Modelling of greenhouse gases and related species in the Arctic environment

GRENE北極気候変動研究事業研究成果報告会日時：2016年3月3日（木）10：00-17：30会場：国立国語研究所　2F講

A Segmentation Algorithm for Characterizing Rise and Fall Segments in Seasonal Cycles: An Application to XCO2 to Estimate Benchmarks and Assess Model Bias

There is more useful information in the time series of satellite-derived column-averaged carbon dioxide (XCO2) than is typically characterized. Often, the entire time series is treated at once without considering detailed features at shorter timescales, such as nonstationary changes in signal characteristics amplitude, period and phase. In many instances, signals are visually and analytically differentiable from other portions in a time series. Each rise (increasing) and fall (decreasing) segment in the seasonal cycle is visually discernable in a graph of the time series. The rise and fall segments largely result from seasonal differences in terrestrial ecosystem production, which means that the segment's signal characteristics can be used to establish observational benchmarks because the signal characteristics are driven by similar underlying processes. We developed an analytical segmentation algorithm to characterize the rise and fall segments in XCO2 seasonal cycles. We present the algorithm for general application of the segmentation analysis and emphasize here that the segmentation analysis is more generally applicable to cyclic time series. We demonstrate the utility of the algorithm with specific results related to the comparison between satellite- and model-derived XCO2 seasonal cycles (20092012) for large bioregions across the globe. We found a seasonal amplitude gradient of 0.740.77 ppm for every 10 of latitude in the satellite data, with similar gradients for rise and fall segments. This translates to a southnorth seasonal amplitude gradient of 8 ppm for XCO2, about half the gradient in seasonal amplitude based on surface site in situ CO2 data (19 ppm). The latitudinal gradients in the period of the satellite-derived seasonal cycles were of opposing sign and magnitude (9 d per 10 latitude for fall segments and 10 d per 10 latitude for rise segments) and suggest that a specific latitude (2 N) exists that defines an inversion point for the period asymmetry. Before (after) the point of asymmetry inversion, the periods of rise segments are lesser (greater) than the periods of fall segments; only a single model could reproduce this emergent pattern. The asymmetry in amplitude and the period between rise and fall segments introduces a novel pattern in seasonal cycle analyses, but, while we show these emergent patterns exist in the data, we are still breaking ground in applying the information for science applications. Maybe the most useful application is that the segmentation analysis allowed us to decompose the model biases into their correlated parts of biases in amplitude, period and phase independently for rise and fall segments. We offer an extended discussion on how such information about model biases and the emergent patterns in satellite-derived seasonal cycles can be used to guide future inquiry and model development

DETERMINING THE LOCATION AND SIZE OF THE BRAIN TUMOR WITH 3D SLICER

Cancer is the leading cause of death in both developed and developing countries. Brain and other central nervous system (CNS) tumors are among the most fatal cancers and account for substantial morbidity and mortality in the United States. Brain tumors account for 85% to 90% of all primary central nervous system (CNS) tumors. Worldwide, an estimated 308,102 people were diagnosed with a primary brain or spinal cord tumor in 2020. Detection of brain tumors on MR images is a time-consuming and laborious task performed by radiologists and doctors. Efforts have been made to develop automated systems to assist physicians in tumor detection and diagnosis and treatment planning. Our aim here is to make the tumor tissue easier to detect by labeling and thresholding the brain MR image

Solar Cell with PbS Quantum Dots Sensitized TiO 2 -Multiwalled Carbon Nanotubes Composite, Sulfide-titania gel and Tin Sulfide Coated C-fabric

Novel approaches to boost quantum dot solar cell (QDSC) efficiencies are in demand. Herein, three strategies are used: (i) a hydrothermally synthesized TiO2–multiwalled carbon nanotube (MWCNT) composite instead of conventional TiO2, (ii) a counter electrode (CE) that has not been applied to QDSCs until now, namely, tin sulfide (SnS) nanoparticles (NPs) coated over a conductive carbon (C)-fabric, and (iii) a quasi-solid-state gel electrolyte composed of S2−, an inert polymer and TiO2 nanoparticles as opposed to a polysulfide solution based hole transport layer. MWCNTs by virtue of their high electrical conductivity and suitably positioned Fermi level (below the conduction bands of TiO2 and PbS) allow fast photogenerated electron injection into the external circuit, and this is confirmed by a higher efficiency of 6.3% achieved for a TiO2–MWCNT/PbS/ZnS based (champion) cell, compared to the corresponding TiO2/PbS/ZnS based cell (4.45%). Nanoscale current map analysis of TiO2 and TiO2–MWCNTs reveals the presence of narrowly spaced highly conducting domains in the latter, which equips it with an average current carrying capability greater by a few orders of magnitude. Electron transport and recombination resistances are lower and higher respectively for the TiO2–MWCNT/PbS/ZnS cell relative to the TiO2/PbS/ZnS cell, thus leading to a high performance cell. The efficacy of SnS/C-fabric as a CE is confirmed from the higher efficiency achieved in cells with this CE compared to the C-fabric based cells. Lower charge transfer and diffusional resistances, slower photovoltage decay, high electrical conductance and lower redox potential impart high catalytic activity to the SnS/C-fabric assembly for sulfide reduction and thus endow the TiO2–MWCNT/PbS/ZnS cell with a high open circuit voltage (0.9 V) and a large short circuit current density (∼20 mA cm−2). This study attempts to unravel how simple strategies can amplify QDSC performances

Magnetotaxis as a Means for Nanofabrication

Magnetotactic bacteria (MTB), discovered in early 1970s contain single-domain crystals of magnetite (Fe3O4) called magnetosomes that tend to form a chain like structure from the proximal to the distal pole along the long axis of the cell. The ability of these bacteria to sense the magnetic field for displacement, also called magnetotaxis, arises from the magnetic dipole moment of this chain of magnetosomes. In aquatic habitats, these organisms sense the geomagnetic field and traverse the oxic-anoxic interface for optimal oxygen concentration along the field lines. Here we report an elegant use of MTB where magnetotaxis of Magnetospirillum magneticum (classified as AMB-1) could be utilized for controlled navigation over a semiconductor substrate for selective deposition. We examined 50mm long coils made out of 18AWG and 20AWG copper conductors having diameters of 5mm, 10mm and 20mm for magnetic field intensity and heat generation. Based on the COMSOL simulations and experimental data, it is recognized that a compound semiconductor manufacturing technology involving bacterial carriers and carbon-based materials such as graphene and carbon nanotubes would be a desirable choice in the future

MACHINE LEARNING IN NEURODEGENERATIVE DISORDERS

Neurodegenerative disorders were responsible for 272,644 deaths in 2016 along in the US. The government spent $655 billion in 2020 for the direct and indirect medical costs from these diseases. Although experiments have been going on to find the cure for the neurodegenerative diseases, there has not been an efficient way till date to completely cure the diseases. Recently, there have been studies in understanding the cause of the diseases so as to plan for the early detection and treatment of diseases such Alzheimer’s, Parkinson’s disease and motor neuron diseases. Since proteins are the functional backbone of our body, understanding their formation and their relation to disease growth is a subject of interest. This is a study to link the application of a few methods developed in recent times to predict the presence of neurodegenerative diseases

Residue Specific and Chirality Dependent Interactions between Carbon Nanotubes and Flagellin

Flagellum is a lash-like cellular appendage found in many single-celled living organisms. The flagellin protofilaments contain 11-helix dual turn structure in a single flagellum. Each flagellin consists of four sub-domains - two inner domains (D0, D1) and two outer domains (D2, D3). While inner domains predominantly consist of α-helices, the outer domains are primarily beta sheets with D3. In flagellum, the outermost sub-domain is the only one that is exposed to the native environment. This study focuses on the interactions of the residues of D3 of an R-type flagellin with 5nm long chiral (5,15) and arm-chair (12,12) single-walled carbon nanotubes (SWNT) using molecular dynamics simulation. It presents the interactive forces between the SWNT and the residues of D3 from the perspectives of size and chirality of the SWNT. It is found that the metallic (arm-chair) SWNT interacts the most with glycine and threonine residues through van der Waals and hydrophobic interactions, whereas the semiconducting (chiral) SWNT interacts largely with the area of protein devoid of glycine by van der Waals, hydrophobic interactions, and hydrogen bonding. This indicates a crucial role that glycine plays in distinguishing metallic from semiconducting SWNTs

Interactions Between Avidin and Graphene for Development of a Biosensing Platform

Fundamental understanding of interactions at the interface of biological molecules, such as proteins, and nanomaterials is crucial for developing various biocompatible hybrid materials and biosensing platforms. Biosensors comprising of graphene-based conductive nanomaterials offer the advantage of higher sensitivity and reliable diagnosis mainly due to their superior specific surface area and ballistic conductivity. Furthermore, conductive nanocomposite structures that immobilize proteins can synergize the properties of both transducers and molecular recognition elements improving the performance of the biosensing device. Here we report for the first time, using a combined molecular dynamics simulations and experimental approach, the interactions between avidin and graphene for the development of a sensing platform that can be used for the detection of biological macromolecules such as mismatch repair proteins through biotinylated DNA substrates. We find that the interactive forces between avidin and graphene are mainly hydrophobic, along with some van der Waals, electrostatic and hydrogen bonding interactions. Notably, the structure and function of the avidin molecule are largely preserved after its adsorption on the graphene surface. The MD results agree well with scanning electron microscopy (SEM) and electrochemical impedance spectroscopy (EIS) analysis of avidin immobilized on a graphenated polypyrrole (G-PPy) conductive nanocomposite confirming the adsorption of avidin on graphene nanoplatelets as observed from the Fourier-transform infrared spectroscopy (FTIR)

Fire retardancy and morphology of nylon 6-clay nanocomposite compositions

We investigated the effect of organically modified clay on the thermal and flammability behavior of nylon 6 nanocomposites. We also used zinc borate along with layered silicate with an aim of achieving synergistic effect in flame retardancy. It is found that addition of 10 wt% clay reduced the onset decomposition (5% wt loss) temperature of nylon 6 by 20°C, while addition of 5 wt% zinc borate and 5 wt% clay in combination reduced it by around 10°C. Differential thermogravimetric analysis indicated that the peak decomposition temperature was not affected by the addition of clay, but the rate of weight loss decreased with increasing clay concentration. The horizontal burning behavior of the nanocomposite films of approximately 0.5mm thickness changed with additive concentration. The nanocomposites with 2.5 wt% and 5 wt% clay burned for almost the same duration as neat nylon 6 but dripping was reduced. The 10 wt% clay nanocomposite sample burned without any dripping and the flame spread rate was reduced by 25-30%. The burn rate of 5 wt % zinc borate/5 wt% clay nanocomposite sample was about 20% higher than that of 10 wt% clay nanocomposite sample, which could be attributed to varying char morphology. Scanning electron microscopy images of the 10wt% clay nanocomposite char surface and cross- section revealed an integrated layer of clay platelets with increasing density gradient from the center to the surface, while the 5 wt% zinc borate/5 wt% clay nanocomposite char appeared foamy and porous. The 5 wt% zinc borate and 5 wt% clay sample developed into a very good intumescent system in cone calorimeter test, swelling about 10-13mm height prior to ignition forming a cellular char structure. This was as effective as the 10wt% clay nanocomposite sample in reducing the heat release and mass loss rate of nylon 6 by around 65%. Fourier transform infrared spectroscopy of the 10 wt% clay nanocomposite char showed the presence of amides, indicating possible residual polymer within the shielded char