Geophysical Monitoring of CO2 Injection at Citronelle Field, Alabama

Carbon dioxide (CO2) injection at the Citronelle oil field in Alabama has been deployed to determine the feasibility of carbon storage and enhanced oil recovery (EOR) in the depleted oil field. Citronelle is a small size city right above the oil field, hence, to detect geohazard risks, geophysical testing method using wireless sensor, and passive seismic technique is used: the non-intrusive measurements were made at well sites along two linear arrays. The outcomes of the geophysical monitoring at the Citronelle oil field are shear-wave velocity profiles that are correlated to the static stress distribution at different injection stages. Injection history interpretation using the stress wave monitoring indicates that CO2 injection resulted in the stressing of the strata

Innovative concrete sensing technologies for nuclear power plants

Postupak nerazornog ispitivanja primjenjuje se za istraživanja tijekom izvođenja i uporabe betonskih konstrukcija koje se koriste za potrebe nuklearne industrije. Beton u nuklearnim elektranama često se odlikuje posebnim svojstvima koja ga čine osjetljivim na propadanje te koja onemogućuju analizu i kontrolu pomoću tradicionalnih nerazornih postupaka. Moderne tehnologije analize unutar betona omogućuju dubinsko istraživanje nuklearnih armiranobetonskih konstrukcija. U radu se analiziraju perspektivne dubinske i površinske analitičke metode te se kritički ocjenjuje primjena senzora u analizi betonskih konstrukcija koje se koriste u nuklearnoj industriji.Nondestructive evaluation has been used to investigate construction and use of concrete structures for the nuclear power industry. Nuclear concrete often has unique structural characteristics which increase proclivity towards degradation and inhibit analysis and inspection using traditional nondestructive techniques. Modern embedded sensing technologies can provide opportunities for the in-depth evaluation of nuclear reinforced-concrete structures. This paper offers an assessment of emerging embedded and surficial sensor techniques, and critically evaluates sensor applicability in the analysis of concrete structures used in the nuclear power industry

Battery Train Fire Risk on a Steel Warehouse Structure

Lithium ion battery fire hazard has been well-documented in a variety of applications. Recently, battery train technology has been introduced as a clean energy concept for railway. In the case of heavy locomotives such as trains, the massive collection of battery stacks required to meet energy demands may pose a significant hazard. The objective of this paper is to review the risk evaluation processes for train fires and investigate the propagation of lithium ion battery fire to a neighboring steel warehouse structure at a rail repair shop through a case study. The methodology of the analyses conducted include a Monte Carlo-based dynamic modeling of fire propagation potentials, an expert-based fire impact analysis, and a finite element (FE) nonlinear fire analysis on the structural frame. The case study is presented as a demonstration of a holistic fire risk analysis for the lithium ion battery fire and results indicate that significant battery fire mitigations strategies should be considered

An Experimental Study for the Effects of Noise on Hyperspectral Imagery Classification

Hyperspectral image (HSI) classification is a very important topic in remote sensing. There are many published methods for HSI classification in the literature. Nevertheless, it is not clear which method is the most robust to noise in HSI data cubes. In this paper, we conduct a systematic study to examine the effects of noise in HSI data cubes on classification methods. We compare ten existing methods for HSI classification when Gaussian white noise (GWN) and shot noise are present in the HSI data cubes. We have figured out which method is the most robust to GWN and shot noise respectively by experimenting on three widely used HSI data cubes. We have also measured the CPU computational time of every method compared in this paper for HSI classification

Model-Independent Determination of H0H_0 and ΩK,0\Omega_{K,0} using Time-Delay Galaxy Lenses and Gamma-Ray Bursts

Combining the `time-delay distance' ($D_{\Delta t}$) measurements from galaxy lenses and other distance indicators provides model-independent determinations of the Hubble constant ($H_0$) and spatial curvature ($\Omega_{K,0}$), only based on the validity of the Friedmann-Lema\^itre-Robertson-Walker (FLRW) metric and geometrical optics. To take the full merit of combining $D_{\Delta t}$ measurements in constraining $H_0$, we use gamma-ray burst (GRB) distances to extend the redshift coverage of lensing systems much higher than that of Type Ia Supernovae (SNe Ia) and even higher than quasars, whilst the general cosmography with a curvature component is implemented for the GRB distance parametrizations. Combining Lensing+GRB yields $H_0=71.5^{+4.4}_{-3.0}$~km s$^{-1}$Mpc$^{-1}$ and $\Omega_{K,0} = -0.07^{+0.13}_{-0.06}$ (1$\sigma$). A flat-universe prior gives slightly an improved $H_0 = 70.9^{+4.2}_{-2.9}$~km s$^{-1}$Mpc$^{-1}$. When combining Lensing+GRB+SN Ia, the error bar $\Delta H_0$ falls by 25\%, whereas $\Omega_{K,0}$ is not improved due to the degeneracy between SN Ia absolute magnitude, $M_B$, and $H_0$ along with the mismatch between the SN Ia and GRB Hubble diagrams at $z\gtrsim 1.4$. Future increment of GRB observations can help to moderately eliminate the $M_B-H_0$ degeneracy in SN Ia distances and ameliorate the restrictions on cosmographic parameters along with $\Omega_{K,0}$ when combining Lensing+SN Ia+GRB. We conclude that there is no evidence of significant deviation from a (an) flat (accelerating) universe and $H_0$ is currently determined at 3\% precision. The measurements show great potential to arbitrate the $H_0$ tension between the local distance ladder and cosmic microwave background measurements and provide a relevant consistency test of the FLRW metric.Comment: Accepted for publication in MNRA

MEMO: Dataset and Methods for Robust Multimodal Retinal Image Registration with Large or Small Vessel Density Differences

The measurement of retinal blood flow (RBF) in capillaries can provide a powerful biomarker for the early diagnosis and treatment of ocular diseases. However, no single modality can determine capillary flowrates with high precision. Combining erythrocyte-mediated angiography (EMA) with optical coherence tomography angiography (OCTA) has the potential to achieve this goal, as EMA can measure the absolute 2D RBF of retinal microvasculature and OCTA can provide the 3D structural images of capillaries. However, multimodal retinal image registration between these two modalities remains largely unexplored. To fill this gap, we establish MEMO, the first public multimodal EMA and OCTA retinal image dataset. A unique challenge in multimodal retinal image registration between these modalities is the relatively large difference in vessel density (VD). To address this challenge, we propose a segmentation-based deep-learning framework (VDD-Reg) and a new evaluation metric (MSD), which provide robust results despite differences in vessel density. VDD-Reg consists of a vessel segmentation module and a registration module. To train the vessel segmentation module, we further designed a two-stage semi-supervised learning framework (LVD-Seg) combining supervised and unsupervised losses. We demonstrate that VDD-Reg outperforms baseline methods quantitatively and qualitatively for cases of both small VD differences (using the CF-FA dataset) and large VD differences (using our MEMO dataset). Moreover, VDD-Reg requires as few as three annotated vessel segmentation masks to maintain its accuracy, demonstrating its feasibility.Comment: Submitted to IEEE JBH

Effects of different fertilization conditions and different geographical locations on the diversity and composition of the rhizosphere microbiota of Qingke (Hordeum vulgare L.) plants in different growth stages

IntroductionThe excessive use of chemical fertilizer causes increasing environmental and food security crisis. Organic fertilizer improves physical and biological activities of soil. Rhizosphere microbiota, which consist of highly diverse microorganisms, play an important role in soil quality. However, there is limited information about the effects of different fertilization conditions on the growth of Qingke plants and composition of the rhizosphere microbiota of the plants.MethodsIn this study, we characterized the rhizosphere microbiota of Qingke plants grown in three main Qingke-producing areas (Tibet, Qinghai, and Gansu). In each of the three areas, seven different fertilization conditions (m1–m7, m1: Unfertilized; m2: Farmer Practice; m3: 75% Farmer Practice; m4: 75% Farmer Practice +25% Organic manure; m5: 50% Farmer Practice; m6: 50% Farmer Practice +50% Organic manure; m7: 100% Organic manure) were applied. The growth and yields of the Qingke plants were also compared under the seven fertilization conditions.ResultsThere were significant differences in alpha diversity indices among the three areas. In each area, differences in fertilization conditions and differences in the growth stages of Qingke plants resulted in differences in the beta diversity of the rhizosphere microbiota. Meanwhile, in each area, fertilization conditions, soil depths, and the growth stages of Qingke plants significantly affected the relative abundance of the top 10 phyla and the top 20 bacterial genera. For most of microbial pairs established through network analysis, the significance of their correlations in each of the microbial co-occurrence networks of the three experimental sites was different. Moreover, in each of the three networks, there were significant differences in relative abundance and genera among most nodes (i.e., the genera Pseudonocardia, Skermanella, Pseudonocardia, Skermanella, Aridibacter, and Illumatobacter). The soil chemical properties (i.e., TN, TP, SOM, AN, AK, CEC, Ca, and K) were positively or negatively correlated with the relative abundance of the top 30 genera derived from the three main Qingke-producing areas (p < 0.05). Fertilization conditions markedly influenced the height of a Qingke plant, the number of spikes in a Qingke plant, the number of kernels in a spike, and the fresh weight of a Qingke plant. Considering the yield, the most effective fertilization conditions for Qingke is combining application 50% chemical fertilizer and 50% organic manure.ConclusionThe results of the present study can provide theoretical basis for practice of reducing the use of chemical fertilizer in agriculture

Population structure analysis and genome-wide association study of a hexaploid oat landrace and cultivar collection

IntroductionOat (Avena sativa L.) is an important cereal crop grown worldwide for grain and forage, owing to its high adaptability to diverse environments. However, the genetic and genomics research of oat is lagging behind that of other staple cereal crops. MethodsIn this study, a collection of 288 oat lines originating worldwide was evaluated using 2,213 single nucleotide polymorphism (SNP) markers obtained from an oat iSelect 6K-beadchip array to study its genetic diversity, population structure, and linkage disequilibrium (LD) as well as the genotype–phenotype association for hullessness and lemma color.ResultsThe average gene diversity and polymorphic information content (PIC) were 0.324 and 0.262, respectively. The first three principal components (PCs) accounted for 30.33% of the genetic variation, indicating that the population structure of this panel of oat lines was stronger than that reported in most previous studies. In addition, accessions could be classified into two subpopulations using a Bayesian clustering approach, and the clustering pattern of accessions was closely associated with their region of origin. Additionally, evaluation of LD decay using 2,143 mapped markers revealed that the intrachromosomal whole-genome LD decayed rapidly to a critical r2 value of 0.156 for marker pairs separated by a genetic distance of 1.41 cM. Genome-wide association study (GWAS) detected six significant associations with the hullessness trait. Four of these six markers were located on the Mrg21 linkage group between 194.0 and 205.7 cM, while the other two significant markers mapped to Mrg05 and Mrg09. Three significant SNPs, showing strong association with lemma color, were located on linkage groups Mrg17, Mrg18, and Mrg20.DiscussionOur results discerned relevant patterns of genetic diversity, population structure, and LD among members of a worldwide collection of oat landraces and cultivars proposed to be ‘typical’ of the Qinghai-Tibetan Plateau. These results have important implications for further studies on association mapping and practical breeding in high-altitude oat

Towards the Properties of Long Gamma-Ray Burst Progenitors with Swift Data

We investigate the properties of both the prompt and X-ray afterglows of gamma-ray bursts (GRBs) in the burst frame with a sample of 33 Swift GRBs. Assuming that the steep decay segment in the canonical X-ray afterglow lightcurves is due to the curvature effect, we fit the lightcurves with a broken power-law to derive the zero time of the last emission epoch of the prompt emission (t1) and the beginning as well as the end time of the shallow decay segment (t2 and t3).We show that both the isotropic peak gamma-ray luminosity and gamma-ray energy are correlated with the isotropic X-ray energy of the shallow decay phase and the isotropic X-ray luminosity at t2. We infer the properties of the progenitor stars based on a model proposed by Kumar et al. who suggested that both the prompt gamma-rays and the X-ray afterglows are due to the accretions of different layers of materials of the GRB progenitor star by a central black hole (BH). We find that most of the derived masses of the core layers are 0.1-5 solar mass with a radius of 10^8-10^10 cm. The rotation parameter is correlated with the burst duration, being consistent with the expectation of collapsar models. The estimated radii and the masses of the fall-back materials for the envelope layers are 10^10-10^12 cm and 10^-3~1 solar mass, respectively. The average accretion rates in the shallow decay phase are correlated with those in the prompt gamma-ray phase, but they are much lower. The derived radii of the envelope are smaller than the photospheric radii of Wolf-Rayet (WR) stars. It is interesting that the assembled mass density profile for the bursts in our sample is also well consistent with the simulation for a pre-supernova star with 25 solar mass.Comment: 12 pages in MNRAS two-column style, 8 figures, 3 tables, accepted for publication in MNRA