ResearchPad - wind Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Forecasting the monthly incidence rate of brucellosis in west of Iran using time series and data mining from 2010 to 2019]]> The identification of statistical models for the accurate forecast and timely determination of the outbreak of infectious diseases is very important for the healthcare system. Thus, this study was conducted to assess and compare the performance of four machine-learning methods in modeling and forecasting brucellosis time series data based on climatic parameters.MethodsIn this cohort study, human brucellosis cases and climatic parameters were analyzed on a monthly basis for the Qazvin province–located in northwestern Iran- over a period of 9 years (2010–2018). The data were classified into two subsets of education (80%) and testing (20%). Artificial neural network methods (radial basis function and multilayer perceptron), support vector machine and random forest were fitted to each set. Performance analysis of the models were done using the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Root Error (MARE), and R2 criteria.ResultsThe incidence rate of the brucellosis in Qazvin province was 27.43 per 100,000 during 2010–2019. Based on our results, the values of the RMSE (0.22), MAE (0.175), MARE (0.007) criteria were smaller for the multilayer perceptron neural network than their values in the other three models. Moreover, the R2 (0.99) value was bigger in this model. Therefore, the multilayer perceptron neural network exhibited better performance in forecasting the studied data. The average wind speed and mean temperature were the most effective climatic parameters in the incidence of this disease.ConclusionsThe multilayer perceptron neural network can be used as an effective method in detecting the behavioral trend of brucellosis over time. Nevertheless, further studies focusing on the application and comparison of these methods are needed to detect the most appropriate forecast method for this disease. ]]> <![CDATA[Sap flow of Salix psammophila and its principal influencing factors at different slope positions in the Mu Us desert]]>

The changes in sap flow of Salix psammophila growing on a gentle slope (lower slope, P1), a middle slope (P2), and an upper slope (P3), and the response of sap flow to meteorological factors at the different slope positions were studied using the continuous and synchronized observations, the instrument were wrapped stem flowmeter EMS 62 sap-flow heat-balance-based system and the LSI-LASTEM automatic weather station. The results revealed that the soil moisture content was the highest and the growth conditions of Salix psammophila were the best at P1, followed by P2. At P3, however, although good apical dominance was observed, the proportion of dead branches was the highest. Furthermore, the daily variation patterns of sap flow on the three slopes presented as multi-peak bell-shaped curves. The daily accumulation changes in sap flow showed a trend of P1 > P3 > P2, and within the same diameter range, the sap flow at P1 was significantly different from that at P2 and P3, whereas the sap flow at P2 and P3 did not vary significantly. All the three slopes showed a significant and positive correlation with photosynthetically active radiation, atmospheric temperature, and vapor pressure difference, and a significant and negative correlation with relative humidity; however, the degrees of correlation varied slightly. The stepwise regression analysis showed that, at different slopes, different variables were selected for different branch diameters, but photosynthetically active radiation and atmospheric temperature played dominant roles on all slopes. This study reveals the sap flow pattern of Salix psammophila on different slopes and its response mechanism to meteorological factors, which was essential for understanding the restoration ability, physiological adaptability, and ecosystem stability of Salix psammophila communities.

<![CDATA[Benefits of zebra stripes: Behaviour of tabanid flies around zebras and horses]]>

Averting attack by biting flies is increasingly regarded as the evolutionary driver of zebra stripes, although the precise mechanism by which stripes ameliorate attack by ectoparasites is unknown. We examined the behaviour of tabanids (horse flies) in the vicinity of captive plains zebras and uniformly coloured domestic horses living on a horse farm in Britain. Observations showed that fewer tabanids landed on zebras than on horses per unit time, although rates of tabanid circling around or briefly touching zebra and horse pelage did not differ. In an experiment in which horses sequentially wore cloth coats of different colours, those wearing a striped pattern suffered far lower rates of tabanid touching and landing on coats than the same horses wearing black or white, yet there were no differences in attack rates to their naked heads. In separate, detailed video analyses, tabanids approached zebras faster and failed to decelerate before contacting zebras, and proportionately more tabanids simply touched rather than landed on zebra pelage in comparison to horses. Taken together, these findings indicate that, up close, striped surfaces prevented flies from making a controlled landing but did not influence tabanid behaviour at a distance. To counteract flies, zebras swished their tails and ran away from fly nuisance whereas horses showed higher rates of skin twitching. As a consequence of zebras’ striping, very few tabanids successfully landed on zebras and, as a result of zebras’ changeable behaviour, few stayed a long time, or probed for blood.

<![CDATA[Social media usage patterns during natural hazards]]>

Natural hazards are becoming increasingly expensive as climate change and development are exposing communities to greater risks. Preparation and recovery are critical for climate change resilience, and social media are being used more and more to communicate before, during, and after disasters. While there is a growing body of research aimed at understanding how people use social media surrounding disaster events, most existing work has focused on a single disaster case study. In the present study, we analyze five of the costliest disasters in the last decade in the United States (Hurricanes Irene and Sandy, two sets of tornado outbreaks, and flooding in Louisiana) through the lens of Twitter. In particular, we explore the frequency of both generic and specific food-security related terms, and quantify the relationship between network size and Twitter activity during disasters. We find differences in tweet volume for keywords depending on disaster type, with people using Twitter more frequently in preparation for Hurricanes, and for real-time or recovery information for tornado and flooding events. Further, we find that people share a host of general disaster and specific preparation and recovery terms during these events. Finally, we find that among all account types, individuals with “average” sized networks are most likely to share information during these disasters, and in most cases, do so more frequently than normal. This suggests that around disasters, an ideal form of social contagion is being engaged in which average people rather than outsized influentials are key to communication. These results provide important context for the type of disaster information and target audiences that may be most useful for disaster communication during varying extreme events.

<![CDATA[Have wind turbines in Germany generated electricity as would be expected from the prevailing wind conditions in 2000-2014?]]>

The planning of the energy transition from fossil fuels to renewables requires estimates for how much electricity wind turbines can generate from the prevailing atmospheric conditions. Here, we estimate monthly ideal wind energy generation from datasets of wind speeds, air density and installed wind turbines in Germany and compare these to reported actual yields. Both yields were used in a statistical model to identify and quantify factors that reduced actual compared to ideal yields. The installed capacity within the region had no significant influence. Turbine age and park size resulted in significant yield reductions. Predicted yields increased from 9.1 TWh/a in 2000 to 58.9 TWh/a in 2014 resulting from an increase in installed capacity from 5.7 GW to 37.6 GW, which agrees very well with reported estimates for Germany. The age effect, which includes turbine aging and possibly other external effects, lowered yields from 3.6 to 6.7% from 2000 to 2014. The effect of park size decreased annual yields by 1.9% throughout this period. However, actual monthly yields represent on average only 73.7% of the ideal yields, with unknown causes. We conclude that the combination of ideal yields predicted from wind conditions with observed yields is suitable to derive realistic estimates of wind energy generation as well as realistic resource potentials.

<![CDATA[On the synchronization techniques of chaotic oscillators and their FPGA-based implementation for secure image transmission]]>

Synchronizing chaotic oscillators has been a challenge to guarantee successful applications in secure communications. That way, three synchronization techniques are applied herein to twenty two chaotic oscillators, three of them based on piecewise-linear functions and nineteen proposed by Julien C. Sprott. These chaotic oscillators are simulated to generate chaotic time series that are used to evaluate their Lyapunov exponents and Kaplan-Yorke dimension to rank their unpredictability. The oscillators with the high positive Lyapunov exponent are implemented into a field-programmable gate array (FPGA), and afterwards they are synchronized in a master-slave topology applying three techniques: the seminal work introduced by Pecora-Carroll, Hamiltonian forms and observer approach, and open-plus-closed-loop (OPCL). These techniques are compared with respect to their synchronization error and latency that is associated to the FPGA implementation. Finally, the chaotic oscillators providing the high positive Lyapunov exponent are synchronized and applied to a communication system with chaotic masking to perform a secure image transmission. Correlation analysis is performed among the original image, the chaotic channel and the recovered image for the three synchronization schemes. The experimental results show that both Hamiltonian forms and OPCL can recover the original image and its correlation with the chaotic channel is as low as 0.00002, demonstrating the advantage of synchronizing chaotic oscillators with high positive Lyapunov exponent to guarantee high security in data transmission.

<![CDATA[High spatio-temporal variability in Acroporidae settlement to inshore reefs of the Great Barrier Reef]]>

Recovery of coral reefs after disturbance relies heavily on replenishment through successful larval settlement and their subsequent survival. As part of an integrated study to determine the potential effects of water quality changes on the resilience of inshore coral communities, scleractinian coral settlement was monitored between 2006 and 2012 at 12 reefs within the inshore Great Barrier Reef. Settlement patterns were only analysed for the family Acroporidae, which represented the majority (84%) of settled larvae. Settlement of Acroporidae to terracotta tiles averaged 0.11 cm-2, representing 34 ± 31.01 (mean ± SD) spat per tile, indicating an abundant supply of competent larvae to the study reefs. Settlement was highly variable among reefs and between years. Differences in settlement among locations partly corresponded to the local cover of adult Acroporidae, while substantial reductions in Acroporidae cover caused by tropical cyclones and floods resulted in a clear reduction in settlement. Much of the observed variability remained unexplained, although likely included variability in both connectivity to, and the fecundity of, adult Acroporidae. The responsiveness of settlement patterns to the decline in Acroporidae cover across all four regions indicates the importance of supply and connectivity, and the vulnerability towards region-wide disturbance. High spatial and temporal variability, in addition to the resource-intensive nature of sampling with settlement tiles, highlights the logistical difficulty of determining coral settlement over large spatial and temporal scales.

<![CDATA[Influence of vertical wind shear on wind- and rainfall areas of tropical cyclones making landfall over South Korea]]>

The wind- and rainfall areas of tropical cyclones (TCs) making landfall over South Korea were examined for the period 1998–2013 by using the Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) and Tropical Rainfall Measuring Mission (TRMM) 3B42 data. Here, the wind- and rainfall areas were defined as the regions where wind speeds and precipitation rates exceed 14 m s-1 and 80 mm day-1 within 1000 km from the TC center, respectively. In general, TCs show significantly asymmetric wind and rainfall structures, with strong vertical wind shear appearing over South Korea during the landfall period. The rainfall area significantly increases with environmental vertical wind shear while the wind area is not sensitive to it. Composite analyses of the cases of strong and weak vertical wind shear confirm that the increase of rainfall area is related to the asymmetric convection (rising/sinking motion in the downshear-left/upshear-right side) induced by the vertical wind shear. This work highlights the importance of local atmospheric environment in determining the area primarily affected by strong winds or heavy rainfall during TC landfalls.

<![CDATA[Impact of solar and wind development on conservation values in the Mojave Desert]]>

In 2010, The Nature Conservancy completed the Mojave Desert Ecoregional Assessment, which characterizes conservation values across nearly 130,000 km2 of the desert Southwest. Since this assessment was completed, several renewable energy facilities have been built in the Mojave Desert, thereby changing the conservation value of these lands. We have completed a new analysis of land use to reassess the conservation value of lands in two locations in the Mojave Desert where renewable energy development has been most intense: Ivanpah Valley, and the Western Mojave. We found that 99 of our 2.59-km2 planning units were impacted by development such that they would now be categorized as having lower conservation value, and most of these downgrades in conservation value were due to solar and wind development. Solar development alone was responsible for a direct development footprint 86.79 km2: 25.81 km2 of this was primarily high conservation value Bureau of Land Management lands in the Ivanpah Valley, and 60.99 km2 was privately owned lands, mostly of lower conservation value, in the Western Mojave. Our analyses allow us to understand patterns in renewable energy development in the mostly rapidly changing regions of the Mojave Desert. Our analyses also provide a baseline that will allow us to assess the effectiveness of the Desert Renewable Energy Conservation Plan in preventing development on lands of high conservation value over the coming decades.

<![CDATA[The Dependence of the Peak Velocity of High-Speed Solar Wind Streams as Measured in the Ecliptic by ACE and the STEREO satellites on the Area and Co-latitude of Their Solar Source Coronal Holes]]>


We study the properties of 115 coronal holes in the time range from August 2010 to March 2017, the peak velocities of the corresponding high‐speed streams as measured in the ecliptic at 1 AU, and the corresponding changes of the Kp index as marker of their geoeffectiveness. We find that the peak velocities of high‐speed streams depend strongly on both the areas and the co‐latitudes of their solar source coronal holes with regard to the heliospheric latitude of the satellites. Therefore, the co‐latitude of their source coronal hole is an important parameter for the prediction of the high‐speed stream properties near the Earth. We derive the largest solar wind peak velocities normalized to the coronal hole areas for coronal holes located near the solar equator and that they linearly decrease with increasing latitudes of the coronal holes. For coronal holes located at latitudes 60°, they turn statistically to zero, indicating that the associated high‐speed streams have a high chance to miss the Earth. Similarly, the Kp index per coronal hole area is highest for the coronal holes located near the solar equator and strongly decreases with increasing latitudes of the coronal holes. We interpret these results as an effect of the three‐dimensional propagation of high‐speed streams in the heliosphere; that is, high‐speed streams arising from coronal holes near the solar equator propagate in direction toward and directly hit the Earth, whereas solar wind streams arising from coronal holes at higher solar latitudes only graze or even miss the Earth.

<![CDATA[Identification of Climatic Factors Affecting the Epidemiology of Human West Nile Virus Infections in Northern Greece]]>

Climate can affect the geographic and seasonal patterns of vector-borne disease incidence such as West Nile Virus (WNV) infections. We explore the association between climatic factors and the occurrence of West Nile fever (WNF) or West Nile neuro-invasive disease (WNND) in humans in Northern Greece over the years 2010–2014. Time series over a period of 30 years (1979–2008) of climatic data of air temperature, relative humidity, soil temperature, volumetric soil water content, wind speed, and precipitation representing average climate were obtained utilising the ECMWF’s (European Centre for Medium-Range Weather Forecasts) Re-Analysis (ERA-Interim) system allowing for a homogeneous set of data in time and space. We analysed data of reported human cases of WNF/WNND and Culex mosquitoes in Northern Greece. Quantitative assessment resulted in identifying associations between the above climatic variables and reported human cases of WNF/WNND. A substantial fraction of the cases was linked to the upper percentiles of the distribution of air and soil temperature for the period 1979–2008 and the lower percentiles of relative humidity and soil water content. A statistically relevant relationship between the mean weekly value climatic anomalies of wind speed (negative association), relative humidity (negative association) and air temperature (positive association) over 30 years, and reported human cases of WNF/WNND during the period 2010–2014 could be shown. A negative association between the presence of WNV infected Culex mosquitoes and wind speed could be identified. The statistically significant associations could also be confirmed for the week the WNF/WNND human cases appear and when a time lag of up to three weeks was considered. Similar statistically significant associations were identified with the weekly anomalies of the maximum and minimum values of the above climatic factors. Utilising the ERA-Interim re-analysis methodology it could be shown that besides air temperature, climatic factors such as soil temperature, relative humidity, soil water content and wind speed may affect the epidemiology of WNV.

<![CDATA[Reconciling Biodiversity Conservation and Widespread Deployment of Renewable Energy Technologies in the UK]]>

Renewable energy will potentially make an important contribution towards the dual aims of meeting carbon emission reduction targets and future energy demand. However, some technologies have considerable potential to impact on the biodiversity of the environments in which they are placed. In this study, an assessment was undertaken of the realistic deployment potential of a range of renewable energy technologies in the UK, considering constraints imposed by biodiversity conservation priorities. We focused on those energy sources that have the potential to make important energy contributions but which might conflict with biodiversity conservation objectives. These included field-scale solar, bioenergy crops, wind energy (both onshore and offshore), wave and tidal stream energy. The spatially-explicit analysis considered the potential opportunity available for each technology, at various levels of ecological risk. The resultant maps highlight the energy resource available, physical and policy constraints to deployment, and ecological sensitivity (based on the distribution of protected areas and sensitive species). If the technologies are restricted to areas which currently appear not to have significant ecological constraints, the total potential energy output from these energy sources was estimated to be in the region of 5,547 TWh/yr. This would be sufficient to meet projected energy demand in the UK, and help to achieve carbon reduction targets. However, we highlight two important caveats. First, further ecological monitoring and surveillance is required to improve understanding of wildlife distributions and therefore potential impacts of utilising these energy sources. This is likely to reduce the total energy available, especially at sea. Second, some of the technologies under investigation are currently not deployed commercially. Consequently this potential energy will only be available if continued effort is put into developing these energy sources/technologies, to enable realisation of their full potential.

<![CDATA[Estimating the effect of multiple environmental stressors on coral bleaching and mortality]]>

Coral cover has been declining in recent decades due to increased temperatures and environmental stressors. However, the extent to which different stressors contribute both individually and in concert to bleaching and mortality is still very uncertain. We develop and use a novel regression approach, using non-linear parametric models that control for unobserved time invariant effects to estimate the effects on coral bleaching and mortality due to temperature, solar radiation, depth, hurricanes and anthropogenic stressors using historical data from a large bleaching event in 2005 across the Caribbean. Two separate models are created, one to predict coral bleaching, and the other to predict near-term mortality. A large ensemble of supporting data is assembled to control for omitted variable bias and improve fit, and a significant improvement in fit is observed from univariate linear regression based on temperature alone. The results suggest that climate stressors (temperature and radiation) far outweighed direct anthropogenic stressors (using distance from shore and nearby human population density as a proxy for such stressors) in driving coral health outcomes during the 2005 event. Indeed, temperature was found to play a role ~4 times greater in both the bleaching and mortality response than population density across their observed ranges. The empirical models tested in this study have large advantages over ordinary-least squares–they offer unbiased estimates for censored data, correct for spatial correlation, and are capable of handling more complex relationships between dependent and independent variables. The models offer a framework for preparing for future warming events and climate change; guiding monitoring and attribution of other bleaching and mortality events regionally and around the globe; and informing adaptive management and conservation efforts.

<![CDATA[Marine Habitat Selection by Marbled Murrelets (Brachyramphus marmoratus) during the Breeding Season]]>

The marbled murrelet (Brachyramphus marmoratus) is a declining seabird that is well-known for nesting in coastal old-growth forests in the Pacific Northwest. Most studies of habitat selection have focused on modeling terrestrial nesting habitat even though marine habitat is believed to be a major contributor to population declines in some regions. To address this information gap, we conducted a 5-year study of marine resource selection by murrelets in Washington, which contains a population experiencing the steepest documented declines and where marine habitat is believed to be compromised. Across five years we tracked 157 radio-tagged murrelets during the breeding season (May to August), and used discrete choice models to examine habitat selection. Using an information theoretic approach, our global model had the most support, suggesting that murrelet resource selection at-sea is affected by many factors, both terrestrial and marine. Locations with higher amounts of nesting habitat (β = 21.49, P < 0.001) that were closer to shore (β = -0.0007, P < 0.001) and in cool waters (β = -0.2026, P < 0.001) with low footprint (β = -0.0087, P < 0.001) had higher probabilities of use. While past conservation efforts have focused on protecting terrestrial nesting habitat, we echo many past studies calling for future efforts to protect marine habitat for murrelets, as the current emphasis on terrestrial habitat alone may be insufficient for conserving populations. In particular, marine areas in close proximity to old-growth nesting habitat appear important for murrelets during the breeding season and should be priorities for protection.

<![CDATA[High-Resolution Gene Flow Model for Assessing Environmental Impacts of Transgene Escape Based on Biological Parameters and Wind Speed]]>

Environmental impacts caused by transgene flow from genetically engineered (GE) crops to their wild relatives mediated by pollination are longstanding biosafety concerns worldwide. Mathematical modeling provides a useful tool for estimating frequencies of pollen-mediated gene flow (PMGF) that are critical for assessing such environmental impacts. However, most PMGF models are impractical for this purpose because their parameterization requires actual data from field experiments. In addition, most of these models are usually too general and ignored the important biological characteristics of concerned plant species; and therefore cannot provide accurate prediction for PMGF frequencies. It is necessary to develop more accurate PMGF models based on biological and climatic parameters that can be easily measured in situ. Here, we present a quasi-mechanistic PMGF model that only requires the input of biological and wind speed parameters without actual data from field experiments. Validation of the quasi-mechanistic model based on five sets of published data from field experiments showed significant correlations between the model-simulated and field experimental-generated PMGF frequencies. These results suggest accurate prediction for PMGF frequencies using this model, provided that the necessary biological parameters and wind speed data are available. This model can largely facilitate the assessment and management of environmental impacts caused by transgene flow, such as determining transgene flow frequencies at a particular spatial distance, and establishing spatial isolation between a GE crop and its coexisting non-GE counterparts and wild relatives.

<![CDATA[Effect of climate on incidence of respiratory syncytial virus infections in a refugee camp in Kenya: A non-Gaussian time-series analysis]]>

Respiratory syncytial virus (RSV) is one of the major causes of acute lower respiratory tract infections (ALRTI) in children. Children younger than 1 year are the most susceptible to RSV infection. RSV infections occur seasonally in temperate climate regions. Based on RSV surveillance and climatic data, we developed statistical models that were assessed and compared to predict the relationship between weather and RSV incidence among refugee children younger than 5 years in Dadaab refugee camp in Kenya. Most time-series analyses rely on the assumption of Gaussian-distributed data. However, surveillance data often do not have a Gaussian distribution. We used a generalized linear model (GLM) with a sinusoidal component over time to account for seasonal variation and extended it to a generalized additive model (GAM) with smoothing cubic splines. Climatic factors were included as covariates in the models before and after timescale decompositions, and the results were compared. Models with decomposed covariates fit RSV incidence data better than those without. The Poisson GAM with decomposed covariates of climatic factors fit the data well and had a higher explanatory and predictive power than GLM. The best model predicted the relationship between atmospheric conditions and RSV infection incidence among children younger than 5 years. This knowledge helps public health officials to prepare for, and respond more effectively to increasing RSV incidence in low-resource regions or communities.

<![CDATA[PSO-Based Smart Grid Application for Sizing and Optimization of Hybrid Renewable Energy Systems]]>

This paper introduces an optimal sizing algorithm for a hybrid renewable energy system using smart grid load management application based on the available generation. This algorithm aims to maximize the system energy production and meet the load demand with minimum cost and highest reliability. This system is formed by photovoltaic array, wind turbines, storage batteries, and diesel generator as a backup source of energy. Demand profile shaping as one of the smart grid applications is introduced in this paper using load shifting-based load priority. Particle swarm optimization is used in this algorithm to determine the optimum size of the system components. The results obtained from this algorithm are compared with those from the iterative optimization technique to assess the adequacy of the proposed algorithm. The study in this paper is performed in some of the remote areas in Saudi Arabia and can be expanded to any similar regions around the world. Numerous valuable results are extracted from this study that could help researchers and decision makers.

<![CDATA[Effects of Leading Edge Defect on the Aerodynamic and Flow Characteristics of an S809 Airfoil]]>


Unexpected performance degradation occurs in wind turbine blades due to leading edge defect when suffering from continuous impacts with rain drops, hails, insects, or solid particles during its operation life. To assess this issue, this paper numerically investigates the steady and dynamic stall characteristics of an S809 airfoil with various leading edge defects. More leading edge defect sizes and much closer to practical parameters are investigated in the paper.


Numerical computation is conducted using the SST k-ω turbulence model, and the method has been validated by comparison with existed published data. In order to ensure the calculation convergence, the residuals for the continuity equation are set to be less than 10−7 and 10−6 in steady state and dynamic stall cases. The simulations are conducted with the software ANSYS Fluent 13.0.


It is found that the characteristics of aerodynamic coefficients and flow fields are sensitive to leading edge defect both in steady and dynamic conditions. For airfoils with the defect thickness of 6%tc, leading edge defect has a relative small influence on the aerodynamics of S809 airfoil. For other investigated defect thicknesses, leading edge defect has much greater influence on the flow field structures, pressure coefficients and aerodynamic characteristics of airfoil at relative small defect lengths. For example, the lift coefficients decrease and drag coefficients increase sharply after the appearance of leading edge defect. However, the aerodynamic characteristics could reach a constant value when the defect length is large enough. The flow field, pressure coefficient distribution and aerodynamic coefficients do not change a lot when the defect lengths reach to 0.5%c,1%c, 2%c and 3%c with defect thicknesses of 6%tc, 12%tc,18%tc and 25%tc, respectively. In addition, the results also show that the critical defect length/thickness ratio is 0.5, beyond which the aerodynamic characteristics nearly remain unchanged. In dynamic stall, leading edge defect imposes a greater influence on the aerodynamic characteristics of airfoil than steady conditions. By increasing in defect length, it is found that the separated area becomes more intense and moves forward along the suction surface.


Leading edge defect has significant influence on the aerodynamic and flow characteristics of the airfoil, which will reach a stable status with enough large defect size. The leading edge separation bubble, circulation in the defect cavity and intense tailing edge vortex are the main features of flow around defective airfoils.

<![CDATA[Improving Physical Task Performance with Counterfactual and Prefactual Thinking]]>

Counterfactual thinking (reflecting on “what might have been”) has been shown to enhance future performance by translating information about past mistakes into plans for future action. Prefactual thinking (imagining “what might be if…”) may serve a greater preparative function than counterfactual thinking as it is future-orientated and focuses on more controllable features, thus providing a practical script to prime future behaviour. However, whether or not this difference in hypothetical thought content may translate into a difference in actual task performance has been largely unexamined. In Experiment 1 (n = 42), participants performed trials of a computer-simulated physical task, in between which they engaged in either task-related hypothetical thinking (counterfactual or prefactual) or an unrelated filler task (control). As hypothesised, prefactuals contained more controllable features than counterfactuals. Moreover, participants who engaged in either form of hypothetical thinking improved significantly in task performance over trials compared to participants in the control group. The difference in thought content between counterfactuals and prefactuals, however, did not yield a significant difference in performance improvement. Experiment 2 (n = 42) replicated these findings in a dynamic balance task environment. Together, these findings provide further evidence for the preparatory function of counterfactuals, and demonstrate that prefactuals share this same functional characteristic.

<![CDATA[Potential Impacts of Offshore Wind Farms on North Sea Stratification]]>

Advances in offshore wind farm (OWF) technology have recently led to their construction in coastal waters that are deep enough to be seasonally stratified. As tidal currents move past the OWF foundation structures they generate a turbulent wake that will contribute to a mixing of the stratified water column. In this study we show that the mixing generated in this way may have a significant impact on the large-scale stratification of the German Bight region of the North Sea. This region is chosen as the focus of this study since the planning of OWFs is particularly widespread. Using a combination of idealised modelling and in situ measurements, we provide order-of-magnitude estimates of two important time scales that are key to understanding the impacts of OWFs: (i) a mixing time scale, describing how long a complete mixing of the stratification takes, and (ii) an advective time scale, quantifying for how long a water parcel is expected to undergo enhanced wind farm mixing. The results are especially sensitive to both the drag coefficient and type of foundation structure, as well as the evolution of the pycnocline under enhanced mixing conditions—both of which are not well known. With these limitations in mind, the results show that OWFs could impact the large-scale stratification, but only when they occupy extensive shelf regions. They are expected to have very little impact on large-scale stratification at the current capacity in the North Sea, but the impact could be significant in future large-scale development scenarios.