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Solar photovoltaic power output is modulated by atmospheric aerosols and clouds and thus contains valuable information on the optical properties of the atmosphere. As a ground-based data source with high spatiotemporal resolution it has great potential to complement other ground-based solar irradiance measurements as well as those of weather models and satellites, thus leading to an improved characterisation of global horizontal irradiance. In this work several algorithms are presented that can retrieve global tilted and horizontal irradiance and atmospheric optical properties from solar photovoltaic data and/or pyranometer measurements. The method is tested on data from two measurement campaigns that took place in the Allgäu region in Germany in autumn 2018 and summer 2019, and the results are compared with local pyranometer measurements as well as satellite and weather model data. Using power data measured at 1 Hz and averaged to 1 min resolution along with a non-linear photovoltaic module temperature model, global horizontal irradiance is extracted with a mean bias error compared to concurrent pyranometer measurements of 5.79 W m−2 (7.35 W m−2) under clear (cloudy) skies, averaged over the two campaigns, whereas for the retrieval using coarser 15 min power data with a linear temperature model the mean bias error is 5.88 and 41.87 W m−2 under clear and cloudy skies, respectively. During completely overcast periods the cloud optical depth is extracted from photovoltaic power using a lookup table method based on a 1D radiative transfer simulation, and the results are compared to both satellite retrievals and data from the Consortium for Small-scale Modelling (COSMO) weather model. Potential applications of this approach for extracting cloud optical properties are discussed, as well as certain limitations, such as the representation of 3D radiative effects that occur under broken-cloud conditions. In principle this method could provide an unprecedented amount of ground-based data on both irradiance and optical properties of the atmosphere, as long as the required photovoltaic power data are available and properly pre-screened to remove unwanted artefacts in the signal. Possible solutions to this problem are discussed in the context of future work.

This study investigates the optimum usage of the new APOLLO Next Generation (APOLLO_NG) cloud retrieval scheme in the Heliosat‑4 solar surface irradiance retrieval scheme. APOLLO_NG replaces the previously used APOLLO scheme and introduces a probabilistic cloud mask instead of binary cloud masking used previously. A cloud probability threshold of 1 % was found optimal for the usage of the Heliosat‑4 cloud scheme. For direct irradiances, the use of an apparent optical depth in optically thin as well as in optically thick, but broken cloud conditions, was investigated. While for thin clouds the cloud optical thickness (COT) modification factor as known from literature was confirmed, a COT modification factor of 0.2 for optically thick, but broken clouds was identified. Furthermore, an improved calibration of the SEVIRI instrument was implemented. The updated method is applied for MSG SEVIRI observations without any additional bias-correction and validated for Europe and Africa against observations from the BSRN and EnerMENA networks. Special focus is placed on the central European region affected mainly by clouds and the North-African region with desert dust aerosols as well as clouds. The hourly SSI showed clear improvements. The relative bias of GHI ranges between −7 and 1.3 % with a mean value of −2.8 %. The relative RMSE of GHI is between 10.3 and 25.5 % and has a mean value of 13.7 %. The relative bias of DIR ranges between −16.6 and 17.8 % and has a mean value of −3.3 %. The relative RMSE of DIR is between 16.7 and 49 % with 29.7 % as mean. For European stations without strong aerosol effects but larger cloud impacts, the average relative GHI and DIR bias is −1.3 % and 3.3 % with mean relative GHI and DIR RMSE of 15.1 % and 30.6 % respectively. The presented method has been implemented into the Copernicus Atmosphere Monitoring Service (CAMS) Radiation Service v4.

The modification of an existing cloud property retrieval scheme for the Spinning Enhanced Visible and Infrared Imager (SEVIRI) instrument on board the geostationary Meteosat satellites is described to utilize its high-resolution visible (HRV) channel for increasing the spatial resolution of its physical outputs. This results in products with a nadir spatial resolution of 1×1 km2 compared to the standard 3×3 km2 resolution offered by the narrowband channels. This improvement thus greatly reduces the resolution gap between current geostationary and polar-orbiting meteorological satellite imagers. In the first processing step, cloudiness is determined from the HRV observations by a threshold-based cloud masking algorithm. Subsequently, a linear model that links the 0.6 µm, 0.8 µm, and HRV reflectances provides a physical constraint to incorporate the spatial high-frequency component of the HRV observations into the retrieval of cloud optical depth. The implementation of the method is described, including the ancillary datasets used. It is demonstrated that the omission of high-frequency variations in the cloud-absorbing 1.6 µm channel results in comparatively large uncertainties in the retrieved cloud effective radius, likely due to the mismatch in channel resolutions. A newly developed downscaling scheme for the 1.6 µm reflectance is therefore applied to mitigate the effects of this scale mismatch. Benefits of the increased spatial resolution of the resulting SEVIRI products are demonstrated for three example applications: (i) for a convective cloud field, it is shown that significantly better agreement between the distributions of cloud optical depth retrieved from SEVIRI and from collocated MODIS observations is achieved. (ii) The temporal evolution of cloud properties for a growing convective storm at standard and HRV spatial resolutions are compared, illustrating an improved contrast in growth signatures resulting from the use of the HRV channel. (iii) An example of surface solar irradiance, determined from the retrieved cloud properties, is shown, for which the HRV channel helps to better capture the large spatiotemporal variability induced by convective clouds. These results suggest that incorporating the HRV channel into the retrieval has potential for improving Meteosat-based cloud products for several application domains.

The successful electricity grid integration of solar energy into day-ahead markets requires at least hourly resolved 48 h forecasts. Technologies as photovoltaics and non-concentrating solar thermal technologies make use of global horizontal irradiance (GHI) forecasts, while all concentrating technologies both from the photovoltaic and the thermal sector require direct normal irradiances (DNI). The European Centre for Medium-Range Weather Forecasts (ECMWF) has recently changed towards providing direct as well as global irradiances. Additionally, the MACC (Monitoring Atmospheric Composition & Climate) near-real time services provide daily analysis and forecasts of aerosol properties in preparation of the upcoming European Copernicus programme. The operational ECMWF/IFS (Integrated Forecast System) forecast system will in the medium term profit from the Copernicus service aerosol forecasts. Therefore, within the MACC‑II project specific experiment runs were performed allowing for the assessment of the performance gain of these potential future capabilities. Also the potential impact of providing forecasts with hourly output resolution compared to three-hourly resolved forecasts is investigated. The inclusion of the new aerosol climatology in October 2003 improved both the GHI and DNI forecasts remarkably, while the change towards a new radiation scheme in 2007 only had minor and partly even unfavourable impacts on the performance indicators. For GHI, larger RMSE (root mean square error) values are found for broken/overcast conditions than for scattered cloud fields. For DNI, the findings are opposite with larger RMSE values for scattered clouds compared to overcast/broken cloud situations. The introduction of direct irradiances as an output parameter in the operational IFS version has not resulted in a general performance improvement with respect to biases and RMSE compared to the widely used Skartveit et al. (1998) global to direct irradiance conversion scheme. Cloudy situations and especially thin ice cloud cases are forecasted much better with respect to biases and RMSE, but large biases are introduced in clear sky cases. When applying the MACC aerosol scheme to include aerosol direct effects, an improvement especially in DNI biases is found for cloud free cases as expected. However, a performance decrease is found for water cloud cases. It is assumed that this is caused by the lack of an explicit modelling of cloud-aerosol interactions, while other meteorological forcings for cloud processes like the temperature field are modified by the aerosols.

A new fast clear-sky model called McClear was developed to estimate the downwelling shortwave direct and global irradiances received at ground level under clear skies. It is a fully physical model replacing empirical relations or simpler models used before. It exploits the recent results on aerosol properties, and total column content in water vapour and ozone produced by the MACC project (Monitoring Atmosphere Composition and Climate). It accurately reproduces the irradiance computed by the libRadtran reference radiative transfer model with a computational speed approximately 105 times greater by adopting the abaci, or look-up table, approach combined with interpolation functions. It is therefore suited for geostationary satellite retrievals or numerical weather prediction schemes with many pixels or grid points, respectively. McClear irradiances were compared to 1 min measurements made in clear-sky conditions at several stations within the Baseline Surface Radiation Network in various climates. The bias for global irradiance comprises between −6 and 25 W m−2. The RMSE ranges from 20 W m−2 (3% of the mean observed irradiance) to 36 W m−2 (5%) and the correlation coefficient ranges between 0.95 and 0.99. The bias for the direct irradiance comprises between −48 and +33 W m−2. The root mean square error (RMSE) ranges from 33 W m−2 (5%) to 64 W m−2 (10%). The correlation coefficient ranges between 0.84 and 0.98. This work demonstrates the quality of the McClear model combined with MACC products, and indirectly the quality of the aerosol properties modelled by the MACC reanalysis.

Solar energy applications need global aerosol optical depth (AOD) information to derive historic surface solar irradiance databases from geostationary meteorological satellites reaching back to the 1980's. This paper validates the MATCH/DLR model originating in the climate community against AERONET ground measurements. Hourly or daily mean AOD model output is evaluated individually for all stations in Europe, Africa and the Middle East – an area highly interesting for solar energy applications being partly dominated by high aerosol loads. Overall, a bias of 0.02 and a root-mean-square error (RMSE) of 0.23 are found for daily mean AOD values, while the RMSE increases to 0.28 for hourly mean AOD values. Large differences between various regions and stations are found providing a feedback loop for the aerosol modelling community. The difference in using daily means versus hourly resolved modelling with respect to hourly resolved observations is evaluated. Nowadays state-of-the-art in solar resource assessment relies on monthly turbidity or AOD climatologies while at least hourly resolved irradiance time series are needed by the solar sector. Therefore, the contribution of higher temporally modelled AOD is evaluated.

Parameterisation of changes of the solar irradiance at ground level with a specific variable (e.g. solar zenithal angle, aerosol optical depth, altitude, etc.) is often used in operational processes because it saves computational time. This paper deals with the modelling of the vertical profile of downwelling solar irradiance for the first two kilometres above ground in clear sky conditions. Two analytical parameterisations are evaluated for direct and global irradiance in spectral bands as well as for the total irradiance. These parameterisations reproduce the vertical profile with good accuracy for global spectral irradiance and are less accurate for direct component, especially in turbid atmosphere. A piecewise linear interpolation technique using irradiance values known at surface and 4 altitudes every 500 m performs better in any case.

An information content analysis for multi-wavelength SYNergetic AErosol Retrieval algorithm SYNAER was performed to quantify the number of independent pieces of information that can be retrieved. In particular, the capability of SYNAER to discern various aerosol types is assessed. This information content depends on the aerosol optical depth, the surface albedo spectrum and the observation geometry. The theoretical analysis is performed for a large number of scenarios with various geometries and surface albedo spectra for ocean, soil and vegetation. When the surface albedo spectrum and its accuracy is known under cloud-free conditions, reflectance measurements used in SYNAER is able to provide for 2–4° of freedom that can be attributed to retrieval parameters: aerosol optical depth, aerosol type and surface albedo. The focus of this work is placed on an information content analysis with emphasis to the aerosol type classification. This analysis is applied to synthetic reflectance measurements for 40 predefined aerosol mixtures of different basic components, given by sea salt, mineral dust, biomass burning and diesel aerosols, water soluble and water insoluble aerosols. The range of aerosol parameters considered through the 40 mixtures covers the natural variability of tropospheric aerosols. After the information content analysis performed in Holzer-Popp et al. (2008) there was a necessity to compare derived degrees of freedom with retrieved aerosol optical depth for different aerosol types, which is the main focus of this paper. The principle component analysis was used to determine the correspondence between degrees of freedom for signal in the retrieval and derived aerosol types. The main results of the analysis indicate correspondence between the major groups of the aerosol types, which are: water soluble aerosol, soot, mineral dust and sea salt and degrees of freedom in the algorithm and show the ability of the SYNAER to discern between this aerosol types. The results of the work will be further used for the development of the promising methodology of the construction error covariance matrices in the assimilation system.

Modelling of aerosol particles with chemical transport models is still based mainly on static emission databases while episodic emissions cannot be treated sufficiently. To overcome this situation, a coupling of chemical mass concentration modelling with satellite-based measurements relying on physical and optical principles has been developed. This study deals with the observation operator for a component-wise assimilation of satellite measurements. It treats aerosol particles classified into water soluble, water insoluble, soot, sea salt and mineral dust containing aerosol particles in the atmospheric boundary layer as separately assimilated aerosol components. It builds on a mapping of aerosol classes used both in observation and model space taking their optical and chemical properties into account. Refractive indices for primary organic carbon particles, anthropogenic particles, and secondary organic species have been defined based on a literature review. Together with a treatment of different size distributions in observations and model state, this allows transforming the background from mass concentrations into aerosol optical depths. A two-dimensional, variational assimilation is applied for component-wise aerosol optical depths. Error covariance matrices are defined based on a validation against AERONET sun photometer measurements. Analysis fields are assessed threefold: (1) through validation against AERONET especially in Saharan dust outbreak situations, (2) through comparison with the British Black Smoke and Sulphur Dioxide Network for soot-containing particles, and (3) through comparison with measurements of the water soluble components SO4, NH4, and NO3 conducted by the EMEP (European Monitoring and Evaluation Programme) network. Separately, for the water soluble, the soot and the mineral dust aerosol components a bias reduction and subsequent a root mean square error reduction is observed in the analysis for a test period from July to November 2003. Additionally, examples of an improved analysis during wildfire and dust outbreak situations are shown.

The synergetic aerosol retrieval method SYNAER (Holzer-Popp et al., 2002a) has been extended to the use of ENVISAT measurements. It exploits the complementary information of a radiometer and a spectrometer onboard one satellite platform to extract aerosol optical depth (AOD) and speciation (as a choice from a representative set of pre-defined mixtures of water-soluble, soot, mineral dust, and sea salt components). SYNAER consists of two retrieval steps. In the first step the radiometer is used for accurate cloud screening, and subsequently to quantify the aerosol optical depth (AOD) at 550 nm and spectral surface brightness through a dark field technique for different pre-defined aerosol mixtures. In the second step the spectrometer is applied to choose the most plausible aerosol mixture through a least square fit of the measured spectrum with simulated spectra using the mixture-dependent values of AOD and surface brightness retrieved in the first step. This method was developed and a first case study evaluation against few (15) multi-spectral ground-based AERONET sun photometer observations was conducted with a sensor pair (ATSR-2 and GOME) onboard ERS-2. Due to instrumental limitations the coverage of SYNAER/ERS-2 is very sparse. Therefore, SYNAER was transferred to similar sensors AATSR and SCIAMACHY onboard ENVISAT. While transferring to the new sensor pair significant improvements in the methodology were made based on a thorough evaluation of the methodology: (1) an update of the aerosol model, (2) improved cloud detection in the tropics and sub tropics, and (3) an enhanced dark field albedo characterization. This paper describes these improvements in detail and assesses their combined impact on the results. After a brief assessment of atmospheric noise impact on comparisons of pixel and station measurements a validation against ground-based measurements establishes error bars for the SYNAER/ENVISAT method version 2.0. A theoretical analysis of the information content with regard to aerosol composition (second retrieval step) is presented to quantify the potential and limitations of this new capability provided by the SYNAER method. Building on this analysis, first seasonal and monthly composition results calculated by applying SYNAER version 2.0 to AATSR and SCIAMACHY are shown to demonstrate the potential of the approach. An inter-comparison to earlier results of SYNAER version 1.0 is made for both the validation and the example datasets.

Monthly mean aerosol optical depth (AOD) over ocean is compared from a total of 9 aerosol retrievals during a 40 months period. Comparisons of AOD have been made both for the entire period and sub periods. We identify regions where there is large disagreement and good agreement between the aerosol satellite retrievals. Significant differences in AOD have been identified in most of the oceanic regions. Several analyses are performed including spatial correlation between the retrievals as well as comparison with AERONET data. During the 40 months period studied there have been several major aerosol field campaigns as well as events of high aerosol content. It is studied how the aerosol retrievals compare during such circumstances. The differences found in this study are larger than found in a previous study where 5 aerosol retrievals over an 8 months period were compared. Part of the differences can be explained by limitations and deficiencies in some of the aerosol retrievals. In particular, results in coastal regions are promising especially for aerosol retrievals from satellite instruments particularly suited for aerosol research. In depth analyses explaining the differences between AOD obtained in different retrievals are clearly needed. We limit this study to identifying differences and similarities and indicating possible sources that affect the quality of the retrievals. This is a necessary first step towards understanding the differences and improving the retrievals.

We have analysed the upper tropospheric humidity with respect to ice (UTHi) data product obtained from the Television Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) instrument onboard the National Oceanic and Atmospheric Administration NOAA-14 polar orbiting satellite. While in the production of the official UTHi product values in excess of 100% are ignored, we do not so - in view of many recent results obtained from a variety of other in-situ and remote sensing instruments showing that ice supersaturation frequently occurs in the upper troposphere. We show that TOVS is able to detect ice supersaturation at the correct locations (however, only in less than one percent of its soundings, presumably because of TOVS's low vertical resolution), and that the supersaturation follows the well known exponential behaviour. We conclude that values of UTHi in excess of saturation should not be considered a measurement error anymore. The similar re-analysis of TOVS data back to 1979 could give important insights into trends of upper tropospheric humidity.

We present a unique, extensive, and open synaptic physiology analysis platform and dataset. Through its application, we reveal principles that relate cell type to synaptic properties and intralaminar circuit organization in the mouse and human cortex. The dynamics of excitatory synapses align with the postsynaptic cell subclass, whereas inhibitory synapse dynamics partly align with presynaptic cell subclass but with considerable overlap. Synaptic properties are heterogeneous in most subclass-to-subclass connections. The two main axes of heterogeneity are strength and variability. Cell subclasses divide along the variability axis, whereas the strength axis accounts for substantial heterogeneity within the subclass. In the human cortex, excitatory-to-excitatory synaptic dynamics are distinct from those in the mouse cortex and vary with depth across layers 2 and 3.

Over the past decades, solar panels have been widely used to harvest solar energy owing to the decreased cost of silicon-based photovoltaic (PV) modules, and therefore it is essential to remotely map and monitor the presence of solar PV modules. Many studies have explored on PV module detection based on color aerial photography and manual photo interpretation. Imaging spectroscopy data are capable of providing detailed spectral information to identify the spectral features of PV, and thus potentially become a promising resource for automated and operational PV detection. However, PV detection with imaging spectroscopy data must cope with the vast spectral diversity of surface materials, which is commonly divided into spectral intra-class variability and inter-class similarity. We have developed an approach to detect PV modules based on their physical absorption and reflection characteristics using airborne imaging spectroscopy data. A large database was implemented for training and validating the approach, including spectra-goniometric measurements of PV modules and other materials, a HyMap image spectral library containing 31 materials with 5627 spectra, and HySpex imaging spectroscopy data sets covering Oldenburg, Germany. By normalizing the widely used Hydrocarbon Index (HI), we solved the intra-class variability caused by different detection angles, and validated it against the spectra-goniometric measurements. Knowing that PV modules are composed of materials with different transparencies, we used a group of spectral indices and investigated their interdependencies for PV detection with implementing the image spectral library. Finally, six well-trained spectral indices were applied to HySpex data acquired in Oldenburg, Germany, yielding an overall PV map. Four subsets were selected for validation and achieved overall accuracies, producer's accuracies and user's accuracies, respectively. This physics-based approach was validated against a large database collected from multiple platforms (laboratory measurements, airborne imaging spectroscopy data), thus providing a robust, transferable and applicable way to detect PV modules using imaging spectroscopy data. We aim to create greater awareness of the potential importance and applicability of airborne and spaceborne imaging spectroscopy data for PV modules identification., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 The Authors. Published by Elsevier Inc.)

Understanding the diversity of cell types in the brain has been an enduring challenge and requires detailed characterization of individual neurons in multiple dimensions. To systematically profile morpho-electric properties of mammalian neurons, we established a single-cell characterization pipeline using standardized patch-clamp recordings in brain slices and biocytin-based neuronal reconstructions. We built a publicly accessible online database, the Allen Cell Types Database, to display these datasets. Intrinsic physiological properties were measured from 1,938 neurons from the adult laboratory mouse visual cortex, morphological properties were measured from 461 reconstructed neurons, and 452 neurons had both measurements available. Quantitative features were used to classify neurons into distinct types using unsupervised methods. We established a taxonomy of morphologically and electrophysiologically defined cell types for this region of the cortex, with 17 electrophysiological types, 38 morphological types and 46 morpho-electric types. There was good correspondence with previously defined transcriptomic cell types and subclasses using the same transgenic mouse lines.

Adrenomedullin (ADM) is a vasoactive peptide in sepsis. The non-neutralizing ADM-binding antibody Adrecizumab improved outcome in animal models of systemic inflammation and sepsis. Herein, we evaluated the preclinical safety of Adrecizumab in various animal species. First, Wistar rats received vehicle, 100, 200 or 400 mg/kg/day of Adrecizumab intravenously (n = 20 each) on days 1, 4, 8 and 14. An additional set of rats received vehicle or 400 mg/kg/day (n = 10 each) on the same days and were followed for 42 days. For toxicokinetics, satellite animals received vehicle (n = 6), 100, 200, or 400 mg/kg/day Adrecizumab intravenously (n = 18 each). A hemodynamic study was performed in Beagle dogs (n = 3) receiving vehicle (day 1), 2 mg/kg (day 3), 10 mg/kg (day 5), 50 mg/kg (day 8) and 10 mg/kg Adrecizumab intravenously (day 29). In final experiments, cynomolgus monkeys received vehicle, 25, 50 or 100 mg/kg/day Adrecizumab intravenously (n = 6 each) on days 1, 4, 8 and 14. Additional groups of monkeys received vehicle or 100 mg/kg/day Adrecizumab intravenously (n = 4 each) on the same days and were followed for 42 days. No mortality or moribund conditions occurred and no toxicologically relevant effects were attributed to Adrecizumab. Adrecizumab significantly increased circulating concentrations of its target peptide ADM, consistent with previous studies and mechanistically relevant. Toxicokinetic analyses showed immediate and dose-dependent peak concentrations, slow elimination and no gender differences. In conclusion, intravenous, repeated administration of high doses of Adrecizumab appeared well-tolerated across species. These results pave the way for further investigation of Adrecizumab in humans (intended dose of 2 mg/kg)., (Copyright © 2019. Published by Elsevier Inc.)

Purpose: Adrenomedullin (ADM) is an important regulator of endothelial barrier function during sepsis. Administration of a murine antibody targeted against the N-terminus of ADM (HAM1101) resulted in improved outcome in models of murine sepsis. We studied the effects of a humanized form of this antibody (HAM8101, also known as Adrecizumab) on vascular barrier dysfunction and survival in rodent models of systemic inflammation and sepsis., Methods: Rats (n=48) received different dosages of HAM8101 or placebo (n = 8 per group), directly followed by administration of lipopolysaccharide (5 mg/kg). Twenty-four hours later, Evans Blue dye was administered to assess vascular leakage in kidney and liver tissue. Furthermore, mice (n = 24) were administered different dosages of HAM8101 or placebo (n = 6 per group), immediately followed by cecal ligation and puncture (CLP). Eighteen hours later, albumin, vascular endothelial growth factor (VEGF), and angiopoietin-1 were analyzed in the kidney. Finally, effects of single and repeated dose administration of HAM1101, HAM8101 and placebo on survival were assessed in CLP-induced murine sepsis (n = 60, n = 10 per group)., Results: Dosages of 0.1 and 2.5 mg/kg HAM8101 attenuated renal albumin leakage in endotoxemic rats. Dosages of 0.1, 2.0, and 20 mg/kg HAM8101 reduced renal concentrations of albumin and the detrimental protein VEGF in septic mice, whereas concentrations of the protective protein angiopoietin-1 were augmented. Both single and repeated administration of both HAM1101 and HAM8101 resulted in improved survival during murine sepsis., Conclusions: Pretreatment with the humanized anti-ADM antibody HAM8101 improved vascular barrier function and survival in rodent models of systemic inflammation and sepsis.

Substantial attention and resources have been directed to improving outcomes of patients with critical illnesses, in particular sepsis, but all recent clinical trials testing various interventions or strategies have failed to detect a robust benefit on mortality. Acute heart failure is also a critical illness, and although the underlying etiologies differ, acute heart failure and sepsis are critical care illnesses that have a high mortality in which clinical trials have been difficult to conduct and have not yielded effective treatments. Both conditions represent a syndrome that is often difficult to define with a wide variation in patient characteristics, presentation, and standard management across institutions. Referring to past experiences and lessons learned in acute heart failure may be informative and help frame research in the area of sepsis. Academic heart failure investigators and industry have worked closely with regulators for many years to transition acute heart failure trials away from relying on dyspnea assessments and all-cause mortality as the primary measures of efficacy, and recent trials have been designed to assess novel clinical composite endpoints assessing organ dysfunction and mortality while still assessing all-cause mortality as a separate measure of safety. Applying the lessons learned in acute heart failure trials to severe sepsis and septic shock trials might be useful to advance the field. Novel endpoints beyond all-cause mortality should be considered for future sepsis trials.

We report the detection of pulsed gamma rays from the Crab pulsar at energies above 100 giga-electron volts (GeV) with the Very Energetic Radiation Imaging Telescope Array System (VERITAS) array of atmospheric Cherenkov telescopes. The detection cannot be explained on the basis of current pulsar models. The photon spectrum of pulsed emission between 100 mega-electron volts and 400 GeV is described by a broken power law that is statistically preferred over a power law with an exponential cutoff. It is unlikely that the observation can be explained by invoking curvature radiation as the origin of the observed gamma rays above 100 GeV. Our findings require that these gamma rays be produced more than 10 stellar radii from the neutron star.

The accretion of matter onto a massive black hole is believed to feed the relativistic plasma jets found in many active galactic nuclei (AGN). Although some AGN accelerate particles to energies exceeding 10(12) electron volts and are bright sources of very-high-energy (VHE) gamma-ray emission, it is not yet known where the VHE emission originates. Here we report on radio and VHE observations of the radio galaxy Messier 87, revealing a period of extremely strong VHE gamma-ray flares accompanied by a strong increase of the radio flux from its nucleus. These results imply that charged particles are accelerated to very high energies in the immediate vicinity of the black hole.