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This paper presents two-dimensional numerical simulations of the self-excited forces on two bridge decks: a streamlined one (Great Belt Bridge) and a bluff one (Sunshine Skyway Bridge). It employs forced vibration simulations using the Open-source code OpenFOAM for flutter derivative identifications. A wide sensitivity study is conducted on the effects of turbulence model, Reynolds number, vibration amplitude, and wind attack angle on flutter derivative identifications. The key findings are as follows. (i) k-ε model shows its superiority in simulating self-excited forces on a bluff bridge deck, while SST k-ω exhibits advantages in the case of a streamlined bridge deck. (ii) Compared with a streamlined bridge deck, flutter derivatives of a bluff bridge deck are more sensitive to the Reynolds number due to the generation of more vortices resulting from flow separation. Both the generation and convection of the vortices are largely affected by the Reynolds number. (iii) Flutter derivatives of the bridge decks can be considered as constants if the vertical amplitude ratio and torsional amplitude are lower than 0.025 and 2°, respectively. Increasing vibration amplitude may result in remarkable variations of some flutter derivatives. (iv) The angle of attack changes the flutter derivatives by affecting the wind pressure distribution on the bridge surface. Its impact on a bluff bridge deck is larger than on a streamlined bridge deck. Besides presenting a detailed study of identifying flutter derivatives using OpenFOAM, this research provides valuable references for setting reasonable values of the investigated factors for identifying flutter derivatives of bluff and streamlined bridge decks.

Accurate representation of the turbulent exchange of carbon, water, and heat between the land surface and the atmosphere is critical for modelling global energy, water, and carbon cycles in both future climate projections and weather forecasts. Evaluation of models' ability to do this is performed in a wide range of simulation environments, often without explicit consideration of the degree of observational constraint or uncertainty and typically without quantification of benchmark performance expectations. We describe a Model Intercomparison Project (MIP) that attempts to resolve these shortcomings, comparing the surface turbulent heat flux predictions of around 20 different land models provided with in situ meteorological forcing evaluated with measured surface fluxes using quality-controlled data from 170 eddy-covariance-based flux tower sites. Predictions from seven out-of-sample empirical models are used to quantify the information available to land models in their forcing data and so the potential for land model performance improvement. Sites with unusual behaviour, complicated processes, poor data quality, or uncommon flux magnitude are more difficult to predict for both mechanistic and empirical models, providing a means of fairer assessment of land model performance. When examining observational uncertainty, model performance does not appear to improve in low-turbulence periods or with energy-balance-corrected flux tower data, and indeed some results raise questions about whether the energy balance correction process itself is appropriate. In all cases the results are broadly consistent, with simple out-of-sample empirical models, including linear regression, comfortably outperforming mechanistic land models. In all but two cases, latent heat flux and net ecosystem exchange of CO2 are better predicted by land models than sensible heat flux, despite it seeming to have fewer physical controlling processes. Land models that are implemented in Earth system models also appear to perform notably better than stand-alone ecosystem (including demographic) models, at least in terms of the fluxes examined here. The approach we outline enables isolation of the locations and conditions under which model developers can know that a land model can improve, allowing information pathways and discrete parameterisations in models to be identified and targeted for future model development.

Accurate information on surface soil moisture (SSM) content at a global scale under different climatic conditions is important for hydrological and climatological applications. Machine-learning-based systematic integration of in situ hydrological measurements, complex environmental and climate data, and satellite observation facilitate the generation of reliable data products to monitor and analyse the exchange of water, energy, and carbon in the Earth system at a proper space–time resolution. This study investigates the estimation of daily SSM using 8 optimised machine learning (ML) algorithms and 10 ensemble models (constructed via model bootstrap aggregating techniques and five-fold cross-validation). The algorithmic implementations were trained and tested using International Soil Moisture Network (ISMN) data collected from 1722 stations distributed across the world. The result showed that the K-neighbours Regressor (KNR) had the lowest root-mean-square error (0.0379 cm3 cm−3) on the “test_random” set (for testing the performance of randomly split data during training), the Random Forest Regressor (RFR) had the lowest RMSE (0.0599 cm3 cm−3) on the “test_temporal” set (for testing the performance on the period that was not used in training), and AdaBoost (AB) had the lowest RMSE (0.0786 cm3 cm−3) on the “test_independent-stations” set (for testing the performance on the stations that were not used in training). Independent evaluation on novel stations across different climate zones was conducted. For the optimised ML algorithms, the median RMSE values were below 0.1 cm3 cm−3. GradientBoosting (GB), Multi-layer Perceptron Regressor (MLPR), Stochastic Gradient Descent Regressor (SGDR), and RFR achieved a median r score of 0.6 in 12, 11, 9, and 9 climate zones, respectively, out of 15 climate zones. The performance of ensemble models improved significantly, with the median RMSE value below 0.075 cm3 cm−3 for all climate zones. All voting regressors achieved r scores of above 0.6 in 13 climate zones; BSh (hot semi-arid climate) and BWh (hot desert climate) were the exceptions because of the sparse distribution of training stations. The metric evaluation showed that ensemble models can improve the performance of single ML algorithms and achieve more stable results. Based on the results computed for three different test sets, the ensemble model with KNR, RFR and Extreme Gradient Boosting (XB) performed the best. Overall, our investigation shows that ensemble machine learning algorithms have a greater capability with respect to predicting SSM compared with the optimised or base ML algorithms; this indicates their huge potential applicability in estimating water cycle budgets, managing irrigation, and predicting crop yields.

Although calcium is known to be enriched in sea spray aerosols (SSAs), the factors that affect its enrichment remain ambiguous. In this study, we examine how environmental factors affect the distribution of water-soluble calcium (Ca2+) distribution in SSAs. We obtained our dataset from observations taken during the R/V Xuelong research cruise in the Ross Sea, Antarctica, from December 2017 to February 2018. Our observations showed that the enrichment of Ca2+ in aerosol samples was enhanced under specific conditions, including lower temperatures (<-3.5 ∘C), lower wind speeds ( m s−1), and the presence of sea ice. Our analysis of individual particle mass spectra revealed that a significant portion of calcium in SSAs was likely bound with organic matter (in the form of a single-particle type, OC-Ca, internally mixed organics with calcium). Our findings suggest that current estimations of Ca2+ enrichment based solely on water-soluble Ca2+ may be inaccurate. Our study is the first to observe a single-particle type dominated by calcium in the Antarctic atmosphere. Our findings suggest that future Antarctic atmospheric modeling should take into account the environmental behavior of individual OC-Ca particles. With the ongoing global warming and retreat of sea ice, it is essential to understand the mechanisms of calcium enrichment and the mixing state of individual particles to better comprehend the interactions between aerosols, clouds, and climate during the Antarctic summer.

Adipose tissue is the site of long-term energy storage. During the fasting state, exercise, and cold exposure, the white adipose tissue mobilizes energy for peripheral tissues through lipolysis. The mobilization of lipids from white adipose tissue to the liver can lead to excess triglyceride accumulation and fatty liver disease. Although the white adipose tissue is known to release free fatty acids, a comprehensive analysis of lipids mobilized from white adipocytes in vivo has not been completed. In these studies, we provide a comprehensive quantitative analysis of the adipocyte-secreted lipidome and show that there is interorgan crosstalk with liver. Our analysis identifies multiple lipid classes released by adipocytes in response to activation of lipolysis. Time-dependent analysis of the serum lipidome showed that free fatty acids increase within 30 min of β3-adrenergic receptor activation and subsequently decrease, followed by a rise in serum triglycerides, liver triglycerides, and several ceramide species. The triglyceride composition of liver is enriched for linoleic acid despite higher concentrations of palmitate in the blood. To further validate that these findings were a specific consequence of lipolysis, we generated mice with conditional deletion of adipose tissue triglyceride lipase exclusively in adipocytes. This loss of in vivo adipocyte lipolysis prevented the rise in serum free fatty acids and hepatic triglycerides. Furthermore, conditioned media from adipocytes promotes lipid remodeling in hepatocytes with concomitant changes in genes/pathways mediating lipid utilization. Together, these data highlight critical role of adipocyte lipolysis in interorgan crosstalk between adipocytes and liver.

The Holocene, which started approximately 11.5 ka, is the latest interglacial period with several rapid climate changes with timescales, from decades to centuries, superimposed on the millennium-scale mean climate trend. Climate models provide useful tools to investigate the underlying dynamic mechanisms for the climate change during this well-studied time period. Thanks to the improvements in the climate model and computational power, transient simulation of the Holocene offers an opportunity to investigate the climate evolution in response to time-varying external forcings and feedbacks. Here, we present the design of a new set of transient experiments for the whole Holocene from 11.5 ka to the preindustrial period (1850; HT-11.5 ka) to investigate both the combined and separated effects of the main external forcing of orbital insolation, atmospheric greenhouse gas (GHG) concentrations, and ice sheets on the climate evolution over the Holocene. The HT-11.5 ka simulations are performed with a relatively high-resolution version of the comprehensive Earth system model CESM1.2.1 without acceleration, both fully and singly forced by time-varying boundary conditions of orbital configurations, atmospheric GHGs, and ice sheets. Preliminary simulation results show a slight decrease in the global annual mean surface air temperature from 11.5 to 7.5 ka due to both changes in orbital insolation and GHG concentrations, with an abrupt cooling at approximately 7.5 ka, which is followed by a continuous warming until the preindustrial period, mainly due to increased GHG concentrations. Both at global and zonal mean scales, the simulated annual and seasonal temperature changes at 6 ka lie within the range of the 14 PMIP4 model results and are overall stronger than their arithmetic mean results for the Middle Holocene simulations. Further analyses on the HT-11.5 ka transient simulation results will be covered by follow-up studies.

Land evaporation (ET) plays a crucial role in the hydrological and energy cycle. However, the widely used model-based products, even though helpful, are still subject to great uncertainties due to imperfect model parameterizations and forcing data. The lack of available observed data has further complicated estimation. Hence, there is an urgency to define the global proxy land ET with lower uncertainties for climate-induced hydrology and energy change. This study has combined three existing model-based products – the fifth-generation ECMWF reanalysis (ERA5), Global Land Data Assimilation System Version 2 (GLDAS2), and the second Modern-Era Retrospective analysis for Research and Applications (MERRA-2) – to obtain a single framework of a long-term (1980–2017) daily ET product at a spatial resolution of 0.25∘. Here, we use the reliability ensemble averaging (REA) method, which minimizes errors using reference data, to combine the three products over regions with high consistencies between the products using the coefficient of variation (CV). The Global Land Evaporation Amsterdam Model Version 3.2a (GLEAM3.2a) and flux tower observation data were selected as the data for reference and evaluation, respectively. The results showed that the merged product performed well over a range of vegetation cover scenarios. The merged product also captured the trend of land evaporation over different areas well, showing the significant decreasing trend in the Amazon Plain in South America and Congo Basin in central Africa and the increasing trend in the east of North America, west of Europe, south of Asia and north of Oceania. In addition to demonstrating a good performance, the REA method also successfully converged the models based on the reliability of the inputs. The resulting REA data can be accessed at https://doi.org/10.5281/zenodo.4595941 (Lu et al., 2021).

Synthetic nanopillars resembling the wing surface of certain insects display antibacterial activities. Here, Jenkins et al. show that these activities do not necessarily require bacterial lysis, and may be mediated by oxidative stress induced by deformation of the bacterial cell envelope.

The outputs of four global climate models (GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR and MIROC5), which were statistically downscaled and bias corrected, were used to drive four hydrological models (Hydrologiska Byråns, HBV; Soil and Water Assessment Tool, SWAT; Soil and Water Integrated Model, SWIM; and Variable Infiltration Capacity, VIC) to simulate the daily discharge at the Cuntan hydrological station in the upper Yangtze River from 1861 to 2299. As the performances of hydrological models in various climate conditions could be different, the models were first calibrated in the period from 1979 to 1990. Then, the models were validated in the comparatively wet period, 1967–1978, and in the comparatively dry period, 1991–2002. A multi-objective automatic calibration programme using a univariate search technique was applied to find the optimal parameter set for each of the four hydrological models. The Nash–Sutcliffe efficiency (NSE) of daily discharge and the weighted least-squares function (WLS) of extreme discharge events, represented by high flow (Q10) and low flow (Q90), were included in the objective functions of the parameterization process. In addition, the simulated evapotranspiration results were compared with the GLEAM evapotranspiration data for the upper Yangtze River basin. For evaluating the performances of the hydrological models, the NSE, modified Kling–Gupta efficiency (KGE), ratio of the root-mean-square error to the standard deviation of the measured data (RSR) and Pearson's correlation coefficient (r) were used. The four hydrological models reach satisfactory simulation results in both the calibration and validation periods. In this study, the daily discharge is simulated for the upper Yangtze River under the preindustrial control (piControl) scenario without anthropogenic climate change from 1861 to 2299 and for the historical period 1861–2005 and for 2006 to 2299 under the RCP2.6, RCP4.5, RCP6.0 and RCP8.5 scenarios. The long-term daily discharge dataset can be used in the international context and water management, e.g. in the framework of Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) by providing clues to what extent human-induced climate change could impact streamflow and streamflow trend in the future. The datasets are available at: https://doi.org/10.4121/uuid:8658b22a-8f98-4043-9f8f-d77684d58cbc (Gao et al., 2019).

The present paper examines flood risk (composed of hazard, exposure, and vulnerability) in a range of spatial perspectives – from the global to the local scale. It deals with observed records, noting that flood damage has been increasing. It also tackles projections for the future, related to flood hazard and flood losses. There are multiple factors driving flood hazard and flood risk and there is a considerable uncertainty in our assessments, and particularly in projections for the future. Further, this paper analyses options for flood risk reduction in several spatial dimensions, from global framework to regional to local scales. It is necessary to continue examination of the updated records of flood-related indices, trying to search for changes that influence flood hazard and flood risk in river basins.

The role of the Tibetan Plateau (TP) in maintaining the large-scale overturning circulation in the Atlantic and Pacific is investigated using a coupled atmosphere–ocean model. For the present day with a realistic topography, model simulation shows a strong Atlantic meridional overturning circulation (AMOC) but a near absence of the Pacific meridional overturning circulation (PMOC), which are in good agreement with the present observations. In contrast, the simulation without the TP depicts a collapsed AMOC and a strong PMOC that dominates deep-water formation. The switch in deep-water formation between the two basins results from changes in the large-scale atmospheric circulation and atmosphere–ocean feedback over the Atlantic and Pacific. The intensified westerly winds and increased freshwater flux over the North Atlantic cause an initial slowdown of the AMOC, while the weakened East Asian monsoon circulation and associated decreased freshwater flux over the North Pacific give rise to the initial intensification of the PMOC. The further decreased heat flux and the associated increase in sea-ice fraction promote the final AMOC collapse over the Atlantic, while the further increased heat flux leads to the final PMOC establishment over the Pacific. Although the simulations were performed in a cold world, it still importantly implicates that the uplift of the TP alone could have been a potential driver for the reorganization of PMOC–AMOC between the late Eocene and early Oligocene.

Infiltration is one of the major procedures in water balance research and pollution load estimation in paddy fields. In this study, a new method for indirectly estimating infiltration of paddy fields in situ was proposed and implemented in Taihu Lake basin. Since when there were no rainfall, irrigation and artificial drainage, the water depth variation process of a paddy field is only influenced by evapotranspiration and infiltration (E + F). Firstly, (E + F) was estimated by deciding the steady decreasing rate of water depth; then the evapotranspiration (ET) of the paddy field was calculated by using the crop coefficient method with the recommended FAO-56 Penman-Monteith equation; finally, the infiltration of the paddy field was obtained by subtracting ET from (E + F). Results show that the mean infiltration of the studied paddy field during rice jointing-booting period was 7.41 mm day−1, and the mean vertical infiltration and lateral seepage of the paddy field were 5.46 and 1.95 mm day−1 respectively.

We locked a 1064 nm continuous wave (CW) laser to a Yb:fiber optical frequency comb stabilized to an ultrastable 972 nm CW laser with the feed-forward method. Consequently, the stability and coherent properties of the ultrastable laser are precisely transferred to the 1064 nm CW laser through the frequency comb’s connection. The relative linewidth of the frequency-stabilized 1064 nm CW laser is narrowed to 1.14 mHz, and the stability reaches 1.5 × 10−17/s at the optical wavelength of 1064 nm. The phase noise characterization in the 1 mHz–10 MHz range is presented to indicate that feed-forward locking a CW laser to an ultrastable comb will offer a potential technique for many important applications, such as optical frequency synthesis and gravitational wave detection.

Both atmospheric deposition and benthic remineralisation influence the marine nitrogen cycle, and hence ultimately also marine primary production. The biological and biogeochemical relations in the eastern tropical South Pacific (ETSP) among nitrogen deposition, benthic denitrification and phosphorus regeneration are analysed in a prognostic box model of the oxygen, nitrogen and phosphorus cycles in the ETSP. Atmospheric nitrogen deposition ( ≈ 1.5 Tg N yr−1 for the years 2000–2009) is offset by half in the model by reduced N2 fixation, with the other half transported out of the model domain. Model- and data-based benthic denitrification in our model domain are responsible for losses of 0.19 and 1.0 Tg Tg N yr−1, respectively, and both trigger nitrogen fixation, partly compensating for the NO3− loss. Model- and data-based estimates of enhanced phosphate release via sedimentary phosphorus regeneration under suboxic conditions are 0.062 and 0.11 Tg N yr−1, respectively. Since phosphate is the ultimate limiting nutrient in the model, even very small additional phosphate inputs stimulate primary production and subsequent export production and NO3− loss in the oxygen minimum zone (OMZ). A sensitivity analysis of the local response to both atmospheric deposition and benthic remineralisation indicates dominant stabilising feedbacks in the ETSP, which tend to keep a balanced nitrogen inventory; i.e. nitrogen input by atmospheric deposition is counteracted by decreasing nitrogen fixation; NO3− loss via benthic denitrification is partly compensated for by increased nitrogen fixation; enhanced nitrogen fixation stimulated by phosphate regeneration is partly counteracted by stronger water-column denitrification. Even though the water column in our model domain acts as a NO3− source, the ETSP including benthic denitrification might be a NO3− sink.

The objective of this study was to determine the effects of graded inclusions of wheat bran (0%, 9.65%, 48.25% wheat bran) and two growth stages (from 32.5 to 47.2 kg and 59.4 to 78.7 kg, respectively) on the apparent ileal digestibility (AID), apparent total tract digestibility (ATTD) and hindgut fermentation of nutrients and energy in growing pigs. Six light pigs (initial body weight [BW] 32.5±2.1 kg) and six heavy pigs (initial BW 59.4±3.2 kg) were surgically prepared with a T-cannula in the distal ileum. A difference method was used to calculate the nutrient and energy digestibility of wheat bran by means of comparison with a basal diet consisting of corn-soybean meal (0% wheat bran). Two additional diets were formulated by replacing 9.65% and 48.25% wheat bran by the basal diet, respectively. Each group of pigs was allotted to a 6×3 Youden square design, and pigs were fed to three experimental diets during three 11-d periods. Hindgut fermentation values were calculated as the differences between ATTD and AID values. For the wheat bran diets, the AID and ATTD of dry matter (DM), ash, organic matter (OM), carbohydrates (CHO), gross energy (GE), and digestible energy (DE) decreased with increasing inclusion levels of wheat bran (p

Ten Dragon 3 projects deal with hydrologic and cryosphere processes, with a focus on the Himalayas and Qinghai – Tibet Plateau, but not limited to that. At the 1st Dragon 3 Progress Symposium in 2013 a significant potential for a better and deeper integration appeared very clearly and we worked out an overview of the ten projects identifying specific issues and objectives shared by at least two projects. At the Mid Term Symposium in 2014 a joint session was held over two days. As regards cryospheric processes science highlights covered: Glacier flow velocity by optical and SAR features tracking and InSAR; Patterns in space and time of glacier flow velocity; Mass change estimated with DTM-s and altimetry; Reflectance and LST used to classify glacier surface and understand surface processes, Inventory and changes in the number and area of lakes in the Qinghai – Tibet Plateau 1970, 1990, 2000 and 2010; Deformation of permafrost along the Qinghai – Tibet railway. Highlights on hydrologic processes included: Global comparison of SMOS, ASCAT and ERA soil moisture data products; Relative deviations evaluated by climate zone; Soil moisture data products improved with ancillary data; Assimilation of FY - , TRMM and GPM precipitation data products in WRF; Improved algorithm and data products on fractional snow cover; Improvement of MODIS ET with assimilation of LST; TRMM data products evaluated in the Yangtze; Calibration of river basin models using LST; System to calibrate, correct and normalize (spatial, spectral) data collected by imaging spectral radiometers; Integration of data acquired by different sensors, e.g. ET Monitor with optical and microwave (SMOS, FY – 3) data; Hydrological data products used both for forcing and evaluation of Qinghai – Tibet Plateau hydrological model; Wetlands vulnerability assessed through changes in land cover 1987 – 2013; Multi incidence angle and multi – temporal SAR to monitor water extent. In the general session a proposal for a Dragon Water Cycle Initiative was presented.

Local coupling between nitrogen fixation and denitrification in current biogeochemical models could result in runaway feedback in open-ocean oxygen minimum zones (OMZs), eventually stripping OMZ waters of all fixed nitrogen. This feedback does not seem to operate at full strength in the ocean, as nitrate does not generally become depleted in open-ocean OMZs. To explore in detail the possible mechanisms that prevent nitrogen depletion in the OMZ of the eastern tropical South Pacific (ETSP), we develop a box model with fully prognostic cycles of carbon, nutrients and oxygen in the upwelling region and its adjacent open ocean. Ocean circulation is calibrated with Δ14C data of the ETSP. The sensitivity of the simulated nitrogen cycle to nutrient and oxygen exchange and ventilation from outside the model domain and to remineralization scales inside an OMZ is analysed. For the entire range of model configurations explored, we find that the fixed-N inventory can be stabilized at non-zero levels in the ETSP OMZ only if the remineralization rate via denitrification is slower than that via aerobic respiration. In our optimum model configuration, lateral oxygen supply into the model domain is required at rates sufficient to oxidize at least about one fifth of the export production in the model domain to prevent anoxia in the deep ocean. Under these conditions, our model is in line with the view of phosphate as the ultimate limiting nutrient for phytoplankton, and implies that for the current notion of nitrogen fixation being favoured in N-deficit waters, the water column of the ETSP could even be a small net source of nitrate.

In this study, hydrological long-term dry and wet periods are analyzed for the Xijiang River basin in South China. Daily precipitation data of 118 stations and data on daily discharge at Gaoyao hydrological station at the mouth of the Xijiang River for the period 1961–2007 are used. At a 24-month timescale, the standardized precipitation index (SPI-24) for the six sub-basins of the Xijiang River and the standardized discharge index (SDI-24) for Gaoyao station are applied. The monthly values of the SPI-24 averaged for the Xijiang River basin correlate highly with the monthly values of the SDI-24. Distinct long-term dry and wet sequences can be detected. The principal component analysis is applied and shows spatial disparities in dry and wet periods for the six sub-basins. The correlation between the SPI-24 of the six sub-basins and the first principal component score shows that 67% of the variability within the sub-basins can be explained by dry and wet periods in the east of the Xijiang River basin. The spatial dipole conditions (second and third principal component) explain spatiotemporal disparities in the variability of dry and wet periods. All sub-basins contribute to hydrological dry periods, while mainly the northeastern sub-basins cause wet periods in the Xijiang River. We can also conclude that long-term dry events are larger in spatial extent and cover all sub-basins while long-term wet events are regional phenomena. A spectral analysis is applied for the SPI-24 and the SDI-24. The results show significant peaks in periodicities of 11–14.7 yr, 2.8 yr, 3.4–3.7 yr, and 6.3–7.3 yr. The same periodic cycles can be found in the SPI-24 of the six sub-basins but with some variability in the mean magnitude. A wavelet analysis shows that significant periodicities have been stable over time since the 1980s. Extrapolations of the reconstructed SPI-24 and SDI-24 represent the continuation of observed significant periodicities at given magnitudes until 2030. The projected hydrological long-term dry and wet periods can be used for planning purposes in water resources management. The applied methodologies prove to be able to identify spatial disparities, and to detect significant periodicities in hydrological long-term dry and wet periods in the Xijiang River basin.

Sensible and latent heat fluxes are often calculated from bulk transfer equations combined with the energy balance. For spatial estimates of these fluxes, a combination of remotely sensed and standard meteorological data from weather stations is used. The success of this approach depends on the accuracy of the input data and on the accuracy of two variables in particular: aerodynamic and surface conductance. This paper presents a Bayesian approach to improve estimates of sensible and latent heat fluxes by using a priori estimates of aerodynamic and surface conductance alongside remote measurements of surface temperature. The method is validated for time series of half-hourly measurements in a fully grown maize field, a vineyard and a forest. It is shown that the Bayesian approach yields more accurate estimates of sensible and latent heat flux than traditional methods.

High-throughput methods for assaying DNA variation require two important steps: (i) discriminating the variation and (ii) de-tecting the signal. In this report, we describe a novel SNP genotyping method that we refer to as melting curve analysis of SNPs (McSNP®). McSNP combines a classic approach for discriminating alleles, restriction enzyme digestion, with a more recent method for detecting DNA fragments, melting curve analysis. Melting curve analysis is performed by slowly heating DNA fragments in the presence of the dsDNA-specific fluorescent dye SYBR® Green I. As the sample is heated, fluorescence rapidly decreases when the melting temperature of a particular fragment is reached. We show that it is possible to determine the composition of simple mixtures of DNA fragments, such as those that result from restriction enzyme digestions of short PCR products. McSNP is well suited for high-throughput genotyping because 96 samples can be analyzed and automatically scored in 20 min. Our results clearly demonstrate that McSNP is a simple, inexpensive, and accurate means of genotyping SNP variation.

Aims. The aim of this study is to examine the efficacy of adding a dipeptidyl peptidase-4 (DPP-4) inhibitor to patients with type 2 diabetes inadequately controlled by metformin and sulphonylurea combination treatment. The response of Asian and non-Asian patients to this regimen was also examined. Methods. The medical and computerized records of 80 patients were examined. These patients had baseline HbA1c levels ranging from 7.0 to 12.5% and had a DPP-4 inhibitor add-on therapy for a minimum period of 12 weeks. The primary endpoint was the change in HbA1c level before and after DPP-4 inhibitor treatment. Results. During oral triple therapy, there was a reduction of HbA1c from 8.3% (7.7–8.9) to 7.2% (6.8–7.6) and 26 patients (32.5%) achieved an HbA1c