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Dataset from the outdoor characterization of a B Series module from Insolight at the rooftop of the Instituto de Energía Solar - Universidad Politécnica de Madrid. These are measurements of a module of the same type as “Outdoor monitoring data of an Insolight B-series module - CPV sub-module” however, in the previous measurements the module was mounted on a two-axis tracker to benchmark its performance, while in these measurements, the module’s integrated planar micro tracking system was used. This data was presented at IEEE PVSC 46 in June 2019 in Chicago. See preprint of conference article. Monitoring campaign: Location: 40.453°N, -3.727°E. Instituto de Energía Solar, Universidad Politécnica de Madrid. 28040 Madrid, Spain. Fixed Mounting Angle: Due South, Slope Angle = 30° Starting date: 30 May 2019 End date: 14 June 2018 Description of data file: Data files format: single comma-separated text file; headers in first row; all of the following parameters; order below is the same as order in file Measurement time: the vector of times represents the times at which the Insolight module firmware sampled the current values of the III-V and Si outputs (measured simultaneously). Date Time (dd/mmm/yyyy HH:MM:SS): time in CEST / UTC+2 Measured meteorological data: these values are measured directly by the IES meteorological station with 1-minute resolution. They have been re-interpolated to match the measurement times. DNI (W/m2): direct normal irradiance as measured by a Normal Incidence Pyrheliometer from Eppley on a solar tracker. Spectral Range: 250-3000 nm. Field of view: 5° DNI_Top (W/m2): equivalent direct normal irradiance as measured by a top component cell of a lattice-matched III-V triple-junction cell in the ICU-3J35 Triband Spectro-heliometer from Solar Added Value on a solar tracker. Spectral range: 300 - 680 nm. Field of view: 5.7º DNI_Mid (W/m2): equivalent direct normal irradiance as measured by a middle component cell of a lattice-matched III-V triple-junction cell in the ICU-3J35 Triband Spectro-heliometer from Solar Added Value on a solar tracker. Spectral range: 680 - 900 nm. Field of view: 5.7º GNI (W/m2): global normal irradiance at the aperture plane as measured with a pyranometer on a solar tracker. Spectral range: 305 – 2800 nm. G(41°) (W/m2): Global Inclined Irradiance as measured with a pyranometer mounted facing due south and at a slope angle of 41° (near to local latitude). Spectral range: 305 – 2800 nm. T_Amb (°C): ambient temperature Wind Speed (m/s): wind speed Wind Dir. (m/s): wind direction Processed meteorological data: these values are calculated from the above meteorological data and provided for convenience DII (W/m2): Direct Inclined (plane of array) Irradiance corresponding to the module slope angle has been calculated using the sun’s known declination and hour angle from the time. GII (W/m2): The Global Inclined (plane of array) Irradiance is calculated by first calculating the DII(41°), that is the DII corresponding to the G(41°) measurement, and finding the Diffuse Inclined Irradiance Diff(41°) = G(41°) – DII(41°). It is assumed that the Diffuse Inclined Irradiance at 41° and 30° is equal, so GII = DII + Diff(41°). SMR_Top_Mid (n.d.): “Spectral Matching Ratio”. This is the ratio between DNI_Top and DNI_Mid. A value of unity indicates a spectrum that is equivalent to AM1.5D with regards to the energy balance between top and middle subcells. Measured module data: The module was placed in a short-ciruit condition and allowed to track using its integrated tracking system. The short circuit current was measured using shut resistors and integrated A/D channels. This hybrid module features both III-V micro cells (under concentration, with planar microtracking) and large area silicon solar cells (for diffuse capture). ISC_measured_IIIV (A): ISC_measured_Si (A) Estimated module data: As is explained in the IEEE PVSC 46 manuscript (see Preprint) the following values are estimated using the previously listed measured data. T_Backplane (°C) PMP_estimated_IIIV (W) PMP_estimated_Si (W)

Sheets with information on the FOODRUS KPIs, including: general description, calculation methodology, and observations.

This is a complementary dataset associated with the following publication: Berrang-Ford, Lea, et al. "Systematic Mapping of Global Research on Climate and Health Using Machine Learning." The Lancet Planetary Health. Meta-data are included.

Research data and scientific software related to spatio-temporal estimations of ecological soil moisture with available data covering the whole territory of Germany and the Kellerwald National Park (Hesse). Temporal trends of modelled soil moisture for the time period 1961–2070 were statistically analyzed. Soil moisture changes (drying-out) at both national and regional levels were mapped. {"references": ["Nickel S, Schr\u00f6der W 2017. Fuzzy modelling and mapping soil moisture for observed and future periods. An alternative for dynamic modelling at the national and regional scale? Annals of Forest Science 74:71"]}

Editorial Complex Optimization and Simulation in Power Systems

This study focuses on formulating the most sustainable concrete by incorporating recycled concrete aggregates and other products retrieved from construction and demolition (C&D) activities. Both recycled coarse aggregates (RCA) and recycled fine aggregates (RFA) are firstly used to fully replace the natural coarse and fine aggregates in the concrete mix design. Later, the cement rich ultrafine particles, recycled glass powder and mineral fibres recovered from construction and demolition wastes (CDW) are further incorporated at a smaller rate either as cement substituent or as supplementary additives. Remarkable properties are noticed when the RCA (4–12 mm) and RFA (0.25–4 mm) are fully used to replace the natural aggregates in a new concrete mix. The addition of recycled cement rich ultrafines (RCU), Recycled glass ultrafines (RGU) and recycled mineral fibres (RMF) into recycled concrete improves the modulus of elasticity. The final concrete, which comprises more than 75% (wt.) of recycled components/materials, is believed to be the most sustainable and green concrete mix. Mechanical properties and durability of this concrete have been studied and found to be within acceptable limits, indicating the potential of recycled aggregates and other CDW components in shaping sustainable and circular construction practices. The authors wish to acknowledge the financial support from EU Horizon 2020 Project VEEP ‘‘Cost-Effective Recycling of C&DW in High Added Value Energy Efficient Prefabricated Concrete Compo-nents for Massive Retrofitting of our Built Environment” (No.723582).

In the context of rapid climate change, phenological advance is a key adaptation for which evidence is accumulating across taxa. Among vertebrates, phenotypic plasticity is known to underlie most of this phenological change, while evidence for micro-evolution is very limited and challenging to obtain. In this study, we quantified phenotypic and genetic trends in timing of spring migration using 8032 dates of arrival at the breeding grounds obtained from observations on 1715 individual common terns (Sterna hirundo) monitored across 27 years, and tested whether these trends were consistent with predictions of a micro-evolutionary response to selection. We observed a strong phenotypic advance of 9.3 days in arrival date, of which c. 5% was accounted for by an advance in breeding values. The Breeder’s equation and Robertson’s Secondary Theorem of Selection predicted qualitatively similar evolutionary responses to selection, and these theoretical predictions were largely consistent with our estimated genetic pattern. Overall, our study provides rare evidence for micro-evolution underlying (part of) an adaptive response to climate change in the wild and illustrates how a combination of adaptive micro-evolution and phenotypic plasticity facilitated a shift towards earlier spring migration in this free-living population of common terns. Data used for models presented in: Micro-evolutionary response of spring migration timing in a wild seabird by Moiron M, Teplitsky C, Haest B, Charmantier A†, Bouwhuis S† († = shared last authors) published in Evolution Letters. for information regarding the analyses, please contact mariamoironc@gmail.com for information regarding the data, please contact sandra.bouwhuis@ifv-vogelwarte.de if you'd like to use the data, please also contact sandra.bouwhuis@ifv-vogelwarte.de These data are part of those collected in an ongoing individual-based longitudinal population study additional data are likely to be available, and we are often very happy to collaborate provided that none of our own staff or students is working on a conflicting project.