On the use of lateral wave for the interlayer debonding detecting in an asphalt airport pavement using a multistatic GPR system

In this paper, we focus on the detection of the interlayer debonding of the asphalt airport pavement by the Ground-penetrating Radar (GPR) system. Since the interlayer debonding usually occurs in the shallow region of the asphalt airport pavement (several centimeters), it is difficult to interpret the anomalies or the defects from the GPR signals composed of many waves under the boundary conditions. Moreover, the wavelength of the ordinary GPR system is over several centimeters. Therefore, the spatial resolution of the system is not accurate enough to consider the millimeter thickness of the debonding layer. To overcome these problems, we propose a new method based on evaluating the lateral wave behavior of common midpoint (CMP) gathers collected by a multiple static GPR system. The multi-static GPR system is a stepped frequency continuous wave (SFCW) radar system, which consists of 8 transmitting and 8 receiving bowtie antennas. The system operates in the frequency range from 50 MHz to 1.5 GHz. After the validation of the simulation, the results of the interlayer debonding detection were evaluated by a field experiment obtained at Tokyo International Airport. The proposed method can detect the debonding layers which are less than 1mm. Also, it is shown that our proposed method has a high consistency with the conventional acoustic finding method in the field measurement. It provides an innovative and effective method for the interlayer debonding detection of a partially damaged airport asphalt pavement, which is difficult to be observed by the ordinary GPR signals

Metallicities of Planet Hosting Stars: A Sample of Giants and Subgiants

This work presents a homogeneous derivation of atmospheric parameters and iron abundances for a sample of giant and subgiant stars which host giant planets, as well as a control sample of subgiant stars not known to host giant planets. The analysis is done using the same technique as for our previous analysis of a large sample of planet-hosting and control sample dwarf stars. A comparison between the distributions of [Fe/H] in planet-hosting main-sequence stars, subgiants, and giants within these samples finds that the main-sequence stars and subgiants have the same mean metallicity of \simeq +0.11 dex, while the giant sample is typically more metal poor, having an average metallicity of = -0.06 dex. The fact that the subgiants have the same average metallicities as the dwarfs indicates that significant accretion of solid metal-rich material onto the planet-hosting stars has not taken place, as such material would be diluted in the evolution from dwarf to subgiant. The lower metallicity found for the planet-hosting giant stars in comparison with the planet-hosting dwarfs and subgiants is interpreted as being related to the underlying stellar mass, with giants having larger masses and thus, on average larger-mass protoplanetary disks. In core accretion models of planet formation, larger disk masses can contain the critical amount of metals necessary to form giant planets even at lower metallicities.Comment: 38 pages, 7 figures, 4 tables, accepted for publication in Ap

TLS-bridged co-prediction of tree-level multifarious stem structure variables from worldview-2 panchromatic imagery: a case study of the boreal forest

In forest ecosystem studies, tree stem structure variables (SSVs) proved to be an essential kind of parameters, and now simultaneously deriving SSVs of as many kinds as possible at large scales is preferred for enhancing the frontier studies on marcoecosystem ecology and global carbon cycle. For this newly emerging task, satellite imagery such as WorldView-2 panchromatic images (WPIs) is used as a potential solution for co-prediction of tree-level multifarious SSVs, with static terrestrial laser scanning (TLS) assumed as a ‘bridge’. The specific operation is to pursue the allometric relationships between TLS-derived SSVs and WPI-derived feature parameters, and regression analyses with one or multiple explanatory variables are applied to deduce the prediction models (termed as Model1s and Model2s). In the case of Picea abies, Pinus sylvestris, Populus tremul and Quercus robur in a boreal forest, tests showed that Model1s and Model2s for different tree species can be derived (e.g. the maximum R2 = 0.574 for Q. robur). Overall, this study basically validated the algorithm proposed for co-prediction of multifarious SSVs, and the contribution is equivalent to developing a viable solution for SSV-estimation upscaling, which is useful for large-scale investigations of forest understory, macroecosystem ecology, global vegetation dynamics and global carbon cycle.This work was financially supported in part by the National Natural Science Foundation of China [grant numbers 41471281 and 31670718] and in part by the SRF for ROCS, SEM, China. (41471281 - National Natural Science Foundation of China; 31670718 - National Natural Science Foundation of China; SRF for ROCS, SEM, China)http://www-tandfonline-com.ezproxy.bu.edu/doi/abs/10.1080/17538947.2016.1247473?journalCode=tjde20Published versio

A stochastic approach to multi-gene expression dynamics

In the last years, tens of thousands gene expression profiles for cells of several organisms have been monitored. Gene expression is a complex transcriptional process where mRNA molecules are translated into proteins, which control most of the cell functions. In this process, the correlation among genes is crucial to determine the specific functions of genes. Here, we propose a novel multi-dimensional stochastic approach to deal with the gene correlation phenomena. Interestingly, our stochastic framework suggests that the study of the gene correlation requires only one theoretical assumption -Markov property- and the experimental transition probability, which characterizes the gene correlation system. Finally, a gene expression experiment is proposed for future applications of the model.Comment: 17 pages, 2 figures, Latex, v2 includes minor modification

SAM-dependent enzyme-catalysed pericyclic reactions in natural product biosynthesis.

Pericyclic reactions-which proceed in a concerted fashion through a cyclic transition state-are among the most powerful synthetic transformations used to make multiple regioselective and stereoselective carbon-carbon bonds. They have been widely applied to the synthesis of biologically active complex natural products containing contiguous stereogenic carbon centres. Despite the prominence of pericyclic reactions in total synthesis, only three naturally existing enzymatic examples (the intramolecular Diels-Alder reaction, and the Cope and the Claisen rearrangements) have been characterized. Here we report a versatile S-adenosyl-l-methionine (SAM)-dependent enzyme, LepI, that can catalyse stereoselective dehydration followed by three pericyclic transformations: intramolecular Diels-Alder and hetero-Diels-Alder reactions via a single ambimodal transition state, and a retro-Claisen rearrangement. Together, these transformations lead to the formation of the dihydropyran core of the fungal natural product, leporin. Combined in vitro enzymatic characterization and computational studies provide insight into how LepI regulates these bifurcating biosynthetic reaction pathways by using SAM as the cofactor. These pathways converge to the desired biosynthetic end product via the (SAM-dependent) retro-Claisen rearrangement catalysed by LepI. We expect that more pericyclic biosynthetic enzymatic transformations remain to be discovered in naturally occurring enzyme 'toolboxes'. The new role of the versatile cofactor SAM is likely to be found in other examples of enzyme catalysis

Estimation of Confidence in the Dialogue based on Eye Gaze and Head Movement Information

In human-robot interaction, human mental states in dialogue have attracted attention to human-friendly robots that support educational use. Although estimating mental states using speech and visual information has been conducted, it is still challenging to estimate mental states more precisely in the educational scene. In this paper, we proposed a method to estimate human mental state based on participants’ eye gaze and head movement information. Estimated participants’ confidence levels in their answers to the miscellaneous knowledge question as a human mental state. The participants’ non-verbal information, such as eye gaze and head movements during dialog with a robot, were collected in our experiment using an eye-tracking device. Then we collect participants’ confidence levels and analyze the relationship between human mental state and non-verbal information. Furthermore, we also applied a machine learning technique to estimate participants’ confidence levels from extracted features of gaze and head movement information. As a result, the performance of a machine learning technique using gaze and head movements information achieved over 80 % accuracy in estimating confidence levels. Our research provides insight into developing a human-friendly robot considering human mental states in the dialogue

Physiological Impairments on Respiratory Oscillometry and Future Exacerbations in Chronic Obstructive Pulmonary Disease Patients without a History of Frequent Exacerbations

Respiratory oscillometry allows measuring respiratory resistance and reactance during tidal breathing and may predict exacerbations in patients with chronic obstructive pulmonary disease (COPD). While the Global Initiative for Chronic Obstructive Lung Disease (GOLD) advocates the ABCD classification tool to determine therapeutic approach based on symptom and exacerbation history, we hypothesized that in addition to spirometry, respiratory oscillometry complemented the ABCD tool to identify patients with a high risk of exacerbations. This study enrolled male outpatients with stable COPD who were prospectively followed-up over 5 years after completing mMRC scale and COPD assessment test (CAT) questionnaires, post-bronchodilator spirometry and respiratory oscillometry to measure resistance, reactance, and resonant frequency (Fres), and emphysema quantitation on computed tomography. Total 134 patients were classified into the GOLD A, B, C, and D groups (n = 48, 71, 5, and 9) based on symptoms on mMRC and CAT and a history of exacerbations in the previous year. In univariable analysis, higher Fres was associated with an increased risk of exacerbation more strongly than other respiratory oscillometry indices. Fres was closely associated with forced expiratory volume in 1 sec (FEV1). In multivariable Cox-proportional hazard models of the GOLD A and B groups, either lower FEV1 group or higher Fres group was associated with a shorter time to the first exacerbation independent of the GOLD group (A vs B) and emphysema severity. Adding respiratory oscillometry to the ABCD tool may be useful for risk estimation of future exacerbations in COPD patients without frequent exacerbation history

How to Weigh a Star Using a Moon

We show that for a transiting exoplanet accompanied by a moon which also transits, the absolute masses and radii of the star, planet and moon are determinable. For a planet-star system, it is well known that the density of the star is calculable from the lightcurve by manipulation of Kepler's Third Law. In an analogous way, the planetary density is calculable for a planet-moon system which transits a star, and thus the ratio-of-densities is known. By combining this ratio with the observed ratio-of-radii and the radial velocity measurements of the system, we show that the absolute dimensions of the star and planet are determinable. This means such systems could be used as calibrators of stellar evolution. The detection of dynamical effects, such as transit timing variations, allows the absolute mass of the moon to be determined as well, which may be combined with the radius to infer the satellite's composition.Comment: 5 pages; Accepted in MNRA