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ABSTRACT The study aimed to investigate the effect of methionine deficiency on conventional nutrient composition, NO and NOS activity in the liver and kidney, and expression of genes related to the NF-κB signal pathway. One hundred 1-day-old broilers were divided into control and methionine deficiency group, and provided with a standard diet. The methionine-deficient group was fed with a methionine-deficient diet for 42 days. Moisture content, protein content, and crude lipid content were determined by freeze drying, the Kjeldahl method, and the ether extraction method. The concentration of NO was measured using the nitrate reductase method, and the activity of NOS was measured using colorimetry. mRNA expression of related genes in the NF-κB signal pathway was detected by reverse transcription-polymerase chain reaction (RT-PCR). The results showed the contents of crude protein and crude lipid in the liver and kidney of the methionine-deficient group were significantly higher than those in the control group (p0.05). Methionine deficiency resulted in significantly increased NO concentration and total nitric oxide synthase (TNOS) activities in the liver and kidney (p

The most common complication in older surgical patients is postoperative delirium (POD). POD is associated with preoperative cognitive impairment and longer durations of intraoperative burst suppression (BSup) – electroencephalography (EEG) with repeated periods of suppression (very low-voltage brain activity). However, BSup has modest sensitivity for predicting POD. We hypothesized that a brain state of lowered EEG power immediately precedes BSup, which we have termed “pre-burst suppression” (preBSup). Further, we hypothesized that even patients without BSup experience these preBSup transient reductions in EEG power, and that preBSup (like BSup) would be associated with preoperative cognitive function and delirium risk. Data included 83 32-channel intraoperative EEG recordings of the first hour of surgery from 2 prospective cohort studies of patients ≥age 60 scheduled for ≥2-h non-cardiac, non-neurologic surgery under general anesthesia (maintained with a potent inhaled anesthetic or a propofol infusion). Among patients with BSup, we defined preBSup as the difference in 3–35 Hz power (dB) during the 1-s preceding BSup relative to the average 3–35 Hz power of their intraoperative EEG recording. We then recorded the percentage of time that each patient spent in preBSup, including those without BSup. Next, we characterized the association between percentage of time in preBSup and (1) percentage of time in BSup, (2) preoperative cognitive function, and (3) POD incidence. The percentage of time in preBSup and BSup were correlated (Spearman’s ρ [95% CI]: 0.52 [0.34, 0.66], p < 0.001). The percentage of time in BSup, preBSup, or their combination were each inversely associated with preoperative cognitive function (β [95% CI]: −0.10 [−0.19, −0.01], p = 0.024; −0.04 [−0.06, −0.01], p = 0.009; −0.04 [−0.06, −0.01], p = 0.003, respectively). Consistent with prior literature, BSup was significantly associated with POD (odds ratio [95% CI]: 1.34 [1.01, 1.78], p = 0.043), though this association did not hold for preBSup (odds ratio [95% CI]: 1.04 [0.95, 1.14], p = 0.421). While all patients had ≥1 preBSup instance, only 20.5% of patients had ≥1 BSup instance. These exploratory findings suggest that future studies are warranted to further study the extent to which preBSup, even in the absence of BSup, can identify patients with impaired preoperative cognition and/or POD risk.

ABSTRACT This study explores the differences of appearance and the digestive systems of two birds (Lonchura striata and Copsychus saularis), which have the same eating pattern in staple ingredients. Each bird was caught naturally and euthanized in appropriate manner, followed by morphology survey on bill, duodenum, jejunum, ileum and appearance of the body parts such as Culmen, Claw, Wing, Tarsus, Toe and Tail. The results showed that the appearance feature between them presented significant differences in the beak length, wing length and tail length, which were correlated to their staple feeding habits. In addition, in the digestive system, the length of duodenum and duodenal indexes showed significant differences (p

ABSTRACT Photoperiod and nutrition are major factors that affect the reproductive efficiency particularly in female animals. In this study we examined the interaction of photoperiod and food restriction on growth, sexual maturation and receptor mRNA expressions of leptin, melatonin, and estrogen in abdominal fat and the ovary of pullets. There were no interaction effects between photoperiod and feeding level on body weight, abdominal fat weight, ovary weight at both 14 wk and 18 wk. Abdominal fat weight of feed restriction group was significantly lower compared with the control group at the age of 14 wk, 18 wk, and age of the first egg (AFE) (p

The tropical western Pacific (TWP) is a preferential area of air uplifting from the surface to the upper troposphere. A significantly intensified upward motion through the troposphere over the TWP in the boreal wintertime (November to March of the following year, NDJFM) has been detected using multiple reanalysis datasets. The upward motion over the TWP is intensified at rates of 8.0 ± 3.1 % per decade and 3.6 ± 3.3 % per decade in NDJFM at 150 hPa from 1958 to 2017, using JRA55 and ERA5 reanalysis datasets, while the MERRA-2 reanalysis data show a 7.5 ± 7.1 % per decade intensified upward motion for the period 1980–2017. Model simulations using the Whole Atmosphere Community Climate Model, version 4 (WACCM4), suggest that warming global sea surface temperatures (SSTs), particularly SSTs over the eastern maritime continent and tropical western Pacific, play a dominant role in the intensification of the upward motion by strengthening the Pacific Walker circulation and enhancing the deep convection over the TWP. Using CO as a tropospheric tracer, the WACCM4 simulations show that an increase in CO at a rate of 0.4 ppbv (parts per billion by volume) per decade at the layer 150–70 hPa in the tropics is mainly resulted from the global SST warming and the subsequent enhanced upward motion over the TWP in the troposphere and strengthened tropical upwelling of Brewer–Dobson (BD) circulation in the lower stratosphere. This implies that more tropospheric trace gases and aerosols from both natural maritime sources and outflow from polluted air from South Asia may enter the stratosphere through the TWP region and affect the stratospheric chemistry and climate.

Cardiovascular disease (CVD) is one of the leading causes of mortality worldwide, and frequently leads to massive heart injury and the loss of billions of cardiac muscle cells and associated vasculature. Critical work in the last 2 decades demonstrated that these lost cells can be partially regenerated by the epicardium, the outermost mesothelial layer of the heart, in a process that highly recapitulates its role in heart development. Upon cardiac injury, mature epicardial cells activate and undergo an epithelial-mesenchymal transition (EMT) to form epicardium-derived progenitor cells (EpiPCs), multipotent progenitors that can differentiate into several important cardiac lineages, including cardiomyocytes and vascular cells. In mammals, this process alone is insufficient for significant regeneration, but it might be possible to prime it by administering specific reprogramming factors, leading to enhanced EpiPC function. Here, we show that oxytocin (OXT), a hypothalamic neuroendocrine peptide, induces epicardial cell proliferation, EMT, and transcriptional activity in a model of human induced pluripotent stem cell (hiPSC)-derived epicardial cells. In addition, we demonstrate that OXT is produced after cardiac cryoinjury in zebrafish, and that it elicits significant epicardial activation promoting heart regeneration. Oxytocin signaling is also critical for proper epicardium development in zebrafish embryos. The above processes are significantly impaired when OXT signaling is inhibited chemically or genetically through RNA interference. RNA sequencing data suggests that the transforming growth factor beta (TGF-β) pathway is the primary mediator of OXT-induced epicardial activation. Our research reveals for the first time an evolutionary conserved brain-controlled mechanism inducing cellular reprogramming and regeneration of the injured mammalian and zebrafish heart, a finding that could contribute to translational advances for the treatment of cardiac injuries.

Registration of multiple point clouds acquired via terrestrial laser scanning (TLS) is usually compulsory to obtain the scanned data covering a whole urban scene. However, the automated processing of aligning multiple scans is still a concern because of the complex urban environment. To this end, we propose a fast and sturdy estimation of 3D shifts between point clouds by an automated markerfree process using global features, converting translation measurement between two point clouds in the space domain to the frequency domain and estimating the phase difference. By using the low-frequency components from the normalized cross-power spectrum, accurate 3D shifts are calculated by solving parameters in the linear equation representing phase difference angles, with the help of a robust estimator. The results of experiments using TLS datasets of different scenes show that the proposed approach is both practical and efficient. In particular, the proposed approach can achieve results with a translation error of less than about 1.0 m on test datasets.

Registration of point clouds is a fundamental problem in the community of photogrammetry and 3D computer vision. Generally, point cloud registration consists of two steps: the search of correspondences and the estimation of transformation parameters. However, to find correspondences from point clouds, generating robust and discriminative features is of necessity. In this paper, we address the problem of extracting robust rotation-invariant features for fast coarse registration of point clouds under the assumption that the pairwise point clouds are transformed with rigid transformation. With a Fourier-based descriptor, point clouds represented by volumetric images can be mapped from the image to feature space. It is achieved by considering a gradient histogram as a continuous angular signal which can be well represented by the spherical harmonics. The rotation-invariance is established based on the Fourier-based analysis, in which high-frequency signals can be filtered out. This makes the extracted features robust to noises and outliers. Then, with the extracted features, pairwise correspondence can be found by the fast search. Finally, the transformation parameters can be estimated by fitting the rigid transformation model using the corresponding points and RANSAC algorithm. Experiments are conducted to prove the effectiveness of our proposed method in the task of point cloud registration. Regarding the experimental results of the point cloud registration using two TLS benchmark point cloud datasets, featuring with limited overlaps and uneven point densities and covering different urban scenes, our proposed method can achieve a fast coarse registration with rotation errors of less than 1 degree and translation errors of less than 1m.

Abstract We report the measurement of the two-neutrino double-beta ($$2\nu \beta \beta $$ 2νββ ) decay of $$^{100}$$ 100 Mo to the ground state of $$^{100}$$ 100 Ru using lithium molybdate ($$\hbox {Li}_2^{\;\;100}\hbox {MoO}_4$$ Li2100MoO4 ) scintillating bolometers. The detectors were developed for the CUPID-Mo program and operated at the EDELWEISS-III low background facility in the Modane underground laboratory (France). From a total exposure of 42.235 kg$$\times $$ × day, the half-life of $$^{100}$$ 100 Mo is determined to be $$T_{1/2}^{2\nu }=[7.12^{+0.18}_{-0.14}\,\mathrm {(stat.)}\pm 0.10\,\mathrm {(syst.)}]\times 10^{18}$$ T1/22ν=[7.12-0.14+0.18(stat.)±0.10(syst.)]×1018 years. This is the most accurate determination of the $$2\nu \beta \beta $$ 2νββ half-life of $$^{100}$$ 100 Mo to date.

Individual, large thrusting earthquakes can cause hundreds to thousands of years of exhumation in a geologically instantaneous moment through landslide generation. The bedrock landslides generated are important weathering agents through the conversion of bedrock into mobile regolith. Despite this, orogen-scale records of surface uplift and exhumation, whether sedimentary or geochemical, contain little to no evidence of individual large earthquakes. We examine how earthquakes and landslides influence exhumation and surface uplift rates with a zero-dimensional numerical model, supported by observations from the 2008 Mw 7.9 Wenchuan earthquake. We also simulate the concentration of cosmogenic radionuclides within the model domain, so we can examine the timescales over which earthquake-driven changes in exhumation can be measured. Our model uses empirically constrained relationships between seismic energy release, weathering, and landsliding volumes to show that large earthquakes generate the most surface uplift, despite causing lowering of the bedrock surface. Our model suggests that when earthquakes are the dominant rock uplift process in an orogen, rapid surface uplift can occur when regolith, which limits bedrock weathering, is preserved on the mountain range. After a large earthquake, there is a lowering in concentrations of 10Be in regolith leaving the orogen, but the concentrations return to the long-term average within 103 years. The timescale of the seismically induced cosmogenic nuclide concentration signal is shorter than the averaging time of most thermochronometers (>103 years). However, our model suggests that the short-term stochastic feedbacks between weathering and exhumation produce measurable increases in cosmogenically measured exhumation rates which can be linked to earthquakes.

In this paper, we propose a framework for obtaining semantic labels of LiDAR point clouds and refining the classification results by combining a deep neural network with a graph-structured smoothing technique. In general, the goal of the semantic scene analysis is to assign a semantic label to each point in the point cloud. Although various related researches have been reported, due to the complexity of urban areas, the semantic labeling of point clouds in urban areas is still a challenging task. In this paper, we address the issues of how to effectively extract features from each point and its local surrounding and how to refine the initial soft labels by considering contextual information in the spatial domain. Specifically, we improve the effectiveness of classification of point cloud in two aspects. Firstly, instead of utilizing handcrafted features as input for classification and refinement, the local context of a point is embedded into deep dimensional space and classified via a deep neural network (PointNet++), and simultaneously soft labels are obtained as initial results for next refinement. Secondly, the initial label probability set is improved by taking the context both in the spatial domain into consideration by constructing a graph structure, and the final labels are optimized by a graph cuts algorithm. To evaluate the performance of our proposed framework, experiments are conducted on a mobile laser scanning (MLS) point cloud dataset. We demonstrate that our approach can achieve higher accuracy in comparison to several commonly-used state-of-the-art baselines. The overall accuracy of our proposed method on TUM dataset can reach 85.38% for labeling eight semantic classes.

GPRs (Ground Penetrating Radar) are widely adopted in underground space survey and mapping, because of their advantages of fast data acquisition, convenience, high imaging resolution and NDT (Non Destructive Testing) inspection. However, at present, the automation of the GPR data post-processing is low and the identification of underground objects needs expert interpretation. The heavy manual interpretation labor limits the GPR applications in large-scale urban scenarios. According to the latest research, it is still an unsolved problem to detect targets or defects in GPR data automatically and needs further exploration. In this paper, we propose a deep learning method for real-time detection of underground targets from GPR data. Seven typical targets in urban underground space are identified and labelled to construct the training dataset. The constructed dataset is consist of 489 labelled samples including rainwater wells, cables, metal/nonmetal pipes, sparse/dense steel reinforcement, voids. The training dataset is further augmented to produce more samples. DarkNet53 convolutional neural network (CNN) is trained using the constructed training dataset including realistic data and augmented data to extract features of the buried objects. And then the end-to-end YOLO detection framework is used to classify and locate the seven specific categories buried targets in the GPR data in real time. Experiments show that the automatic real-time detection method proposed in this paper can effectively detect the buried objects in the ground penetrating radar image in real time at Shenzhen test site (typical urban road scene).

The morphology and effective density of externally mixed black carbon (extBC) aerosols, important factors affecting the radiative forcing of black carbon, were studied using a tandem technique coupling a differential mobility analyzer (DMA) with a single-particle soot photometer (SP2). The study extended the mass–mobility relationship to large extBC particles with a mobility diameter (dmob) larger than 350 nm, a size range seldom included in previous tandem measurements of BC aggregates in the atmosphere. The experiment was conducted at an urban site in Beijing during a 19 d winter period from 23 January to 10 February 2018. Ambient dry particles were selected by the DMA, and the size-resolved extBC particles were distinguished from particles with a thick coating (internally mixed) according to the time delay between the incandescence signal peak and the scattering peak detected by the SP2. The masses of the extBC particles were then quantified. The time differences between the DMA size selection and the SP2 measurement were processed previously. The normalized number size distributions were investigated at the prescribed dmob sizes in the range of 140–750 nm to provide the typical mass of extBC at each dmob. On this basis, the mass–mobility relationship of the ambient extBC was established, inferring a mass–mobility scaling exponent (Dfm) (an important quantity for characterizing the morphology of fractal-like BC aggregates) with a value of 2.34±0.03 in the mobility range investigated in this study. This value is comparable with those of diesel exhaust particles, implying a predominant contribution of vehicle emissions to the ambient extBC in urban Beijing. Compared to the clean period, a higher Dfm value was observed in the polluted episode, indicating a more compact BC aggregate structure than that in the clean period. The effective densities (ρeff) of the extBC in the same dmob range were also derived, with values gradually decreasing from 0.46 g cm−3 at 140 nm mobility to 0.14 g cm−3 at 750 nm mobility. The ρeff values were slightly lower than those measured using the DMA–aerosol particle mass analyzer (APM) system. The difference in ρeff values was likely due to the lower BC masses determined by the SP2 compared to those measured by the APM at the same mobility, since the SP2 measured the refractory BC (rBC) mass instead of the total mass of the BC aggregate, which consists of both rBC and a possible fraction of nonrefractory components measured by the APM. The ρeff values in the 280–350 nm dmob range were much closer to the values for soot aggregates reported in the literature. It might be related to the more compact structure of BC aggregates in this range, resulting from the reconstruction effect by volatile and/or semivolatile components in the atmosphere. The reconstruction effect might also result in a hiatus in the increased dynamic shape factor in the range of 200–350 nm, which presented an overall increase from 2.16 to 2.93 in the 140–750 nm dmob range.

For conducting change detection using 3D scans of a construction site, the registration between point clouds at different acquisition times is normally necessary. However, due to the complexity of constructing areas, the automatic registration of temporal scans is a challenging problem. In this work, we propose a fast and maker-free method for coarse registration between point clouds by converting the 3D matching problem into a 2D correlation problem, taking the special properties of building structures into consideration. Our proposed method consists of two major steps: the conversion from 3D points to 2D image data and the estimation of transformation parameters between 2D images in the frequency domain. In the conversion step, the point cloud of each scan is projected into a 2D grey image, by which the ground footprint of the point cloud is obtained. In the following step, we represent the 2D image in frequency-domain and estimate the horizontal transformation parameters by using Fourier-Mellin transformation. A real application is performed to validate the feasibility and effectiveness of our workflow using photogrammetric point clouds of a construction site in two different acquisition time. Regarding the real application of coarse registration of point clouds, our proposed method can achieve a registration error of less than 1 degree and more efficient than the classical baseline methods for the fast orientation between scans.

Organic aerosol (OA) concentrations are simulated over the Beijing–Tianjin–Hebei (BTH) region from 9 to 26 January 2014 using the Weather Research and Forecasting model coupled with chemistry (WRF-CHEM), with the goal of examining the impact of heterogeneous HONO sources on SOA formation and SOA formation from different pathways during wintertime haze days. The model generally shows good performance with respect to simulating air pollutants and organic aerosols against measurements in BTH. Model results show that heterogeneous HONO sources substantially enhance near-surface SOA formation, increasing the regional average near-surface SOA concentration by about 46.3 % during the episode. Oxidation and partitioning of primary organic aerosols treated as semi-volatile dominate SOA formation, contributing 58.9 % of the near-surface SOA mass in BTH. Irreversible uptake of glyoxal and methylglyoxal on aerosol surfaces constitutes the second most important SOA formation pathway during the episode, with the SOA contribution increasing from 8.5 % under non-haze conditions to 30.2 % under haze conditions. Additionally, direct emissions of glyoxal and methylglyoxal from residential sources contribute about 25.5 % of the total SOA mass on average in BTH. Our study highlights the importance of heterogeneous HONO sources and primary residential emissions of glyoxal and methylglyoxal to SOA formation over the BTH region in winter.

We release two datasets that track the enhanced landsliding induced by the 2008 Mw 7.9 Wenchuan earthquake over a portion of the Longmen Mountains, at the eastern margin of the Tibetan Plateau (Sichuan, China). The first dataset is a geo-referenced multi-temporal polygon-based inventory of pre- and coseismic landslides, post-seismic remobilisations of coseismic landslide debris and post-seismic landslides (new failures). It covers 471 km2 in the earthquake's epicentral area, from 2005 to 2018. The second dataset records the debris flows that occurred from 2008 to 2017 in a larger area (∼17 000 km2), together with information on their triggering rainfall as recorded by a network of rain gauges. For some well-monitored events, we provide more detailed data on rainfall, discharge, flow depth and density. The datasets can be used to analyse, on various scales, the patterns of landsliding caused by the earthquake. They can be compared to inventories of landslides triggered by past or new earthquakes or by other triggers to reveal common or distinctive controlling factors. To our knowledge, no other inventories that track the temporal evolution of earthquake-induced mass wasting have been made freely available thus far. Our datasets can be accessed from https://doi.org/10.5281/zenodo.1405489. We also encourage other researchers to share their datasets to facilitate research on post-seismic geological hazards.

In the present study, the WRF-Chem model is used to assess contributions of residential coal combustion (RCC) emissions to the air quality in Beijing–Tianjin–Hebei (BTH) during a persistent air pollution episode from 9 to 25 January 2014. In general, the predicted temporal variations and spatial distributions of the mass concentrations of air pollutants are in good agreement with observations at monitoring sites in BTH. The WRF-Chem model also reasonably reproduces the temporal variations in aerosol species when compared with the aerosol mass spectrometer measurements in Beijing. The RCC emissions play an important role in the haze formation in BTH, contributing about 23.1 % of PM2.5 (fine particulate matter) and 42.6 % of SO2 during the simulation period on average. Organic aerosols dominate the PM2.5 from the RCC emissions in BTH, with a contribution of 42.8 %, followed by sulfate (17.1 %). The air quality in Beijing is remarkably improved when the RCC emissions in BTH and the surrounding areas are excluded in model simulations, with a 30 % decrease in PM2.5 mass concentrations. However, if only the RCC emissions in Beijing are excluded, the local PM2.5 mass concentration is decreased by 18.0 % on average. Our results suggest that the implementation of the residential coal replacement by clean energy sources in Beijing is beneficial to the local air quality. Should residential coal replacement be carried out in BTH and its surrounding areas, the air quality in Beijing would be improved remarkably. Further studies would need to consider uncertainties in the emission inventory and meteorological fields.

The hydro-stochastic interpolation method based on traditional block Kriging has often been used to predict mean annual runoff in river basins. A caveat in such a method is that the statistic technique provides little physical insight into relationships between the runoff and its external forcing, such as the climate and land cover. In this study, the spatial runoff is decomposed into a deterministic trend and deviations from it caused by stochastic fluctuations. The former is described by the Budyko method (Fu's equation) and the latter by stochastic interpolation. This coupled method is applied to spatially interpolate runoff in the Huaihe River basin of China. Results show that the coupled method significantly improves the prediction accuracy of the mean annual runoff. The error of the predicted runoff by the coupled method is much smaller than that from the Budyko method and the hydro-stochastic interpolation method alone. The determination coefficient for cross-validation, Rcv2, from the coupled method is 0.87, larger than 0.81 from the Budyko method and 0.71 from the hydro-stochastic interpolation. Further comparisons indicate that the coupled method has also reduced the error in overestimating low runoff and underestimating high runoff suffered by the other two methods. These results confirm that the coupled method offers an effective and more accurate way to predict the mean annual runoff in river basins.

Abstract Background Giant cell arteritis (GCA) is an immune mediated inflammatory disease of medium and large arteries which afflicts older people. The classical presentation features include: headache, visual disturbances, and jaw claudication. Patients diagnosed with GCA have also been observed to be at higher risk for the subsequent development of strokes. Case presentation We describe a case of an 84-year old right-handed man who presented to hospital with dysarthria, dysphagia, right-sided facial drop, a history of generalized weakness and multiple falls. He was admitted to geriatric medicine with the working diagnosis of a posterior circulation stroke syndrome. He was also started on antibiotic treatment for a possible community-acquired pneumonia because of the presence of a low-grade fever and a chest radiograph showing ill-defined left lower lobe airspace disease. Initial lab results were remarkable for an erythrocyte sedimentation rate (ESR) of 112 mm/h and a C-reactive protein (CRP) level of 110 mg/L consistent with an active inflammatory state. Neurovascular imaging showed mild atherosclerotic changes of the aortic arch and proximal great vessels without significant stenosis. The patient was started on daily high-dose prednisone because of the possibility of a cerebral vasculitis. Bilateral biopsy of temporal arteries showed giant cell arteritis. The patient’s neurologic status and inflammatory markers significantly improved (ESR 52 mm/h, CRP 7.0 mg/L) and he was eventually discharged to a seniors home with services. Conclusion The initial presentation of giant cell arteritis as a stroke syndrome, especially in the posterior circulation territory, is exceedingly rare. Other atypical presenting symptoms may include chronic cough and fever of unknown origin. The elevated ESR and CRP levels were clues to the diagnosis and clinical decision-making should be driven by a high index of suspicion since no single test (ESR, CRP, temporal artery biopsy) has perfect sensitivity. Elevated CRP may have a role in increasing stroke risk. This case report illustrates that in older people clinicians must consider atypical presentations of disease more often since timely diagnosis and initiation of treatment can result in optimal outcomes.

A novel reduced order model (ROM) for unsteady hypersonic aerodynamics is developed, which is applicable for the variations of multi-parameters. The key to the developed ROM lies in the CFD-based model reduction of the steady aerodynamic component, which stems from the quasi-steady nature of aerodynamic forces in the hypersonic regime. Concretely, the proper orthogonal decomposition (POD) method, combined with Kriging interpolation, is used to construct the ROM for the steady aerodynamic component; meanwhile the unsteady part is directly obtained from Donov’s third-order piston theory. The new procedure is applied to a three-dimensional low aspect ratio wing (Lockheed F-104 Starfighter wing). It is shown that the developed ROM is able to accurately predict the unsteady hypersonic aerodynamic loads over a wide range of different flight conditions compared with the direct CFD computation.

There is increasing concern about the effects of ocean acidification on marine biogeochemical and ecological processes and the organisms that drive them, including marine bacteria. Here, we examine the effects of elevated CO2 on the bacterioplankton community during a mesocosm experiment using an artificial phytoplankton community in subtropical, eutrophic coastal waters of Xiamen, southern China. Through sequencing the bacterial 16S rRNA gene V3-V4 region, we found that the bacterioplankton community in this high-nutrient coastal environment was relatively resilient to changes in seawater carbonate chemistry. Based on comparative ecological network analysis, we found that elevated CO2 hardly altered the network structure of high-abundance bacterioplankton taxa but appeared to reassemble the community network of low abundance taxa. This led to relatively high resilience of the whole bacterioplankton community to the elevated CO2 level and associated chemical changes. We also observed that the Flavobacteria group, which plays an important role in the microbial carbon pump, showed higher relative abundance under the elevated CO2 condition during the early stage of the phytoplankton bloom in the mesocosms. Our results provide new insights into how elevated CO2 may influence bacterioplankton community structure.

In the present study, a persistent heavy haze episode from 13 to 20 January 2014 in Beijing–Tianjin–Hebei (BTH) is simulated using the WRF-CHEM model through ensemble simulations to investigate impacts of meteorological uncertainties on the haze formation. Model results show that uncertainties in meteorological conditions substantially influence the aerosol constituent simulations at an observation site in Beijing, and the ratio of the ensemble spread to the ensemble mean (RESM) exceeds 50 %. The ensemble mean generally preforms well in reproducing the fine particles' (PM2.5) temporal variations and spatial distributions against measurements in BTH. The meteorological uncertainties do not alter the PM2.5 distribution pattern in BTH principally or dominate the haze formation and development, but remarkably affect the simulated PM2.5 level, and the RESM for the simulated PM2.5 concentrations can be up to 30 % at the regional scale. In addition, the rather large RESM in PM2.5 simulations at the city scale also causes difficulties in evaluation of the control strategies. Therefore, our results suggest that the ensemble simulation is imperative to take into account the impact of the meteorological uncertainties on the haze prediction.

Rock avalanches are extremely rapid, massive flow-like movements of fragmented rock. The travel path of the rock avalanches may be confined by channels in some cases, which are referred to as channelized rock avalanches. Channelized rock avalanches are potentially dangerous due to their difficult-to-predict travel distance. In this study, we constructed a dataset with detailed characteristic parameters of 38 channelized rock avalanches triggered by the 2008 Wenchuan earthquake using the visual interpretation of remote sensing imagery, field investigation and literature review. Based on this dataset, we assessed the influence of different factors on the runout distance and developed prediction models of the channelized rock avalanches using the multivariate regression method. The results suggested that the movement of channelized rock avalanche was dominated by the landslide volume, total relief and channel gradient. The performance of both models was then tested with an independent validation dataset of eight rock avalanches that were induced by the 2008 Wenchuan earthquake, the Ms 7.0 Lushan earthquake and heavy rainfall in 2013, showing acceptable good prediction results. Therefore, the travel-distance prediction models for channelized rock avalanches constructed in this study are applicable and reliable for predicting the runout of similar rock avalanches in other regions.

Black carbon (BC) has important impact on climate and environment due to its light absorption ability, which greatly depends on its physicochemical properties including morphology, size and mixing state. The size distribution of the refractory BC (rBC) was investigated in urban Beijing in the late winter of 2014, during which there were frequent haze events, through analysis of measurements obtained using a single-particle soot photometer (SP2). By assuming void-free rBC with a density of 1.8 g cm−3, the mass of the rBC showed an approximately lognormal distribution as a function of the volume-equivalent diameter (VED), with a peak diameter of 213 nm. Larger VED values of the rBC were observed during polluted periods than on clean days, implying an alteration in the rBC sources, as the size distribution of the rBC from a certain source was relative stable, and VED of an individual rBC varied little once it was emitted into the atmosphere. The potential source contribution function analysis showed that air masses from the south to east of the observation site brought higher rBC loadings with more thick coatings and larger core sizes. The mean VED of the rBC presented a significant linear correlation with the number fraction of thickly coated rBC, extrapolating to be ∼ 150 nm for the completely non-coated or thinly coated rBC. It was considered as the typical mean VED of the rBC from local traffic sources in this study. Local traffic was estimated to contribute 35 to 100 % of the hourly rBC mass concentration with a mean of 59 % during the campaign. Lower local traffic contributions were observed during polluted periods, suggesting increasing contributions from other sources (e.g., coal combustion and biomass burning) to the rBC. Thus, the heavy pollution in Beijing was greatly influenced by other sources in addition to the local traffic.

Rapid industrialization and urbanization have caused frequent occurrence of haze in China during wintertime in recent years. The sulfate aerosol is one of the most important components of fine particles (PM2. 5) in the atmosphere, contributing significantly to the haze formation. However, the heterogeneous formation mechanism of sulfate remains poorly characterized. The relationships of the observed sulfate with PM2. 5, iron, and relative humidity in Xi'an, China have been employed to evaluate the mechanism and to develop a parameterization of the sulfate heterogeneous formation involving aerosol water for incorporation into atmospheric chemical transport models. Model simulations with the proposed parameterization can successfully reproduce the observed sulfate rapid growth and diurnal variations in Xi'an and Beijing, China. Reasonable representation of sulfate heterogeneous formation in chemical transport models considerably improves the PM2. 5 simulations, providing the underlying basis for better understanding the haze formation and supporting the design and implementation of emission control strategies.

In the present study, the WRF-CHEM model is used to evaluate the contributions of trans-boundary transport to the air quality in Beijing during a persistent air pollution episode from 5 to 14 July 2015 in Beijing–Tianjin–Hebei (BTH), China. Generally, the predicted temporal variations and spatial distributions of PM2.5 (fine particulate matter), O3 (ozone), and NO2 are in good agreement with observations in BTH. The WRF-CHEM model also reproduces reasonably well the temporal variations of aerosol species compared to measurements in Beijing. The factor separation approach is employed to evaluate the contributions of trans-boundary transport of non-Beijing emissions to the PM2.5 and O3 levels in Beijing. On average, in the afternoon during the simulation episode, the local emissions contribute 22.4 % to the O3 level in Beijing, less than 36.6 % from non-Beijing emissions. The O3 concentrations in Beijing are decreased by 5.1 % in the afternoon due to interactions between local and non-Beijing emissions. The non-Beijing emissions play a dominant role in the PM2.5 level in Beijing, with a contribution of 61.5 %, much higher than 13.7 %, from Beijing local emissions. The emission interactions between local and non-Beijing emissions enhance the PM2.5 concentrations in Beijing, with a contribution of 5.9 %. Therefore, the air quality in Beijing is generally determined by the trans-boundary transport of non-Beijing emissions during summertime, showing that the cooperation with neighboring provinces to mitigate pollutant emissions is key for Beijing to improve air quality.