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The boundary layer's separation loss in compressor cascades constitutes a significant portion of profile loss, critically influencing aerodynamic performance optimization and control. This study employs Large Eddy Simulation (LES) to examine separation losses at varying attack angles, focusing on a rectangular compressor cascade. Specifically, it explores the long separation bubble at a 45% blade height cross-section under designed incidence. Analysis of the separation bubble's transition process revealed a notable surge in total pressure loss rate prior to transition, which stabilized following reattachment. The study thoroughly investigates the evolution of long bubbles, employing quadrant analysis of Reynolds stress, critical point theory, and an in-depth examination of individual vortex dynamics. The findings indicate that the peak of cross-flow within the separation bubble acts as the primary mechanism initiating the transition. This insight is corroborated by DNS calculations of natural transitions on flat plates. Building upon these findings, the study discusses the effects of varying attack angles on transition processes. Notably, increased incidence prompted the upstream migration of the long separation bubble, transforming it into a short bubble at the leading edge. This shift led to a fivefold increase in separation loss and doubled the frequency of transverse flow fluctuations.

Measurements of dissolved organic carbon (DOC), nitrogen (DON), and phosphorus (DOP) concentrations are used to characterize the dissolved organic matter (DOM) pool and are important components of biogeochemical cycling in the coastal ocean. Here, we present the first edition of a global database (CoastDOM v1; available at https://doi.org/10.1594/PANGAEA.964012, Lønborg et al., 2023) compiling previously published and unpublished measurements of DOC, DON, and DOP in coastal waters. These data are complemented by hydrographic data such as temperature and salinity and, to the extent possible, other biogeochemical variables (e.g. chlorophyll a, inorganic nutrients) and the inorganic carbon system (e.g. dissolved inorganic carbon and total alkalinity). Overall, CoastDOM v1 includes observations of concentrations from all continents. However, most data were collected in the Northern Hemisphere, with a clear gap in DOM measurements from the Southern Hemisphere. The data included were collected from 1978 to 2022 and consist of 62 338 data points for DOC, 20 356 for DON, and 13 533 for DOP. The number of measurements decreases progressively in the sequence DOC > DON > DOP, reflecting both differences in the maturity of the analytical methods and the greater focus on carbon cycling by the aquatic science community. The global database shows that the average DOC concentration in coastal waters (average ± standard deviation (SD): 182±314 µmol C L−1; median: 103 µmol C L−1) is 13-fold higher than the average coastal DON concentration (13.6±30.4 µmol N L−1; median: 8.0 µmol N L−1), which is itself 39-fold higher than the average coastal DOP concentration (0.34±1.11 µmol P L−1; median: 0.18 µmol P L−1). This dataset will be useful for identifying global spatial and temporal patterns in DOM and will help facilitate the reuse of DOC, DON, and DOP data in studies aimed at better characterizing local biogeochemical processes; closing nutrient budgets; estimating carbon, nitrogen, and phosphorous pools; and establishing a baseline for modelling future changes in coastal waters.

This study aims to analyze statistical behavior of the continental shelf wave motions, including continental shelf waves (CSWs) and arrested topographic waves (ATWs), in the northern South China Sea. The baseline consists of tide-gauge data from stations Kanmen, Xiamen, Shanwei, and Zhapo as well as along-track sea level anomaly (SLA) data derived from multiple satellite altimeters from 1993 to 2020. The subtidal signals propagating along the coast with periods shorter than 40 d and phase speeds of about 10 m s−1 are interpreted as CSWs. The cross-shelf structure of along-track SLAs indicates that Mode 1 of CSWs is the predominant component trapped in the area shallower than about 200 m. The amplitudes of CSWs reach a maximum of 0.6 m during July–September and a minimum of 0.2 m during April–June. The inter-seasonal and seasonal signals represent ATWs. The amplitudes of ATWs reach 0.10 m during October–December, twice that during July–September. These observations can be well interpreted in the framework of linear wave theory. The cross-shelf structures of CSWs and ATWs derived from along-track SLAs illustrate that the methods are suitable for observing dynamic behavior of the CSWs.

Using satellite observations from 2003 to 2020 and cruise observations from 2019 and 2021, this study reveals an unexpected minor role of upwelling in seasonal and interannual variations in chlorophyll a (Chl a) concentrations in the coastal upwelling region east of Hainan Island (UEH) in the northwestern South China Sea (NWSCS). The results show strong seasonal and interannual variability in the Chl a concentration in the core upwelling area of the UEH. Different from the strongest upwelling in summer, the Chl a concentration in the UEH area reaches a maximum of 1.18 mg m−3 in autumn and winter, with a minimum value of 0.74 mg m−3 in summer. The Chl a concentration in summer increases to as high as 1.0 mg m−3 with weak upwelling, whereas the maximum Chl a concentration in October increases to 2.5 mg m−3. The analysis of environmental factors shows that, compared to the limited effects of upwelling, the along-shelf coastal current from the northern shelf and the increased precipitation are crucially important to the Chl a concentration variation in the study area. These results provide new insights for predicting marine productivity in upwelling areas, i.e., multiple mechanisms, especially horizontal advection, should be considered in addition to the upwelling process.

Soil fertility and plant productivity are globally constrained by N availability. Proteins are the largest N reservoir in soils, and the cleavage of proteins into small peptides and amino acids has been shown to be the rate-limiting step in the terrestrial N cycle. However, we are still lacking a profound understanding of the environmental controls of this process. Here we show that integrated effects of climate and soil geochemistry drive protein cleavage across large scales. We measured gross protein depolymerization rates in mineral and organic soils sampled across a 4000 km long European transect covering a wide range of climates, geologies and land uses. Based on structural equation models we identified that soil organic N cycling was strongly controlled by substrate availability, e.g., by soil protein content. Soil geochemistry was a secondary predictor, by controlling protein stabilization mechanisms and protein availability. Precipitation was identified as the main climatic control on protein depolymerization, by affecting soil weathering and soil organic matter accumulation. In contrast, land use was a poor predictor of protein depolymerization. Our results highlight the need to consider geology and precipitation effects on soil geochemistry when estimating and predicting soil N cycling at large scales.

Surface waves and internal tides have a great contribution to vertical mixing processes in the upper ocean. In this study, three mixing schemes, including non-breaking surface-wave-generated turbulent mixing, mixing induced by the wave transport flux residue and internal-tide-generated turbulent mixing, are introduced to study the effects surface waves and internal tides on vertical mixing. The three schemes are jointly incorporated into the Marine Science and Numerical Modeling (MASNUM) ocean circulation model as a part of the vertical diffusive terms, which are calculated by the surface wave parameters simulated from the MASNUM wave model and the surface amplitudes of the mode-1 M2 internal tides extracted from satellite altimetry data using a two-dimensional plane wave fit method. The effects of the mixing schemes on Indian Ocean modeling are tested by five climatological experiments. The surface waves and internal tides enhance the vertical mixing processes in the sea surface and ocean interior, respectively. The combination of the mixing schemes is able to strengthen the vertical water exchange and draw more water from the sea surface to the ocean interior. The simulated results show significant improvement in the thermal structure, mixed layer depth and surface currents if the three schemes are all adopted.

Semidwarf wheat contributes to significant yield increase worldwide, however, few dwarf cultivars of wheat are cultivated due to grain yield penalty. In this study, a new dwarf wheat Triticum aestivum L., cv. Xiaoyan 101, was investigated to explore its photosynthetic performance and yield potential. In the comparison of the semidwarf wheat cultivars, Jing 411 and Xiaoyan 101, although the first three leaves (including flag leaves) did not differ significantly in both genotypes, Xiaoyan 101 conferred a higher content of photosynthetic pigments and higher photochemical efficiency but had lower contents of hydrogen peroxide and malondialdehyde in lower leaves in the canopy. In addition, the antioxidant enzymes-encoding genes were upregulated while the senescence-associated genes (TaSAG3, TaSAG5, TaSAG7, and TaSAG12) were downregulated in lower leaves in the canopy of Xiaoyan 101. Ultimately, Xiaoyan 101 produced approximate or even higher grain yield than the local semidwarf wheat varieties. Therefore, it is possible to breed dwarf wheat with enhanced photosynthetic activity but without yield sacrifice.

An efficient recognition and extraction of the estuarine turbidity maximum zone (TMZ) is important for studying terrestrial hydrological processes. Although many studies relevant to the TMZ have been conducted worldwide, the extraction methods and criteria used to describe the TMZ vary significantly both spatially and temporally. To improve the applicability of the methods adopted in previous studies and to develop a novel model to accurately extract the TMZ in multiple estuaries and different seasons from remote-sensing imageries, this study estimated the total suspended solid (TSS) and chlorophyll a (Chl a) concentrations in three estuaries. These were the Pearl River estuary (PRE), the Hanjiang River estuary (HRE), and the Moyangjiang River estuary (MRE) of Guangdong Province, China. The spatial distribution characteristics of the TSS and Chl a concentrations were analyzed. A nearly opposite association was found between the TSS and Chl a concentrations in the three estuaries, particularly in the PRE. The regions with high (low) TSS concentrations had relatively low (high) Chl a concentrations and, therefore, a turbidity maximum zone index (TMZI), defined as the ratio of the difference and sum of the logarithmic transformation of the TSS and Chl a concentrations, was firstly proposed. By calculating the TMZI values in the PRE on 20 November 2004 (low-flow season), it was found that the criterion TMZI>0.2 could be used to identify the TMZs of the PRE effectively. The TMZ extraction results were generally consistent with the visual-interpretation results. The area-based accuracy measures showed that the quality (Q) of the extraction reached 0.8429. The same criterion was applied in the PRE on 18 October 2015 (high-flow season), and high accuracy and consistency across seasons were observed (Q=0.8171). The western shoal of the PRE was the main distribution area of TMZs. Extracting TMZs by the newly proposed index performed well in different estuaries and on different dates (HRE on 13 August 2008 in the high-flow season and MRE on 6 December 2013 in the low-flow season). Compared to the previous fixed threshold of TSS or turbidity methods, extracting the TMZ using the TMZI had higher accuracy and better applicability (Q: 0.1046–0.4770 vs. 0.8171–0.8429). Evidently, this unified TMZI is potentially an optimized method for the global monitoring and extraction of TMZs of estuaries from different satellite remote-sensing imageries. It can be used to help the understanding of the spatial and temporal variation in TMZs and estuarine processes at regional and global scales as well as improve the management and sustainable development of regional society and the natural environment.

Theoretical models of the Earth's atmosphere adhere to an underlying concept of flow driven by radiative transfer and the nature of the surface over which the flow is taking place: heat from the sun and/or anthropogenic sources are the sole sources of energy driving atmospheric constituent transport. However, another source of energy is prevalent in the human environment at the very local scale – the transfer of kinetic energy from moving vehicles to the atmosphere. We show that this source of energy, due to being co-located with combustion emissions, can influence their vertical distribution to the extent of having a significant influence on lower-troposphere pollutant concentrations throughout North America. The effect of vehicle-induced turbulence on freshly emitted chemicals remains notable even when taking into account more complex urban radiative transfer-driven turbulence theories at high resolution. We have designed a parameterization to account for the at-source vertical transport of freshly emitted pollutants from mobile emissions resulting from vehicle-induced turbulence, in analogy to sub-grid-scale parameterizations for plume rise emissions from large stacks. This parameterization allows vehicle-induced turbulence to be represented at the scales inherent in 3D chemical transport models, allowing this process to be represented over larger regions than is currently feasible with large eddy simulation models. Including this sub-grid-scale parameterization for the vertical transport of emitted pollutants due to vehicle-induced turbulence in a 3D chemical transport model of the atmosphere reduces pre-existing North American nitrogen dioxide biases by a factor of 8 and improves most model performance scores for nitrogen dioxide, particulate matter, and ozone (for example, reductions in root mean square errors of 20 %, 9 %, and 0.5 %, respectively).

To explore the role of receptor-like kinases in the regulation of photosynthesis, an uncharacterized TaRKL1 encoding a receptor-like cytoplasmic kinase was investigated in Triticum aestivum cv. Xiaoyan 101 with Barley stripe mosaic virus-induced gene silencing system (BSMV-VIGS). The results showed that the CO2 assimilation rate, stomatal conductance, and transpiration rate were significantly lower in the BSMV:TaRKL1 plants than those in the BSMV:γ00 plants (control). Moreover, the maximum photochemical efficiency and electron transport flux decreased while the dissipated energy flux was enhanced in the BSMV:TaRKL1 plants compared to the control. Additionally, the contents of chlorophylls and carotenoids were reduced in the BSMV:TaRKL1 plants. However, the hydrogen peroxide content was significantly enhanced in the BSMV:TaRKL1 plants, which resulted from lower ascorbate peroxidase activity. Consistent with the inhibition of photosynthesis, the transcription levels of the photosynthesis-related, antioxidant enzymes, senescence-associated genes, and four abscisic acid biosynthesis genes were downregulated substantially. Collectively, this study for the first time showed that TaRKL1 regulates photosynthesis and H2O2 homeostasis. It may be a potential target gene for radiation-use efficiency improvement in wheat.

The purpose of this study is to determine the chemical composition of the essential oils of Cinnamomum camphora (L.) Presl leaves (CCPL) from 5 different habitats in China by GC-MS, and to evaluate their antimicrobial activities against 3 foodborne pathogens, using a paper disc diffusion method. A total of 30 compounds were identified with a predominance of oxygenated monoterpenes, including linalool (42.65%-96.47%), eucalyptol (39.07%-55.35%) and camphor (26.08%) as well as monoterpene hydrocarbons such as sabinene (6.18%-12.93%) and α-terpineol (8.19%-13.81%). Through cluster analysis, CCPL from 5 different habitats can be well divided into 2 categories. Combining with principal component analysis, the habitats can be better correlated with the chemical constituents of the essential oils. The antimicrobial activities of 5 extracted essential oils against 2 gram-negative bacteria and one gram-positive bacteria were assessed. It showed that the essential oil extracted from the CCPL harvested in Jinxi had the strongest antibacterial property. The results of this study provided basis for resource identification of CCPL and quality difference identification of essential oils. Research on the antibacterial properties of several pathogenic strains has proved its application value as a natural food preservative.

Emergency response is the critical phase in disaster management, which can save lives and reduce losses by useful, accurate, and timely information. The surveying and mapping authorities at all levels are making great efforts to meet the increasing demand for geospatial data in disaster and risk management. In this paper, it takes the Sichuan province of China as an example. It presents a geospatial information based emergency response system for geological disasters from the perspective of the provincial mapping authority. The scheme of the response system aims to solve many problems that arose in practical disaster management and to meet the requirements of public safety and government management by geospatial information and services. Built on historical experience and improved through practical application, the system has now effectively improved the workflow in all phases of emergency response. The paper discusses the critical contents of the system’s general framework in terms of emergency mechanism, GIS technology, geospatial data, emergency equipment, and professional teams. A case study is applied in this paper to explain how the system makes its function. The end of the article gives an analysis of its benefits and disadvantages and a comparison with other similar systems.

Casing treatment has been broadly used as a prudent passive flow control technique to improve the stall margin with a small drop in efficiency. The effect of grooves in certain details is overlooked however, different grooves shape (angels and location) has a remarkable effect on the controlling impact. In the current research work, an investigation on the effect of fillet and chamfer corners of rectangular circumferential grooves with various tip gap height on the performance of casing treatment is carried out with the help of CFD simulation. The performance of different models of grooves with various tip gap height on NASA rotor 37 is investigated by discretizing 3D RANS equations based on finite volume technique. Rectangular circumferential grooves casing treatment (CGCT) profile and smooth wall casing performances are evaluated. Moreover, the adiabatic efficiencies and the stall margins of smooth wall casing, rectangular grooves and rectangular grooves with fillet and chamfer corners are compared to assess the impacts of profiles of grooves on the stability and performance of axial flow compressor with different tip gaps. The stall margin of models 1–6 increased by 4.39 %, 2.52 %, 2.16 %, 1.75 %, 1.69 % and 2.06 % respectively. While the adiabatic efficiency of the models 1–6 decreased by 0.9 %, 1.01 %, 1.08 %, 1.12 %, 1.22 % and 1.16 % respectively.

Despite its clear importance, the monitoring of atmospheric ammonia, including its sources, sinks, and links to the greater nitrogen cycle, remains limited. Satellite data are helping to fill the gap in monitoring from sporadic conventional ground- and aircraft-based observations to better inform policymakers and assess the impact of any ammonia-related policies. Presented is a description and survey that demonstrate the capabilities of the Cross-track Infrared Sounder (CrIS) ammonia product for monitoring, air quality forecast model evaluation, dry deposition estimates, and emission estimates from an agricultural hotspot. For model evaluation, while there is a general agreement in the spatial allocation of known major agricultural ammonia hotspots across North America, the satellite observations show some high-latitude regions during peak forest fire activity often have ammonia concentrations approaching those in agricultural hotspots. The CrIS annual ammonia dry depositions in Canada (excluding the territories) and the US have average and annual variability values of ∼0.8±0.08 and ∼1.23±0.09 Tg N yr−1, respectively. These satellite-derived dry depositions of reactive nitrogen from NH3 with NO2 show an annual ratio of NH3 compared to their sum (NH3+NO2) of ∼82 % and ∼55 % in Canada and the US, respectively. Furthermore, we show the use of CrIS satellite observations to estimate annual and seasonal emissions near Lethbridge, Alberta, Canada, a region dominated by high-emission concentrated animal feeding operations (CAFOs); the satellite annual emission estimate of 37.1±6.3 kt yr−1 is at least double the value reported in current bottom-up emission inventories for this region.

Urban information extraction from satellite based remote sensing data could provide the basic scientific decision-making data for the construction and management of future cities. In particular, long-term satellite based remote sensing such as Landsat observations provides a rich source of data for urban area mapping. Urban area mapping based on the single-temporal Landsat observations is vulnerable to data quality (such as cloud coverage and stripe), and it is difficult to extract urban areas accurately. The composite of dense time series Landsat observations can significantly reduce the effect of data quality on urban area mapping. Multidimensional array is currently effective theory for geographic big data analysis and management, providing a theoretical basis for the composite of dense time series Landsat observations. Google Earth Engine (GEE) not only provides rich satellite based remote sensing data for the composite of dense time series data, but also has powerful massive data analysis capabilities. In the study, we chose Random Forest (RF) algorithm for the urban area extraction owing to its stable performance, high classification accuracy and feature importance evaluation. In this work, the study area is located in the central part of the city of Beijing, China. Our main data source is all Landsat8 OLI images in Beijing (path/row: 123/32) in 2017.Based on the multidimensional array for geographic big data theory and the GEE cloud computing platform, four commonly used reducer methods are selected to composite the annual dense time series Landsat 8 OLI data. After collecting the training samples, RF algorithm was selected for supervised classification, feature importance evaluation and accuracy verification for urban area mapping. The results showed that 1), compared with the single temporal image of Landsat 8 OLI, the quality of annual composite image was improved obviously, especially for urban extraction in cloudy areas; 2) for the evaluation results of feature importance based on RF algorithm, Coastal, Blue, NIR, SWIR1 and SWIR2 bands were the more important characteristic bands, while the Green and Red bands were comparatively less important; 3) the annual composite images obtained by the ee.Reducer.min, ee.Reducer.max, ee.Reducer.mean and ee.Reducer.median methods were classified and accuracy verification was carried out using the verification points. The overall accuracy of the urban area mapping reached 0.805, 0.820, 0.868 and 0.929, respectively. In summary, the ee.Reducer.median method is a suitable method for annual dense time series Landsat image composite, which could improve the data quality, and ensure the difference of features and the higher accuracy of urban area mapping.

The solid-phase peptide synthesis (SPPS) strategy, as the main procedure of peptide manufacturing, has a profound impact on the research of peptides. The rapid development of nanotechnology is expected to promote the evolution of the solid phase to miniaturization, convenience and multi-function. In this work, silica-coated magnetic ferriferous oxide (Fe3O4) nanoparticles (MNP/SiO2) were used as new generation of solid phase for SPPS in Fmoc chemistry. The superparamagnetic solid phase facilitated a multi-step synthesis reaction due to its magnetic maneuverability, which could efficiently separate reaction intermediates, and were then redispersed in the next-step synthetic solution for peptide elongation. In addition, this strategy further allowed the simultaneous acquisition of magnetic nanoparticle–peptide conjugates as available bioprobes to examine the biological function of synthesized peptides. The feasibility of this novel magnetic nanoparticle-based solid phase peptide synthesis (MNP-SPPS) strategy was confirmed by the synthesis of arginine-glycine-aspartic acid-glycine-glycine (RGDGG) as a model pentapeptide. The simultaneously acquired magnetic nanoparticle–peptide conjugates (RGDGG-MNP/SiO2), possessing excellent biological functions, could be recognized and further internalized by tumor cells through receptor-mediated endocytosis, thereby achieving the extraction and removal of malignant cells in vitro under an external magnetic field. The RGDGG-MNP/SiO2 could further be used as a contrasting agent for tumor-targeting T2 magnetic resonance imaging in vivo. This study developed a novel MNP-SPPS strategy that could realize the simple synthesis of peptides, and the synchronously obtained nanoprobes could quickly detect the biological activity of the target synthetic sequence. This strategy may have broad application prospects in combinatorial chemistry and the construction of peptide libraries in the future.

Because of their high specificity and low side effects, protein drugs possess a substantial global market. However, the low bioavailability of protein is still a major obstacle to their expanded applications, which is expected to be answered with proper protein formulations. Taking corneal neovascularization (CNV) as an example, we demonstrated a co-assembled system of hexa-histidine and Ava (Avastin) with metal ions (HmA@Ava) could cross the cornea, the most important bio-barrier during the treatment of most diseases of the anterior segment in clinics. We found that the nanosized HmA@Ava efficiently encapsulated Ava with impressive loading capacity without destroying the bioactivity of Ava and assisted Ava penetration through the corneal barriers to effectively inhibit CNV development in an alkali burn rat model with sustained and pH-dependent Ava release. Our results suggested that the co-assembled strategy of protein and HmA is a proper formulation to protein drugs, with promising penetration ability to deliver protein across bio-barriers, which could open a path for topical administration of protein drugs for treatment of various ocular diseases and hold enormous potential for delivery of therapeutic proteins not only for ocular diseases but also for other diseases that require protein treatment.

Atmospheric dimethyl sulfide, DMS(g), is a climatically important sulfur compound and is the main source of biogenic sulfate aerosol in the Arctic atmosphere. DMS(g) production and emission to the atmosphere increase during the summer due to the greater ice-free sea surface and higher biological activity. We implemented DMS(g) in the Environment and Climate Change Canada’s (ECCC) online air quality forecast model, GEM-MACH (Global Environmental Multiscale–Modelling Air quality and CHemistry), and compared model simulations with DMS(g) measurements made in Baffin Bay and the Canadian Arctic Archipelago in July and August 2014. Two seawater DMS(aq) datasets were used as input for the simulations: (1) a DMS(aq) climatology dataset based on seawater concentration measurements (Lana et al., 2011) and (2) a DMS(aq) dataset based on satellite detection (Galí et al., 2018). In general, GEM-MACH simulations under-predict DMS(g) measurements, which is likely due to the negative biases in both DMS(aq) datasets. However, a higher correlation and smaller bias were obtained with the satellite dataset. Agreement with the observations improved when climatological values were replaced by DMS(aq) in situ values that were measured concurrently with atmospheric observations over Baffin Bay and the Lancaster Sound area in July 2014. The addition of DMS(g) to the GEM-MACH model resulted in a significant increase in atmospheric SO2 for some regions of the Canadian Arctic (up to 100 %). Analysis of the size-segregated sulfate aerosol in the model shows that a significant increase in sulfate mass occurs for particles with a diameter smaller than 200 nm due to the formation and growth of biogenic aerosol at high latitudes (>70∘ N). The enhancement in sulfate particles is most significant in the size range from 50 to 100 nm; however, this enhancement is stronger in the 200–1000 nm size range at lower latitudes (∘ N). These results emphasize the important role of DMS(g) in the formation and growth of fine and ultrafine sulfate-containing particles in the Arctic during the summertime.

Background The aim of this network meta‐analysis was to compare the performance of blue dye alone or in combination with radioisotope (technetium‐99m, Tc) with three novel techniques for sentinel lymph node detection in breast cancer: indocyanine green fluorescence (ICG), superparamagnetic iron oxide (SPIO) nanoparticles and contrast‐enhanced ultrasound imaging (CEUS). Methods PubMed, Embase, the Cochrane Library, China Knowledge Research Integrated Database, ClinicalTrials.gov and OpenGrey databases were searched up to 31 November 2017, without language restriction. Studies that compared the detection performance of at least one of the novel methods (ICG, SPIO and CEUS) with that of traditional methods (blue dye and/or radioisotope) were included in network meta‐analysis. Results Thirty‐five studies were included. Pooled risk ratios (RRs) for Tc (1·09, 95 per cent c.i. 1·04 to 1·15), ICG (1·12, 1·07 to 1·16) and SPIO (1·09, 1·01 to 1·18) showed statistically better performance in detecting sentinel lymph nodes than blue dye alone. ICG had the lowest false‐negative rate, with a RR of 0·29 (0·16 to 0·54), followed by Tc (RR 0·44, 0·20 to 0·96) and SPIO (RR 0·45, 0·14 to 1·45), with blue dye alone as the reference group. Conclusion SPIO or ICG alone are superior to blue dye alone and comparable to the standard dual‐modality technique of blue dye with Tc.

In order to explore the association of long-term high light (HL) with leaf senescence in wheat, two wheat genotypes Xiaoyan 54 (HL-tolerant) and Jing 411 (HL-sensitive) grown in low light were subjected to HL for 2-8 d. The results showed that 6-8 d of HL led to dramatic decline of chlorophyll content, photochemical efficiency, and activity of Rubisco and antioxidant enzymes. Meanwhile, the content of malondialdehyde (MDA), soluble proteins, soluble sugars, superoxide anion, and ascorbic acid increased markedly. Additionally, the expression of senescence-associated genes (SAGs) was induced by HL. Xiaoyan 54 accumulated less MDA, soluble sugars, and superoxide anions but showed a higher ratio of reduced to oxidized ascorbic acid than that in Jing 411 under long-term HL stress. Moreover, most of the assayed SAGs were less induced in Xiaoyan 54 than that in Jing 411. Altogether, the reduction of antioxidant enzyme activities and accumulation of soluble sugars may result in long-term HL-induced leaf senescence.

We examine the potential benefits of very high resolution for air-quality forecast simulations using a nested system of the Global Environmental Multiscale – Modelling Air-quality and Chemistry chemical transport model. We focus on simulations at 1 and 2.5 km grid-cell spacing for the same time period and domain (the industrial emissions region of the Athabasca oil sands). Standard grid cell to observation station pair analyses show no benefit to the higher-resolution simulation (and a degradation of performance for most metrics using this standard form of evaluation). However, when the evaluation methodology is modified, to include a search over equivalent representative regions surrounding the observation locations for the closest fit to the observations, the model simulation with the smaller grid-cell size had the better performance. While other sources of model error thus dominate net performance at these two resolutions, obscuring the potential benefits of higher-resolution modelling for forecasting purposes, the higher-resolution simulation shows promise in terms of better aiding localized chemical analysis of pollutant plumes, through better representation of plume maxima.

In high altitude and Mach number, the inflow air with the high temperature will influence on the aero-engine performance while the mass injection pre-compressor cooling (MIPCC) technology is one of the problem-solving ways to reduce high temperature. To explore the convection coupling process between droplet and inflow air, the compressible Reynolds average N-S equations in the compressor coupled with the pre-cooling section is solved by the finite volume method to analyze its performance changes at different water injection rates and droplet sizes. Results show that, in the flight of 3.5 Mach number, the larger water injection rate easily form the shock wave due to the disturbance of droplets in the pre-cooling section. Furthermore, the temperature on the pressure surface near the trailing edge of the rotor blade aggravates along the radial migration, leading to uneven temperature distribution in the radial direction. Within the water injection rates of 0-8% and the particle sizes of 10-20 µm, the inflow mass flow of air improves by 15.3-31.4%; the temperature ratio of compressor drops by 3.6-16.14%, which results in the decrease of specific compression work of the compressor and the changing trend from “increasing” to “decreasing” for the compressor efficiency.

Flow characteristics inside the compressor are of great importance for aeroengine performance under the high adverse pressure gradient. To meet the need for quick performance estimation, the numerical simulation is a meaningful investigation method to predict the similarity flow characteristics of aeroengine compressor at high Mach flight. Thus, this paper aims to satisfy the accuracy of compressor flow field at high altitude based on the similarity criterion. The accuracy for solution results by the application of the similarity criterion and the derivation of compressor boundary conditions is verified with the experimental data. Then, the parametric definitions of air intake are put forward to get the inlet boundary conditions of compressor. The comparative simulation results are conducted between similarity and prototype flow fields at design boundary conditions. The results show that among the most important dimensionless criterion is Mach number at high-speed flow, so the same equivalent mass flow and equivalent speed are recommended. In addition, the flow characteristics of the compressor at high altitude and high Mach number have a good similarity. Consequently, it can extend to further study compressor performance of aeroengine at different flight altitudes and Mach numbers.

The safety and stability of lining structures are core concerns of tunnel and underground engineering. It is crucial to determine whether a lining structure would crack and which direction the crack would expand with seismic excitation. In previous literature, the principle based on stress and strain has been widely used to predict the seismic damage of lining structures, whereas it cannot specify the cracking modes. Taking account of that deficiency, this paper introduces the strain energy density ratio (SEDR) principle and proposes a seismic damage prediction method for lining structures, which can precisely predict the crack positions and expansion directions. Moreover, numerical simulations of the typical seismic damage sections of two tunnels in the Great Wenchuan Earthquake and a calculating example of the theoretical equations are conducted to verify the proposed method. In summary, the numerical simulation results show that the arch springing cracks first, and the invert cracks next; then the cracks expand to the spandrel, and finally, they form oblique cracks, annular cracks, and longitudinal cracks, whose positions and patterns are in accordance with the field investigation results. In terms of the calculating example results, the obtained two-fold SEDR and cracking angle θ are 1.87 and −6.28°, respectively, which are consistent with the numerical simulation results. Therefore, one can see that the proposed seismic damage prediction method based on the SEDR principle is quite accurate. This method can be used to predict the seismic damage of lining structures and provide a reference for the research of the damage mechanism of tunnels.

The oil sands (OS) of Alberta, Canada, which are classified as unconventional oil, are the third-largest oil reserves in the world. We describe here a 6-year effort to improve the emissions data used for air quality (AQ) modeling of the roughly 100 km  ×  100 km oil extraction and processing industrial complex operating in the Athabasca Oil Sands Region (AOSR) of northeastern Alberta. This paper reviews the national, provincial, and sub-provincial emissions inventories that were available during the three phases of the study, supplemented by hourly SO2 and NOx emissions and stack characteristics for larger point sources measured by a continuous emission monitoring system (CEMS), as well as daily reports of SO2 from one AOSR facility for a 1-week period during a 2013 field campaign when the facility experienced upset conditions. Next it describes the creation of several detailed hybrid emissions inventories and the generation of model-ready emissions input files for the Global Environmental Multiscale–Modelling Air quality and CHemistry (GEM-MACH) AQ modeling system that were used during the 2013 field study and for various post-campaign GEM-MACH sensitivity studies, in particular for a high-resolution model domain with 2.5 km grid spacing covering much of western Canada and centered over the AOSR. Lastly, it compares inventory-based bottom-up emissions with aircraft-observation-based top-down emissions estimates. Results show that emissions values obtained from different data sources can differ significantly, such as a possible 10-fold difference in PM2.5 emissions and approximately 40 and 20 % differences for total VOC (volatile organic compound) and SO2 emissions. A novel emissions-processing approach was also employed to allocate emissions spatially within six large AOSR mining facilities in order to address the urban-scale spatial extent of the facilities and the high-resolution 2.5 km model grid. Gridded facility- and process-specific spatial surrogate fields that were generated using spatial information from GIS (geographic information system) shapefiles and satellite images were used to allocate non-smokestack emissions for each facility to multiple grid cells instead of treating these emissions as point sources and allocating them to a single grid cell as is normally done. Facility- and process-specific temporal profiles and VOC speciation profiles were also developed. The pre-2013 vegetation and land-use databases normally used to estimate biogenic emissions and meteorological surface properties were modified to account for the rapid change in land use in the study area due to marked, year-by-year changes in surface mining activities, including the 2013 opening of a new mine. Lastly, mercury emissions data were also processed in addition to the seven criteria-air-contaminant (CAC) species (NOx, VOC, SO2, NH3, CO, PM2.5, and PM10) to support AOSR mercury modeling activities. Six GEM-MACH modeling papers in this special issue used some of these new sets of emissions and land-use input files.

Environment and Climate Change Canada's online air quality forecasting model, GEM-MACH, was extended to simulate atmospheric concentrations of benzene and seven polycyclic aromatic hydrocarbons (PAHs): phenanthrene, anthracene, fluoranthene, pyrene, benz(a)anthracene, chrysene, and benzo(a)pyrene. In the expanded model, benzene and PAHs are emitted from major point, area, and mobile sources, with emissions based on recent emission factors. Modelled PAHs undergo gas–particle partitioning (whereas benzene is only in the gas phase), atmospheric transport, oxidation, cloud processing, and dry and wet deposition. To represent PAH gas–particle partitioning, the Dachs–Eisenreich scheme was used, and we have improved gas–particle partitioning parameters based on an empirical analysis to get significantly better gas–particle partitioning results than the previous North American PAH model, AURAMS-PAH. Added process parametrizations include the particle phase benzo(a)pyrene reaction with ozone via the Kwamena scheme and gas-phase scavenging of PAHs by snow via vapour sorption to the snow surface.The resulting GEM-MACH-PAH model was used to generate the first online model simulations of PAH emissions, transport, chemical transformation, and deposition for a high-resolution domain (2.5 km grid cell spacing) in North America, centred on the PAH data-rich region of southern Ontario, Canada and the northeastern US. Model output for two seasons was compared to measurements from three monitoring networks spanning Canada and the US Average spring–summertime model results were found to be statistically unbiased from measurements of benzene and all seven PAHs. The same was true for the fall–winter seasonal mean, except for benzo(a)pyrene, which had a statistically significant positive bias. We present evidence that the benzo(a)pyrene results may be ameliorated via further improvements to particulate matter and oxidant processes and transport. Our analysis focused on four key components to the prediction of atmospheric PAH levels: spatial variability, sensitivity to mobile emissions, gas–particle partitioning, and wet deposition. Spatial variability of PAHs ∕ PM2.5 at a 2.5 km resolution was found to be comparable to measurements. Predicted ambient surface concentrations of benzene and the PAHs were found to be critically dependent on mobile emission factors, indicating the mobile emissions sector has a significant influence on ambient PAH levels in the study region. PAH wet deposition was overestimated due to additive precipitation biases in the model and the measurements. Our overall performance evaluation suggests that GEM-MACH-PAH can provide seasonal estimates for benzene and PAHs and is suitable for emissions scenario simulations.

Estimates of potential harmful effects on ecosystems in the Canadian provinces of Alberta and Saskatchewan due to acidifying deposition were calculated, using a 1-year simulation of a high-resolution implementation of the Global Environmental Multiscale-Modelling Air-quality and Chemistry (GEM-MACH) model, and estimates of aquatic and terrestrial ecosystem critical loads. The model simulation was evaluated against two different sources of deposition data: total deposition in precipitation and total deposition to snowpack in the vicinity of the Athabasca oil sands. The model captured much of the variability of observed ions in wet deposition in precipitation (observed versus model sulfur, nitrogen and base cation R2 values of 0.90, 0.76 and 0.72, respectively), while being biased high for sulfur deposition, and low for nitrogen and base cations (slopes 2.2, 0.89 and 0.40, respectively). Aircraft-based estimates of fugitive dust emissions, shown to be a factor of 10 higher than reported to national emissions inventories (Zhang et al., 2018), were used to estimate the impact of increased levels of fugitive dust on model results. Model comparisons to open snowpack observations were shown to be biased high, but in reasonable agreement for sulfur deposition when observations were corrected to account for throughfall in needleleaf forests. The model–observation relationships for precipitation deposition data, along with the expected effects of increased (unreported) base cation emissions, were used to provide a simple observation-based correction to model deposition fields. Base cation deposition was estimated using published observations of base cation fractions in surface-collected particles (Wang et al., 2015).Both original and observation-corrected model estimates of sulfur, nitrogen, and base cation deposition were used in conjunction with critical load data created using the NEG-ECP (2001) and CLRTAP (2017) methods for calculating critical loads, using variations on the Simple Mass Balance model for terrestrial ecosystems, and the Steady State Water Chemistry and First-order Acidity Balance models for aquatic ecosystems. Potential ecosystem damage was predicted within each of the regions represented by the ecosystem critical load datasets used here, using a combination of 2011 and 2013 emissions inventories. The spatial extent of the regions in exceedance of critical loads varied between 1  ×  104 and 3.3  ×  105 km2, for the more conservative observation-corrected estimates of deposition, with the variation dependent on the ecosystem and critical load calculation methodology. The larger estimates (for aquatic ecosystems) represent a substantial fraction of the area of the provinces examined.Base cation deposition was shown to be sufficiently high in the region to have a neutralizing effect on acidifying deposition, and the use of the aircraft and precipitation observation-based corrections to base cation deposition resulted in reasonable agreement with snowpack data collected in the oil sands area. However, critical load exceedances calculated using both observations and observation-corrected deposition suggest that the neutralization effect is limited in spatial extent, decreasing rapidly with distance from emissions sources, due to the rapid deposition of emitted primary dust particles as a function of their size. We strongly recommend the use of observation-based correction of model-simulated deposition in estimating critical load exceedances, in future work.

We evaluate four high-resolution model simulations of pollutant emissions, chemical transformation, and downwind transport for the Athabasca oil sands using the Global Environmental Multiscale – Modelling Air-quality and Chemistry (GEM-MACH) model, and compare model results with surface monitoring network and aircraft observations of multiple pollutants, for simulations spanning a time period corresponding to an aircraft measurement campaign in the summer of 2013. We have focussed here on the impact of different representations of the model's aerosol size distribution and plume-rise parameterization on model results. The use of a more finely resolved representation of the aerosol size distribution was found to have a significant impact on model performance, reducing the magnitude of the original surface PM2.5 negative biases 32 %, from −2.62 to −1.72 µg m−3. We compared model predictions of SO2, NO2, and speciated particulate matter concentrations from simulations employing the commonly used Briggs (1984) plume-rise algorithms to redistribute emissions from large stacks, with stack plume observations. As in our companion paper (Gordon et al., 2017), we found that Briggs algorithms based on estimates of atmospheric stability at the stack height resulted in under-predictions of plume rise, with 116 out of 176 test cases falling below the model : observation 1 : 2 line, 59 cases falling within a factor of 2 of the observed plume heights, and an average model plume height of 289 m compared to an average observed plume height of 822 m. We used a high-resolution meteorological model to confirm the presence of significant horizontal heterogeneity in the local meteorological conditions driving plume rise. Using these simulated meteorological conditions at the stack locations, we found that a layered buoyancy approach for estimating plume rise in stable to neutral atmospheres, coupled with the assumption of free rise in convectively unstable atmospheres, resulted in much better model performance relative to observations (124 out of 176 cases falling within a factor of 2 of the observed plume height, with 69 of these cases above and 55 of these cases below the 1 : 1 line and within a factor of 2 of observed values). This is in contrast to our companion paper, wherein this layered approach (driven by meteorological observations not co-located with the stacks) showed a relatively modest impact on predicted plume heights. Persistent issues with over-fumigation of plumes in the model were linked to a more rapid decrease in simulated temperature with increasing height than was observed. This in turn may have led to overestimates of near-surface diffusivity, resulting in excessive fumigation.

Many stakeholders are seeking methods to reduce carbon dioxide (CO2) emissions in urban areas, but reliable, high-resolution inventories are required to guide these efforts. We present the development of a high-resolution CO2 inventory available for the Greater Toronto Area and surrounding region in Southern Ontario, Canada (area of ∼ 2.8 × 105 km2, 26 % of the province of Ontario). The new SOCE (Southern Ontario CO2 Emissions) inventory is available at the 2.5 × 2.5 km spatial and hourly temporal resolution and characterizes emissions from seven sectors: area, residential natural-gas combustion, commercial natural-gas combustion, point, marine, on-road, and off-road. To assess the accuracy of the SOCE inventory, we developed an observation–model framework using the GEM-MACH chemistry–transport model run on a high-resolution grid with 2.5 km grid spacing coupled to the Fossil Fuel Data Assimilation System (FFDAS) v2 inventories for anthropogenic CO2 emissions and the European Centre for Medium-Range Weather Forecasts (ECMWF) land carbon model C-TESSEL for biogenic fluxes. A run using FFDAS for the Southern Ontario region was compared to a run in which its emissions were replaced by the SOCE inventory. Simulated CO2 mixing ratios were compared against in situ measurements made at four sites in Southern Ontario – Downsview, Hanlan's Point, Egbert and Turkey Point – in 3 winter months, January–March 2016. Model simulations had better agreement with measurements when using the SOCE inventory emissions versus other inventories, quantified using a variety of statistics such as correlation coefficient, root-mean-square error, and mean bias. Furthermore, when run with the SOCE inventory, the model had improved ability to capture the typical diurnal pattern of CO2 mixing ratios, particularly at the Downsview, Hanlan's Point, and Egbert sites. In addition to improved model–measurement agreement, the SOCE inventory offers a sectoral breakdown of emissions, allowing estimation of average time-of-day and day-of-week contributions of different sectors. Our results show that at night, emissions from residential and commercial natural-gas combustion and other area sources can contribute > 80 % of the CO2 enhancement, while during the day emissions from the on-road sector dominate, accounting for > 70 % of the enhancement.

Atmospheric ammonia (NH3) is a short-lived pollutant that plays an important role in aerosol chemistry and nitrogen deposition. Dominant NH3 emissions are from agriculture and forest fires, both of which are increasing globally. Even remote regions with relatively low ambient NH3 concentrations, such as northern Alberta and Saskatchewan in northern Canada, may be of interest because of industrial oil sands emissions and a sensitive ecological system. A previous attempt to model NH3 in the region showed a substantial negative bias compared to satellite and aircraft observations. Known missing sources of NH3 in the model were re-emission of NH3 from plants and soils (bidirectional flux) and forest fire emissions, but the relative impact of these sources on NH3 concentrations was unknown. Here we have used a research version of the high-resolution air quality forecasting model, GEM-MACH, to quantify the relative impacts of semi-natural (bidirectional flux of NH3 and forest fire emissions) and direct anthropogenic (oil sand operations, combustion of fossil fuels, and agriculture) sources on ammonia volume mixing ratios, both at the surface and aloft, with a focus on the Athabasca Oil Sands region during a measurement-intensive campaign in the summer of 2013. The addition of fires and bidirectional flux to GEM-MACH has improved the model bias, slope, and correlation coefficients relative to ground, aircraft, and satellite NH3 measurements significantly.By running the GEM-MACH-Bidi model in three configurations and calculating their differences, we find that averaged over Alberta and Saskatchewan during this time period an average of 23.1 % of surface NH3 came from direct anthropogenic sources, 56.6 % (or 1.24 ppbv) from bidirectional flux (re-emission from plants and soils), and 20.3 % (or 0.42 ppbv) from forest fires. In the NH3 total column, an average of 19.5 % came from direct anthropogenic sources, 50.0 % from bidirectional flux, and 30.5 % from forest fires. The addition of bidirectional flux and fire emissions caused the overall average net deposition of NHx across the domain to be increased by 24.5 %. Note that forest fires are very episodic and their contributions will vary significantly for different time periods and regions.This study is the first use of the bidirectional flux scheme in GEM-MACH, which could be generalized for other volatile or semi-volatile species. It is also the first time CrIS (Cross-track Infrared Sounder) satellite observations of NH3 have been used for model evaluation, and the first use of fire emissions in GEM-MACH at 2.5 km resolution.

D-Glyceric acid (D-GA) is a glycerol derivative with various promising biological functions. This paper reports the adsorption of D-GA from aqueous solution using a strong basic resin. The effect of pH on the uptake of D-GA was studied, and several models were used to investigate the interactions of D-GA and the resin. A theoretical model based on ion exchange and adsorption was developed to fit the isotherms under various pH or temperatures. Kinetic experiments under different initial D-GA concentrations were also performed to define the controlling mechanism of the overall adsorption process. The results showed that the uptake process of D-GA was controlled by the rate of D-GA diffusion through the polymeric matrix of the resin. This study provides valuable information and theoretical support for the scale-up and optimization of operating conditions for the recovery of D-GA.

This paper exemplified a way to increase pressure ratio and improve efficiency with addition of multi splitters in centrifugal impeller with a vaneless diffuser. DDA 404-III back swept impeller of centrifugal compressor, studied through experiment is modified with the addition of splitters blades and a sample impeller is designed and analyzed with big splitter close to pressure surface and small splitter close to suction surface. Keeping all flow conditions and impeller definitions, same as experimentally validated impeller, in order to investigate effects of the location of the splitters between two main blades. It was observed that total pressure ratio is increased from 4.1 to 4.5 with 2 % increase in efficiency with big splitter close to pressure surface of main blade and small splitter close to suction surface of main blade. It was observed that relative Mach number reduces at inlet of modified impeller.

PPARD is involved in multiple biological processes, especially for those associated with energy metabolism. PPARD regulates lipid metabolism through up-regulate expression of genes associating with adipogenesis. This makes PPARD a significant candidate gene for production traits of livestock animals. Association studies between PPARD polymorphisms and production traits have been reported in pigs but are limited for other animals, including cattle. Here, we investigated the expression profile and polymorphism of bovine PPARD as well as their association with growth traits in Chinese cattle. Our results showed that the highest expression of PPARD was detected in kidney, following by adipose, which is consistent with its involvement in energy metabolism. Three SNPs of PPARD were detected and used to undergo selection pressure according the result of Hardy–Weinberg equilibrium analysis (P < PIC < 0.5), indicating their relatively high selection potential. Association analysis suggested that individuals with the GAAGTT combined genotype of three SNPs detected showed optimal values in all of the growth traits analyzed. These results revealed that the GAAGTT combined genotype of three SNPs detected in the bovine PPARD gene was a significant potential genetic marker for marker-assisted selection in Chinese cattle. However, this should be further verified in larger populations before being applied to breeding.

Fully quantifying the influence of vegetation on atmospheric chemistry remains challenging. Here, the authors show that forest canopy shading and turbulence significantly modify air pollution throughout the atmospheric boundary layer, and must be taken into account in models of the atmosphere.

Abstract Quantum materials such as antiferromagnets or superconductors are complex in that chemical, electronic, and spin phenomena at atomic scales can manifest in their collective properties. Although there are some clues for designing such materials, they remain mainly unpredictable. In this work, we find that enhancement of transition temperatures in BaFe2As2-based crystals are caused by removing local-lattice strain and electronic-structure disorder by thermal annealing. While annealing improves Néel-ordering temperature in BaFe2As2 crystal (T N = 132 K to 136 K) by improving in-plane electronic defects and reducing overall a-lattice parameter, it increases superconducting-ordering temperature in optimally cobalt-doped BaFe2As2 crystal (T c = 23 to 25 K) by precipitating-out the cobalt dopants and giving larger overall a-lattice parameter. While annealing improves local chemical and electronic uniformity resulting in higher T N in the parent, it promotes nanoscale phase separation in the superconductor resulting in lower disparity and strong superconducting band gaps in the dominant crystal regions, which lead to both higher overall T c and critical-current-density, J c .

In predictability problem research, the conditional nonlinear optimal perturbation (CNOP) describes the initial perturbation that satisfies a certain constraint condition and causes the largest prediction error at the prediction time. The CNOP has been successfully applied in estimation of the lower bound of maximum predictable time (LBMPT). Generally, CNOPs are calculated by a gradient descent algorithm based on the adjoint model, which is called ADJ-CNOP. This study, through the two-dimensional Ikeda model, investigates the impacts of the nonlinearity on ADJ-CNOP and the corresponding precision problems when using ADJ-CNOP to estimate the LBMPT. Our conclusions are that (1) when the initial perturbation is large or the prediction time is long, the strong nonlinearity of the dynamical model in the prediction variable will lead to failure of the ADJ-CNOP method, and (2) when the objective function has multiple extreme values, ADJ-CNOP has a large probability of producing local CNOPs, hence making a false estimation of the LBMPT. Furthermore, the particle swarm optimization (PSO) algorithm, one kind of intelligent algorithm, is introduced to solve this problem. The method using PSO to compute CNOP is called PSO-CNOP. The results of numerical experiments show that even with a large initial perturbation and long prediction time, or when the objective function has multiple extreme values, PSO-CNOP can always obtain the global CNOP. Since the PSO algorithm is a heuristic search algorithm based on the population, it can overcome the impact of nonlinearity and the disturbance from multiple extremes of the objective function. In addition, to check the estimation accuracy of the LBMPT presented by PSO-CNOP and ADJ-CNOP, we partition the constraint domain of initial perturbations into sufficiently fine grid meshes and take the LBMPT obtained by the filtering method as a benchmark. The result shows that the estimation presented by PSO-CNOP is closer to the true value than the one by ADJ-CNOP with the forecast time increasing.

Taking the piston of heavy commercial vehicle as an example, in-cylinder local heat transfer boundary condition is obtained through the calculation of intake, spray, combustion and exhaust process; the heat transfer boundaries of the inner oil gallery and the bottom of the piston are obtained by the transient piston injection cooling calculation; the numerical simulation of temperature field of piston is realized by the coupling of gas side, lubrication oil side and structure with consideration of the temperature’s influence on the thermal conductivity of the piston. Furthermore, the thermal deformation of the piston is analysed. Results show that the calculated values are in agreement with the experimental temperature values of the piston measuring points; The highest temperature appears at the junction of the bowl and the top surface of the piston at the exhaust valve side; The heat transfer coefficient and gas temperature at the junction of the bowl and the top surface of the piston are in high value, the in-cylinder local heat transfer is significant ; In the straight inlet pipe of the inner oil gallery, the temperature of the lube oil is the lowest while heat transfer coefficient is the highest, so the cooling effect is the most obvious; The radial expansion deformation is large at the top and bottom of the piston skirt while small at the middle.

We apply time-resolved MeV electron diffraction to study the electron-lattice energy relaxation in thin film Au-insulator heterostructures. Through precise measurements of the transient Debye-Waller-factor, the mean-square atomic displacement is directly determined, which allows to quantitatively follow the temporal evolution of the lattice temperature after short pulse laser excitation. Data obtained over an extended range of laser fluences reveal an increased relaxation rate when the film thickness is reduced or the Au-film is capped with an additional insulator top-layer. This behavior is attributed to a cross-interfacial coupling of excited electrons in the Au film to phonons in the adjacent insulator layer(s). Analysis of the data using the two-temperature-model taking explicitly into account the additional energy loss at the interface(s) allows to deduce the relative strength of the two relaxation channels.

The balance between turbulent transport and emissions is a key issue in understanding the formation of O3 and particulate matter with diameters less than 2.5 μm (PM2.5). Discrepancies between observed and simulated concentrations for these species have, in the past, been ascribed to insufficient turbulent mixing, particularly for atmospherically stable environments. This assumption may be simplistic – turbulent mixing deficiencies may explain only part of these discrepancies, and as turbulence parameterizations are improved, the timing of primary PM2.5 emissions may play a much more significant role in the further reduction of model error. In a study of these issues, two regional air-quality models, the Community Multi-scale Air Quality model (CMAQ, version 4.6) and A Unified Regional Air-quality Modelling System (AURAMS, version 1.4.2), were compared to observations for a domain in north-western North America. The air-quality models made use of the same emissions inventory, emissions processing system, meteorological driving model, and model domain, map projection and horizontal grid, eliminating these factors as potential sources of discrepancies between model predictions. The initial statistical comparison between the models and monitoring network data showed that AURAMS' O3 simulations outperformed those of this version of CMAQ4.6, while CMAQ4.6 outperformed AURAMS for most PM2.5 statistical measures. A process analysis of the models revealed that many of the differences between the models' results could be attributed to the strength of turbulent diffusion, via the choice of an a priori lower limit in the magnitude of vertical diffusion coefficients, with AURAMS using 0.1 m2 s−1 and CMAQ4.6 using 1.0 m2 s−1. The use of the larger CMAQ4.6 value for the lower limit of vertical diffusivity within AURAMS resulted in a similar performance for the two models (with AURAMS also showing improved PM2.5, yet degraded O3, and a similar time series as CMAQ4.6). The differences between model results were most noticeable at night, when the higher minimum turbulent diffusivity resulted in an erroneous secondary peak in predicted night-time O3. A spatially invariant and relatively high lower limit in diffusivity could not reduce errors in both O3 and PM2.5 fields, implying that other factors aside from the strength of turbulence might be responsible for the PM2.5 over-predictions. Further investigation showed that the magnitude, timing and spatial allocation of area source emissions could result in improvements to PM2.5 performance with minimal O3 performance degradation. AURAMS was then used to investigate a land-use-dependant lower limit in diffusivity of 1.0 m2 s−1 in urban regions, linearly scaling to 0.01 m2s−1 in rural areas, as employed in CMAQ5.0.1. This strategy was found to significantly improve mean statistics for PM2.5 throughout the day and mean O3 statistics at night, while significantly degrading (halving) midday PM2.5 correlation coefficients and slope of observed to model simulations. Time series of domain-wide model error statistics aggregated by local hour were shown to be a useful tool for performance analysis, with significant variations in performance occurring at different hours of the day. The use of the land-use-dependant lower limit in diffusivity was also shown to reduce the model's sensitivity to the temporal allocation of its emissions inputs. The modelling scenarios suggest that while turbulence plays a key role in O3 and PM2.5 formation in urban regions, and in their downwind transport, the spatial and temporal allocation of primary PM2.5 emissions also has a potentially significant impact on PM2.5 concentration levels. The results show the complex nature of the interactions between turbulence and emissions, and the potential of the strength of the former to mask the impact of changes in the latter.

Prochlorococcus, the smallest but most abundant marine primary producer, plays an important role in carbon cycling of the global ocean. As a phototroph, Prochlorococcus is thought to be confined to the euphotic zone, with commonly observed maximum depths of ~ 150–200 m, but here we show for the first time the substantial presence of Prochlorococcus populations in the dark ocean ("deep Prochlorococcus" hereafter). Intensive studies at the Luzon Strait in the western Pacific Ocean show that the deep Prochlorococcus populations are exported from the euphotic zone. Multiple physical processes including internal solitary waves could be responsible for the transportation. These findings reveal a novel mechanism for picoplankton carbon export other than the known mechanisms such as sinking of phytodetritus and aggregates or grazing-mediated transportation.

The offline Eulerian AURAMS (A Unified Regional Air quality Modelling System) chemical transport model was adapted to simulate airborne concentrations of seven PAHs (polycyclic aromatic hydrocarbons): phenanthrene, anthracene, fluoranthene, pyrene, benz[a]anthracene, chrysene + triphenylene, and benzo[a]pyrene. The model was then run for the year 2002 with hourly output on a grid covering southern Canada and the continental USA with 42 km horizontal grid spacing. Model predictions were compared to ~5000 24 h-average PAH measurements from 45 sites, most of which were located in urban or industrial areas. Eight of the measurement sites also provided data on particle/gas partitioning which had been modelled using two alternative schemes. This is the first known regional modelling study for PAHs over a North American domain and the first modelling study at any scale to compare alternative particle/gas partitioning schemes against paired field measurements. The goal of the study was to provide output concentration maps of use to assessing human inhalation exposure to PAHs in ambient air. Annual average modelled total (gas + particle) concentrations were statistically indistinguishable from measured values for fluoranthene, pyrene and benz[a]anthracene whereas the model underestimated concentrations of phenanthrene, anthracene and chrysene + triphenylene. Significance for benzo[a]pyrene performance was close to the statistical threshold and depended on the particle/gas partitioning scheme employed. On a day-to-day basis, the model simulated total PAH concentrations to the correct order of magnitude the majority of the time. The model showed seasonal differences in prediction quality for volatile species which suggests that a missing emission source such as air–surface exchange should be included in future versions. Model performance differed substantially between measurement locations and the limited available evidence suggests that the model's spatial resolution was too coarse to capture the distribution of concentrations in densely populated areas. A more detailed analysis of the factors influencing modelled particle/gas partitioning is warranted based on the findings in this study.

A unified regional air-quality modelling system (AURAMS) was used to investigate the effects of reductions in ammonia emissions on regional air quality, with a focus on particulate-matter formation. Three simulations of one-year duration were performed for a North American domain: (1) a base-case simulation using 2002 Canadian and US national emissions inventories augmented by a more detailed Canadian emissions inventory for agricultural ammonia; (2) a 30% North-American-wide reduction in agricultural ammonia emissions; and (3) a 50% reduction in Canadian beef-cattle ammonia emissions. The simulations show that a 30% continent-wide reduction in agricultural ammonia emissions lead to reductions in median hourly PM2.5 mass of −3 on an annual basis. The atmospheric response to these emission reductions displays marked seasonal variations, and on even shorter time scales, the impacts of the emissions reductions are highly episodic: 95th-percentile hourly PM2.5 mass decreases can be up to a factor of six larger than the median values. A key finding of the modelling work is the linkage between gas and aqueous chemistry and transport; reductions in ammonia emissions affect gaseous ammonia concentrations close to the emissions site, but substantial impacts on particulate matter and atmospheric deposition often occur at considerable distances downwind, with particle nitrate being the main vector of ammonia/um transport. Ammonia emissions reductions therefore have trans-boundary consequences downwind. Calculations of critical-load exceedances for sensitive ecosystems in Canada suggest that ammonia emission reductions will have a minimal impact on current ecosystem acidification within Canada, but may have a substantial impact on future ecosystem acidification. The 50% Canadian beef-cattle ammonia emissions reduction scenario was used to examine model sensitivity to uncertainties in the new Canadian agricultural ammonia emissions inventory, and the simulation results suggest that further work is needed to improve the emissions inventory for this particular sector. It should be noted that the model in its current form neglects coarse mode base cation chemistry, so the predicted effects of ammonia emissions reductions shown here should be considered upper limits.

Through an idealized model of a partial differential equation with discontinuous 'on-off'' switches in the forcing term, we investigate the effect of the model error generated by the traditional discretization of discontinuous physical 'on-off'' processes on the variational data assimilation (VDA) in detail. Meanwhile, the validity of the adjoint approach in the VDA with 'on-off'' switches is also examined. The theoretical analyses illustrate that in the analytic case, the gradient of the associated cost function (CF) with respect to an initial condition (IC) exists provided that the IC does not trigger the threshold condition. But in the discrete case, if the on switches (or off switches) in the forward model are straightforwardly assigned the nearest time level after the threshold condition is (or is not) exceeded as the usual treatment, the discrete CF gradients (even the one-sided gradient of CF) with respect to some ICs do not exist due to the model error, which is the difference between the analytic and numerical solutions to the governing equation. Besides, the solution of the corresponding tangent linear model (TLM) obtained by the conventional approach would not be a good first-order linear approximation to the nonlinear perturbation solution of the governing equation. Consequently, the validity of the adjoint approach in VDA with parameterized physical processes could not be guaranteed. Identical twin numerical experiments are conducted to illustrate the influences of these problems on VDA when using adjoint method. The results show that the VDA outcome is quite sensitive to the first guess of the IC, and the minimization processes in the optimization algorithm often fail to converge and poor optimization retrievals would be generated as well. Furthermore, the intermediate interpolation treatment at the switch times of the forward model, which reduces greatly the model error brought by the traditional discretization of 'on-off'' processes, is employed in this study to demonstrate that when the 'on-off'' switches in governing equations are properly numerically treated, the validity of the adjoint approach in VDA with discontinuous physical 'on-off'' processes can still be guaranteed.

Mechanical stimulation is known to regulate the calcification of endplate chondrocytes. The ANK protein has a strong influence on anti-calcification by transports intracellular inorganic pyrophosphate (PPi) to the extracellular. It is known that TGF-β1 is able to induced Ank gene expression and protect chondrocyte calcification. Intermittent cyclic mechanical tension (ICMT) could induce calcification of endplate chondrocytes by decrease the expression of Ank gene. In this study, we investigated the relation of intermittent cyclic mechanical unconfined compression (ICMC) and Ank gene expression. We found that ICMC decreased the Ank gene expression in the endplate chondrocytes, and there was an decreased in the TGF-β1 expression after ICMC stimulation. The Ank gene expression significantly increased when treated by transforming growth factor alpha 1 (TGF-β1) in a dose-dependent manner and decreased when treated by SB431542 (ALK inhibitor) in a dose-dependent manner. Our results implicate that ICMC-induced downregulation of Ank gene expression may be regulated by TGF-β1 in endplate chondrocytes.

Adult skeletal muscle regeneration involves serial steps among which inflammation in the wounded area is critical for the healing process. However, accelerated tissue regeneration and the inhibition of excessive inflammation are always the targets of tissue engineering, because excessive inflammation in the early stage can impede the regeneration in the following step. In this study, a feasible ibuprofen-loaded poly (L-lactide) (PLLA) fibrous scaffold was designed to evaluate the ability of preventing excessive inflammatory response and promoting regeneration using 35 Sprague-Dawley (SD) rats. The cytotoxicity assay of PLLA and ibuprofen-loaded PLLA fibrous scaffolds (IBU/PLLA) showed that there were no significant cell cytotoxicity on L6 cells. The histological results showed that the IBU/PLLA group had slighter inflammation than PLLA and control groups during the whole process. In the later stage, the regeneration process of the IBU/PLLA group took place on the 7th day, which was almost more than one week earlier than the PLLA and control groups. qRT-PCR analysis further displayed that the IBU/PLLA group had a lower level of inflammatory factors and higher expression of repair factors than the PLLA and control groups, especially from the 7th day, and lasted until the 21st day. Furthermore, there were no statistical differences between the PLLA group and the control group from histological results and qRT-PCR analysis. Taken together, through the muscle wound healing process, the results demonstrated that the ibuprofen-loaded PLLA fibrous scaffolds had better control of excessive inflammation and faster process of healing than non-ibuprofen-loaded groups.

TOPEX/POSEIDON (T/P) sea level deviation (SLD) time series from 3 October 1992 to 15 May 1997 combined with upper ocean thermal structures are used to observe the characteristics and analyze the dynamics of equatorial waves in the Pacific Ocean. The evolution of the Kelvin wave propagating along an eastward shoaling thermocline in the equatorial Pacific is investigated. The behaviour of this wave as it propagates eastward can be approximately described with the solutions of the perturbed Korteweg-de Vries (PKDV) equation and modified Green's Law. Assuming that the nonlinear term and dispersive term of this equation are balanced, the amplitude increases as the thermocline decreases to the power -3/8. Approaching the eastern Pacific, the nonlinearity increases and the relation changes to the power -9/8. The dispersion relation, and mass and energy conservations are investigated. The results indicate that under a varying thermocline, the nonlinear Kelvin solitary waves indeed exist in the real ocean.

Drug development for dementias is significantly hampered by the lack of easily accessible biomarkers. Fluid biomarkers of dementias provide indications of disease stage, but have little prognostic value, cannot detect early pathological changes, and can only be measured in CSF (cerebrospinal fluid) which significantly limits their applicability. In contrast, imaging based biomarkers can provide indications of probability of disease progression, yet are limited in applicability due to cost, radiation and radio-tracers. These aspects highlight the need for other approaches to the development of biomarkers of dementia, which should focus on not only providing information about pathological changes, but also on being measured easily and reproducibly. For other diseases, focus on development of assays monitoring highly specific protease-generated cleavage fragments of proteins has provided assays, which in serum or plasma have the ability to predict early pathological changes. Proteolytic processing of brain proteins, such as tau, APP, and α-synuclein, is a key pathological event in dementias. Here, we speculate that aiming biomarker development for dementias at detecting small brain protein degradation fragments of generated by brain-derived proteases specifically in blood samples could lead to the development of novel markers of disease progression, stage and importantly of treatment efficacy.

Not available.