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Fashion products made from repurposed materials (e.g., backpacks made from pineapple leaves) have become more prevalent nowadays, and their environmental sustainability is one of the core advantages. Yet, it is currently unclear how consumers respond to products made from repurposed materials. We conducted three experiments to examine the effects of three material features, namely function, sustainability, and distinguishability, on consumer preferences for fashion products made from repurposed materials. The results indicate that, when the function of repurposed materials is as good as that of conventional materials, consumers prefer a product made from repurposed materials over the same product made from conventional materials. Also, consumers in general prefer repurposed materials to be less visually distinguishable. Finally, when the sustainability of the repurposed products is emphasized, consumers appear more likely to choose products made from repurposed materials, even when these products have an inferior function. In conclusion, to promote fashion products made from repurposed materials, marketers may emphasize the function and sustainability of repurposed materials, and producers may manufacture repurposed materials that visually resemble conventional materials.

Flight trajectories of fruit flies and mosquitoes in a wind tunnel.This data file is a MySQL database file which must be uploaded to a MySQL database management system (DBMS) (e.g., via the MAMP installation: http://localhost:8888/MAMP/?language=English, as was used in the associated manuscript). Once you have installed a MySQL DBMS on your machine, make a new database called “wind_tunnel_db”. To populate this database using the data file, first download all of the data files and join them together using: cat wind_tunnel_db_* > wind_tunnel_db.sql Then run the following command to populate the wind_tunnel_db MySQL database with the result. /path/to/mysql -uroot -proot wind_tunnel_db < /path/to/wind_tunnel_db.sql replacing the paths and username/passwords as appropriate. It will take several minutes since it is a large file. The database contains several tables, which are mostly self explanatory. The key tables of interest are the “experiment” table, which lists the 4 experiments contained in this data set, the “timepoint” table, which contains the position, velocity, etc., of every fly/mosquito at every measured time point, and the “trajectory” table, which indicates which set of time points correspond to which individual trajectories. Other useful tables that have been pre-populated are the “crossing” table, which specifies trajectory segments corresponding to each plume crossing, and the “crossing_group” table, which groups sets of crossings together according to experiment and crossing identification criteria. The code that interacts with this database and recreates the figures in the associated manuscript is contained at https://github.com/rkp8000/wind_tunnel.wind_tunnel_db_aaPart 2wind_tunnel_db_abPart 3wind_tunnel_db_acPart 4wind_tunnel_db_adPart 5wind_tunnel_db_aePart 6wind_tunnel_db_afPart 7wind_tunnel_db_agPart 8wind_tunnel_db_ahPart 9wind_tunnel_db_aiInfotaxis databaseBase database for running infotaxis simulations. To see how to prepare and populate this database with simulated trajectory data, see the file _paper_auxiliary_code in the GitHub repository http://github.com/rkp8000/wind_tunnel.infotaxis_db.sql Natural decision-making often involves extended decision sequences in response to variable stimuli with complex structure. As an example, many animals follow odor plumes to locate food sources or mates, but turbulence breaks up the advected odor signal into intermittent filaments and puffs. This scenario provides an opportunity to ask how animals use sparse, instantaneous, and stochastic signal encounters to generate goal-oriented behavioral sequences. Here we examined the trajectories of flying fruit flies (Drosophila melanogaster) and mosquitoes (Aedes aegypti) navigating in controlled plumes of attractive odorants. While it is known that mean odor-triggered flight responses are dominated by upwind turns, individual responses are highly variable. We asked whether deviations from mean responses depended on specific features of odor encounters, and found that odor-triggered turns were slightly but significantly modulated by two features of odor encounters. First, encounters with higher concentrations triggered stronger upwind turns. Second, encounters occurring later in a sequence triggered weaker upwind turns. To contextualize the latter history dependence theoretically, we examined trajectories simulated from three normative tracking strategies. We found that neither a purely reactive strategy nor a strategy in which the tracker learned the plume centerline over time captured the observed history dependence. In contrast, “infotaxis”, in which flight decisions maximized expected information gain about source location, exhibited a history dependence aligned in sign with the data, though much larger in magnitude. These findings suggest that while true plume tracking is dominated by a reactive odor response it might also involve a history-dependent modulation of responses consistent with the accumulation of information about a source over multi-encounter timescales. This suggests that short-term memory processes modulating decision sequences may play a role in natural plume tracking.

DataForAssessingSeasonalEffectsOnElectricityAndWaterForRepositoryThis Excel file contains data used to conduct a seasonal analysis to assess whether seasonal patterns exist in electricity use in dorms and whether these patterns differ by latitude. The first worksheet contains metadata.Fall 2010 Campus Conservation Nationals surveyThis online survey was administered to students attending colleges who participated in the Fall 2010 Campus Conservation Nationals competition. Not all schools who participated in the competition administered the survey.CCN_F10_survey.pdfSpring 2012 Campus Conservation Nationals surveyThis online survey was administered to students attending colleges who participated in the Spring 2012 Campus Conservation Nationals competition. Not all schools who participated in the competition administered the survey.CCN_Spring12_survey.pdfFall 10 Campus Conservation Nationals electricity, water, webhit, and commitment dataThis data file contains data at the dorm level collected by Lucid before, during, and after the Fall 2010 CCN competition. The first sheet contains metadata defining all variable names.Fall10_CCN_elec_water_webhits_commitments.xlsxSpring 2012 Campus Conservation Nationals electricity, water, and commitment dataThis data file contains data at the dorm level collected by Lucid before, during, and after the Spring 2012 CCN competition. The first sheet contains metadata defining all variable names.Spring12_CCN_elec_water_commitments_no.xlsxFall 10 CCN data aggregated at dorm level with psychological variablesThis data file contains data at the dorm level collected from our online survey and merged with the resource use data. The first sheet contains metadata defining all variable names.Fall10_CCN_dormagg_with_psych_variables.xlsxSpring 2012 CCN data with psychological variablesThis data file contains data at the dorm level collected from our online survey and merged with the resource use data. The first sheet contains metadata defining all variable names.Spring12__CCN_dormagg_with_psych_variables.xlsx “Campus Conservation Nationals” (CCN) is a recurring, nation-wide electricity and water-use reduction competition among dormitories on college campuses. We conducted a two year empirical study of the competition’s effects on resource consumption and the relationship between conservation, use of web technology and various psychological measures. Significant reductions in electricity and water use occurred during the two CCN competitions examined (n = 105,000 and 197,000 participating dorm residents respectively). In 2010, overall reductions during the competition were 4% for electricity and 6% for water. The top 10% of dorms achieved 28% and 36% reductions in electricity and water respectively. Participation was larger in 2012 and reductions were slightly smaller (i.e. 3% electricity). The fact that no seasonal pattern in electricity use was evident during non-competition periods suggests that results are attributable to the competition. Post competition resource use data collected in 2012 indicates that conservation behavior was sustained beyond the competition. Surveys were used to assess psychological and behavioral responses (n = 2,900 and 2,600 in 2010 and 2012 respectively). Electricity reductions were significantly correlated with: web visitation, specific conservation behaviors, awareness of the competition, motivation and sense of empowerment. However, participants were significantly more motivated than empowered. Perceived benefits of conservation were skewed towards global and future concerns while perceived barriers tended to be local. Results also suggest that competitions may be useful for “preaching beyond the choir” – engaging those who might lack prior intrinsic or political motivation. Although college life is distinct, certain conclusions related to competitions, self-efficacy, and motivation and social norms likely extend to other residential settings.

This repository consists of two databases- CASE-ONSHORE and CASE-OFFSHORE, generated using OpenFAST v2.4 on NREL's 10-MW reference wind turbine for training data-driven probabilistic load surrogate models. The data is to be used for mapping 10-minute average environmental conditions to the corresponding 10-minute load statistics such as load average, fatigue and range at various locations on the tower and blades.

The repository contains the underlining data for "On the wake deflection of vertical axis wind turbines by pitched blades" This repository consists of experimental (PIV and force measurements) data in the wake of VAWTs with different blade pitch angles. The measured cases include an isolated VAWT with -10, 0, 10 degree pitch, respectively. Author contribution: Ming Huang: Conceptualization; Methodology; Validation; Experimental design; Carrying out the experiment; postprocessing Yugandhar Vijaykumar Patil: Design assistant; Carrying out the experiment; postprocessing Andrea Sciacchitano: Conceptualization; Experimental design; Methodology; Validation; Delphine De Tavernier: Conceptualization Carlos Simao Ferreira: Conceptualization; Methodology; Validation; Experimental design

The dataset covers biotic and abiotic data from the aquatic habitat of a population of the sediment-rooted macrophyte Myriophyllum spicatum in the temperate climate region (The Netherlands). The growth of M. spicatum was monitored in 0.2025 m2 plant baskets installed in an experimental ditch. Parameters monitored included biomass (fresh and dry weight), shoot length, seasonal short-term growth rates of shoots, relevant environmental parameters and weather data. This dataset includes the 2-year experimental biotic (macrophyte biomass and growth data) and environmental data (water quality data, sediment data). A second file includes the statistical data. A third file includes the weather data.

Figure 1data_Exp 2Figure 1 data: Condition of experimental seedlings in hummocks with contrasting shrub density and tree canopy in Experiment 2: No Trees - Low Shrub biomass (NTLS), No Trees - High Shrub biomass (NTHS), Present Trees - Low Shrub biomass (PTLS) and Present Trees - High shrub biomass (PTHS) during the warmest growing season (2011) and at the end of the experiment (2013). Seedling condition was defined as: healthy (< 50% of the needles turned yellow or brown) or unhealthy (> 50% of the needles turned yellow or brown). Seedlings were 1 month old at plantation time in the July 2010.Table 1_environmental conditions_Exp 1Table 1 data: Environmental conditions and vegetation characteristics in hummocks (circular and bands) and lawns for Experiment 1. Water table depth below surface is an average for the four growing seasons (2010-2013)Table 2_ photosynthesis data_Exp 1Table 2 photosynthesis data: Photosynthesis rates for experimental pine seedlings in hummocks (circular and bands) versus adjacent lawns for Experiment 1.Table 2_seedling responses_Exp 1Table 2 data: Responses of experimental pine seedlings in hummocks (circular and bands) versus adjacent lawns for Experiment 1 after 4 growing seasons. ST: Seeds inserted on top of moss; SB: Seeds inserted below moss; Small seedling (1 month old at plantation time); Large seedling (2 months old at plantation time). Emergence = % of planted seeds emerged after 1 year. Condition = % healthy seedlings. Stem growth corresponds to vertical stem growth for germinating (ST and SB) seedlings and new stem growth for older (small and large) seedlings.Table 3_regression seedling-environment_Exp 1Table 3 data for generalized linear models assessing the responses of experimental pine seedlings in hummocks (circular and bands) and adjacent lawns for Experiment 1 during the whole experimental period (2010-2013). ST: Seedlings from seeds inserted on top of moss; SB: Seedlings from seeds inserted below moss; Small seedling (1 month old at plantation time); Large seedling (2 months old at plantation time). Condition = % healthy seedlings. Growth = stem growth.Table 4_Environmental data_Exp 2Table 4: Environmental conditions in hummocks with contrasting shrub density and tree canopy in Experiment 2: No Trees - Low Shrub biomass (NTLS), No Trees - High Shrub biomass (NTHS), Present Trees - Low Shrub biomass (PTLS) and Present Trees - High shrub biomass (PTHS).Table 4 and Table S5a_seedling performance_Exp 2Table 4: Seedling performance in hummocks with contrasting shrub density and tree canopy in Experiment 2: No Trees - Low Shrub biomass (NTLS), No Trees - High Shrub biomass (NTHS), Present Trees - Low Shrub biomass (PTLS) and Present Trees - High shrub biomass (PTHS). Seedling emergence, condition and survival from seeds inserted below the moss (SB), and from small planted seedlings.Table S3_cox regression (survival analysis)_Exp 1Table S3: Data for Cox survival analysis for experimental pine seedlings in hummocks (circular and bands) versus adjacent lawns during 2010-2013. ST: Seedlings from seeds inserted on top of moss; SB: Seedlings from seeds inserted below moss; Small seedling (1 month old, 10 cm tall at plantation time); Large seedling (2 months old, 30 cm tall at plantation time).Table S4_ regression seedling-environment 2011_Exp 1Table S4: Data for generalized linear models assessing the responses of experimental pine seedlings in hummocks (circular and bands) and adjacent lawns for Experiment 1 in 2011. Small seedling (1 month old, 10 cm tall at plantation time); Large seedling (2 months old, 30 cm tall at plantation time). Condition = % healthy seedlings. Growth = stem growth. Boreal ecosystems are warming roughly twice as fast as the global average, resulting in woody expansion that could further speed up the climate warming. Boreal peatbogs are waterlogged systems that store more than 30% of the global soil carbon. Facilitative effects of shrubs and trees on the establishment of new individuals could increase tree cover with profound consequences for the structure and functioning of boreal peatbogs, carbon sequestration and climate. We conducted two field experiments in boreal peatbogs to assess the mechanisms that explain tree seedling recruitment and to estimate the strength of positive feedbacks between shrubs and trees. We planted seeds and seedlings of Pinus sylvestris in microsites with contrasting water-tables and woody cover and manipulated both shrub canopy and root competition. We monitored seedling emergence, growth and survival for up to four growing seasons and assessed how seedling responses related to abiotic and biotic conditions. We found that tree recruitment is more successful in drier topographical microsites with deeper water-tables. On these hummocks, shrubs have both positive and negative effects on tree seedling establishment. Shrub cover improved tree seedling condition, growth and survival during the warmest growing season. In turn, higher tree basal area correlates positively with soil nutrient availability, shrub biomass and abundance of tree juveniles. Synthesis. Our results suggest that shrubs facilitate tree colonization of peatbogs which further increases shrub growth. These facilitative effects seem to be stronger under warmer conditions suggesting that a higher frequency of warmer and dry summers may lead to stronger positive interactions between shrubs and trees that could eventually facilitate a shift from moss to tree-dominated systems.