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This is a Phase 3 multicenter, double-blind, double-dummy, randomized study. Only subjects with PV who have received HU for at least 12 weeks, have been receiving a stable dose before screening, and still have symptoms related to PV will be enrolled. Subjects will be randomized (1:1) to 1 of 2 treatment arms: A: ruxolitinib and HU-placebo B: HU and ruxolitinib-placebo Subjects randomized to either arm may be eligible to transition to open-label ruxolitinib after Week 16. The purpose of the RELIEF study is to compare symptoms in polycythemia vera (PV) subjects treated with ruxolitinib versus subjects treated with hydroxyurea (HU) as measured by the percent of subjects who achieve a clinically meaningful symptom improvement (ie, total symptom score reduction of ≥ 50% reduction) at Week 16 compared to Baseline. The study is also designed to demonstrate that these responses are durable with continued treatment.

# Reproductive data Fagus sylvatica: Widespread masting breakdown in beech [https://doi.org/10.5061/dryad.qz612jmps](https://doi.org/10.5061/dryad.qz612jmps) This dataset, used in the Global Change Biology article "Widespread breakdown in masting in European beech due to rising summer temperatures", contains 50 time series of population-level annual reproductive data by European beech (*Fagus sylvatica*, L) across Europe. The dataset builds on the open-access dataset [MASTREE+](https://doi.org/10.1111/gcb.16130), and expands it for European beech. ## Description of the data The dataset column names follow that of MASTREE+. A description of MASTREE+ column names (Modified from Table 1 in the [MASTREE+ article)](https://doi.org/10.1111/gcb.16130): | *Columns* | *Description* | *Contains NA?* | | :-------------------- | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :------------- | | Alpha\_Number | Unique code associated with each original source of data, that is, the publication, report or thesis containing extracted data, or the previously unpublished data set included in MASTREE+. | No | | Segment | Temporal segment of a time-series containing gaps (note that years with no observations are not recorded). Individual timeseries can consist of multiple segments. | No | | Site\_number | Code to differentiate multiple sites from the same original source (Alpha\_Number/Study\_ID). | No | | Variable\_number | Code to differentiate multiple measures of reproductive output from the same species-site combination (e.g. where seeds and cones were recorded separately). | No | | Year | Year of observation. | No | | Species | Species identifier, standardised to The Plant List nomenclature. ‘spp.’ is used to indicate a record identified to the genus level only. ‘MIXED’ indicates a non-species-specific community-level estimate of annual reproductive effort. | No | | Species\_code | Six-character species identifier. | No | | Mono\_Poly | Monocarpic (semelparous) or Polycarpic (iteroparous) species. | No | | Value | The measured value of annual reproductive output. | No | | VarType | Continuous or ordinal data. Continuous time-series are recorded on a continuous scale. Ordinal series are recorded on an ordered categorical scale. All ordinal series are rescaled to start at 1 (lowest reproductive effort) and to contain only integer values. | No | | Max\_value | The unit of measurement, where VarType is continuous (otherwise: NA). | No | | Unit | The maximum value in a time-series. | No | | Variable | Categorical classification of the measured variable. Options limited to: cone, flower, fruit, seed, pollen, total reproduction organs. | No | | Collection\_method | Classification of the method used to measure reproductive effort. Options are limited to: cone count, cone scar count, flower count, fruit count, fruit scar sound, seed count, seed trap, pollen count, lake sediment pollen count, harvest record, visual crop assessment, other quantification, dendrochronological reconstruction. | No | | Latitude | Latitude of the record, in decimal degrees. | No | | Longitude | Longitude of the record, in decimal degrees. | No | | Coordinate\_flag | A flag to indicate the precision of the latitude and longitude. A = coordinates provided in the original source B = coordinates estimated by the compiler based on a map or other location information provided in the original source C = coordinates estimated by the compiler as the approximate centre point of the smallest clearly defined geographical unit provided in the original source (e.g. county, state, island), and potentially of low precision. | No | | Site | A site name or description, based on information in the original source. | No | | Country | The country where the observation was recorded. | No | | Elevation | The elevation of the sample site in metres above sea level, where provided in the original source (otherwise: NA). | Yes | | Spatial\_unit | Categorical classification of spatial scale represented by the record, estimated by the compiler based on information provided in the original source. stand = <100 ha, patch = 100–10,000 ha, region = 10,000–1,000,000 ha, super-region = >1,000,000 ha. | No | | No\_indivs | Either the number of monitored individual plants, or the number of litter traps. NA indicates no information in the original source, and 9999 indicates that while the number of monitored individuals was not specified, the source indicated to the compiler that the sample size was likely ≥10 individuals or litter traps. | No | | Start | The first year of observations for the complete time-series, including all segments. | No | | End | The final year of observations for the complete time-series, including all segments. | No | | Length | The number of years of observations. Note that may not be equal to the number of years between the Start and End of the time-series, due to gaps in the time-series. | No | | Reference | Identification for the original source of the data. | No | | Record\_type | Categorisation of the original source. Peer-reviewed = extracted from peer reviewed literature Grey = extracted from grey literature Unpublished = unpublished data. | No | | ID\_enterer | Identification of the original compiler of the data. AHP, Andrew Hacket-Pain; ES, Eliane Schermer; JVM, Jose Moris; XTT, Tingting Xue; TC, Thomas Caignard; DV, Davide Vecchio; DA, Davide Ascoli; IP, Ian Pearse; JL, Jalene LaMontagne; JVD, Joep van Dormolen. | No | | Date\_entry | Date of data entry into MASTREE+ in the format yyyy-mm-dd. | No | | Note on data location | Notes on the location of the data within the original source, such as page or figure number. If not provided, NA. | Yes | | Comments | Additional comments. If not provided, NA. | Yes | | Study\_ID | Unique code associated with each source of data. M\_ = series extracted from published literature; A\_ = series incorporated from Ascoli et al. (2020), Ascoli, Maringer, et al. (2017) and Ascoli, Vacchiano, et al. (2017); PLK\_ = series incorporated from Pearse et al. (2017); D\_ = unpublished data sets. NA is attributed if no study ID has been previously associated with this time-series in MASTREE+ v.1. | Yes | Note that the new beech reproductive data has been assigned an arbitrary Alpha_Number for the purpose of this study. Future MASTREE+ updates which incorporate this new data may alter the time series ID columns (e.g. Alpha_Number, Site_number, Variable_number). MASTREE+ updates can be found on [GITHUB](https://github.com/JJFoest/MASTREEplus). Climate change effects on tree reproduction are poorly understood even though the resilience of populations relies on sufficient regeneration to balance increasing rates of mortality. Forest-forming tree species often mast, i.e. reproduce through synchronised year-to-year variation in seed production, which improves pollination and reduces seed predation. Recent observations in European beech show, however, that current climate change can dampen interannual variation and synchrony of seed production, and that this masting breakdown drastically reduces the viability of seed crops. Importantly, it is unclear under which conditions masting breakdown occurs, and how widespread breakdown is in this pan-European species. Here, we analysed 50 long-term datasets of population-level seed production, sampled across the distribution of European beech, and identified increasing summer temperatures as the general driver of masting breakdown. Specifically, increases in site-specific mean maximum temperatures during June and July were observed across most of the species range, while the interannual variability of population-level seed production (CVp) decreased. The declines in CVp were greatest where temperatures increased most rapidly. Additionally, the occurrence of crop failures and low-seed years has decreased during the last four decades, signalling altered starvation effects of masting on seed predators. Notably, CVp did not vary among sites according to site mean summer temperature. Instead, masting breakdown occurs in response to warming local temperatures (i.e. increasing relative temperatures), such that the risk is not restricted to populations growing in warm average conditions. As lowered CVp can reduce viable seed production despite the overall increase in seed count, our results warn that a covert mechanism is underway that may hinder the regeneration potential of European beech under climate change, with great potential to alter forest functioning and community dynamics.

As part of the Copenhagen Accord, individual countries have submitted greenhouse gas reduction proposals for the year 2020. This paper analyses the implications for emission reductions, the carbon price, and abatement costs of these submissions. The submissions of the Annex I (industrialised) countries are estimated to lead to a total reduction target of 12-18% below 1990 levels. The submissions of the seven major emerging economies are estimated to lead to an 11-14% reduction below baseline emissions, depending on international (financial) support. Global abatement costs in 2020 are estimated at about USD 60-100 billion, assuming that at least two-thirds of Annex I emission reduction targets need to be achieved domestically. The largest share of these costs are incurred by Annex I countries, although the costs as share of GDP are similar for Annex I as a group and the seven emerging economies as a group, even when assuming substantial international transfers from Annex I countries to the emerging economies to finance their abatement costs. If the restriction of achieving two-thirds of the emission reduction target domestically is abandoned, it would more than double the international carbon price and at the same time reduce global abatement costs by almost 25%.

Abstract The design and operation of a new clapboard-type internal circulating fluidized-bed gasifier is proposed in this article. By arranging the clapboard in the bed, the gasifier is thus divided into two regions, which are characterized by different fluidization velocities. The bed structure is designed so that it can guide the circulating flow passing through the two regions, and therefore the feedstock particles entrained in the flow experience longer residence time. The experimental results based on the present new design, operating in the temperature range of 790°C–850°C, indicate that the gas yield is from 1.6–1.9 Nm3/kg feedstock, the gas enthalpies are 5,345 kJ/Nm3 for wood chip and 4,875 kJ/m3 for rice husk, and a gasification efficiency up to 75% can be obtained.

The hygrothermal behaviour of an internally insulated historic wall is still hard to predict, mainly because the physical characteristics of the materials composing the historic wall are unknown. In this study, the hygrothermal assessment of an internally thermal insulated masonry wall of an historic palace located in Ferrara, in Italy, is shown. In situ non-destructive monitoring method is combined with a hygrothermal simulation tool, aiming to better analyse and discuss future refurbishment scenarios. In this context, the original U-value of the wall (not refurbished) is decreased from 1.44 W/m2K to 0.26 W/m2K (10 cm stone wool). Under the site specific conditions of this wall, not reached by the sun or rain, it was verified that even in the absence of vapour barrier, no frost damage is likely to occur and the condensation risk is very limited. Authors proposed further discussion based on simulation. The results showed that the introduction of a second gypsum board to the studied technology compensated such absence, while the reduction of the insulation material thickness provides a reduction of RH peaks in the interstitial area by 1%; this second solution proved to be more efficient, providing a 3% RH reduction and the avoidance of further thermal losses.

Malnutrition is a common sequel among patients affected by Crohn's disease (CD). The pathogenic mechanisms include poor dietary intake, increased resting energy expenditure (REE), nutrient malabsorption and loss. So far, few studies have been carried out in CD adult patients, assessing the effect of disease activity on both REE and body composition. Vaisman et al (2006) studied sixteen CD patients in remission (> 3 mo) and showed no effect of REE on lower BMI, although in the presence of similar energy intake in according with previous studies (Al-Jaouni et al., 2000; Schneeweiss et al., 1999). While, Gong et al., 2015 found that patients with active disease had an increase in REE compared to patients in remission as already shown by Rigaud et al., 1993; Kushner and Schoeller, 1991. Overall, the effect of disease activity on REE is still uncertain and requires further investigation. The aim of this study is to investigate the effect disease activity on resting energy expenditure (REE), body composition, inflammatory markers, food intake and quality of life in subjects affected by Crohn's Disease (CD)

Data type: XRD patterns; SEM micrographs and EDX maps; particle size distributions; atomic concentrations; hydrogen loading profiles; kinetic models; volume expansions. Data format: *.opj; *.tif. Origin of the data: laboratory equipment from Hereon (XRD, SEM, PSD Analyzer, BET, XPS, Sievert apparatus) and UniPV (SEM). Software needed to plot the data: folders need to be unzipped, Origin.

Data and scripts to replicate the results and the figures presented in "Declining cost of renewables and climate change curb the need for African hydropower expansion"