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Bias correction of climate variables is a standard practice in climate change impact (CCI) studies. Various methodologies have been developed within the framework of quantile mapping. However, it is well known that quantile mapping may significantly modify the long-term statistics due to the time dependency of the temperature bias. Here, a method to overcome this issue without compromising the day-to-day correction statistics is presented. The methodology separates the modeled temperature signal into a normalized and a residual component relative to the modeled reference period climatology, in order to adjust the biases only for the former and preserve the signal of the later. The results show that this method allows for the preservation of the originally modeled long-term signal in the mean, the standard deviation and higher and lower percentiles of temperature. To illustrate the improvements, the methodology is tested on daily time series obtained from five Euro CORDEX regional climate models (RCMs).

Global climate model (GCM) outputs feature systematic biases that render them unsuitable for direct use by impact models, especially for hydrological studies. To deal with this issue, many bias correction techniques have been developed to adjust the modelled variables against observations, focusing mainly on precipitation and temperature. However, most state-of-the-art hydrological models require more forcing variables, in addition to precipitation and temperature, such as radiation, humidity, air pressure, and wind speed. The biases in these additional variables can hinder hydrological simulations, but the effect of the bias of each variable is unexplored. Here we examine the effect of GCM biases on historical runoff simulations for each forcing variable individually, using the JULES land surface model set up at the global scale. Based on the quantified effect, we assess which variables should be included in bias correction procedures. To this end, a partial correction bias assessment experiment is conducted, to test the effect of the biases of six climate variables from a set of three GCMs. The effect of the bias of each climate variable individually is quantified by comparing the changes in simulated runoff that correspond to the bias of each tested variable. A methodology for the classification of the effect of biases in four effect categories (ECs), based on the magnitude and sensitivity of runoff changes, is developed and applied. Our results show that, while globally the largest changes in modelled runoff are caused by precipitation and temperature biases, there are regions where runoff is substantially affected by and/or more sensitive to radiation and humidity. Global maps of bias ECs reveal the regions mostly affected by the bias of each variable. Based on our findings, for global-scale applications, bias correction of radiation and humidity, in addition to that of precipitation and temperature, is advised. Finer spatial-scale information is also provided, to suggest bias correction of variables beyond precipitation and temperature for regional studies.

Streamflow in south-central Chile (SCC, ∼ 37–42∘ S) is vital for agriculture, forestry production, hydroelectricity, and human consumption. Recent drought episodes have generated hydrological deficits with damaging effects on these activities. This region is projected to undergo major reductions in water availability, concomitant with projected increases in water demand. However, the lack of long-term records hampers the development of accurate estimations of natural variability and trends. In order to provide more information on long-term streamflow variability and trends in SCC, here we report findings of an analysis of instrumental records and a tree-ring reconstruction of the summer streamflow of the Río Imperial (∼ 37∘ 40′ S–38∘ 50′ S). This is the first reconstruction in Chile targeted at this season. Results from the instrumental streamflow record (∼ 1940 onwards) indicated that the hydrological regime is fundamentally pluvial with a small snowmelt contribution during spring, and evidenced a decreasing trend, both for the summer and the full annual record. The reconstruction showed that streamflow below the average characterized the post-1980 period, with more frequent, but not more intense, drought episodes. We additionally found that the recent positive phase of the Southern Annular Mode has significantly influenced streamflow. These findings agree with previous studies, suggesting a robust regional signal and a shift to a new hydrological scenario. In this paper, we also discuss implications of these results for water managers and stakeholders; we provide rationale and examples that support the need for the incorporation of tree-ring reconstructions into water resources management.

This research aims to determined the effect of promotions and discounts on purchasing decisions cosmetics brand The Body Shop Outlet Sun Plaza Medan. The type of this research is quantitative descriptive with survey method. Sample of this research is 100 consumers of The Body Shop Outlet Sun Plaza Medan, using proportionate stratified random sampling. The hypothesis in this research is tasted using multiple regression analysis and descriptive statistical analysis. The research showed that the promotions partial positive and significant influence on purchasing decisions, while the discounts are not positive and significant impact on the consumer purchasing decisions on brand cosmetic products The Body Shop Outlet Sun Plaza Medan. Simultaneously the influence of promotions and discounts positive and significant impact on purchasing decisions cosmetics brand The Body Shop Outlet Sun Plaza Medan. 110502228

The niche concept is essential to understanding how biotic and abiotic factors regulate the abundance and distribution of living entities, and how these organisms utilize, affect and compete for resources in the environment. However, it has been challenging to determine the number and types of important niche dimensions. By contrast, there is strong mechanistic theory and empirical evidence showing that the elemental composition of living organisms shapes ecological systems, from organismal physiology to food web structure. We propose an approach based on a multidimensional elemental view of the ecological niche. Visualizing the stoichiometric composition of individuals in multivariate space permits quantification of niche dimensions within and across species. This approach expands on previous elemental characterizations of plant niches, and adapts metrics of niche volume, overlap and nestedness previously used to quantify isotopic niches. We demonstrate the applicability of the multidimensional stoichiometric niche using data on carbon, nitrogen, and phosphorus of terrestrial and freshwater communities composed by multiple trophic groups. First, we calculated the stoichiometric niche volumes occupied by terrestrial and freshwater food webs, by trophic groups, by individual species, and by individuals within species, which together give a measure of the extent of stoichiometric diversity within and across levels of organization. Then we evaluated complementarity between these stoichiometric niches, through metrics of overlap and nestedness. Our case study showed that vertebrates, invertebrates, and primary producers do not overlap in their stoichiometric niches, and that large areas of stoichiometric space are unoccupied by organisms. Within invertebrates, niche differences emerged between freshwater and terrestrial food webs, and between herbivores and non-herbivores (detritivores and predators). These niche differences were accompanied by changes in the covariance structure of the three elements, suggesting fundamental shifts in organismal physiology and/or structure. We also demonstrate the sensitivity of results to sample size, and suggest that representative sampling is better than rarefaction in characterizing the stoichiometric niche occupied by food webs. Overall, our approach demonstrates that stoichiometric traits provide a common currency to estimate the dimensionality of stoichiometric niches, and help reduce and rationalize the number of axis required to characterize communities.

The second Cabauw Intercomparison of Nitrogen Dioxide measuring Instruments (CINDI-2) took place in Cabauw (the Netherlands) in September 2016 with the aim of assessing the consistency of multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements of tropospheric species (NO2, HCHO, O3, HONO, CHOCHO and O4). This was achieved through the coordinated operation of 36 spectrometers operated by 24 groups from all over the world, together with a wide range of supporting reference observations (in situ analysers, balloon sondes, lidars, long-path DOAS, direct-sun DOAS, Sun photometer and meteorological instruments). In the presented study, the retrieved CINDI-2 MAX-DOAS trace gas (NO2, HCHO) and aerosol vertical profiles of 15 participating groups using different inversion algorithms are compared and validated against the colocated supporting observations, with the focus on aerosol optical thicknesses (AOTs), trace gas vertical column densities (VCDs) and trace gas surface concentrations. The algorithms are based on three different techniques: six use the optimal estimation method, two use a parameterized approach and one algorithm relies on simplified radiative transport assumptions and analytical calculations. To assess the agreement among the inversion algorithms independent of inconsistencies in the trace gas slant column density acquisition, participants applied their inversion to a common set of slant columns. Further, important settings like the retrieval grid, profiles of O3, temperature and pressure as well as aerosol optical properties and a priori assumptions (for optimal estimation algorithms) have been prescribed to reduce possible sources of discrepancies. The profiling results were found to be in good qualitative agreement: most participants obtained the same features in the retrieved vertical trace gas and aerosol distributions; however, these are sometimes at different altitudes and of different magnitudes. Under clear-sky conditions, the root-mean-square differences (RMSDs) among the results of individual participants are in the range of 0.01–0.1 for AOTs, (1.5–15) ×1014molec.cm-2 for trace gas (NO2, HCHO) VCDs and (0.3–8)×1010molec.cm-3 for trace gas surface concentrations. These values compare to approximate average optical thicknesses of 0.3, trace gas vertical columns of 90×1014molec.cm-2 and trace gas surface concentrations of 11×1010molec.cm-3 observed over the campaign period. The discrepancies originate from differences in the applied techniques, the exact implementation of the algorithms and the user-defined settings that were not prescribed. For the comparison against supporting observations, the RMSDs increase to a range of 0.02–0.2 against AOTs from the Sun photometer, (11–55)×1014molec.cm-2 against trace gas VCDs from direct-sun DOAS observations and (0.8–9)×1010molec.cm-3 against surface concentrations from the long-path DOAS instrument. This increase in RMSDs is most likely caused by uncertainties in the supporting data, spatiotemporal mismatch among the observations and simplified assumptions particularly on aerosol optical properties made for the MAX-DOAS retrieval. As a side investigation, the comparison was repeated with the participants retrieving profiles from their own differential slant column densities (dSCDs) acquired during the campaign. In this case, the consistency among the participants degrades by about 30 % for AOTs, by 180 % (40 %) for HCHO (NO2) VCDs and by 90 % (20 %) for HCHO (NO2) surface concentrations. In former publications and also during this comparison study, it was found that MAX-DOAS vertically integrated aerosol extinction coefficient profiles systematically underestimate the AOT observed by the Sun photometer. For the first time, it is quantitatively shown that for optimal estimation algorithms this can be largely explained and compensated by considering biases arising from the reduced sensitivity of MAX-DOAS observations to higher altitudes and associated a priori assumptions.

Publisher Copyright: © 2015 John Wiley & Sons Ltd. The hepatitis C virus (HCV) epidemic was forecasted through 2030 for 15 countries in Europe, the Middle East and Asia, and the relative impact of two scenarios was considered: increased treatment efficacy while holding the annual number of treated patients constant and increased treatment efficacy and an increased annual number of treated patients. Increasing levels of diagnosis and treatment, in combination with improved treatment efficacy, were critical for achieving substantial reductions in disease burden. A 90% reduction in total HCV infections within 15 years is feasible in most countries studied, but it required a coordinated effort to introduce harm reduction programmes to reduce new infections, screening to identify those already infected and treatment with high cure rate therapies. This suggests that increased capacity for screening and treatment will be critical in many countries. Birth cohort screening is a helpful tool for maximizing resources. Among European countries, the majority of patients were born between 1940 and 1985. A wider range of birth cohorts was seen in the Middle East and Asia (between 1925 and 1995). Peer reviewed

In this paper, it is set forth an action research case study, rooted in the principles of Multicultural Education and Teacher Education for Cultural Diversity and Inclusion. The study was developed in a Portuguese Public Secondary School with a cultural and social diverse school population, namely, immigrant students and those of the 2nd and 3rd generations of immigrant families from Portuguese-speaking African countries. The research was focused on a process of inservice teachers training and aimed teachers’ professional development for cultural diversity and inclusion. The research data analysis (interviews, field notes, teachers’ portfolios and reports of critical reflection) emphasised new conceptions on multicultural and inclusive education, changes in pedagogical practices, teachers’ reflexivity, students’ attitudes and behaviours, and school organisation. 2016 Annual Meeting of the American Educational Research Association, April 8-12, Washington Unidade de Investigação e Desenvolvimento em Educação e Formação da Universidade de Lisboa.

Veidas – ilgą ir turiningą tradiciją turintis literatūrinis vaizdinys, figūruojantis ir šiuolaikinėje lietuvių poezijoje. Išeities tašku šaltinių atrankai straipsnyje pasirinkus kūnišką, vizualiai atpažįstamą lyrinio subjekto ar jo sutinkamą kito veidą, šis fenomenas suvokiamas ir plačiau – pagal E. Lévino veido sampratą. Šiuolaikinės poezijos veido veidą (pastarasis – tapatybės prasme) straipsnyje siekiama atskleisti nagrinėjant skirtingų kartų poetų kūrybą, pradedant XX a. pabaiga (paskutinis dešimtmetis) ir baigiant naujausia kūryba: J. Vaičiūnaitės, J. Juškaičio, O. Baliukonytės, J. Jekentaitės, R. Mikutavičiaus, R. Stankevičiaus, S. Vilimaitės, S. Kandratavičiaus ir kitų autorių eilėraščiais. Tai, kad ne vienu atveju veidas įgyja religinį krikščioniškosios tradicijos akiratį, lemia atitinkamą teorinį straipsnio pagrindą. Teorinė straipsnio prieiga yra hermeneutinės metodologijos požiūriu formuluojamas teologinės (D. Miethas) ir filosofinės etikos (E. Lévinas) derinys. Etinio metafizikos reikšmingumo ieškoma poetinėse lyrinio subjekto, žmogiškojo ir dieviškojo kito, tradicinių šventųjų veido reprezentacijose.