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Seismic surveys along subduction zones have identified anomalously high ratio of P‐ to S‐wave velocity (VP/VS) in the subducting oceanic crust that are possibly due to the presence of pore water. Such interpretations postulate that the pore structure is homogeneous at the scale of the seismic wavelength. Here we present the first statistical evidence of a heterogeneous pore structure in oceanic crust at scales larger than laboratory samples. The spatial correlation of measured bulk density profiles of the crustal section of the Samail ophiolite suggests that the pore structure is heterogeneous at scales smaller than ∼1 m. Wave‐induced fluid flow cannot follow the loading during the seismic wave propagation at this estimated heterogeneity, which implies that fluid‐filled microscopic pores and cracks have a limited impact on the observed high VP/VS anomalies in the subducting oceanic crust. Large‐scale cracks may therefore play an important role in shaping these anomalies. Plain Language Summary: Seismic studies along subduction zones have identified unusually high ratios of P‐ to S‐wave velocity (VP/VS) in the subducting oceanic crust, which indicates the presence of water‐filled cracks and pores. The close link between pore water and local seismic activity highlights the importance of quantitatively interpreting these seismic anomalies in terms of pore characteristics. Previous interpretations have assumed that the microscopic pore structure is quite homogeneous, even at macroscopic scales as large as the seismic wavelength. However, our analysis of a bulk density profile of the crustal section of the Samail ophiolite, Oman, which is a fossilized oceanic plate preserved on land, indicates that the pore structure is more heterogeneous than previously assumed. This means that the fluid flow within the unit volume that represents the macroscopic physical properties of the rock cannot follow the wave‐induced loading during seismic wave propagations. This results in a relatively small impact of water on the seismic velocity, as inferred from theoretical models that predict the effective elastic properties of rock containing fluid‐filled cracks. Therefore, microscopic cracks may not have a large impact on the high VP/VS values of subducting oceanic crust, whereas large‐scale cracks may play a more significant role. Key Points: The bulk density of the crustal section of the Samail ophiolite is more spatially heterogeneous than previously assumedThe effect of fluid‐saturated microcracks on low‐frequency seismic velocities is modeled as an unrelaxed condition for this heterogeneityThe high VP/VS anomaly in the subducting oceanic crust can be explained by both microcracks and large‐scale cracks [ABSTRACT FROM AUTHOR]

The long-debated question in analytical chemistry of which of the area ratio or the intensity ratio is the more precise has yielded no definitive analytical conclusion. To address this issue theoretically, we derived analytical solutions for the lower limits of estimation precision for spectral parameters, including the intensity ratio and area ratio, based on the Cramér-Rao lower bound (CRLB) framework for a Gaussian spectrum. The precisions of spectral parameter estimations from the analytical solutions were consistent with results obtained from Monte Carlo simulations. Our theoretical and simulation results revealed that the precision of estimating the area ratio surpassed that of the intensity ratio by a factor of 2 . Additionally, our experimental results aligned well with both theoretical predictions and simulation outcomes, further validating our approach. This increased precision of the area ratio is due to negative covariance between intensity and bandwidth, rather than the area containing more intensity information, as often misinterpreted. Consequently, and quite counter intuitively, prior bandwidth and intensity related information does not improve the area ratio precision: it worsens it. The analytical solution we derived represents the fundamental limits of spectral parameter measurement precision. Thus, it can be used as an alternative method for estimating the minimum error when experimental measurement uncertainty cannot be determined., (© 2024. The Author(s).)

The comprehensive production of detailed bathymetric maps is important for disaster prevention, resource exploration, safe navigation, marine salvage, and monitoring of marine organisms. However, owing to observation difficulties, the amount of data on the world's seabed topography is scarce. Therefore, it is essential to develop methods that effectively use the limited data. In this study, based on dictionary learning and sparse coding, we modified the super-resolution technique and applied it to seafloor topographical maps. Improving on the conventional method, before dictionary learning, we performed pre-processing to separate the teacher image into a low-frequency component that has a general structure and a high-frequency component that captures the detailed topographical features. We learn the topographical features by training the dictionary. As a result, the root-mean-square error (RMSE) was reduced by 30% compared with bicubic interpolation and accuracy was improved, especially in the rugged part of the terrain. The proposed method, which learns a dictionary to capture topographical features and reconstructs them using a dictionary, produces super-resolution with high interpretability.

Heterogeneous reactions are chemical reactions that occur at the interfaces of multiple phases, and often show a nonlinear dynamical behavior due to the effect of the time-variant surface area with complex reaction mechanisms. It is important to specify the kinetics of heterogeneous reactions in order to elucidate the microscopic elementary processes and predict the macroscopic future evolution of the system. In this study, we propose a data-driven method based on a sparse modeling algorithm and sequential Monte Carlo algorithm for simultaneously extracting substantial reaction terms and surface models from a number of candidates by using partial observation data. We introduce a sparse modeling approach with non-uniform sparsity levels in order to accurately estimate rate constants, and the sequential Monte Carlo algorithm is employed to estimate time courses of multi-dimensional hidden variables. The results estimated using the proposed method show that the rate constants of dissolution and precipitation reactions that are typical examples of surface heterogeneous reactions, necessary surface models, and reaction terms underlying observable data were successfully estimated from only observable temporal changes in the concentration of the dissolved intermediate products.

Background/aim: The aim of this study was to explore whether the treatment effect or immune response to a cancer vaccine can be predicted by the percentage of CD4 + CD25 + Foxp3 + regulatory T cells (Tregs) in peripheral blood mononuclear cells (PBMCs) after vaccination., Patients and Methods: Sixteen patients (9 men, 7 women; median age 61.5 years) enrolled in the CHP-MAGE-A4 cancer vaccine clinical trial who had a fixed dose (300 μg of CHP-MAGE-A4 cancer vaccine and 0.5 Klinische Einheit (KE) of OK432 and received at least four vaccinations were investigated. Safety, immune response, and clinical effects were assessed before and after the cancer vaccination., Results: Treg ratios that remained low both before and after vaccination were associated with a good prognosis, and a low Treg/CD4 lymphocyte ratio 7-weeks after the initial vaccination was correlated with a better prognosis., Conclusion: The Treg ratio following vaccination appears to have some utility for predicting patient prognosis., (Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.)

In this study, we applied sparse multiple linear regression (SMLR) analysis to clarify the relationships between soil properties and adsorption characteristics for a range of soils across Japan and identify easily-obtained physical and chemical soil properties that could be used to predict K and n values of cadmium, lead and fluorine. A model was first constructed that can easily predict the K and n values from nine soil parameters (pH, cation exchange capacity, specific surface area, total carbon, soil organic matter from loss on ignition and water holding capacity, the ratio of sand, silt and clay). The K and n values of cadmium, lead and fluorine of 17 soil samples were used to verify the SMLR models by the root mean square error values obtained from 512 combinations of soil parameters. The SMLR analysis indicated that fluorine adsorption to soil may be associated with organic matter, whereas cadmium or lead adsorption to soil is more likely to be influenced by soil pH, IL. We found that an accurate K value can be predicted from more than three soil parameters for most soils. Approximately 65% of the predicted values were between 33 and 300% of their measured values for the K value; 76% of the predicted values were within ±30% of their measured values for the n value. Our findings suggest that adsorption properties of lead, cadmium and fluorine to soil can be predicted from the soil physical and chemical properties using the presented models., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

The down-dip limit of the seismogenic zone and up-dip and down-dip limits of the deep low-frequency tremors in southwest Japan are clearly imaged by the hypocentre distribution. Previous studies using smooth constraints in inversion analyses estimated that long-term slow slip events (L-SSEs) beneath the Bungo Channel are distributed smoothly from the down-dip part of the seismogenic zone to the up-dip part of the tremors. Here, we use fused regularisation, a type of sparse modelling suitable for detecting discontinuous changes in the model parameters to estimate the slip distribution of L-SSEs. The largest slip abruptly becomes zero at the down-dip limit of the seismogenic zone, is immediately reduced to half at the up-dip limit of the tremors, and becomes zero near its down-dip limit. Such correspondences imply that some thresholds exist in the generation processes for both tremors and SSEs. Hence, geodetic data inversion with sparse modelling can detect such high resolution in the slip distribution.

It is essential to extract nonlinear dynamics from time-series data as an inverse problem in natural sciences. We propose a Bayesian statistical framework for extracting nonlinear dynamics of surface heterogeneous reactions from sparse and noisy observable data. Surface heterogeneous reactions are chemical reactions with conjugation of multiple phases, and they have the intrinsic nonlinearity of their dynamics caused by the effect of surface-area between different phases. We adapt a belief propagation method and an expectation-maximization (EM) algorithm to partial observation problem, in order to simultaneously estimate the time course of hidden variables and the kinetic parameters underlying dynamics. The proposed belief propagation method is performed by using sequential Monte Carlo algorithm in order to estimate nonlinear dynamical system. Using our proposed method, we show that the rate constants of dissolution and precipitation reactions, which are typical examples of surface heterogeneous reactions, as well as the temporal changes of solid reactants and products, were successfully estimated only from the observable temporal changes in the concentration of the dissolved intermediate product.

Tsunami deposits accumulated on the Tohoku coastal area in Japan due to the impact of the Tohoku-oki earthquake. In the study reported in this paper, we applied principal component analysis (PCA) and cluster analysis (CA) to determine the concentrations of heavy metals in tsunami deposits that had been diluted with water or digested using 1 M HCl. The results suggest that the environmental risk is relatively low, evidenced by the following geometric mean concentrations: Pb, 16 mg kg(-1) and 0.003 ml L(-1); As, 1.8 mg kg(-1) and 0.004 ml L(-1); and Cd, 0.17 mg kg(-1) and 0.0001 ml L(-1). CA was performed after outliers were excluded using PCA. The analysis grouped the concentrations of heavy metals for leaching in water and acid. For the acid case, the first cluster contained Ni, Fe, Cd, Cu, Al, Cr, Zn, and Mn; while the second contained Pb, Sb, As, and Mo. For water, the first cluster contained Ni, Fe, Al, and Cr; and the second cluster contained Mo, Sb, As, Cu, Zn, Pb, and Mn. Statistical analysis revealed that the typical toxic elements, As, Pb, and Cd have steady correlations for acid leaching but are relatively sparse for water leaching. Pb and As from the tsunami deposits seemed to reveal a kind of redox elution mechanism using 1 M HCl., (Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.)

It has been suggested that Saturn's moon Enceladus possesses a subsurface ocean. The recent discovery of silica nanoparticles derived from Enceladus shows the presence of ongoing hydrothermal reactions in the interior. Here, we report results from detailed laboratory experiments to constrain the reaction conditions. To sustain the formation of silica nanoparticles, the composition of Enceladus' core needs to be similar to that of carbonaceous chondrites. We show that the presence of hydrothermal reactions would be consistent with NH3- and CO2-rich plume compositions. We suggest that high reaction temperatures (>50 °C) are required to form silica nanoparticles whether Enceladus' ocean is chemically open or closed to the icy crust. Such high temperatures imply either that Enceladus formed shortly after the formation of the solar system or that the current activity was triggered by a recent heating event. Under the required conditions, hydrogen production would proceed efficiently, which could provide chemical energy for chemoautotrophic life.

Metastable minerals commonly form during reactions between water and rock. The nucleation mechanism of polymorphic phases from solution are explored here using a two-dimensional Potts model. The model system is composed of a solvent and three polymorphic solid phases. The local state and position of the solid phase are updated by Metropolis dynamics. Below the critical temperature, a large cluster of the least stable solid phase initially forms in the solution before transitioning into more-stable phases following the Ostwald step rule. The free-energy landscape as a function of the modal abundance of each solid phase clearly reveals that before cluster formation, the least stable phase has an energetic advantage because of its low interfacial energy with the solution, and after cluster formation, phase transformation occurs along the valley of the free-energy landscape, which contains several minima for the regions of three phases. Our results indicate that the solid-solid and solid-liquid interfacial energy contribute to the formation of the complex free-energy landscape and nucleation pathways following the Ostwald step rule.

Background: It has recently been shown that certain chemotherapeutic agents can improve host immune responses. The present study aimed to demonstrate the mechanism by which chemotherapeutic agents modify the tumor microenvironment and induce tumor-specific immune responses., Methods: Three mouse cancer cell lines [CT26 mouse colon cancer cells, B16 melanoma cells and Lewis lung carcinoma (LLC)], 5 human carcinoma cell lines (human esophageal squamous cell carcinoma cell lines TE8 and HEC46 and the human pancreatic carcinoma cell lines PK-9, AsPC-1 and SUIT-2) and 5 chemotherapeutic agents [mitoxantrone (MIT), mitomycin C(MMC), 5-fluorouracil (5FU), camptothecin (CPT-11) and cisplatin (CDDP)] that are frequently used in a clinical setting for cancer treatment were utilized to investigate the surface expression level of calreticulin and HLA class I after exposure to chemotherapeutic agents., Results: Increased calreticulin (CRT) expression on the surface of mouse cell lines and, moreover, increased surface expression levels of both CRT and HLA class I in all human cell lines were observed in cells treated by the chemotherapeutic agents as compared with non-treated cells. The surface expression level of CRT was significantly correlated with the HLA class I expression level in all human cell lines., Conclusions: In conclusion, chemotherapeutic drugs can improve the immunogenicity of cancer cells in a cell-specific manner through the mechanism of translocation of CRT.

Detection of sodium-salt-rich ice grains emitted from the plume of the Saturnian moon Enceladus suggests that the grains formed as frozen droplets from a liquid water reservoir that is, or has been, in contact with rock. Gravitational field measurements suggest a regional south polar subsurface ocean of about 10 kilometres thickness located beneath an ice crust 30 to 40 kilometres thick. These findings imply rock-water interactions in regions surrounding the core of Enceladus. The resulting chemical 'footprints' are expected to be preserved in the liquid and subsequently transported upwards to the near-surface plume sources, where they eventually would be ejected and could be measured by a spacecraft. Here we report an analysis of silicon-rich, nanometre-sized dust particles (so-called stream particles) that stand out from the water-ice-dominated objects characteristic of Saturn. We interpret these grains as nanometre-sized SiO2 (silica) particles, initially embedded in icy grains emitted from Enceladus' subsurface waters and released by sputter erosion in Saturn's E ring. The composition and the limited size range (2 to 8 nanometres in radius) of stream particles indicate ongoing high-temperature (>90 °C) hydrothermal reactions associated with global-scale geothermal activity that quickly transports hydrothermal products from the ocean floor at a depth of at least 40 kilometres up to the plume of Enceladus.

Geochemical discrimination has recently been recognised as a potentially useful proxy for identifying tsunami deposits in addition to classical proxies such as sedimentological and micropalaeontological evidence. However, difficulties remain because it is unclear which elements best discriminate between tsunami and non-tsunami deposits. Herein, we propose a mathematical methodology for the geochemical discrimination of tsunami deposits using machine-learning techniques. The proposed method can determine the appropriate combinations of elements and the precise discrimination plane that best discerns tsunami deposits from non-tsunami deposits in high-dimensional compositional space through the use of data sets of bulk composition that have been categorised as tsunami or non-tsunami sediments. We applied this method to the 2011 Tohoku tsunami and to background marine sedimentary rocks. After an exhaustive search of all 262,144 (= 2(18)) combinations of the 18 analysed elements, we observed several tens of combinations with discrimination rates higher than 99.0%. The analytical results show that elements such as Ca and several heavy-metal elements are important for discriminating tsunami deposits from marine sedimentary rocks. These elements are considered to reflect the formation mechanism and origin of the tsunami deposits. The proposed methodology has the potential to aid in the identification of past tsunamis by using other tsunami proxies.

We apply the Markov-random-field model to linear seismic tomography and propose a method to estimate the hyperparameters for the smoothness and the magnitude of the noise. Optimal hyperparameters can be determined analytically by minimizing the free energy function, which is defined by marginalizing the evaluation function. In synthetic inversion tests under various settings, the assumed velocity structures are successfully reconstructed, which shows the effectiveness and robustness of the proposed method. The proposed mathematical framework can be applied to inversion problems in various fields in the natural sciences.