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Seabirds are well known to be attracted by fishing boats to forage on offal and baits. We used recently developed loggers that record accurate GPS position and detect the presence of boats through their radar emissions to examine how albatrosses use Area Restricted Search (ARS) and if so, have specific ARS behaviours, when attending boats. As much as 78.5% of locations with a radar detection (contact with boat) during a trip occurred within ARS: 36.8% of all large-scale ARS (n = 212) and 14.7% of all small-scale ARS (n = 1476) were associated with the presence of a boat. During small-scale ARS, birds spent more time and had greater sinuosity during boat-associated ARS compared with other ARS that we considered natural. For, small-scale ARS associated with boats, those performed over shelves were longer in duration, had greater sinuosity, and birds spent more time sitting on water compared with oceanic ARS associated with boats. We also found that the proportion of small-scale ARS tend to be more frequently nested in larger-scale ARS was higher for birds associated with boats and that ARS behaviour differed between oceanic (tuna fisheries) and shelf-edge (mainly Patagonian toothfish fisheries) habitats. We suggest that, in seabird species attracted by boats, a significant amount of ARS behaviours are associated with boats, and that it is important to be able to separate ARS behaviours associated to boats from natural searching behaviours. Our study suggest that studying ARS characteristics should help attribute specific behaviours associated to the presence of boats and understand associated risks between fisheries. [ABSTRACT FROM AUTHOR]

The aim of this investigation was to establish the validity of a GPS-based tracking system (Polar Team Pro System, PTPS) for estimating sprint performance and to evaluate additional diagnostic indices derived from the temporal course of the movement velocity. Thirty-four male soccer players (20 ± 4 years) performed a 20 m sprint test measured by timing gates (TG), and while wearing the PTPS. To evaluate the relevance of additional velocity-based parameters to discriminate between faster and slower athletes, the median-split method was applied to the 20-m times. Practical relevance was estimated using standardized mean differences (d) between the subgroups. Differences between the criterion reference (TG) and PTPS for the 10 and 20 m splits did not vary from zero (dt10: -0.01 ± 0.07 s, P = 0.7, d < -0.1; dt20: -0.01 ± 0.08 s, P = 0.4, d < -0.2). Although subgroups revealed large differences in their sprint times (d = -2.5), the average accelerations between 5 and 20 km/h as well as 20 and 25 km/h showed merely small effects (d < 0.5). Consequently, analyses of velocity curves derived from PTPS may help to clarify the occurrence of performance in outdoor sports. Thus, training consequences can be drawn which contribute to the differentiation and individualization of sprint training. [ABSTRACT FROM AUTHOR]

The traditional U-turn design has significantly improved traffic operations for relieving traffic congestion. However, the U-turn diversion and merge segments still cause traffic conflicts and delays. In this paper, an exclusive spur dike U-turn lane (ESUL) is proposed with the aim of addressing the disadvantages of the traditional U-turn design. ESUL provides a separate U-turn lane to diverge, decelerate, U-turn, accelerate and merge without interacting with through traffic. The effectiveness of ESUL is demonstrated through a field data investigation, simulation and analysis with VISSIM software. The proposed design is evaluated in terms of three parameters: travel time, delay and number of stops. Compared to the traditional U-turn design, ESUL can reduce travel time by 29.15%, delay by 66.70% and the number of stops by 100% at most. The results showed that ESUL has better performance than the traditional U-turn design and could be implemented to reduce traffic congestion and the potential hazards caused by U-turn maneuvers. [ABSTRACT FROM AUTHOR]

The purpose of Fuzzy Comprehensive CS-SVR Model (FCCS-SVR) is to evaluate and monitor the health status of a radar equipment and then keep its safe operation. Due to reasons such as few samples, slow changes and the nonlinear structure of data of fault monitoring signal, the health status evaluation of a radar system is quite difficult. By establishing the evaluation index system of a radar, the combination of AHP method and Entropy weight method is studied in this paper. In order to evaluate the value of health status, several optimization algorithms including PSO, GA, BA and CS are used for optimizing the parameters of SVR model. Meanwhile, in order to avoid the problem that the system is at the edge of the state, a radar health assessment method based on the combination of Fuzzy Comprehensive Evaluation and Cuckoo Search-Support Vector Regression (CS-SVR), which is named as Fuzzy Comprehensive CS-SVR (FCCS-SVR), is further proposed. The result of case analysis reflects that the state evaluation of the radar system is realized. The system performance analysis shows that the use of FCCS-SVR evaluation method provides a high recognition rate and can accurately assess the health status of the radar system. [ABSTRACT FROM AUTHOR]

Fisheries compete with seabirds for vanishing marine resources, but also produce fishery waste consumed by seabirds. Marine birds may therefore avoid or seek fishing vessels, and have evolved complex, plastic behavioural responses to vessel presence. Understanding these responses is essential to the conservation of a globally declining seabird community. We studied Cape gannets (Morus capensis), which compete with fisheries for reduced sardine (Sardinops sagax) resources in the Benguela upwelling region off South Africa. Using bird-borne GPS trackers coupled with newly-developed ship-radar detectors we show that foraging gannets seldom attended fishing vessels. Rather, they switched from eating scarce sardines or energetically-poor fishery waste to targeting locally abundant saury (Scomberesox saurus). This pelagic fish is brought into the seascape by warm water influx, and is not commercially exploited by fisheries. Cape gannets thereby show dietary plasticity, allowing them to maintain adult body condition and chick growth rates. This diet switch is a strong indicator that Cape gannets forage in an ecologically perturbed marine environment. [ABSTRACT FROM AUTHOR]

This paper constructed a stacked-autoencoder neural network model (SAE model) to estimate sea state bias (SSB) based on radar altimeter data. Six cycles of the geophysical data record (GDR) from Jason-1/2 radar altimeters were used as a training dataset, and the other 2 cycles of the GDR from Jason-1/2 were used for testing. The inputs to this SAE model include the significant wave height (SWH), wind speed (U), sea surface height (SSH), backscatter coefficient (σ0) and automatic gain control (AGC), and the model outputs the SSB. The model includes one input layer, three hidden layers and one output layer. The SSBs in the GDR of Jason-1/2 were obtained from a nonparametric model based on the SWH and U as input variables; thus, the model has high accuracy but low efficiency. The SSBs in the GDR of HY-2A were computed using a four-parameter parametric model that uses the SWH and U as input variables; therefore, this model’s computational speed is high but its accuracy is low. Thus, we used the HY-2A radar altimeter as an unseen validation dataset to evaluate the performance of the SAE model. Then, we analyzed the contrasting results of these methods, including the differences in the SSB, explained variance, residual error and operational efficiency. The results demonstrate not only that the accuracy of the SAE model is superior to that of the conventional parametric model but also that its operational efficiency is better than that of the nonparametric model. [ABSTRACT FROM AUTHOR]

Lakes are a key geographical feature in Canada and have an impact on the regional climate. In the winter, they are important for recreational activities such as snowmobiling and ice fishing and act as part of an important supply route for northern communities. The ability to accurately report lake ice characteristics such as thickness is vital, however, it is underreported in Canada and there is a lack of lake ice thickness records for temperate latitude areas such as Central Ontario. Here, we evaluate the application of previously developed temperature models and RADARSAT-2 for estimating lake ice thickness in Central Ontario and provide insight into the regions long term ice thickness variability. The ALS Environmental Science Shallow Water Ice Profiler (SWIP) was used for validation of both temperature and radar-based models. Results indicate that the traditional approach that uses temperatures to predict ice thickness during ice growth has low RMSE values of 2.3 cm and correlations of greater than 0.9. For ice decay, similar low RMSE values of 2.1 cm and high correlations of 0.97 were found. Using RADARSAT-2 to estimate ice thickness results in R2 values of 0.6 (p < 0.01) but high RMSE values of 11.7 cm. Uncertainty in the RADARSAT-2 approach may be linked to unexplored questions about scattering mechanisms and the interaction of radar signal with mid-latitude lake ice. The application of optimized temperature models to a long-term temperature record revealed a thinning of ice cover by 0.81 cm per decade. [ABSTRACT FROM AUTHOR]

The traditional shipborne navigation system uses a two-dimensional electronic chart as a platform to integrate and control a variety of electronic navigation equipment information. It cannot intuitively restore the actual traffic environment or fundamentally improve the perception ability of the crew in poor visibility conditions. This paper proposes integrating three-dimensional simulations and real ship driving systems and presents research on “virtual–real” and “dynamic–static” ship navigation technology and equipment. In the proposed method, the hydrologic factors, topographic features, waterways, traffic dynamics, and ship driving information are effectively integrated, with a focus on achieving key advancements such as the integration of simulations and real ship driving as well as multi-source information fusion. A multi-angle, all-around, multi-level visual display for water traffic environments in poor visibility conditions is provided to enhance the ability of crews to perceive their traffic environments and thereby to provide auxiliary navigation for ships in complex weather conditions. [ABSTRACT FROM AUTHOR]

Wind and temperature data are important parameters in aircraft performance studies. The lack of accurate measurements of these parameters forces researchers to rely on numerical weather prediction models, which are often filtered for a larger area with decreased local accuracy. Aircraft, however, also transmit information related to weather conditions, in response to interrogation by air traffic controller surveillance radars. Although not intended for this purpose, aircraft surveillance data contains information that can be used for weather models. This paper presents a method that can be used to reconstruct a weather field from surveillance data that can be received with a simple 1090 MHz receiver. Throughout the paper, we answer two main research questions: how to accurately infer wind and temperature from aircraft surveillance data, and how to reconstruct a real-time weather grid efficiently. We consider aircraft as moving sensors that measure wind and temperature conditions indirectly at different locations and flight levels. To address the first question, aircraft barometric altitude, ground velocity, and airspeed are decoded from down-linked surveillance data. Then, temperature and wind observations are computed based on aeronautical speed conversion equations. To address the second question, we propose a novel Meteo-Particle (MP) model for constructing the wind and temperature fields. Short-term local prediction is also possible by employing a predictor layer. Using an unseen observation test dataset, we are able to validate that the mean absolute errors of inferred wind and temperature using MP model are 67% and 26% less than using the interpolated model based on GFS reanalysis data. [ABSTRACT FROM AUTHOR]

Comparing the functional performance of biological systems often requires comparing multiple mechanical properties. Such analyses, however, are commonly presented using orthogonal plots that compare N ≤ 3 properties. Here, we develop a multidimensional visualization strategy using permutated radar charts (radial, multi-axis plots) to compare the relative performance distributions of mechanical systems on a single graphic across N ≥ 3 properties. Leveraging the fact that radar charts plot data in the form of closed polygonal profiles, we use shape descriptors for quantitative comparisons. We identify mechanical property-function correlations distinctive to rigid, flexible, and damage-tolerant biological materials in the form of structural ties, beams, shells, and foams. We also show that the microstructures of dentin, bone, tendon, skin, and cartilage dictate their tensile performance, exhibiting a trade-off between stiffness and extensibility. Lastly, we compare the feeding versus singing performance of Darwin’s finches to demonstrate the potential of radar charts for multidimensional comparisons beyond mechanics of materials. [ABSTRACT FROM AUTHOR]

Honeybees, Apis mellifera, perform re-orientation flights to learn about the new surroundings of the hive when their hive is transported to a new location. Since the pattern of re-orientation flights has not yet been studied, we asked whether this form of exploratory behavior differs from the well described exploratory orientation flights performed by young honeybees before they start foraging. We also investigated whether the exploratory components of re-orientation flights differ from foraging flights and if so how. We recorded re-orientation flights using harmonic radar technology and compared the patterns and flight parameters of these flights with the first exploratory orientation flights of young honeybees and foraging flights of experienced foragers. Just as exploratory orientation flights of young honeybees, re-orientation flights can be classified into short- and long-range flights, and most short-range re-orientation flights were performed under unfavorable weather conditions. This indicates that bees adapt the flight pattern of their re-orientation and orientation flights to changing weather conditions in a similar way. Unlike exploratory orientation flights, more than one sector of the landscape was explored during a long-range re-orientation flight, and significantly longer flight durations and flight distances were observed. Thus, re-orienting bees explored a larger terrain than bees performing their first exploratory orientation flight. By displacing some bees after their first re-orientation flight, we could demonstrate that a single re-orientation flight seems to be sufficient to learn the new location of the hive. The flight patterns of re-orientation flights differed clearly from those of foraging flights. Thus, re-orientation flights represent a special exploratory behavior that is triggered by a change in the location of the hive. [ABSTRACT FROM AUTHOR]

Introduction: The aim of the study was to (i) analyze the match performance of professional female tennis players in different Grand Slams; (ii) model the relationships between match performance variables and relative quality; and (iii) build typical performance profiles for those players in Grand Slams. Method: Data of a total of 1369 matches were collected within 2014–2017 four Grand Slams (Australian Open: n = 499; Roland Garros: n = 249; Wimbledon: n = 249 and US Open, n = 372). Correlations between 37 performance variables and relative quality (difference of expected rounds between two competing players of given ranking) were determined and automatically classified into two groups of magnitudes via two-step cluster analysis. Higher-correlated variables were used to build players’ typical performance profiles via regression-based technique to give percentage evaluation scores (%ES), which means the percentage of matches where a performance variable value would be expected to be lower than the observed value considering the RQ of two competing players. Results: Players had more service winners, double faults, return winners and return unforced errors in the Australian Open and US Open, implying a “fast-fast” serve strategy, and higher dominance ratio and better serving performance in Wimbledon. While receiving players had better chances to break opponents’ service game in Roland Garros. Distance covered became similar in all Grand Slams. All studied variables showed obvious correlation with RQ expect for those of physical performance. Conclusions: The findings (i) indicate that female game in Grand Slams remained to be a contest over baseline, although players had good efficiency at net; (ii) demonstrate the influence of relative quality on serve and return, break point, net point and efficiency performance; and (iii) evidence the usefulness of applying %ES to evaluate performance of individual player. [ABSTRACT FROM AUTHOR]

Aims: In the current study we investigated the effects of resisted sprint training on sprinting performance and underlying mechanical parameters (force-velocity-power profile) based on two different training protocols: (i) loads that represented maximum power output (Lopt) and a 50% decrease in maximum unresisted sprinting velocity and (ii) lighter loads that represented a 10% decrease in maximum unresisted sprinting velocity, as drawn from previous research (L10). Methods: Soccer [n = 15 male] and rugby [n = 21; 9 male and 12 female] club-level athletes were individually assessed for horizontal force-velocity and load-velocity profiles using a battery of resisted sprints, sled or robotic resistance respectively. Athletes then performed a 12-session resisted (10 × 20-m; and pre- post-profiling) sprint training intervention following the L10 or Lopt protocol. Results: Both L10 and Lopt training protocols had minor effects on sprinting performance (average of -1.4 to -2.3% split-times respectively), and provided trivial, small and unclear changes in mechanical sprinting parameters. Unexpectedly, Lopt impacted velocity dominant variables to a greater degree than L10 (trivial benefit in maximum velocity; small increase in slope of the force-velocity relationship), while L10 improved force and power dominant metrics (trivial benefit in maximal power; small benefit in maximal effectiveness of ground force orientation). Conclusions: Both resisted-sprint training protocols were likely to improve performance after a short training intervention in already sprint trained athletes. However, widely varied individualised results indicated that adaptations may be dependent on pre-training force-velocity characteristics. [ABSTRACT FROM AUTHOR]

This paper proposes a novel vehicle detection system that can overcome some limitations of typical vehicle detection systems using AdaBoost-based methods. The performance of the AdaBoost-based vehicle detection system is dependent on its training data. Thus, its performance decreases when the shape of a target differs from its training data, or the pattern of a preceding vehicle is not visible in the image due to the light conditions. A stacked Difference of Gaussian (DoG)–based feature extraction algorithm is proposed to address this issue by recognizing common characteristics, such as the shadow and rear wheels beneath vehicles—of vehicles under various conditions. The common characteristics of vehicles are extracted by applying the stacked DoG shaped kernel obtained from the 3D plot of an image through a convolution method and investigating only certain regions that have a similar patterns. A new vehicle detection system is constructed by combining the novel stacked DoG feature extraction algorithm with the AdaBoost method. Experiments are provided to demonstrate the effectiveness of the proposed vehicle detection system under different conditions. [ABSTRACT FROM AUTHOR]

Pre-construction assessments of bird collision risk at proposed wind farms are often confounded by insufficient or poor quality data describing avian flight paths through the development area. These limitations can compromise the practical value of wind farm impact studies. We used radar- and observer-based methods to quantify great white pelican flights in the vicinity of a planned wind farm on the Cape west coast, South Africa, and modelled turbine collision risk under various scenarios. Model outputs were combined with pre-existing demographic data to evaluate the possible influence of the wind farm on the pelican population, and to examine impact mitigation options. We recorded high volumes of great white pelican movement through the wind farm area, coincident with the breeding cycle of the nearby colony and associated with flights to feeding areas located about 50 km away. Pelicans were exposed to collision risk at a mean rate of 2.02 High Risk flights.h-1. Risk was confined to daylight hours, highest during the middle of the day and in conditions of strong north-westerly winds, and 82% of High Risk flights were focused on only five of the proposed 35 turbine placements. Predicted mean mortality rates (22 fatalities.yr-1, 95% Cl, 16–29, with average bird and blade speeds and 95% avoidance rates) were not sustainable, resulting in a negative population growth rate (λ = 0.991). Models suggested that removal of the five highest risk turbines from the project, or institution of a curtailment regimen that shuts down at least these turbines at peak traffic times, could theoretically reduce impacts to manageable levels. However, in spite of the large quantities of high quality data used in our analyses, our collision risk model remains compromised by untested assumptions about pelican avoidance rates and uncertainties about the existing dynamics of the pelican population, and our findings are probably not reliable enough to ensure sustainable development. [ABSTRACT FROM AUTHOR]

Background: In advanced prostate cancer, osteoclast inhibitors prevent and palliate skeletal related events associated with bone metastases. However, it is uncertain whether they play a disease-modifying role earlier in the course of the disease. Methods: Medline, EMBASE, Cochrane Central Register of Controlled Trials and Cochrane Database of Systematic Reviews and ASCO conference proceedings were searched for randomized controlled trials that compared osteoclast inhibitors with placebo and/or standard of care (SOC) in patients with high-risk, non-metastatic prostate cancer. The primary outcome measure was incidence of new bone metastases; secondary outcomes included overall survival (OS), prostate cancer specific survival, mortality unrelated to prostate cancer, toxicity and health related quality of life outcomes. Results are presented as relative risk (RR) with 95% confidence intervals (CI). Results: Six randomized controlled trials (5947 participants) were included, five evaluating bisphosphonates and one denosumab. Overall, there was no difference in incidence of bone metastases between participants treated with osteoclast inhibitors versus placebo/SOC (RR 1.09, 95%CI 0.84–1.41, p = 0.51) however significant heterogeneity was observed between studies. The denosumab trial was the largest and only positive trial amongst the included studies (RR 0.83, 95%CI 0.73–0.95, p = 0.007). No significant difference was observed in OS (RR 0.99 95% CI 0.89–1.10, p = 0.84) nor prostate cancer specific survival (RR 1.12 95%CI 0.93–1.36, p = 0.24). Most studies reported increased rates of osteonecrosis of the jaw (5% or less) and hypocalcemia (2% or less) with osteoclast inhibitors. Conclusions: While there is limited evidence that bisphosphonates alter the natural history of high-risk, non-metastatic prostate cancer, denosumab delays onset of bone metastases in this patient population. Neither class of osteoclast inhibitor demonstrated an impact on survival outcomes. Future trials with better defined patient selection and a robust definition for high risk disease is critical. [ABSTRACT FROM AUTHOR]

Worldwide, more than one million people die on the roads each year. A third of these fatal accidents are attributed to speeding, with properties of the individual driver and the environment regarded as key contributing factors. We examine real-world speeding behavior and its interaction with illuminance, an environmental property defined as the luminous flux incident on a surface. Drawing on an analysis of 1.2 million vehicle movements, we show that reduced illuminance levels are associated with increased speeding. This relationship persists when we control for factors known to influence speeding (e.g., fluctuations in traffic volume) and consider proxies of illuminance (e.g., sight distance). Our findings add to a long-standing debate about how the quality of visual conditions affects drivers’ speed perception and driving speed. Policy makers can intervene by educating drivers about the inverse illuminance‒speeding relationship and by testing how improved vehicle headlights and smart road lighting can attenuate speeding. [ABSTRACT FROM AUTHOR]

Mapping three-dimensional (3D) surface deformation caused by an earthquake is very important for the environmental, cultural, economic and social sustainability of human beings. Synthetic aperture radar (SAR) systems made it possible to measure precise 3D deformations by combining SAR interferometry (InSAR) and multiple aperture interferometry (MAI). In this paper, we retrieve the 3D surface deformation field of the 2010 Haiti earthquake which occurred on January 12, 2010 by a magnitude 7.0 Mw by using the advanced interferometric technique that integrates InSAR and MAI data. The surface deformation has been observed by previous researchers using the InSAR and GPS method, but 3D deformation has not been measured yet due to low interferometric coherence. The combination of InSAR and MAI were applied to the ALOS PALSAR ascending and descending pairs, and were validated with the GPS in-situ measurements. The archived measurement accuracy was as little as 1.85, 5.49 and 3.08 cm in the east, north and up directions, respectively. This result indicates that the InSAR/MAI-derived 3D deformations are well matched with the GPS deformations. The 3D deformations are expected to allow us to improve estimation of the area affected by the 2010 Haiti earthquake. [ABSTRACT FROM AUTHOR]

Background: This theoretical study examines the use of radar to continuously monitor “accumulation of blood in the head” (ACBH) non-invasively and from a distance, after the location of a hematoma or hemorrhage in the brain was initially identified with conventional medical imaging. Current clinical practice is to monitor ABCH with multiple, subsequent, conventional medical imaging. The radar technology introduced in this study could provide a lower cost and safe alternative to multiple conventional medical imaging monitoring for ACBH. Materials and methods: The goal of this study is to evaluate the feasibility of using radar to monitor changes in blood volume in the brain through a numerical simulation of ACBH monitoring from remote, with a directional spiral slot antennae, in 3-D models of the brain. The focus of this study is on evaluating the effect of frequencies on the antennae reading. To that end we performed the calculations for frequencies of 100 MHz, 500 MHz and 1 GHz. Results and discussion: The analysis shows that the ACBH can be monitored with radar and the monitoring resolution improves with an increase in frequency, in the range studied. However, it also appears that when typical clinical dimensions of hematoma and hemorrhage are used, the variable ratio of blood volume radius and radar wavelength can bring the measurements into the Mie and Rayleigh regions of the radar cross section. In these regions there is an oscillatory change in signal with blood volume size. For some frequencies there is an increase in signal with an increase in volume while in others there is a decrease. Conclusions: While radar can be used to monitor ACBH non-invasively and from a distance, the observed Mie region dependent oscillatory relation between blood volume size and wavelength requires further investigation. Classifiers, multifrequency algorithms or ultra-wide band radar are possible solutions that should be explored in the future. [ABSTRACT FROM AUTHOR]

We utilize L-band interferometric synthetic aperture radar (InSAR) data in this study to retrieve a ground velocity map for the near field of the Ganos section of the north Anatolian fault (NAF) zone. The segmentation and creep distribution of this section, which last ruptured in 1912 to generate a moment magnitude (Mw)7.3 earthquake, remains incompletely understood. Because InSAR processing removes the mean orbital plane, we do not investigate large scale displacements due to regional tectonics in this study as these can be determined using global positioning system (GPS) data, instead concentrating on the close-to-the-fault displacement field. Our aim is to determine whether, or not, it is possible to retrieve robust near field velocity maps from stacking L-band interferograms, combining both single and dual polarization SAR data. In addition, we discuss whether a crustal velocity map can be used to complement GPS observations in an attempt to discriminate the present-day surface displacement of the Ganos fault (GF) across multiple segments. Finally, we characterize the spatial distribution of creep on shallow patches along multiple along-strike segments at shallow depths. Our results suggest the presence of fault segmentation along strike as well as creep on the shallow part of the fault (i.e. the existence of a shallow creeping patch) or the presence of a smoother section on the fault plane. Data imply a heterogeneous fault plane with more complex mechanics than previously thought. Because this study improves our knowledge of the mechanisms underlying the GF, our results have implications for local seismic hazard assessment. [ABSTRACT FROM AUTHOR]

Dyslexia is a developmental learning disorder of single word reading accuracy and/or fluency, with compelling research directed towards understanding the contributions of the visual system. While dyslexia is not an oculomotor disease, readers with dyslexia have shown different eye movements than typically developing students during text reading. Readers with dyslexia exhibit longer and more frequent fixations, shorter saccade lengths, more backward refixations than typical readers. Furthermore, readers with dyslexia are known to have difficulty in reading long words, lower skipping rate of short words, and high gaze duration on many words. It is an open question whether it is possible to harness these distinctive oculomotor scanning patterns observed during reading in order to develop a screening tool that can reliably identify struggling readers, who may be candidates for dyslexia. Here, we introduce a novel, fast, objective, non-invasive method, named Rapid Assessment of Difficulties and Abnormalities in Reading (RADAR) that screens for features associated with the aberrant visual scanning of reading text seen in dyslexia. Eye tracking parameter measurements that are stable under retest and have high discriminative power, as indicated by their ROC (receiver operating characteristic) curves, were obtained during silent text reading. These parameters were combined to derive a total reading score (TRS) that can reliably separate readers with dyslexia from typical readers. We tested TRS in a group of school-age children ranging from 8.5 to 12.5 years of age. TRS achieved 94.2% correct classification of children tested. Specifically, 35 out of 37 control (specificity 94.6%) and 30 out of 32 readers with dyslexia (sensitivity 93.8%) were classified correctly using RADAR, under a circular validation condition (see section /Total Reading Score) where the individual evaluated was not included in the test construction group. In conclusion, RADAR is a novel, automated, fast and reliable way to identify children at high risk of dyslexia that is amenable to large-scale screening. Moreover, analysis of eye movement parameters obtained with RADAR during reading will likely be useful for implementing individualized treatment strategies and for monitoring objectively the success of chosen interventions. We envision that it will be possible to use RADAR as a sensitive, objective, and quantitative first pass screen to identify individuals with reading disorders that manifest with abnormal oculomotor reading strategies, like dyslexia. [ABSTRACT FROM AUTHOR]

The locomotory gait analysis of the microswimmer, Caenorhabditis elegans, is a commonly adopted approach for strain recognition and examination of phenotypic defects. Gait is also a visible behavioral expression of worms under external stimuli. This study developed an adaptive data analysis method based on empirical mode decomposition (EMD) to reveal the biological cues behind intricate motion. The method was used to classify the strains of worms according to their gaitprints (i.e., phenotypic traits of locomotion). First, a norm of the locomotory pattern was created from the worm of interest. The body curvature of the worm was decomposed into four intrinsic mode functions (IMFs). A radar chart showing correlations between the predefined database and measured worm was then obtained by dividing each IMF into three parts, namely, head, mid-body, and tail. A comprehensive resemblance score was estimated after k-means clustering. Simulated data that use sinusoidal waves were generated to assess the feasibility of the algorithm. Results suggested that temporal frequency is the major factor in the process. In practice, five worm strains, including wild-type N2, TJ356 (zIs356), CL2070 (dvIs70), CB0061 (dpy-5), and CL2120 (dvIs14), were investigated. The overall classification accuracy of the gaitprint analyses of all the strains reached nearly 89%. The method can also be extended to classify some motor neuron-related locomotory defects of C. elegans in the same fashion. [ABSTRACT FROM AUTHOR]

For the period 1996-2010, we provide the first indication of the drivers behind mangrove land cover and land use change across the (pan-)tropics using time-series Japanese Earth Resources Satellite (JERS-1) Synthetic Aperture Radar (SAR) and Advanced Land Observing Satellite (ALOS) Phased Array-type L-band SAR (PALSAR) data. Multi-temporal radar mosaics were manually interpreted for evidence of loss and gain in forest extent and its associated driver. Mangrove loss as a consequence of human activities was observed across their entire range. Between 1996-2010 12% of the 1168 1°x1° radar mosaic tiles examined contained evidence of mangrove loss, as a consequence of anthropogenic degradation, with this increasing to 38% when combined with evidence of anthropogenic activity prior to 1996. The greatest proportion of loss was observed in Southeast Asia, whereby approximately 50% of the tiles in the region contained evidence of mangrove loss, corresponding to 18.4% of the global mangrove forest tiles. Southeast Asia contained the greatest proportion (33.8%) of global mangrove forest. The primary driver of anthropogenic mangrove loss was found to be the conversion of mangrove to aquaculture/agriculture, although substantial advance of mangroves was also evident in many regions. [ABSTRACT FROM AUTHOR]

Dempster-Shafer evidence theory has been extensively used in many information fusion systems since it was proposed by Dempster and extended by Shafer. Many scholars have been conducted on conflict management of Dempster-Shafer evidence theory in past decades. However, how to determine a potent parameter to measure evidence conflict, when the given environment is in an open world, namely the frame of discernment is incomplete, is still an open issue. In this paper, a new method which combines generalized conflict coefficient, generalized evidence distance, and generalized interval correlation coefficient based on ordered weighted averaging (OWA) operator, to measure the conflict of evidence is presented. Through ordered weighted average of these three parameters, the combinatorial coefficient can still measure the conflict effectively when one or two parameters are not valid. Several numerical examples demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Understanding the characteristics of vessel traffic flow is crucial in maintaining navigation safety, efficiency, and overall waterway transportation management. Factors influencing vessel traffic flow possess diverse features such as hierarchy, uncertainty, nonlinearity, complexity, and interdependency. To reveal the impact mechanism of the factors influencing vessel traffic flow, a hierarchical model and a coupling model are proposed in this study based on the interpretative structural modeling method. The hierarchical model explains the hierarchies and relationships of the factors using a graph. The coupling model provides a quantitative method that explores interaction effects of factors using a coupling coefficient. The coupling coefficient is obtained by determining the quantitative indicators of the factors and their weights. Thereafter, the data obtained from Port of Tianjin is used to verify the proposed coupling model. The results show that the hierarchical model of the factors influencing vessel traffic flow can explain the level, structure, and interaction effect of the factors; the coupling model is efficient in analyzing factors influencing traffic volumes. The proposed method can be used for analyzing increases in vessel traffic flow in waterway transportation system. [ABSTRACT FROM AUTHOR]

This paper summarizes the results of a two-day dynamic monitoring of Michelangelo's David subject to environmental loads (city traffic and pedestrian loading induced by tourists visiting the Accademia Gallery). The monitoring was carried out by a no-contact technique using an interferometric radar, whose effectiveness in measuring the resonant frequencies of structures and historic monuments has proved over the last years through numerous monitoring activities. Owing to the dynamic behavior of the measurement system (radar and tripod), an accelerometer has been installed on the radar head to filter out the movement component of the measuring instrument from the measurement of the David's displacement. Measurements were carried out in the presence and absence of visitors, to assess their influence on the dynamic behavior of the statue. A numerical model of the statue was employed to evaluate the experimental results. [ABSTRACT FROM AUTHOR]

Body Mass Index has traditionally been used as a measure of health, but Fat Mass Index (FMI) and Lean Mass Index (LMI) have been shown to be more predictive of mortality and health risk. Total body FMI and LMI reference curves have particularly been useful in quantifying sarcopenia and sarcopenic obesity. Research has shown regional composition has significant associations to health outcomes. We derived FMI and LMI reference curves of the regions of the body (leg, arm, and trunk) for 15,908 individuals in the 1999–2004 National Health and Nutrition Examination Survey data for each sex and ethnicity using the Lambda-Mu-Sigma (LMS) method and developed software to visualize this regional composition. These reference curves displayed differentiation between males and females during puberty and sharper limb LMI declines during late adulthood for males. For adults ages 30–50, females had 39%, 83%, and 47% larger arm, leg, and trunk FMI values than males, respectively. Males had 49%, 20%, and 15% higher regional LMI values than females for the arms, legs, and trunk respectively. The leg FMI and LMI of black females were 14% and 15% higher respectively than those of Hispanic and white females. White and Hispanic males had 37% higher trunk FMI values than black males. Hispanic females had 20% higher trunk FMI than white and black females. These data underscore the importance of accounting for sex and ethnicity in studies of regional composition. This study is the first to produce regional LMI and FMI reference tables and curves from the NHANES dataset. These reference curves provide a framework useful in studies and research involving sarcopenia, obesity, sarcopenic obesity, and other studies of compositional phenotypes. Further, the software tool we provide for visualizing regional composition will prove useful in monitoring progress in physical therapy, diets, or other attempts to attain healthier compositions. [ABSTRACT FROM AUTHOR]

The detection of duct height has a significant effect on marine radar or wireless apparatus applications. The paper presents two models to verify the adaptation of evaporation duct models in the SCS in winter. A meteorological gradient instrument used to measure evaporation ducts was fabricated using hydrological and meteorological sensors at different heights. An experiment on the adaptive characteristics of evaporation duct models was carried out over the SCS. The heights of the evaporation ducts were measured by means of log-linear fit, Paulus-Jeske (PJ) and Naval Postgraduate School (NPS) models. The results showed that NPS model offered significant advantages in stability compared with the PJ model. According the collected data computed by the NPS model, the mean deviation (MD) was -1.7 m, and the Standard Deviation (STD) of the MD was 0.8 m compared with the true value. The NPS model may be more suitable for estimating the evaporation duct height in the SCS in winter due to its simpler system characteristics compared with meteorological gradient instruments. [ABSTRACT FROM AUTHOR]

The widespread availability of relatively cheap, reliable and easy to use digital camera traps has led to their extensive use for wildlife research, monitoring and public outreach. Users of these units are, however, often frustrated by the limited options for controlling camera functions, the generation of large numbers of images, and the lack of flexibility to suit different research environments and questions. We describe the development of a user-customisable open source camera trap platform named ‘WiseEye’, designed to provide flexible camera trap technology for wildlife researchers. The novel platform is based on a Raspberry Pi single-board computer and compatible peripherals that allow the user to control its functions and performance. We introduce the concept of confirmatory sensing, in which the Passive Infrared triggering is confirmed through other modalities (i.e. radar, pixel change) to reduce the occurrence of false positives images. This concept, together with user-definable metadata, aided identification of spurious images and greatly reduced post-collection processing time. When tested against a commercial camera trap, WiseEye was found to reduce the incidence of false positive images and false negatives across a range of test conditions. WiseEye represents a step-change in camera trap functionality, greatly increasing the value of this technology for wildlife research and conservation management. [ABSTRACT FROM AUTHOR]

Clustering a set of objects into homogeneous groups is a fundamental operation in data mining. Recently, many attentions have been put on categorical data clustering, where data objects are made up of non-numerical attributes. For categorical data clustering the rough set based approaches such as Maximum Dependency Attribute (MDA) and Maximum Significance Attribute (MSA) has outperformed their predecessor approaches like Bi-Clustering (BC), Total Roughness (TR) and Min-Min Roughness(MMR). This paper presents the limitations and issues of MDA and MSA techniques on special type of data sets where both techniques fails to select or faces difficulty in selecting their best clustering attribute. Therefore, this analysis motivates the need to come up with better and more generalize rough set theory approach that can cope the issues with MDA and MSA. Hence, an alternative technique named Maximum Indiscernible Attribute (MIA) for clustering categorical data using rough set indiscernible relations is proposed. The novelty of the proposed approach is that, unlike other rough set theory techniques, it uses the domain knowledge of the data set. It is based on the concept of indiscernibility relation combined with a number of clusters. To show the significance of proposed approach, the effect of number of clusters on rough accuracy, purity and entropy are described in the form of propositions. Moreover, ten different data sets from previously utilized research cases and UCI repository are used for experiments. The results produced in tabular and graphical forms shows that the proposed MIA technique provides better performance in selecting the clustering attribute in terms of purity, entropy, iterations, time, accuracy and rough accuracy. [ABSTRACT FROM AUTHOR]

In this paper, a new compact wideband monopole antenna is presented for wireless communication applications. This antenna comprises of a new radiating patch, a new arc-shaped strip, microstrip feed line, and a notched ground plane. The proposed radiating patch is combined with a rectangular and semi-circular patch and is integrated with a partial ground plane to provide a wide impedance bandwidth. The new arc-shaped strip between the radiating patch and microstrip feed line creates an extra surface on the patch, which helps further widen the bandwidth. Inserting one step notch on the ground plane further enhances the bandwidth. The antenna has a compact size of 16×20×1.6mm3. The measured result indicated that the antenna achieves a 127% bandwidth at VSWR≤2, ranging from 4.9GHz to 22.1GHz. Stable radiation patterns with acceptable gain are achieved. Also, a measured bandwidth of 107.7% at VSWR≤1.5 (5.1-17GHz) is obtained, which is suitable for UWB outdoor propagation. This antenna is compatible with a good number of wireless standards, including UWB band, Wimax 5.4 GHz band, MVDDS (12.2–12.7GHz), and close range radar and satellite communication in the X-band (8-12GHz), and Ku band (12-18GHz). [ABSTRACT FROM AUTHOR]

Background: Therapeutic use and abuse of prescription opioids in the United States increased substantially between 1990 and 2010. The Centers for Disease Control estimated deaths related to pharmaceutical opioids reached nearly 19,000 in 2014. Of prescription opioids sold, 10% are extended release (ER) and 90% immediate release (IR). However, most regulations and interventions have focused on decreasing ER abuse. Our objective was to compare rates of abuse and diversion of ER and IR opioid analgesics over time using multiple surveillance programs. Methods: Rates of abuse and diversion of ER and IR opioid formulations were compared using data from four surveillance programs in the Researched Abuse, Diversion and Addiction Related Surveillance (RADARS®) System. Data were evaluated from 2009 through 2015, and Poisson regression used to compare IR and ER opioid cases over time. Results: From 2009 to 2015, IR opioids were prescribed at a rate 12 to 16 times higher than ER. In the Poison Center Program, population-adjusted rates of Intentional Abuse for IR were 4.6 fold higher than ER opioids (p<0.001). In the Drug Diversion Program, population-adjusted rates of diversion were 6.1 fold higher for IR than ER opioids (p<0.001). In the Opioid Treatment Program, population-adjusted rates of endorsements for abuse were 1.6 fold higher for IR opioids than ER (p = 0.002). In the Survey of Key Informants' Patients Program, population-adjusted rates of endorsements for abuse were 1.5 fold higher for IR opioids than ER (p<0.001). Conclusions: Between 2009 and 2015, IR opioids were prescribed at a much higher rate than ER opioids. Results from four surveillance programs show population-adjusted rates of prescription opioid abuse were markedly higher for IR than ER medications. For the greatest public health benefit, future interventions to decrease prescription opioid abuse should focus on both IR and ER formulations. [ABSTRACT FROM AUTHOR]

This paper proposes an efficient frequency estimator based on Chinese Remainder Theorem for undersampled waveforms. Due to the emphasis on frequency offset recognition (i.e., frequency shift and compensation) of small-point DFT remainders, compared to estimators using large-point DFT remainders, it can achieve higher noise robustness in low signal-to-noise ratio (SNR) cases and higher accuracy in high SNR cases. Numerical results show that, by incorporating a remainder screening method and the Tsui spectrum corrector, the proposed estimator not only lowers the SNR threshold of detection, but also provides a higher accuracy than the large-point DFT estimator when the DFT size decreases to 1/90 of the latter case. [ABSTRACT FROM AUTHOR]

We present preliminary results from a method for estimating the optimal effective permittivity for reconstructing microwave-radar images. Using knowledge of how microwave-radar images are formed, we identify characteristics that are typical of good images, and define a fitness function to measure the relative image quality. We build a polynomial interpolant of the fitness function in order to identify the most likely permittivity values of the tissue. To make the estimation process more efficient, the polynomial interpolant is constructed using a locally and dimensionally adaptive sampling method that is a novel combination of stochastic collocation and polynomial chaos. Examples, using a series of simulated, experimental and patient data collected using the Tissue Sensing Adaptive Radar system, which is under development at the University of Calgary, are presented. These examples show how, using our method, accurate images can be reconstructed starting with only a broad estimate of the permittivity range. [ABSTRACT FROM AUTHOR]

Globally, billions of flying animals undergo seasonal migrations, many of which occur at night. The temporal and spatial scales at which migrations occur and our inability to directly observe these nocturnal movements makes monitoring and characterizing this critical period in migratory animals’ life cycles difficult. Remote sensing, therefore, has played an important role in our understanding of large-scale nocturnal bird migrations. Weather surveillance radar networks in Europe and North America have great potential for long-term low-cost monitoring of bird migration at scales that have previously been impossible to achieve. Such long-term monitoring, however, poses a number of challenges for the ornithological and ecological communities: how does one take advantage of this vast data resource, integrate information across multiple sensors and large spatial and temporal scales, and visually represent the data for interpretation and dissemination, considering the dynamic nature of migration? We assembled an interdisciplinary team of ecologists, meteorologists, computer scientists, and graphic designers to develop two different flow visualizations, which are interactive and open source, in order to create novel representations of broad-front nocturnal bird migration to address a primary impediment to long-term, large-scale nocturnal migration monitoring. We have applied these visualization techniques to mass bird migration events recorded by two different weather surveillance radar networks covering regions in Europe and North America. These applications show the flexibility and portability of such an approach. The visualizations provide an intuitive representation of the scale and dynamics of these complex systems, are easily accessible for a broad interest group, and are biologically insightful. Additionally, they facilitate fundamental ecological research, conservation, mitigation of human–wildlife conflicts, improvement of meteorological products, and public outreach, education, and engagement. [ABSTRACT FROM AUTHOR]

Insect pollinators such as bumblebees play a vital role in many ecosystems, so it is important to understand their foraging movements on a landscape scale. We used harmonic radar to record the natural foraging behaviour of Bombus terrestris audax workers over their entire foraging career. Every flight ever made outside the nest by four foragers was recorded. Our data reveal where the bees flew and how their behaviour changed with experience, at an unprecedented level of detail. We identified how each bee’s flights fit into two categories—which we named exploration and exploitation flights—examining the differences between the two types of flight and how their occurrence changed over the course of the bees’ foraging careers. Exploitation of learned resources takes place during efficient, straight trips, usually to a single foraging location, and is seldom combined with exploration of other areas. Exploration of the landscape typically occurs in the first few flights made by each bee, but our data show that further exploration flights can be made throughout the bee’s foraging career. Bees showed striking levels of variation in how they explored their environment, their fidelity to particular patches, ratio of exploration to exploitation, duration and frequency of their foraging bouts. One bee developed a straight route to a forage patch within four flights and followed this route exclusively for six days before abandoning it entirely for a closer location; this second location had not been visited since her first exploratory flight nine days prior. Another bee made only rare exploitation flights and continued to explore widely throughout its life; two other bees showed more frequent switches between exploration and exploitation. Our data shed light on the way bumblebees balance exploration of the environment with exploitation of resources and reveal extreme levels of variation between individuals. [ABSTRACT FROM AUTHOR]

Solar power towers produce electrical energy from sunlight at an industrial scale. Little is known about the effects of this technology on flying animals and few methods exist for automatically detecting or observing wildlife at solar towers and other tall anthropogenic structures. Smoking objects are sometimes observed co-occurring with reflected, concentrated light (“solar flux”) in the airspace around solar towers, but the identity and origins of such objects can be difficult to determine. In this observational pilot study at the world’s largest solar tower facility, we assessed the efficacy of using radar, surveillance video, and insect trapping to detect and observe animals flying near the towers. During site visits in May and September 2014, we monitored the airspace surrounding towers and observed insects, birds, and bats under a variety of environmental and operational conditions. We detected and broadly differentiated animals or objects moving through the airspace generally using radar and near solar towers using several video imaging methods. Video revealed what appeared to be mostly small insects burning in the solar flux. Also, we occasionally detected birds flying in the solar flux but could not accurately identify birds to species or the types of insects and small objects composing the vast majority of smoking targets. Insect trapping on the ground was somewhat effective at sampling smaller insects around the tower, and presence and abundance of insects in the traps generally trended with radar and video observations. Traps did not tend to sample the larger insects we sometimes observed flying in the solar flux or found dead on the ground beneath the towers. Some of the methods we tested (e.g., video surveillance) could be further assessed and potentially used to automatically detect and observe flying animals in the vicinity of solar towers to advance understanding about their effects on wildlife. [ABSTRACT FROM AUTHOR]

In the last few decades, awareness of environmental issues has increased significantly. Little has changed, however, in human activities contributing to environmental damage. Why is it so difficult for us to change our behavior in a domain that is clearly so important to the future of humanity? Here we propose and test the possibility that self-signaling, the way we view ourselves based on our past behaviors, is one of the factors contributing to the difficulty of taking environmental action. In three experiments, we show that previous self-interested thoughts or behaviors serve as important signals that hinder the likelihood of acting in line with an individual’s reported concern for the environment. This study not only helps explain the gap between environmental awareness and action, but also suggests alternative strategies for policymakers and environmental agencies to promote proenvironmental behavior. [ABSTRACT FROM AUTHOR]

It is a major challenge to search for survivors after chemical or nuclear leakage or explosions. At present, biological radar can be used to achieve this goal by detecting the survivor’s respiration signal. However, owing to the random posture of an injured person at a rescue site, the radar wave may directly irradiate the person’s head or feet, in which it is difficult to detect the respiration signal. This paper describes a multichannel-based antenna array technology, which forms an omnidirectional detection system via 24-GHz Doppler biological radar, to address the random positioning relative to the antenna of an object to be detected. Furthermore, since the survivors often have random body movement such as struggling and twitching, the slight movements of the body caused by breathing are obscured by these movements. Therefore, a method is proposed to identify random human-body movement by utilizing multichannel information to calculate the background variance of the environment in combination with a constant-false-alarm-rate detector. The conducted outdoor experiments indicate that the system can realize the omnidirectional detection of random human-body movement and distinguish body movement from environmental interference such as movement of leaves and grass. The methods proposed in this paper will be a promising way to search for survivors outdoors. [ABSTRACT FROM AUTHOR]

Despite the large number of studies that have examined the acute effects of different warm up modalities (WU) on physical performance, none of them have documented the time course of potential performance recovery in tennis players. The aim of this study was twofold: (a) to analyze and compare the acute effects of two different WU modalities (traditional WU [TWU] and dynamic WU [DWU]) on physical performance (i.e., CMJ, sprint, serve speed and accuracy) in elite junior players, as well as (b) to monitor the time course of any WU-induced changes after 30 and 60 min of simulated match-play. Twelve junior elite players completed both WUs modalities (TWU and DWU) in a counterbalanced order on separate days. In each experimental session, counter movement jump (CMJ), 20-m sprint, tennis serve speed and accuracy tests were performed before (immediately after TWU or DWU) during (30 min) and after 60 min of a simulated match play. Measures were compared via four factorial (WU intervention and time) repeated measures ANOVAs. There were main effects of WU (TWU and DWU) throughout the time for all the variables analysed. The results indicate that DWU routine led to significantly faster 20 m sprint times and higher CMJs as well as faster and more accurate tennis serves at both post warm-up and 30 min match-play testing moments in comparison with the scores reported by the TWU routine (p < 0.05; positive effects with a probability of >75–99%). No significant intergroup differences were found at 60-min match-play testing moment in any variable (except for the 20 m sprint). Therefore, the findings of this study recommend for optimal performance in these elite tennis players, DWU routines should be performed prior to formal training and competition rather than TWU routines. [ABSTRACT FROM AUTHOR]