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The influence of a keyhole defect on local deformation behaviour in additive manufactured Ti-6Al-4V was investigated by comparing it to a representative bulk region without a defect. High resolution digital image correlation (HRDIC) was used to measure the differences in strain localisation at the microstructural length-scale. A nanoscale speckle pattern was used to allow small changes in strain to be detected and resolved within individual lamella and at pre-existing crack locations around the defect. Strain localisation was observed around the defect and formed well below the macroscopic yield stress. In contrast, minimal deformation was found in the bulk at this stress level. Following further deformation into the plastic regime, the strain localisation around the keyhole became more heterogenous with a distinct strain field. A large amount of strain localisation and slip was observed either side of the defect normal to the loading direction compared to relatively little in the regions close to the defect in line with the loading direction. This HRDIC observation was consistent with finite element analysis of the expected strain fields around the defect both below and above the yield point. Furthermore, micro-cracks were observed in αp/αp and αp/βt interfaces in both regions with the more pronounced strain fields around the defect leading to an increased number of long micro-cracks than in the bulk. The formation mechanisms of micro-cracks have been discussed, emphasising the role of localised strain caused by the defect.

Leaf area index (LAI) with an explicit biophysical meaning is a critical variable to characterize terrestrial ecosystems. Long-term global datasets of LAI have served as fundamental data support for monitoring vegetation dynamics and exploring its interactions with other Earth components. However, current LAI products face several limitations associated with spatiotemporal consistency. In this study, we employed the back propagation neural network (BPNN) and a data consolidation method to generate a new version of the half-month 1/12∘ Global Inventory Modeling and Mapping Studies (GIMMS) LAI product, i.e., GIMMS LAI4g, for the period 1982–2020. The significance of the GIMMS LAI4g was the use of the latest PKU GIMMS normalized difference vegetation index (NDVI) product and 3.6 million high-quality global Landsat LAI samples to remove the effects of satellite orbital drift and sensor degradation and to develop spatiotemporally consistent BPNN models. The results showed that the GIMMS LAI4g exhibited overall higher accuracy and lower underestimation than its predecessor (GIMMS LAI3g) and two mainstream LAI products (Global LAnd Surface Satellite (GLASS) LAI and Long-term Global Mapping (GLOBMAP) LAI) using field LAI measurements and Landsat LAI samples. Its validation against Landsat LAI samples revealed an R2 of 0.96, root mean square error of 0.32 m2 m−2, mean absolute error of 0.16 m2 m−2, and mean absolute percentage error of 13.6 % which meets the accuracy target proposed by the Global Climate Observation System. It outperformed other LAI products for most vegetation biomes in a majority area of the land. It efficiently eliminated the effects of satellite orbital drift and sensor degradation and presented a better temporal consistency before and after the year 2000. The consolidation with the reprocessed MODIS LAI allows the GIMMS LAI4g to extend the temporal coverage from 2015 to a recent period (2020), producing the LAI trend that maintains high consistency before and after 2000 and aligns with the reprocessed MODIS LAI trend during the MODIS era. The GIMMS LAI4g product could potentially facilitate mitigating the disagreements between studies of the long-term global vegetation changes and could also benefit the model development in earth and environmental sciences. The GIMMS LAI4g product is open access and available under Attribution 4.0 International at https://doi.org/10.5281/zenodo.7649107 (Cao et al., 2023).

Global products of remote sensing Normalized Difference Vegetation Index (NDVI) are critical to assessing the vegetation dynamic and its impacts and feedbacks on climate change from local to global scales. The previous versions of the Global Inventory Modeling and Mapping Studies (GIMMS) NDVI product derived from the Advanced Very High Resolution Radiometer (AVHRR) provide global biweekly NDVI data starting from the 1980s, being a reliable long-term NDVI time series that has been widely applied in Earth and environmental sciences. However, the GIMMS NDVI products have several limitations (e.g., orbital drift and sensor degradation) and cannot provide continuous data for the future. In this study, we presented a machine learning model that employed massive high-quality global Landsat NDVI samples and a data consolidation method to generate a new version of the GIMMS NDVI product, i.e., PKU GIMMS NDVI (1982–2022), based on AVHRR and Moderate-Resolution Imaging Spectroradiometer (MODIS) data. A total of 3.6 million Landsat NDVI samples that were well spread across the globe were extracted for vegetation biomes in all seasons. The PKU GIMMS NDVI exhibits higher accuracy than its predecessor (GIMMS NDVI3g) in terms of R2 (0.97 over 0.94), root mean squared error (RMSE: 0.05 over 0.09), mean absolute error (MAE: 0.03 over 0.07), and mean absolute percentage error (MAPE: 9 % over 20 %). Notably, PKU GIMMS NDVI effectively eliminates the evident orbital drift and sensor degradation effects in tropical areas. The consolidated PKU GIMMS NDVI has a high consistency with MODIS NDVI in terms of pixel value (R2 = 0.956, RMSE = 0.048, MAE = 0.034, and MAPE = 6.0 %) and global vegetation trend (0.9×10-3 yr−1). The PKU GIMMS NDVI product can potentially provide a more solid data basis for global change studies. The theoretical framework that employs Landsat data samples can facilitate the generation of remote sensing products for other land surface parameters. The PKU GIMMS NDVI product is open access and available under a Creative Commons Attribution 4.0 License at https://doi.org/10.5281/zenodo.8253971 (Li et al., 2023).

Abstract The T2K experiment presents new measurements of neutrino oscillation parameters using $$19.7(16.3)\times 10^{20}$$ 19.7 ( 16.3 ) × 10 20 protons on target (POT) in (anti-)neutrino mode at the far detector (FD). Compared to the previous analysis, an additional $$4.7\times 10^{20}$$ 4.7 × 10 20 POT neutrino data was collected at the FD. Significant improvements were made to the analysis methodology, with the near-detector analysis introducing new selections and using more than double the data. Additionally, this is the first T2K oscillation analysis to use NA61/SHINE data on a replica of the T2K target to tune the neutrino flux model, and the neutrino interaction model was improved to include new nuclear effects and calculations. Frequentist and Bayesian analyses are presented, including results on $$\sin ^2\theta _{13}$$ sin 2 θ 13 and the impact of priors on the $$\delta _{\textrm{CP}}$$ δ CP measurement. Both analyses prefer the normal mass ordering and upper octant of $$\sin ^2\theta _{23}$$ sin 2 θ 23 with a nearly maximally CP-violating phase. Assuming the normal ordering and using the constraint on $$\sin ^2\theta _{13}$$ sin 2 θ 13 from reactors, $$\sin ^2\theta _{23}=0.561^{+0.021}_{-0.032}$$ sin 2 θ 23 = 0 . 561 - 0.032 + 0.021 using Feldman–Cousins corrected intervals, and $$\varDelta {}m^2_{32}=2.494_{-0.058}^{+0.041}\times 10^{-3}~\text {eV}^2$$ Δ m 32 2 = 2 . 494 - 0.058 + 0.041 × 10 - 3 eV 2 using constant $$\varDelta \chi ^{2}$$ Δ χ 2 intervals. The CP-violating phase is constrained to $$\delta _{\textrm{CP}}=-1.97_{-0.70}^{+0.97}$$ δ CP = - 1 . 97 - 0.70 + 0.97 using Feldman–Cousins corrected intervals, and $$\delta _{\textrm{CP}}=0,\pi $$ δ CP = 0 , π is excluded at more than 90% confidence level. A Jarlskog invariant of zero is excluded at more than $$2\sigma $$ 2 σ credible level using a flat prior in $$\delta _{\textrm{CP}},$$ δ CP , and just below $$2\sigma $$ 2 σ using a flat prior in $$\sin \delta _{\textrm{CP}}.$$ sin δ CP . When the external constraint on $$\sin ^2\theta _{13}$$ sin 2 θ 13 is removed, $$\sin ^2\theta _{13}=28.0^{+2.8}_{-6.5}\times 10^{-3},$$ sin 2 θ 13 = 28 . 0 - 6.5 + 2.8 × 10 - 3 , in agreement with measurements from reactor experiments. These results are consistent with previous T2K analyses.

We report the first detection of polarization angle orthogonal jumps, a phenomenon previously only observed from radio pulsars, from a fast radio burst (FRB) source FRB 20201124A. We find three cases of orthogonal jumps in over 2000 bursts, all resembling those observed in pulsar single pulses. We propose that the jumps are due to the superposition of two orthogonal emission modes that could only be produced in a highly magnetized plasma, and they are caused by the line of sight sweeping across a rotating magnetosphere. The shortest jump timescale is of the order of 1 millisecond, which hints that the emission modes come from regions smaller than the light cylinder of most pulsars or magnetars. This discovery provides convincing evidence that FRB emission originates from the complex magnetosphere of a magnetar, suggesting an FRB emission mechanism that is analogous to radio pulsars despite a huge luminosity difference between two types of objects.

Among multimessenger observations of the next Galactic core-collapse supernova, Super-Kamiokande (SK) plays a critical role in detecting the emitted supernova neutrinos, determining the direction to the supernova (SN), and notifying the astronomical community of these observations in advance of the optical signal. In 2022, SK has increased the gadolinium dissolved in its water target (SK-Gd) and has achieved a Gd concentration of 0.033%, resulting in enhanced neutron detection capability, which in turn enables more accurate determination of the supernova direction. Accordingly, SK-Gd’s real-time supernova monitoring system has been upgraded. SK_SN Notice, a warning system that works together with this monitoring system, was released on 2021 December 13, and is available through GCN Notices. When the monitoring system detects an SN-like burst of events, SK_SN Notice will automatically distribute an alarm with the reconstructed direction to the supernova candidate within a few minutes. In this paper, we present a systematic study of SK-Gd’s response to a simulated Galactic SN. Assuming a supernova situated at 10 kpc, neutrino fluxes from six supernova models are used to characterize SK-Gd’s pointing accuracy using the same tools as the online monitoring system. The pointing accuracy is found to vary from 3° to 7° depending on the models. However, if the supernova is closer than 10 kpc, SK_SN Notice can issue an alarm with three-degree accuracy, which will benefit follow-up observations by optical telescopes with large fields of view.

Preceding a core-collapse supernova (CCSN), various processes produce an increasing amount of neutrinos of all flavors characterized by mounting energies from the interior of massive stars. Among them, the electron antineutrinos are potentially detectable by terrestrial neutrino experiments such as KamLAND and Super-Kamiokande (SK) via inverse beta decay interactions. Once these pre-supernova (pre-SN) neutrinos are observed, an early warning of the upcoming CCSN can be provided. In light of this, KamLAND and SK, both located in the Kamioka mine in Japan, have been monitoring pre-SN neutrinos since 2015 and 2021, respectively. Recently, we performed a joint study between KamLAND and SK on pre-SN neutrino detection. A pre-SN alert system combining the KamLAND detector and the SK detector was developed and put into operation, which can provide a supernova alert to the astrophysics community. Fully leveraging the complementary properties of these two detectors, the combined alert is expected to resolve a pre-SN neutrino signal from a 15 M _⊙ star within 510 pc of the Earth at a significance level corresponding to a false alarm rate of no more than 1 per century. For a Betelgeuse-like model with optimistic parameters, it can provide early warnings up to 12 hr in advance.

We report the first search result for the flux of astrophysical electron antineutrinos for energies ${ \mathcal O }(10)\,\mathrm{MeV}$ in the gadolinium-loaded Super-Kamiokande (SK) detector. In 2020 June, gadolinium was introduced to the ultrapure water of the SK detector in order to detect neutrons more efficiently. In this new experimental phase, SK-Gd, we can search for electron antineutrinos via inverse beta decay with efficient background rejection thanks to the high efficiency of the neutron tagging technique. In this paper, we report the result for the initial stage of SK-Gd, during 2020 August 26, and 2022 June 1 with a 22.5 × 552 kton · day exposure at 0.01% Gd mass concentration. No significant excess over the expected background in the observed events is found for the neutrino energies below 31.3 MeV. Thus, the flux upper limits are placed at the 90% confidence level. The limits and sensitivities are already comparable with the previous SK result with pure water (22.5 × 2970 kton · day) owing to the enhanced neutron tagging. Operation with Gd increased to 0.03% started in 2022 June.

Identifying the molecular mechanisms of response to systemic therapy in prostate cancer remains crucial. Here, the authors apply single cell-ATAC and RNAseq to models of early treatment response and resistance to enzalutamide and identify chromatin and gene expression patterns that can predict treatment response.

In recent years, air pollution related to PM2.5 has caused a significant impact on human health. The Grand Canal (GC) is not only a great Cultural heritage created in ancient China but also the longest and largest canal in the world. Based on remotely sensed PM2.5 gridded data in the GC region covering 2000 to 2018, we used the holistic methods of standard deviation ellipse, local moran index, slope trend analysis to reveal the spatiotemporal evolutions of PM2.5 concentrations in the GC regions and investigated the driving factors of PM2.5 concentrations by using the geographically weighted regression (GWR) model. Results show that (1) PM2.5 concentrations in the GC region exhibited an increasing trend and followed by a decreasing trend from 2000 to 2018 (the turning point emerged in 2010). (2) The standard deviation ellipse analyses show that the spatial distributions of PM2.5 concentrations featured more and more concentrated over time, whereas, after the year 2010, the distributions gradually featured scattered. (3) The concentrations of PM2.5 exhibited the strong effects of local spatial autocorrelation and areas with "high-high" agglomeration were mainly located in the central and west regions of the GC region and gradually expanded to the north over time. (4) The areas of regions with rapidly increasing in PM2.5 concentrations gradually decreased over time, however, those with rapidly decreasing in PM2.5 concentrations increased. (5) The influences of the natural factors and socio-economic factors on the distributions of PM2.5 concentrations varied spatially. In detail, the elevation was negatively correlated with PM2.5 concentrations, whereas an opposite relationship between industrial structure and PM2.5 concentrations was observed. The coefficients of rainfall, population density, GDP per capita and foreign investment show different results in positive and negative correlations depending on the position.

Abstract The electron (anti-)neutrino component of the T2K neutrino beam constitutes the largest background in the measurement of electron (anti-)neutrino appearance at the far detector. The electron neutrino scattering is measured directly with the T2K off-axis near detector, ND280. The selection of the electron (anti-)neutrino events in the plastic scintillator target from both neutrino and anti-neutrino mode beams is discussed in this paper. The flux integrated single differential charged-current inclusive electron (anti-)neutrino cross-sections, dσ/dp and dσ/d cos(θ), and the total cross-sections in a limited phase-space in momentum and scattering angle (p > 300 MeV/c and θ ≤ 45°) are measured using a binned maximum likelihood fit and compared to the neutrino Monte Carlo generator predictions, resulting in good agreement.

Synthetic Aperture Radar (SAR) images acquired by Earth observation satellites often constitute the only source of information for monitoring the progression of flood events over larger regions. Particularly attractive are the SAR data acquired by the Copernicus Sentinel-1 satellites because they are free and open, and combine a short revisit time with a good spatial and radiometric resolution. In this contribution, we discuss how a Sentinel-1 data processing system should be designed to optimally benefit from the dense Sentinel-1 time series and advanced algorithms such as change detection or machine learning methods. This was one of the questions addressed by an expert group tasked by the Joint Research Centre of the European Commission to investigate the feasibility of an automated, global, satellite-based flood monitoring product for the Copernicus Emergency Management Service. Drawing from the expert group report, we distinguish three broad categories of data processing architectures, namely single-image, dual-image, and data cube processing architectures. While the latter architecture is the most demanding in terms of large storage and compute capacities, it is also the most promising to derive high-quality Sentinel-1 flood maps comprised not just of the flood mask but also of data fields describing the retrieval uncertainty and masks showing where Sentinel-1 cannot detect floods due to physical reasons. Therefore, we recommend to use data cube processing architectures and showcase the use of the Austrian Data Cube for monitoring a small-scale flood event that occurred in Austria in November 2019.

Change detection has been widely used in many flood-mapping algorithms using pairs of Synthetic Aperture Radar (SAR) intensity images as floodwater often leads to a substantial decrease of backscatter. However, limitations still exist in many areas, such as shadow, layover, urban areas and densely vegetated areas, where the SAR backscatter is not sufficiently impacted by floodwater-related surface changes. This study focuses on these so-called exclusion areas, i.e. areas where SAR does not allow detecting water based on change detection. Our approach considers both pixel-based time series analyses and object-based spatial analyses using 20m Sentinel-1 Interferometric Wide Swath data, including 922 Sentinel-1 tiles covering the River Severn basin (UK) and the Lake Maggiore area (Italy). The results show that our exclusion map presents a good agreement (∼63%) with reference data derived from different data sources and indicate that it may complement SAR-derived flood extent maps. Allowing to accurately identify potential misclassifications in flood extent mapping, our exclusion map provides valuable information for flood management and, in particular, flood forecasting and prediction.

Coastal regions of China feature high population densities as well as wind-sensitive structures and are therefore vulnerable to tropical cyclones (TCs) with approximately six to eight landfalls annually. This study predicts TC wind hazard curves in terms of design wind speed versus return periods for major coastal cities of China to facilitate TC-wind-resistant design and disaster mitigation as well as insurance-related risk assessment. The 10 min wind information provided by the Japan Meteorological Agency (JMA) from 1977 to 2015 is employed to rebuild TC wind field parameters (radius of maximum winds Rmax,s and shape parameter of radial pressure profile Bs) at surface level using a height-resolving boundary layer model. These parameters will be documented to develop an improved JMA dataset. The probabilistic behaviors of historical tracks and wind field parameters at the first time step within a 500 km radius subregion centered at a site of interest are examined to determine preferable probability distribution models before stochastically generating correlated genesis parameters utilizing the Cholesky decomposition method. Recursive models are applied for translation speed, Rmax,s and Bs during the TC track and wind field simulations. Site-specific TC wind hazards are studied using 10 000-year Monte Carlo simulations and compared with code suggestions as well as other studies. The resulting estimated wind speeds for northern cities (Ningbo and Wenzhou) under a TC climate are higher than code recommendations, while those for southern cities (Zhanjiang and Haikou) are lower. Other cities show a satisfactory agreement with code provisions at the height of 10 m. Some potential reasons for these findings are discussed to emphasize the importance of independently developing hazard curves of TC winds.

One of the most important processes in the global mercury (Hg) biogeochemical cycling is the deposition of atmospheric Hg, including gaseous elemental mercury (GEM), gaseous oxidized mercury (GOM), and particulate-bound mercury (PBM), to the land surfaces. Results of wet, dry, and forest Hg deposition from global observation networks, individual monitoring studies, and observation-based simulations have been reviewed in this study. Uncertainties in the observation and simulation of global speciated atmospheric Hg deposition to the land surfaces have been systemically estimated based on assessment of commonly used observation methods, campaign results for comparison of different methods, model evaluation with observation data, and sensitivity analysis for model parameterization. The uncertainties of GOM and PBM dry deposition measurements come from the interference of unwanted Hg forms or incomplete capture of targeted Hg forms, while that of GEM dry deposition observation originates from the lack of a standardized experimental system and operating procedure. The large biases in the measurements of GOM and PBM concentrations and the high sensitivities of key parameters in resistance models lead to high uncertainties in GOM and PBM dry deposition simulation. Non-precipitation Hg wet deposition could play a crucial role in alpine and coastal regions, and its high uncertainties in both observation and simulation affect the overall uncertainties of Hg wet deposition. The overall uncertainties in the observation and simulation of the total global Hg deposition were estimated to be ± (25–50) % and ± (45–70) %, respectively, with the largest contributions from dry deposition. According to the results from uncertainty analysis, future research needs were recommended, among which a global Hg dry deposition network, unified methods for GOM and PBM dry deposition measurements, quantitative methods for GOM speciation, campaigns for comprehensive forest Hg behavior, and more efforts in long-term Hg deposition monitoring in Asia are the top priorities.

It is argued that heavy-quarks traversing a Quark Gluon Plasma, undergo a multi-stage modification process, similar to the case of light flavors. Such an approach is applied to heavy-quark energy loss, which includes a rare-scattering, multiple emission formalism at momenta large compared to the mass (sensitive only to the transverse diffusion coefficient qˆ), and a single scattering induced emission formalism (Gunion-Bertsch) at momenta comparable to the mass of the quark [sensitive to qˆ, and the longitudinal drag (eˆ) and diffusion (eˆ2) coefficients]. The application of such a multi-stage approach within a 2+1D viscous fluid-dynamical simulation leads to simultaneous agreement with experimental data for the nuclear modification factor of both B and D mesons, as measured by the CMS collaboration at the LHC. The extracted transport coefficients are found to be consistent with those for light flavors. Keywords: Heavy-ion collisions, Quark-gluon-plasma, Heavy-quark, Jet quenching

In this paper, a new geometric stitching method is proposed which utilizes digital elevation model (DEM)-aided block adjustment to solve relative orientation parameters for dual-camera with weak convergence geometry. A rational function model (RFM) with affine transformation is chosen as the relative orientation model. To deal with the weak geometry, a reference DEM is used in this method as an additional constraint in the block adjustment, which only calculates the planimetry coordinates of tie points (TPs). After that we can use the obtained affine transform coefficients to generate virtual grid, and update rational polynomial coefficients (RPCs) to complete the geometric stitching. Our proposed method was tested on GaoFen-2(GF-2) dual-camera panchromatic (PAN) images. The test results show that the proposed method can achieve an accuracy of better than 0.5 pixel in planimetry and have a seamless visual effect. For regions with small relief, when global DEM with 1 km grid, SRTM with 90 m grid and ASTER GDEM V2 with 30 m grid replaced DEM with 1m grid as elevation constraint， it is almost no loss of accuracy. The test results proved the effectiveness and feasibility of the stitching method.

Large columnar grains with strong texture in direct laser deposited (DLDed) Ti-6Al-4V (Ti-64) is widely reported to cause issues like strong mechanical property anisotropy and poor tensile strength, which make this material unsuitable for many uses in the aerospace industry. In this study, a microstructure refinement investigation was carried out by adding various amounts of boron from 0.05 wt% to 1.0 wt%. The effects of boron additions, even with 0.05 wt%, are very strong on the microstructure refinement. The presence of large columnar grains was eliminated along with the α lath refinement, the grain boundary α elimination and the texture weakening. β reconstruction results showed that boron is very effective in the β grain refinement and the β texture weakening, which contributes to the transformed α lath refinement and the α texture weakening, respectively. Furthermore, the tensile strength of DLDed Ti-64 with different boron additions is improved. A good balance of the tensile strength and ductility, with considerably reduced anisotropy, was achieved by adding 0.05 wt% boron. A comprehensive understanding between the boron additions, microstructure refinement and tensile performance improvement was fully established, which could enable greater usage of DLDed Ti-64 in the aerospace industry. Keywords: Direct laser deposition, Ti-6A-4V, Microstructures, Texture, Tensile properties

Our work addresses the problem of extracting trees from mobile laser scanning data. The work is a two step-wise strategy, including terrain point removal and tree segmentation. First, a voxel-based upward growing filtering is proposed to remove terrain points from the mobile laser scanning data. Then, a tree segmentation is presented to extract individual trees via a Euclidean distance clustering approach and Voxel-based Normalized Cut (VNCut) segmentation approach. A road section data acquired by a RIEGL VMX-450 system are selected for evaluating the proposed tree segmentation method. Qualitative analysis shows that our algorithm achieves a good performance.

Recent studies have shown the potential of Synthetic Aperture Radars (SAR) for mapping of rice fields and some other vegetation types. For rice field classification, conventional classification techniques have been mostly used including manual threshold-based and supervised classification approaches. The challenge of the threshold-based approach is to find acceptable thresholds to be used for each individual SAR scene. Furthermore, the influence of local incidence angle on backscatter hinders using a single threshold for the entire scene. Similarly, the supervised classification approach requires different training samples for different output classes. In case of rice crop, supervised classification using temporal data requires different training datasets to perform classification procedure which might lead to inconsistent mapping results. In this study we present an automatic method to identify rice crop areas by extracting phonological parameters after performing an empirical regression-based normalization of the backscatter to a reference incidence angle. The method is evaluated in the Red River Delta (RRD), Vietnam using the time series of ENVISAT Advanced SAR (ASAR) Wide Swath (WS) mode data. The results of rice mapping algorithm compared to the reference data indicate the Completeness (User accuracy), Correctness (Producer accuracy) and Quality (Overall accuracies) of 88.8%, 92.5 % and 83.9 % respectively. The total area of the classified rice fields corresponds to the total rice cultivation areas given by the official statistics in Vietnam (R²  0.96). The results indicates that applying a phenology-based classification approach using backscatter time series in optimal incidence angle normalization can achieve high classification accuracies. In addition, the method is not only useful for large scale early mapping of rice fields in the Red River Delta using the current and future C-band Sentinal-1A&B backscatter data but also might be applied for other rice cultivation areas.

The aim of this study was to compare the cardiovascular and respiratory effects and the bispectral scale index (BIS) as well as the recovery period characteristics in response to treatment with a propofol/alfentanil admixture of different concentrations in dogs undergoing splenectomy. We conducted a prospective, randomised, blinded experimental trial. Anaesthesia was induced and maintained by continuous-infusion anaesthesia of propofol and alfentanil or a propofol/alfentanil admixture after premedication with acepromazine (0.03 mg/kg). Dogs were assigned to receive different concentrations of the admixture. Changes in BIS value, heart rate (HR), respiratory rate (fR), non-invasive arterial blood pressure, pulse oximetry (SpO2), end-tidal carbon dioxide concentrations (ETCO2) and rectal temperature (RT) were recorded at predefined time points during anaesthesia. Data [mean ± standard deviation (SD)] were analysed by analysis of variance (ANOVA) for repeated measures followed by a Dunnett's test and Student's t-test (P < 0.05) and where necessary, the Mann-Whitney U-test. No significant differences were found between groups with respect to age, body mass, SpO2, ETCO2, fR, systolic, diastolic and mean arterial blood pressure (SAP, DAP and MAP). BIS values were significantly lower in Group 2 when compared to Group 1 at T7, T8, T9. The HR of Group 2 was significantly lower at T2 to T9 when compared to Group 1. The propofol and alfentanil admixture provided satisfactory results in dogs undergoing splenectomy. Thus, an admixture of propofol/alfentanil may be used for total IV anaesthesia in dogs at the infusion rates determined in this study.

In longitudinal multi-mode pushover analysis of bridges with elevated pile foundation systems, the inelastic contributions of the second mode cannot be neglected. Generalized pushover analysis cannot be applied directly in this condition. A modified generalized pushover procedure is developed for estimating seismic demands of bridges with elevated pile foundation systems. Modified generalized pushover procedure, modal pushover analysis and incremental dynamic analysis of a bridge with elevated pile foundation systems are conducted. The results show that the modified generalized pushover procedure can provide reasonable estimations of moments and predict more accurate plastic hinge rotations compared with modal pushover analysis.