Absorption,dissociation, locus of control and presence in virtual reality

The present study aimed to explore the relationship between a number of psychological variables and a reported sense of presence in immersive virtual reality (IVR). It was hypothesised that participants’ scores on measures of absorption, dissociation, and external locus of control would be positively and significantly correlated with a measure of their sense of presence in IVR. A total of 64 people took part. Significant correlations were found between presence and dissociation (r = 0.403, p < 0.01), and presence and locus of control (r = 0.268, p < 0.05). However, the correlation between presence and absorption was not significant (r = −0.037, p = 0.386). The findings reported here suggest a complex interrelationship of psychological variables in relation to presence in IVR that warrants further research.     

Testing the potential of multi-spectral remote sensing for retrospectively estimating fire severity in African Savannahs

The remote sensing of fire severity is a noted goal in studies of forest and grassland wildfires. Experiments were conducted to discover and evaluate potential relationships between the characteristics of African savannah fires and post-fire surface spectral reflectance in the visible to shortwave infrared spectral region. Nine instrumented experimental fires were conducted in semi-arid woodland savannah of Chobe National Park (Botswana), where fire temperature (T_max) and duration (dt) were recorded using thermocouples positioned at different heights and locations. These variables, along with measures of fireline intensity (FLI), integrated temperature with time (T_sum) and biomass (and carbon/nitrogen) volatilised were compared to post-fire surface spectral reflectance. Statistically significant relationships were observed between (i) the fireline intensity and total nitrogen volatilised (r² = 0.54, n = 36, p < 0.001), (ii) integrated temperature (T_sum−μ) and total biomass combusted (r² = 0.72, n = 32, p < 0.001), and (iii) fire duration as measured at the top-of-grass sward thermocouple (dt_T) and total biomass combusted (r² = 0.74, n = 34, p < 0.001) and total nitrogen volatilised (r² = 0.73, n = 34, p < 0.001). The post-fire surface spectral reflectance was found to be related to dt and T_sum via a quadratic relationship that varied with wavelength. The use of visible and shortwave infrared band ratios produced statistically significant linear relationships with fire duration as measured by the top thermocouple (dt_T) (r² = 0.76, n = 34, p < 0.001) and the mean of T_sum (r² = 0.82, n = 34, p < 0.001). The results identify fire duration as a versatile measure that relates directly to the fire severity, and also illustrate the potential of spectrally-based fire severity measures. However, the results also point to difficulties when applying such spectrally-based techniques to Earth Observation satellite imagery, due to the small-scale variability noted on the ground. Results also indicate the potential for surface spectral reflectance to increase following higher severity fires, due to the laying down of high albedo white mineral ash. Most current techniques for mapping burned area rely on the general assumption that surface albedo decreases following a fire, and so if the image spatial resolution was high enough such methods may fail. Determination of the effect of spatial resolution on a sensor's ability to detect white ash was investigated using a validated optical mixture modelling approach. The most appropriate mixing model to use (linear or non-linear) was assessed using laboratory experiments. A linear mixing model was shown most appropriate, with results suggesting that sensors having spatial resolutions significantly higher than those of Landsat ETM+ will be required if patches of white ash are to be used to provide EO-derived information on the spatial variation of fire severity.     

The use of waveform lidar to measure northern temperate mixed conifer and deciduous forest structure in New Hampshire

The direct retrieval of canopy height and the estimation of aboveground biomass are two important measures of forest structure that can be quantified by airborne laser scanning at landscape scales. These and other metrics are central to studies attempting to quantify global carbon cycles and to improve understanding of the spatial variation in forest structure evident within differing biomes. Data acquired using NASA's Laser Vegetation Imaging Sensor (LVIS) over the Bartlett Experimental Forest (BEF) in central New Hampshire (USA) was used to assess the performance of waveform lidar in a northern temperate mixed conifer and deciduous forest.Using coincident plots established for this study, we found strong agreement between field and lidar measurements of height (r² = 0.80, p < 0.000) at the footprint level. Allometric calculations of aboveground biomass (AGBM) and LVIS metrics (AGBM: r² = 0.61, PRESS RMSE = 58.0 Mg ha^− 1, p < 0.000) and quadratic mean stem diameter (QMSD) and LVIS metrics (r² = 0.54, p = 0.002) also showed good agreement at the footprint level. Application of a generalized equation for determining AGBM proposed by Lefsky et al. (2002a) to footprint-level field data from Bartlett resulted in a coefficient of determination of 0.55; RMSE = 64.4 Mg ha^− 1; p = 0.002. This is slightly weaker than the strongest relationship found with the best-fit single term regression model.Relationships between a permanent grid of USDA Forest Service inventory plots and the mean values of aggregated LVIS metrics, however, were not as strong. This discrepancy suggests that validation efforts must be cautious in using pre-existing field data networks as a sole means of calibrating and verifying such remote sensing data. Stratification based on land-use or species composition, however, did provide the means to improve regression relationships at this scale. Regression models established at the footprint level for AGBM and QMSD were applied to LVIS data to generate predicted values for the whole of Bartlett. The accuracy of these models was assessed using varying subsets of the USFS NERS plot data. Coefficient of determinations ranged from fair to strong with aspects of land-use history and species composition influencing both the fit and the level of error seen in the predicted relationships.     

Effects of soil moisture and water depth on ERS SAR backscatter measurements from an Alaskan wetland complex

We conducted a preliminary investigation of the response of ERS C-band SAR backscatter to variations in soil moisture and surface inundation in wetlands of interior Alaska. Data were collected from 5 wetlands over a three-week period in 2007. Results showed a positive correlation between backscatter and soil moisture in sites dominated by herbaceous vegetation cover (r = 0.74, p < 0.04). ERS SAR backscatter was negatively correlated to water depth in all open (non-forested) wetlands when water table levels were more than 6 cm above the wetland surface (r = − 0.82, p < 0.001). There was no relationship between backscatter and soil moisture in the forested (black spruce-dominated) wetland site. Our preliminary results show that ERS SAR data can be used to monitor variations in hydrologic conditions in high northern latitude wetlands (including peatlands), particularly sites with sparse tree cover.     

Performance measures in courses using computer-aided personalized system of instruction

Archived data from four courses taught with computer-aided personalized system of instruction (CAPSI) – an online, self-paced, instructional program – were used to explore the relationship between objectively rescored final exam grades, peer reviewing, and progress rate – i.e., the rate at which students completed unit tests. There was a strong positive correlation (r = .68, p < .01) between rate of progress and the amount of peer reviewing students did. This was predictable because peer reviewers had to be further along in the course than the students whose unit tests they reviewed. Students who completed all the units tended to obtain higher final exam scores than those who did not. For students who completed all the units there was little difference between the final exam performance of those who had a high progress rate and those who had a low progress rate. Considering all students together there was a moderate correlation between progress rate and final exam performance (r = .36, p < .01). In addition, there was a moderate positive correlation (r = .33, p < .01) between the amount of peer reviewing students did and their performance on the final exam. This correlation was substantially reduced (r = .13, p < .20) when rate of progress was partialed out. Thus, overall, students who progressed more rapidly through the course did more peer reviewing and learned more as measured by final exam performance. Interestingly, there were students who showed good learning without much participation in course related behaviors such as completing unit tests and peer reviewing. It is concluded that the CAPSI instructional program provides a good learning environment for students who utilize its components but it also accommodates other learning styles. In addition, there may be a distinction between students who complete all assigned units and those who do not regardless of their tendencies to procrastinate.     

Cardiovascular risk analysis by means of pulse morphology and clustering methodologies

The purpose of this study was the development of a clustering methodology to deal with arterial pressure waveform (APW) parameters to be used in the cardiovascular risk assessment. One hundred sixteen subjects were monitored and divided into two groups. The first one (23 hypertensive subjects) was analyzed using APW and biochemical parameters, while the remaining 93 healthy subjects were only evaluated through APW parameters. The expectation maximization (EM) and k-means algorithms were used in the cluster analysis, and the risk scores (the Framingham Risk Score (FRS), the Systematic COronary Risk Evaluation (SCORE) project, the Assessing cardiovascular risk using Scottish Intercollegiate Guidelines Network (ASSIGN) and the PROspective Cardiovascular Münster (PROCAM)), commonly used in clinical practice were selected to the cluster risk validation. The result from the clustering risk analysis showed a very significant correlation with ASSIGN (r = 0.582, p < 0.01) and a significant correlation with FRS (r = 0.458, p < 0.05). The results from the comparison of both groups also allowed to identify the cluster with higher cardiovascular risk in the healthy group. These results give new insights to explore this methodology in future scoring trials.     

Comparison of MODIS, eddy covariance determined and physiologically modelled gross primary production (GPP) in a Douglas-fir forest stand

Quantification of the magnitude of net terrestrial carbon (C) uptake, and how it varies inter-annually, is an important question with future potential sequestration influenced by both increased atmospheric CO₂ and changing climate. However the assessment of differences in measured and modeled C accumulation is a challenging task due to the significant fine scale variation occurring in terrestrial productivity due to soil, climate and vegetation characteristics as well as difficulties in measuring carbon accumulation over large spatial areas. The Moderate Resolution Imaging Spectroradiometer (MODIS) offers a means of monitoring gross primary production (GPP), both spatially and temporally, routinely from space. However it is critical to compare and contrast the temporal dynamics of the C and water fluxes with those measured from ground-based networks, or estimated using physiological models. In this paper, using a number of approaches, our objective is to determine if any systematic biases exists in either the MODIS, or the modeled estimates of fluxes, relative to the measurements made over an evergreen, needleleaf temperate rainforest on Vancouver Island, Canada. Results indicate that 8-day GPP as predicted with a simple physiological model (3PGS), forced using local meteorology and canopy characteristics, matched measured fluxes very well (r² = 0.86, p < 0.001) with no significant difference between eddy covariance (EC) and modeled GPP (p < 0.001). In addition, modeled water supply closely matched measured relative available soil water content at the site. Using canopy characteristics from the MODIS fraction of photosynthetically active radiation (fPAR) algorithm, slightly reduced the correspondence of the predictions due to a large number of unsuccessful retrievals (83%) due to sun angle, snow and cloud. Predictions of GPP based on the MODIS GPP algorithm, forced using local meteorology and canopy characteristics, were also highly correlated with EC measurements (r² = 0.89, p < 0.001) however these estimates were biased under predicting GPP. Estimates of GPP based on the most recent MODIS reprocessing (collection 4.5) remained highly correlated (r² = 0.88, p < 0.001) yet were also the most biased with the estimates being 30% less than the EC-measured GPP. Most of the variance in GPP at the site was explained by the absorbed photosynthetically active radiation. We also compared the nighttime respiration as measured over 2 years at the site with the minimum 8-day MODIS land surface temperature and found a significant relationship (r² = 0.57), similar to other studies.     

The effects of video on cognitive load and social presence in multimedia-learning

Two studies examined the use of video in multimedia learning environments. In Study 1, participants (N = 26) viewed one of two versions of a computer-based multimedia presentation: video, which included a video of a lecture with synchronized slides, or no video, which included the slides but only an audio narration of the lecture. Learning, cognitive load and social presence were assessed, but a significant difference was found only for cognitive load, with video experiencing greater cognitive load, t (24) = 2.45, p < .05. In Study 2, students (N = 25) were randomly assigned to either video or no video condition. Background knowledge and visual/verbal learning preference were assessed before viewing the presentation, and learning, cognitive load, and social presence were assessed after viewing. No significant differences were found for learning or social presence. However, a significant visual/verbal learning preference by condition interaction was found for cognitive load, F (1,21) = 4.51, p < .05: low visual-preference students experienced greater cognitive load in the video condition, while high visual-preference students experienced greater cognitive load in the no video condition.     

Remote sensing of photosynthetic light-use efficiency across two forested biomes: Spatial scaling

Eddy covariance (EC) measurements have greatly advanced our knowledge of carbon exchange in terrestrial ecosystems. However, appropriate techniques are required to upscale these spatially discrete findings globally. Satellite remote sensing provides unique opportunities in this respect, but remote sensing of the photosynthetic light-use efficiency (ε), one of the key components of Gross Primary Production, is challenging. Some progress has been made in recent years using the photochemical reflectance index, a narrow waveband index centered at 531 and 570 nm. The high sensitivity of this index to various extraneous effects such as canopy structure, and the view observer geometry has so far prevented its use at landscape and global scales. One critical aspect of upscaling PRI is the development of generic algorithms to account for structural differences in vegetation. Building on previous work, this study compares the differences in the PRI: ? relationship between a coastal Douglas-fir forest located on Vancouver Island, British Columbia, and a mature Aspen stand located in central Saskatchewan, Canada. Using continuous, tower-based observations acquired from an automated multi-angular spectro-radiometer (AMSPEC II) installed at each site, we demonstrate that PRI can be used to measure ? throughout the vegetation season at the DF-49 stand (r² = 0.91, p < 0.00) as well as the deciduous site (r² = 0.88, p < 0.00). It is further shown that this PRI signal can be also observed from space at both sites using daily observations from the Moderate Resolution Imaging Spectro-radiometer (MODIS) and a multi-angular implementation of atmospheric correction (MAIAC) (r² = 0.54 DF-49; r² = 0.63 SOA; p < 0.00). By implementing a simple hillshade model derived from airborne light detection and ranging (LiDAR) to approximate canopy shadow fractions (α_s), it is further demonstrated that the differences observed in the relationship between PRI and ε at DF-49 and SOA can be attributed largely to differences in α_s. The findings of this study suggest that algorithms used to separate physiological from extraneous effects in PRI reflectance may be more broadly applicable and portable across these two climatically and structurally different biome types, when the differences in canopy structure are known.     

Oriented growth of A2Te3 (A = Sb, Bi) films and their devices with enhanced thermoelectric performance

Oriented thermoelectric (TE) p-Sb₂Te₃ and n-Bi₂Te₃ thin films with special nanostructures have been synthesized by a simple vacuum thermal evaporation technique. The composition and microstructure of the films were studied by X-ray diffraction (XRD) and scanning electron microscopy (SEM), presenting a well preferential crystal growth with dense slender columnar grains grown perpendicular to the substrate, and energy dispersive X-ray spectrum (EDX) indicating the compositions distribution in the films. The electric transport properties, i.e., conductivity and Seebeck coefficient, and the thermal transportation of the oriented films show optimized properties. Prototype devices were built up by p and n elements in series and parallel circuits. The largest output power and cooling could be achieved in Sb₂Te₃ parallel device with P_max = 6.51 μW at ΔT = 106 K, and cooling of 4.1 K at 2 V. The 24-pair p-n couples series device could output maximum voltage of 313 mV at ΔT = 102 K. The power generation and the cooling of the devices show times enhanced TE performances than those consisting of common films. The results proved that introducing nanostructures into films is an effective choice to obtain high-efficient micro TE device.     

Simultaneous measurements of plant structure and chlorophyll content in broadleaf saplings with a terrestrial laser scanner

Plant structure and chlorophyll content strongly affect rates of photosynthesis. Rapid, objective, and repeatable methods are needed to measure these vegetative parameters to advance our understanding and modeling of plant ecophysiological processes. Terrestrial laser scanners (TLS) can be used to measure structural and potentially chemical properties of objects by quantifying the x,y,z coordinates and intensity of laser light, respectively, returned from an object's surface. The objective of this study was to determine the potential usefulness of TLS with a green (532 nm) laser to simultaneously measure the spatial distribution of chlorophyll a and b content (Chl_ab), leaf area (LA), and leaf angle (LAN). The TLS measurements were obtained from saplings of two tree species (Quercus macrocarpa and Acer saccharum) and from an angle-adjustable cardboard surface. The green laser return intensity value was strongly correlated with wet-chemically determined Chl_ab (r² = 0.77). Strong agreement was shown between measured and TLS-derived LA (r² = 0.95, intercept = − 1.43, slope = 0.97). The TLS derived LANs of both species followed a plagiophile LAN distribution, and the measured angles of the cardboard surface allowed us to quantify that these LAN values were strongly correlated with TLS derived angles (r² = 1.0, intercept and slope = 0.98). Our results show that terrestrial laser scanners are feasible for simultaneous measurement of LA, LAN, and Chl_ab in simple canopies of small broadleaved plants. Further research is needed in more complex and larger canopies.     

Impact of test-driven development on productivity, code and tests: A controlled experiment

Context

Test-driven development is an approach to software development, where automated tests are written before production code in highly iterative cycles. Test-driven development attracts attention as well as followers in professional environment; however empirical evidence of its superiority regarding its effect on productivity, code and tests compared to test-last development is still fairly limited. Moreover, it is not clear if the supposed benefits come from writing tests before code or maybe from high iterativity/short development cycles.

Objective

This paper describes a family of controlled experiments comparing test-driven development to micro iterative test-last development with emphasis on productivity, code properties (external quality and complexity) and tests (code coverage and fault-finding capabilities).

Method

Subjects were randomly assigned to test-driven and test-last groups. Controlled experiments were conducted for two years, in an academic environment and in different developer contexts (pair programming and individual programming contexts). Number of successfully implemented stories, percentage of successful acceptance tests, McCabe’s code complexity, code coverage and mutation score indicator were measured.

Results

Experimental results and their selective meta-analysis show no statistically significant differences between test-driven development and iterative test-last development regarding productivity (χ²(6) = 4.799, p = 1.0, r = .107, 95% CI (confidence interval): −.149 to .349), code complexity (χ²(6) = 8.094, p = .46, r = .048, 95% CI: −.254 to .341), branch coverage (χ²(6) = 13.996, p = .059, r = .182, 95% CI: −.081 to .421), percentage of acceptance tests passed (one experiment, Mann-Whitney U = 125.0, p = .98, r = .066) and mutation score indicator (χ²(4) = 3.807, p = .87, r = .128, 95% CI: −.162 to .398).

Conclusion

According to our findings, the benefits of test-driven development compared to iterative test-last development are small and thus in practice relatively unimportant, although effects are positive. There is an indication of test-driven development endorsing better branch coverage, but effect size is considered small.     

Salt-marsh characterization, zonation assessment and mapping through a dual-wavelength LiDAR

Linking intertidal processes to their natural patterns within a framework of coastal erosion requires monitoring techniques providing high-resolution spatio-temporal data from the scale of processes to this of patterns. The Scanning Hydrographic Operational Airborne LiDAR Survey (SHOALS) consists of a ubiquitous topographic and bathymetric LiDAR (Light Detection And Ranging) system that has become an important technology for generating high-resolution Digital Terrain Models (DTM) and Digital Surface Models (DSM) over intertidal landscapes. The objectives of this project are i) to highlight the capacity of SHOALS Topography and intensity data (Red and Near-InfraRed) to detect intertidal vegetation, ii) to assess the salt-marsh zonation, and iii) to map intertidal habitats and its adjacent coastal areas (Gulf of St. Lawrence, Canada). The study area was selected based on the spectrum of land cover types, encompassing beach, salt-marsh, arable farm and urban coastal environments. Surfaces constructed from the LiDAR survey included DSM, DTM, Normalized Surface Model (NSM), Digital Intensity Model for InfraRed (DIMI), Digital Intensity Model for Red (DIMR), and Normalized Difference LiDAR Vegetation Index Model (NDLVIM), derived from the two previous models. The correlation between the so-called NDLVI and the amount of salt-marsh vegetation, measured in situ, was 0.87 (p < 0.01). Then, LiDAR-assessed salt-marsh ecological zonation allowed finding out intermediate and strong relationships between NDLVI and Topography (r² = 0.89, p < 0.038) and Topographic heterogeneity (r² = 0.54, p < 0.1394), respectively. Finally, NDLVI and Topography surfaces were classified using maximum likelihood algorithm into 17 classes, whose overall accuracy and kappa coefficient were 91.89% and 0.9088, respectively. These results support that (1) intertidal vegetation can be discriminated by NDLVI, (2) salt-marsh ecological zonation pattern, and (3) accurate coastal land cover maps can be satisfactorily generated from a single LiDAR survey using the NDLVIM and DTM approach.     

The effects of clinical information presentation on physicians' and nurses' decision-making in ICUs

This research evaluated physicians' agreement about patients' diagnoses and nurses' ability to detect patient change using traditional charts (TC) and a work domain analysis-based paper prototype (PP) and also sought to determine whether differences persisted when the PP was represented as an electronic prototype (EP). Nurses' change detection improved using the PP and EP compared to TC (PP vs TC, t_(df=6) = 1.94, p < 0.03; EP vs TC, t_(df=6) = 3.14, p < 0.01) and detection was better using the EP compared with the PP (t_(df=6) = 5.96, p < 0.001). Physicians were more likely to agree about failed physiological systems using the EP compared with the PP (t_(df=10) = 3.14, p < 0.01), but agreement about patient diagnoses was higher using the PP compared with the EP (t_(df=10) = 2.23; p < 0.02). These results are attributed to information grouping around physiological functions and the direct association of cause-and-effect relations in clinical information design.     

Self-regulated learning through writing on computers: Consequences for reading comprehension

The overall aim for the present study was to analyze the consequences for reading ability among the children of a computer supported self-regulated learning environment in grade two. By means of a quasi-experimental design in a natural setting, an experimental group (n = 39) was compared to a control group from a national sample (n = 3409) on reading comprehension. The statistical analyses showed that the experimental group achieved better on reading comprehension both as a group (p < .001) as well as girls (p < .001) and boys (p < .05) separately. The proportion of high achievers was higher, and the proportion of low achievers was lower in the experimental group. In order to explain the level of reading comprehension in the experimental group Structural Equation Modelling (SEM) was used. The main explanatory factor for reading comprehension was writing with β = .44. As a tentative conclusion it was suggested that the extended writing in combination with the self-regulated learning environment can promote reading comprehension in grade two, whereas home literacy had no impact on reading comprehension in this context.     

Assessment of QuickBird high spatial resolution imagery to detect red attack damage due to mountain pine beetle infestation

High spatial resolution remotely sensed data has the potential to complement existing forest health programs for both strategic planning over large areas, as well as for detailed and precise identification of tree crowns subject to stress and infestation. The area impacted by the current mountain pine beetle (Dendroctonus ponderosae Hopkins) outbreak in British Columbia, Canada, has increased 40-fold over the previous 5 years, with approximately 8.5 million ha of forest infested in 2005. As a result of the spatial extent and intensity of the outbreak, new technologies are being assessed to help detect, map, and monitor the damage caused by the beetle, and to inform mitigation of future beetle outbreaks. In this paper, we evaluate the capacity of high spatial resolution QuickBird multi-spectral imagery to detect mountain pine beetle red attack damage. ANOVA testing of individual spectral bands, as well as the Normalized Difference Vegetation Index (NDVI) and a ratio of red to green reflectance (Red-Green Index or RGI), indicated that the RGI was the most successful (p < 0.001) at separating non-attack crowns from red attack crowns. Based on this result, the RGI was subsequently used to develop a binary classification of red attack and non-attack pixels. The total number of QuickBird pixels classified as having red attack damage within a 50 m buffer of a known forest health survey point were compared to the number of red attack trees recorded at the time of the forest health survey. The relationship between the number of red attack pixels and observed red attack crowns was assessed using independent validation data and was found to be significant (r² = 0.48, p < 0.001, standard error = 2.8 crowns). A comparison of the number of QuickBird pixels classified as red attack, and a broader scale index of mountain pine beetle red attack damage (Enhanced Wetness Difference Index, calculated from a time series of Landsat imagery), was significant (r² = 0.61, p < 0.001, standard error = 1.3 crowns). These results suggest that high spatial resolution imagery, in particular QuickBird satellite imagery, has a valuable role to play in identifying tree crowns with red attack damage. This information could subsequently be used to augment existing detailed forest health surveys, calibrate synoptic estimates of red attack damage generated from overview surveys and/or coarse scale remotely sensed data, and facilitate the generation of value-added information products, such as estimates of timber volume impacts at the forest stand level.     

Development of virtual reality proprioceptive rehabilitation system for stroke patients

In this study, the virtual reality (VR) proprioception rehabilitation system was developed for stroke patients to use proprioception feedback in upper limb rehabilitation by blocking visual feedback. To evaluate its therapeutic effect, 10 stroke patients (onset > 3 month) trained proprioception feedback rehabilitation for one week and visual feedback rehabilitation for another week in random order. Proprioception functions were checked before, a week after, and at the end of training. The results show the click count, error distance and total error distance among proprioception evaluation factors were significantly reduced after proprioception feedback training compared to visual feedback training (respectively, p = 0.005, p = 0.001, and p = 0.007). In addition, subjects were significantly improved in conventional behavioral tests after training. In conclusion, we showed the effectiveness and possible use of the VR to recover the proprioception of stroke patients.     

Disentangling the relationships between plant pigments and the photochemical reflectance index reveals a new approach for remote estimation of carotenoid content

The Photochemical Reflectance Index (PRI) is used as an indicator of leaf and plant canopy photosynthetic efficiency. However, the photosynthetic efficiency-PRI relationship has been shown to be inconsistent over time, likely due to changes in foliar pigment content.We measured reflectance spectra and biochemical properties from 24 leaves of two deciduous tree species and acquired pigment and reflectance data from the Leaf Optical Properties EXperiment database for an additional nine species. These data were used as inputs for the PROSPECT-5 leaf optical model. We found measurements of PRI to be significantly (p < 0.05) correlated with chlorophyll content, carotenoid content, and the carotenoid/chlorophyll ratio. However, only the PRI-carotenoid/chlorophyll ratio relationship was consistent across all analyses. Two predictive equations were derived from PROSPECT-5 simulations: a curvilinear PRI model (PRI(clm)) predicted the carotenoid/chlorophyll ratio (r² = 0.99), and a linear model using the chlorophyll index (CI(lm)) predicted chlorophyll content (r² = 0.98). Multiplying PRI(clm) with CI(lm) canceled the influence of chlorophyll content on PRI(clm) and thus allowed for prediction of carotenoid content from 11 deciduous tree species (r² = 0.83). Our results confirm that the PRI is significantly influenced by chlorophyll and carotenoid pools and demonstrate a new approach for non-destructive estimation of leaf carotenoid content using the PRI. Because variation in foliar physiological status is known to relate to leaf carotenoid content and the carotenoid/chlorophyll ratio, convolving the PRI with a chlorophyll index is likely to be useful for understanding the photosynthetic performance of deciduous vegetation across a wide range of temporal periods, ranging from daily to seasonal time scales.     

Monitoring turbidity in Tampa Bay using MODIS/Aqua 250-m imagery

We developed an approach to map turbidity in estuaries using a time series (May 2003 to April 2006) of 250-m resolution images from the Moderate Resolution Imaging Spectroradiometer (MODIS) on NASA's Aqua satellite, using Tampa Bay as a case study. Cross-calibration of the MODIS 250-m data (originally designed for land use) with the well-calibrated MODIS 1-km ocean data showed that the pre-launch radiometric calibration of the 250-m bands was adequate. A simple single scattering atmospheric correction provided reliable retrievals of remote sensing reflectance at 645 nm (0.002 < R_rs(645) < 0.015 sr^− 1, median bias = − 7%, slope = 0.95, intercept = 0.00, r² = 0.97, n = 15). A more rigorous approach, using a multiple scattering atmospheric correction of the cross-calibrated at-sensor radiances, retrieved similar R_rs(645). R_rs(645) estimates, after stringent data quality control, showed a close correlation with in situ turbidity (turbidity = 1203.9 × R_rs(645)^1.087, 0.9 < turbidity < 8.0 NTU, r² = 0.73, n = 43). MODIS turbidity imagery derived using the developed approach showed that turbidity in Hillsborough Bay (HB) was consistently higher than that in other sub-regions except in August and September, when higher concentrations of colored dissolved organic matter seem to have caused underestimates of turbidity. In comparison, turbidity in Middle Tampa Bay (MTB) was generally lowest among the Bay throughout the year. Both Old Tampa Bay (OTB) and Low Tampa Bay (LTB) showed marked seasonal variations with higher turbidity in LTB during the dry season and in OTB during the wet season, respectively. This seasonality is linked to wind-driven bottom resuspension events in lower portion of the Bay and river inputs of sediments in the upper portion of the Bay. The Bay also experiences significant interannual variation in turbidity, which was attributed primarily to changes in wind forcing. Compared with the once-per-month, non-synoptic in situ surveys, synoptic and frequent sampling facilitated by satellite remote sensing provides improved assessments of turbidity patterns and thus a valuable tool for operational monitoring of water quality of estuarine and coastal waters such as in Tampa Bay.     

Optimal protruding node length of bicycle seats determined using cycling postures and subjective ratings

This study examined body posture, subjective discomfort, and stability, requiring the participants to ride a stationary bicycle for 20 min (cadence: 60 rpm; workrate: 120 W), using various combinations of two handle heights and five seat-protruding node lengths (PNLs). The results indicated that bicycle handle height significantly influenced body posture, and that seat PNL caused differences in the riders' subjective discomfort and stability scores. The various PNLs affected only the trunk angle (approximately 6°), but had significantly positive (r = 0.994, p < .005) and negative (r = −0.914, p < .05) correlations with the subjective discomfort rating for perineum and ischial tuberosity, respectively. When the participants were seated at PNL = 0 or 3 cm, cycling using dropped handles was less stable compared with using straight handles; however, the handle height did not affect the cycling stability when the PNL was ≥6 cm. The results suggest that a 6-cm PNL is the optimal reference for bicycle seat designs.