Quantitative imaging of bilirubin by photoacoustic microscopy

Noninvasive detection of both bilirubin concentration and its distribution is important for disease diagnosis. Here we implemented photoacoustic microscopy (PAM) to detect bilirubin distribution. We first demonstrate that our PAM system can measure the absorption spectra of bilirubin and blood. We also image bilirubin distributions in tissue-mimicking samples, both without and with blood mixed. Our results show that PAM has the potential to quantitatively image bilirubin in vivo for clinical applications

Genome-wide association analysis identifies resistance loci for bacterial blight in a diverse collection of indica rice germplasm

Bacterial blight, which is caused by Xanthomonas oryzae pv. oryzae (Xoo), is one of the most devastating rice diseases worldwide. The development and use of disease-resistant cultivars have been the most effective strategy to control bacterial blight. Identifying the genes mediating bacterial blight resistance is a prerequisite for breeding cultivars with broad-spectrum and durable resistance. We herein describe a genome-wide association study involving 172 diverse Oryza sativa ssp. indica accessions to identify loci influencing the resistance to representative strains of six Xoo races. Twelve resistance loci containing 121 significantly associated signals were identified using 317,894 single nucleotide polymorphisms, which explained 13.3–59.9% of the variability in lesion length caused by Xoo races P1, P6, and P9a. Two hotspot regions (L11 and L12) were located within or nearby two cloned R genes (xa25 and Xa26) and one fine-mapped R gene (Xa4). Our results confirmed the relatively high resolution of genome-wide association studies. Moreover, we detected novel significant associations on chromosomes 2, 3, and 6–10. Haplotype analyses of xa25, the Xa26 paralog (MRKc; LOC_Os11g47290), and a Xa4 candidate gene (LOC_11g46870) revealed differences in bacterial blight resistance among indica subgroups. These differences were responsible for the observed variations in lesion lengths resulting from infections by Xoo races P1 and P9a. Our findings may be relevant for future studies involving bacterial blight resistance gene cloning, and provide insights into the genetic basis for bacterial blight resistance in indica rice, which may be useful for knowledge-based crop improvement. (Résumé d'auteur

Complete analysis on QED corrections to Bq → τ+ τ−B_{q}\, \to\, \tau^+\, \tau^-

Motivated by a dynamical enhancement of the electromagnetic corrections by a power of $\Lambda_{\mathrm{QCD}}/m_b$ in $B_{d,s}\, \to\, \mu^+\, \mu^-$ at next-to-leading order (NLO), we extend the QED factorization effects on the leptonic $B$ meson decays with light muon leptons to tauonic final states, $B_{d,s} \, \to\, \tau^+\, \tau^-$, using soft-collinear effective theory (SCET). This extension is necessary owing to the appearance of the large $\tau$ mass, which will lead to different power counting in SCET and also different results. We provide a complete NLO electromagnetic corrections to $B_{d,s} \, \to\, \tau^+\, \tau^-$, which include hard functions and hard-collinear functions below the bottom quark mass scale $\mu_b$. The power enhanced electromagnetic effects from hard-collinear contributions on $B_{d,s}\, \to\, \mu^+\, \mu^-$ discussed before also exist in $B_{d,s} \, \to\, \tau^+\, \tau^-$. However the logarithm term arising from contributions of hard-collinear photon and lepton virtualities for $B_{d,s}\, \to\, \tau^+\, \tau^-$ is not large as it is in muon case due to the hard-collinear scale of $\tau$ mass, which lead to only approximately $0.04\%$ QED corrections to the branching fraction of $B_{d,s} \, \to\, \tau^+\, \tau^-$ compared with overall reduction about $0.5\%$ in $B_{d,s}\, \to\, \mu^+\, \mu^-$.Comment: 29 pages, 3 figure

Hydrodynamic analysis of a semi-submersible wind-tidal combined power generation device

Energy shortages and environmental pollution are becoming increasingly severe globally. The exploitation and utilization of renewable energy have become an effective way to alleviate these problems. To improve power production capacity, power output quality, and cost effectiveness, comprehensive marine energy utilization has become an inevitable trend in marine energy development. Based on a semi-submersible wind–tidal combined power generation device, a three-dimensional frequency domain potential flow theory is used to study the hydrodynamic performance of such a device. For this study, the RAOs and hydrodynamic coefficients of the floating carrier platform to the regular wave were obtained. The influence of the tidal turbine on the platform in terms of frequency domain was considered as added mass and damping. The direct load of the tidal turbine was obtained by CFX. FORTRAN software was used for the second development of adaptive query workload aware software, which can include the external force. The motion response of the platform to the irregular wave and the tension of the mooring line were calculated under the limiting condition (one mooring line breakage). The results showed that the motion response of the carrier to the surge and sway direction is more intense, but the swing amplitude is within the acceptable range. Even in the worst case scenario, the balance position of the platform was still in the positioning range, which met the requirements of the working sea area. The safety factor of the mooring line tension also complied with the requirements of the design specification. Therefore, it was found that the hydrodynamic performance and motion responses of a semi-submersible wind–tidal combined power generation device can meet the power generation requirements under all design conditions, and the device presents a reliable power generation system

Photoacoustic microscopy of bilirubin in tissue phantoms

Determining both bilirubin’s concentration and its spatial distribution are important in disease diagnosis. Here, for the first time, we applied quantitative multiwavelength photoacoustic microscopy (PAM) to detect bilirubin concentration and distribution simultaneously. By measuring tissue-mimicking phantoms with different bilirubin concentrations, we showed that the root-mean-square error of prediction has reached 0.52 and 0.83  mg/dL for pure bilirubin and for blood-mixed bilirubin detection (with 100% oxygen saturation), respectively. We further demonstrated the capability of the PAM system to image bilirubin distribution both with and without blood. Finally, by underlaying bilirubin phantoms with mouse skins, we showed that bilirubin can be imaged with consistent accuracy down to >400  μm in depth. Our results show that PAM has potential for noninvasive bilirubin monitoring in vivo, as well as for further clinical applications

Quantitative imaging of bilirubin by photoacoustic microscopy

Noninvasive detection of both bilirubin concentration and its distribution is important for disease diagnosis. Here we implemented photoacoustic microscopy (PAM) to detect bilirubin distribution. We first demonstrate that our PAM system can measure the absorption spectra of bilirubin and blood. We also image bilirubin distributions in tissue-mimicking samples, both without and with blood mixed. Our results show that PAM has the potential to quantitatively image bilirubin in vivo for clinical applications

Tracking sustainability: co-evolution of economic and ecological activities in the industrialization of the United Kingdom and China

The co-evolution of economic and ecological activities represents one of the fundamental challenges in the realm of sustainable development. This study on the word trends in mainstream newspapers from the UK and China reveals that both early-industrialised countries and latecomers follow three modes of economic and ecological co-evolution. First, both economic and ecological words demonstrate an S-shaped growth trajectory, and the mode underscores the importance of information propagation, whilst also highlighting the crucial role of self-organisation in the accept society. Second, the co-occurrence of these two type words exhibits a Z-shaped relationship: for two-thirds of the observed period, they display synergistic interactions, while the remaining time shows trade-offs. Lastly, the words related to ecological degradation follow M-shaped trajectories in parallel with economic growth, suggesting periodic disruptions and reconstructions in their interrelationships. Our findings contribute to a more nuanced understanding of the co-evolutionary mechanisms that govern collective behaviours in human society

Machine learning classification models for fetal skeletal development performance prediction using maternal bone metabolic proteins in goats

Background: In developing countries, maternal undernutrition is the major intrauterine environmental factor contributing to fetal development and adverse pregnancy outcomes. Maternal nutrition restriction (MNR) in gestation has proven to impact overall growth, bone development, and proliferation and metabolism of mesenchymal stem cells in offspring. However, the efficient method for elucidation of fetal bone development performance through maternal bone metabolic biochemical markers remains elusive. Methods: We adapted goats to elucidate fetal bone development state with maternal serum bone metabolic proteins under malnutrition conditions in mid- and late-gestation stages. We used the experimental data to create 72 datasets by mixing different input features such as one-hot encoding of experimental conditions, metabolic original data, experimental-centered features and experimental condition probabilities. Seven Machine Learning methods have been used to predict six fetal bone parameters (weight, length, and diameter of femur/humerus). Results: The results indicated that MNR influences fetal bone development (femur and humerus) and fetal bone metabolic protein levels (C-terminal telopeptides of collagen I, CTx, in middle-gestation and N-terminal telopeptides of collagen I, NTx, in late-gestation), and maternal bone metabolites (low bone alkaline phosphatase, BALP, in middle-gestation and high BALP in late-gestation). The results show the importance of experimental conditions (ECs) encoding by mixing the information with the serum metabolic data. The best classification models obtained for femur weight (Fw) and length (FI), and humerus weight (Hw) are Support Vector Machines classifiers with the leave-one-out cross-validation accuracy of 1. The rest of the accuracies are 0.98, 0.946 and 0.696 for the diameter of femur (Fd), diameter and length of humerus (Hd, Hl), respectively. With the feature importance analysis, the moving averages mixed ECs are generally more important for the majority of the models. The moving average of parathyroid hormone (PTH) within nutritional conditions (MA-PTH-experim) is important for Fd, Hd and Hl prediction models but its removal for enhancing the Fw, Fl and Hw model performance. Further, using one feature models, it is possible to obtain even more accurate models compared with the feature importance analysis models. In conclusion, the machine learning is an efficient method to confirm the important role of PTH and BALP mixed with nutritional conditions for fetal bone growth performance of goats. All the Python scripts including results and comments are available into an open repository at https://gitlab.com/muntisa/goat-bones-machine-learning

Supercritical CO2 fracking for enhanced shale gas recovery and CO2 sequestration: Results, status and future challenges

 Supercritical carbon dioxide(ScCO2)-based fracturing technology associating with CO2 enhanced shale gas recovery is a promising technology to reduce the water consumption of shale gas production and could provide the potential for CO2 sequestration. Advancing the understanding of complex gas shale reservoir behavior in the presence ofmultiphase and multicomponent gases (ScCO2, gaseous CO2 and CH4 etc.) via laboratory experiments, theoretical model development and field validation studies is very important. In this paper, the progress of some key scientific problems such as the mechanism of ScCO2 drilling and completion, the ScCO2 fracturing technology, the competition adsorption behaviors of CO2/CH4 in shale, the coupled multiphase and multicomponent CO2/CH4 flow during the CO2 enhanced shale gas recovery process and the CO2 sequestration potential in shale formation were discussed. Finally, the challenges of the technique will face and the further research is needed in the future is also exposed.Cited as: Zhou, J., Hu, N., Xian, X., Zhou, L., Tang, J., Kang, Y., Wang, H. Supercritical CO2 fracking for enhanced shale gas recovery and CO2 sequestration: Results, status and future challenges. Advances in Geo-Energy Research, 2019, 3(2): 207-224, doi: 10.26804/ager.2019.02.1

Supercritical CO2 fracking for enhanced shale gas recovery and CO2 sequestration: results, status and future challenges

Supercritical carbon dioxide(ScCO2)-based fracturing technology associating with CO2 enhanced shale gas recovery is a promising technology to reduce the water consumption of shale gas production and could provide the potential for CO2 sequestration. Advancing the understanding of complex gas shale reservoir behavior in the presence ofmultiphase and multicomponent gases (ScCO2, gaseous CO2 and CH4 etc.) via laboratory experiments, theoretical model development and field validation studies is very important. In this paper, the progress of some key scientific problems such as the mechanism of SCCO2 drilling and completion, the ScCO2 fracturing technology, the competition adsorption behaviors of CO2/CH4 in shale, the coupled multiphase and multicomponent CO2/CH4 flow during the CO2 enhanced shale gas recovery process and the CO2 sequestration potential in shale formation were discussed. Finally, the challenges of the technique will face and the further research is needed in the future is also exposed