanisms activated in response to microplastic exposure, the activities of several antioxidant-related enzymes and the phosphorylation status of mitogen-activated protein kinases (MAPKs) were determined. Exposure to polystyrene microbeads of all sizes led to significant size-dependent effects, including reduced growth rate, reduced fecundity, decreased lifespan and longer reproduction time. Rotifers exposed to 6-µm fluorescently labeled microbeads exhibited almost no fluorescence after 24 h, while rotifers exposed to 0.05- and 0.5-µm fluorescently labeled microbeads displayed fluorescence until 48 h, suggesting that 6-µm microbeads are more effectively egested from B. koreanus than 0.05- or 0.5-µm microbeads. This observation provides a potential explanation for our findings that microbead toxicity was size-dependent and smaller microbeads were more toxic. In vitro tests revealed that antioxidant-related enzymes and MAPK signaling pathways were significantly activated in response to microplastic exposure in a size-dependent manner.

Quantum resistor-capacitor circuit with Majorana fermion modes in a chiral topological superconductor.

We investigate the mesoscopic resistor-capacitor circuit consisting of a quantum dot coupled to spatially separated Majorana fermion modes in a chiral topological superconductor. We find substantially enhanced relaxation resistance due to the nature of Majorana fermions, which are their own antiparticles and are composed of particle and hole excitations in the same abundance. Further, if only a single Majorana mode is involved, the zero-frequency relaxation resistance is completely suppressed due to a destructive interference. As a result, the Majorana mode opens an exotic dissipative channel on a superconductor which is typically regarded as dissipationless due to its finite superconducting gap.

Exercise-induced expression of genes associated with aging in the hippocampus of rats.

Recent research has underscored the influence of aging and exercise on brain function. In this study, we aimed to explore alterations in the expression of novel molecular factors and gain insight into underlying molecular mechanisms in the hippocampus of rats engaged in voluntary wheel running. We assessed the expression of aging-related genes in the hippocampus using a high-throughput whole genome DNA microarray approach in rats engaged in voluntary running for four weeks. The results indicated that compared to the control group, wheel running significantly altered the expressions of aging-related genes in the hippocampus. Functional categorization, utilizing pathway-focused gene classifications and disease state-focused gene classifications, along with Ingenuity Pathway Analysis (IPA), revealed changes in expression pattern in major categories of cell death and survival, renal necrosis/cell death, and cardiovascular disease genes. These findings suggest that exercise may mitigate the risk of age-related cognitive decline by regulating of aging-related genes in the hippocampus. Further research is warranted to elucidate the mechanisms driving changes in gene expression and to determine the long-term effects of exercise on brain function.

Effects of bisphenol A on reproduction, oxidative stress, and lipid regulation in the marine rotifer Brachionus plicatilis.

This study reports the effects of bisphenol A (BPA) on the rotifer Brachionus plicatilis, focusing on growth performance, reproductive output, oxidative stress responses, and lipid metabolism genes. High BPA levels disrupted peak daily offspring production and led to oxidative stress and increased superoxide dismutase and catalase activity. The research identified distinctive monoacylglycerol O-acyltransferase (MGAT) and diacylglycerol O-acyltransferase (DGAT) genes in B. plicatilis, B. rotundiformis, and B. koreanus, enhancing understanding of lipid metabolism in these species. BPA exposure significantly altered MGAT and DGAT expression, and feeding status affected these regulatory patterns. When food was unavailable, BPA reduced DGAT2 and MGAT2a expression. However, under feeding conditions, DGAT2 and MGAT1 levels increased, indicating that nutritional status and BPA exposure interact to affect gene expression.

Multigenerational resilience of the marine rotifer Brachionus plicatilis to high temperature after additive exposure to high salinity and nanoplastics.

To study multigenerational resilience to high temperature (HT) conditions, we exposed Brachionus plicatilis marine rotifers to HT, high salinity (HS), and nanoplastics (NPs), and measured reproductive and life-cycle endpoints. After exposure to HT, rotifer lifespans were reduced, but daily production of offspring increased. However, both combined HT/HS and HT/HS/NP exposure led to additional decreases in longevity and reproductive ability; the antioxidant defense mechanisms of the rotifers were also notably upregulated as measured by reactive oxygen species levels. Fatty-acid profiles were reduced in all conditions. In multigenerational experiments, the negative effects of HT dissipated rapidly; however, the effects of HT/HS and HT/HS/NPs required four generations to disappear completely. The findings indicated that B. plicatilis were able to recover from these environmental stressors. This study demonstrated the resilience of aquatic organisms in response to changing environmental conditions and provides insights into the complex interactions of different abiotic stressors.

Interactions between lipid metabolism and the microbiome in aquatic organisms: A review.

Marine organisms' lipid metabolism contributes to marine ecosystems by producing a variety of lipid molecules. Historically, research focused on the lipid metabolism of the organisms themselves. Recent microbiome studies, however, have revealed that gut microbial communities influence the amount and type of lipids absorbed by organisms, thereby altering the organism's lipid metabolism. This has highlighted the growing importance of research on gut microbiota. This review highlights mechanisms by which gut microbiota facilitate lipid digestion and diversify the lipid pool in aquatic animals through the accelerated degradation of exogenous lipids and the transformation of lipid molecules. We also assess how environmental factors and pollutants, along with the innovative use of probiotics, interact with the gut microbiome to influence lipid metabolism within the host. We aim to elucidate the complex interactions between lipid metabolism and gut microbiota in aquatic animals by synthesizing current research and identifying knowledge gaps, providing a foundation for future explorations.