Flexible Planar Monopole Built-in GIS PD Sensor Based on Meandering Technology.

To address the problem of low space utilization of existing rigid Ultra-High Frequency (UHF) sensors for partial discharge (PD) in Gas-Insulated Switchgears (GIS) and the problem of disrupting the electric field distribution inside the GIS. This paper draws on the idea of flexible wearable antennas and introduces planar monopole antennas commonly used in the communication field as GIS PD detection sensors and carried out research on flexible planar monopole sensing technology built into GIS PD. The VSWR of monopole antenna in the UHF low band is optimized by the meandering technique. The size of the designed flexible antenna is 142 mm × 195 mm × 0.28 mm. The simulation and physical test results show that the improved monopole antenna with meandering technology has a VSWR of ≤2 in the frequency bands 570 MHz-830 MHz, 1.38 GHz-1.8 GHz, and 2.2 GHz-2.76 GHz when the bending radius is 0 mm, 200 mm, and 400 mm, respectively. The VSWR in the frequency band 450 MHz-3 GHz is ≤5. A 220 kV GIS PD detection platform was built to test the performance of the designed antenna, and the results showed that the antenna could detect the PD signal after bending deformation with a high Signal Noise Ratio (SNR).

How to improve automated external defibrillator placement for out-of-hospital cardiac arrests: A case study.

INTRODUCTION: In out-of-hospital cardiac arrests (OHCAs), the use of an automatic external defibrillator (AED) by a bystander remains low, as AEDs may be misplaced with respect to the locations of OHCAs. As the distribution of historical OHCAs is potentially predictive of future OHCA locations, the purpose of this study is to assess AED positioning with regard to past locations of OHCAs, in order to improve the efficiency of public access defibrillation programs. METHODS: This is a retrospective observational study from 2014 to 2018. The locations of historical OHCAs and AEDs were loaded into a geodata processing tool. Median distances between AEDs were collected, as well as the number and rates of OHCAs covered (distance of <100 meters from the nearest AED). Areas with high densities of uncovered OHCAs (hotspots) were identified in order to propose the placement of additional AEDs. Areas over-covered by AEDs (overlays) were also identified in order to propose the relocation of overlapping AEDs. RESULTS: There were 2,971 OHCA, 79.3% of which occurred at home, and 633 AEDs included in the study. The global coverage rate was 7.5%. OHCAs occurring at home had a coverage rate of 4.5%. Forty hotspots were identified, requiring the same number of additional AEDs. The addition of these would increase the coverage from 7.5% to 17.6%. Regarding AED overlays, 17 AEDs were found to be relocatable without reducing the AED coverage of historical OHCAs. DISCUSSION: This study confirms that geodata tools can assess AED locations and increase the efficiency of their placement. Historical hotspots and AED overlays should be considered, with the aim of efficiently relocating or adding AEDs. At-home OHCAs should become a priority target for future public access defibrillation programs as they represent the majority of OHCAs but have the lowest AED coverage rates.

An improved method using adaptive smoothing for GNSS tomographic imaging of ionosphere.

Global navigation satellite system (GNSS) is a well-established sensors in the recent ionosphere research. By comparing with classical meteorological equipments, the GNSS application can obtain more reliable and precious ionospheric total electron content (TEC) result. However, the most used GNSS ionospheric tomography technique is sensitive to a priori information due to the sparse and non-uniform distribution of GNSS stations. In this paper, we propose an improved method based on adaptive Laplacian smoothing and algebraic reconstruction technique (ALS-ART). Compared with traditional constant constraints, this method is less dependent on a priori information and adaptive smoothing constraints is closer to the actual situation. Tomography experiments using simulated data show that reconstruction accuracy of ionospheric electron density using ALS-ART method is significantly improved. We also use the method to do the analysis of real observation data and compare the tomography results with ionosonde observation data. The results demonstrate the superiority and reliability of the proposed method compared to traditional constant constraints method which will further improve the capability of obtaining precious ionosphere TEC by using GNSS.

The estimation of non-irrigated crop area and production using the regression analysis approach: A case study of Bursa Region (Turkey) in the mid-nineteenth century.

Agricultural land cover and its changing extent are directly related to human activities, which have an adverse impact on the environment and ecosystems. The historical knowledge of crop production and its cultivation area is a key element. Such data provide a base for monitoring and mapping spatio-temporal changes in agricultural land cover/use, which is of great significance to examine its impacts on environmental systems. Historical maps and related data obtained from historical archives can be effectively used for reconstruction purposes through using sample data from ground observations, government inventories, or other historical sources. This study considered historical population and cropland survey data obtained from Ottoman Archives and cropland suitability map, accessibility, and geophysical attributes as ancillary data to estimate non-irrigated crop production and its corresponding cultivation area in the 1840s Bursa Region, Turkey. We used the regression analysis approach to estimate agricultural land area and grain production for the unknown data points in the study region. We provide the spatial distribution of production and its cultivation area based on the estimates of regression models. The reconstruction can be used in line with future historical research aiming to model landscape, climate, and ecosystems to assess the impact of human activities on the environmental systems in preindustrial times in the Bursa Region context.

Comparison of Activity Monitors Accuracy in Assessing Intermittent Outdoor Walking.

PURPOSE: This study aimed to determine and compare the accuracy of different activity monitors in assessing intermittent outdoor walking in both healthy and clinical populations through the development and validation of processing methodologies. METHODS: In study 1, an automated algorithm was implemented and tested for the detection of short (≤1 min) walking and stopping bouts during prescribed walking protocols performed by healthy subjects in environments with low and high levels of obstruction. The following parameters obtained from activity monitors were tested, with different recording epochs0.1s/0.033s/1s/3s/10s and wearing locationsscapula/hip/wrist/ankle: GlobalSat DG100 (GS) and Qstarz BT-Q1000XT/-Q1000eX (QS) speed; ActiGraph wGT3X+ (AG) vector magnitude (VM) raw data, VM counts, and steps; and StepWatch3 (SW) steps. Furthermore, linear mixed models were developed to estimate walking speeds and distances from the monitors parameters. Study 2 validated the performance of the activity monitors and processing methodologies in a clinical population showing profile of intermittent walking due to functional limitations during outdoor walking sessions. RESULTS: In study 1, GS1s, scapula, QS1s, scapula/wrist speed, and AG0.033s, hip VM raw data provided the highest bout detection rates (>96.7%) and the lowest root mean square errors in speed (≤0.4 km·h-1) and distance (<18 m) estimation. Using SW3s, ankle steps, the root mean square error for walking/stopping duration estimation reached 13.6 min using proprietary software and 0.98 min using our algorithm (total recording duration, 282 min). In study 2, using AG0.033s, hip VM raw data, the bout detection rate (95% confidence interval) reached 100% (99%-100%), and the mean (SD) absolute percentage errors in speed and distance estimation were 9% (6.6%) and 12.5% (7.9%), respectively. CONCLUSIONS: GPS receivers and AG demonstrated high performance in assessing intermittent outdoor walking in both healthy and clinical populations.

Landscape Genetics of Plants: Challenges and Opportunities.

Dispersal is one of the most important but least understood processes in plant ecology and evolutionary biology. Dispersal of seeds maintains and establishes populations, and pollen and seed dispersal are responsible for gene flow within and among populations. Traditional views of dispersal and gene flow assume models that are governed solely by geographic distance and do not account for variation in dispersal vector behavior in response to heterogenous landscapes. Landscape genetics integrates population genetics with Geographic Information Systems (GIS) to evaluate the effects of landscape features on gene flow patterns (effective dispersal). Surprisingly, relatively few landscape genetic studies have been conducted on plants. Plants present advantages because their populations are stationary, allowing more reliable estimates of the effects of landscape features on effective dispersal rates. On the other hand, plant dispersal is intrinsically complex because it depends on the habitat preferences of the plant and its pollen and seed dispersal vectors. We discuss strategies to assess the separate contributions of pollen and seed movement to effective dispersal and to delineate the effects of plant habitat quality from those of landscape features that affect vector behavior. Preliminary analyses of seed dispersal for three species indicate that isolation by landscape resistance is a better predictor of the rates and patterns of dispersal than geographic distance. Rates of effective dispersal are lower in areas of high plant habitat quality, which may be due to the effects of the shape of the dispersal kernel or to movement behaviors of biotic vectors. Landscape genetic studies in plants have the potential to provide novel insights into the process of gene flow among populations and to improve our understanding of the behavior of biotic and abiotic dispersal vectors in response to heterogeneous landscapes.

Universal scaling laws of collective human flow patterns in urban regions.

Detail observation of human locations became available recently by the development of information technology such as mobile phones with GPS (Global Positioning System). We analyzed temporal changes of global human flow patterns in urban regions based on mobile phones' GPS data in 9 large cities in Japan. By applying a new concept of drainage basins in analogous to river flow patterns, we discovered several universal scaling relations. These include, the number of moving people in a drainage basin of diameter L is proportional to [Formula: see text] in the morning rush hour, which is surprisingly different from reasonable intuition of proportionality to the 2 dimensional area, [Formula: see text]. We show that this unexpected 3 dimensional feature is related to the strong attraction of the city center to become a 3 dimensional structure due skyscrapers.

Improvement of GPS-attached Pocket PM2.5 Measuring Device for Personal Exposure Assessment.

Assessment of personal exposure to particulate matter with an aerodynamic diameter less than or 2.5 µm (PM2.5) is necessary to study the association between PM exposure and health risk. Development of a personal PM2.5 sensor or device is required for the evaluation of individual exposure level. In this study, we aimed to develop a small-sized, lightweight sensor with a global positioning system (GPS) attached that can measure PM2.5 and PM10 every second to assess continuous personal exposure levels. The participants in this study were apparently healthy housewives (n = 15) and university female teaching staff (n = 15) who live in a high PM2.5 area, Yangon, Myanmar. The average PM2.5 exposure levels during 24 h were 16.1 ± 10.0 µg/m3 in the housewives and 15.8 ± 4.0 µg/m3 in the university female teaching staff. The university female teaching staff showed high exposure concentrations during commuting hours, and had stable, relatively low concentrations at work, whereas the housewives showed short-term high exposure peaks due to differences in their lifestyles. This is the first study to show that a GPS-attached standalone PM2.5 and PM10 Sensor [PRO] can be successfully used for mobile sensing, easy use, continuous measurement, and rapid data analysis.

Bayesian hierarchical spatial count modeling of taxi speeding events based on GPS trajectory data.

Speeding behavior, especially serious speeding, is more common in taxi driver than other driving population due to their high exposure under traffic environment, which increases the risk of being involved in crashes. In order to prevent the taxi and other road users from speed-related crash, previous studies have revealed contributors of demographic and driving operation affecting taxi speeding frequency. However, researches regarding road factors, and spatial effect are typically rare. For this sake, the current study explores the contributions of 10 types of road characteristics and two kinds of spatial effects (spatial correlation and spatial heterogeneity) on taxi total speeding and serious speeding frequency. Taxi GPS trajectory data in a Chinese metropolis were used to identify speeding event. The study then established four kinds of Bayesian hierarchical count models base on Poisson and negative binominal distribution to estimate the contributor impacts, respectively. Results show that Bayesian hierarchical spatial Poisson log-linear model is optimum for fitting both total and serious speeding frequency. For the analysis, it is found that drivers are more likely to commit speeding on long multilane road with median strip, and road with non-motorized vehicle lane, bus-only lane and viaduct or road tunnel. Roads with low speed limit, and work zone are associated with increasing speeding as well. In terms of serious speeding, bus-only lane is not a contributor, while road speed camera number and one-way organization are significantly positive to the speeding frequency. Furthermore, it reveals that two spatial effects significantly increase the occurrence of speeding events; the impact of spatial heterogeneity is more critical.

A novel NIR-image segmentation method for the precise estimation of above-ground biomass in rice crops.

Traditional methods to measure spatio-temporal variations in biomass rely on a labor-intensive destructive sampling of the crop. In this paper, we present a high-throughput phenotyping approach for the estimation of Above-Ground Biomass Dynamics (AGBD) using an unmanned aerial system. Multispectral imagery was acquired and processed by using the proposed segmentation method called GFKuts, that optimally labels the plot canopy based on a Gaussian mixture model, a Montecarlo based K-means, and a guided image filtering. Accurate plot segmentation results enabled the extraction of several canopy features associated with biomass yield. Machine learning algorithms were trained to estimate the AGBD according to the growth stages of the crop and the physiological response of two rice genotypes under lowland and upland production systems. Results report AGBD estimation correlations with an average of r = 0.95 and R2 = 0.91 according to the experimental data. We compared our segmentation method against a traditional technique based on clustering. A comprehensive improvement of 13% in the biomass correlation was obtained thanks to the segmentation method proposed herein.

Cell Phone Activity in Categories of Places and Associations With Growth in Cases of COVID-19 in the US.

Importance: It is unknown how well cell phone location data portray social distancing strategies or if they are associated with the incidence of coronavirus disease 2019 (COVID-19) cases in a particular geographical area. Objective: To determine if cell phone location data are associated with the rate of change in new COVID-19 cases by county across the US. Design, Setting, and Participants: This cohort study incorporated publicly available county-level daily COVID-19 case data from January 22, 2020, to May 11, 2020, and county-level daily cell phone location data made publicly available by Google. It examined the daily cases of COVID-19 per capita and daily estimates of cell phone activity compared with the baseline (where baseline was defined as the median value for that day of the week from a 5-week period between January 3 and February 6, 2020). All days and counties with available data after the initiation of stay-at-home orders for each state were included. Exposures: The primary exposure was cell phone activity compared with baseline for each day and each county in different categories of place. Main Outcomes and Measures: The primary outcome was the percentage change in COVID-19 cases 5 days from the exposure date. Results: Between 949 and 2740 US counties and between 22 124 and 83 745 daily observations were studied depending on the availability of cell phone data for that county and day. Marked changes in cell phone activity occurred around the time stay-at-home orders were issued by various states. Counties with higher per-capita cases (per 100 000 population) showed greater reductions in cell phone activity at the workplace (ß, -0.002; 95% CI, -0.003 to -0.001; P < 0.001), areas classified as retail (ß, -0.008; 95% CI, -0.011 to -0.005; P < 0.001) and grocery stores (ß, -0.006; 95% CI, -0.007 to -0.004; P < 0.001), and transit stations (ß, -0.003, 95% CI, -0.005 to -0.002; P < 0.001), and greater increase in activity at the place of residence (ß, 0.002; 95% CI, 0.001-0.002; P < 0.001). Adjusting for county-level and state-level characteristics, counties with the greatest decline in workplace activity, transit stations, and retail activity and the greatest increases in time spent at residential places had lower percentage growth in cases at 5, 10, and 15 days. For example, counties in the lowest quartile of retail activity had a 45.5% lower growth in cases at 15 days compared with the highest quartile (SD, 37.4%-53.5%; P < .001). Conclusions and Relevance: Our findings support the hypothesis that greater reductions in cell phone activity in the workplace and retail locations, and greater increases in activity at the residence, are associated with lesser growth in COVID-19 cases. These data provide support for the value of monitoring cell phone location data to anticipate future trends of the pandemic.

CONGENITAL SYPHILIS IN THE PARAÍBA VALLEY USING A SPATIAL APPROACH.

OBJECTIVE: To compare spatial patterns of congenital syphilis (CS) with those of socioeconomic and medical variables in Paraíba Valley, São Paulo, between 2012 and 2016. METHODS: Ecological and exploratory study developed using spatial analysis tools, with information on CS cases obtained from official data reports. Rates were found for CS cases per 1,000 live births, number of family health teams and pediatricians available in the health system per 100,000 inhabitants, and social vulnerability index values. Thematic maps were constructed with these variables and compared using TerraView 4.2.2 software. Estimated global Moran (IM) indexes were calculated. In order to detect areas with priority attention regarding the incidence of CS, BoxMaps were developed. The Spearman correlation was estimated for the variable values and compared using the Kruskal-Wallis test. P <0.05 was significant. RESULTS: 144,613 births and 870 CS cases (6.04/1000 live births) occurred during the study period. The average value of CS rates per municipality was 4.0±4.1, (0.0-17.6/1000 live births). Higher CS rates occurred in municipalities of the Upper Vale do Paraíba, contrary to the proportions of pediatricians who were in the far east of the region. The thematic maps of the variables presented a mosaic aspect, which characterized the random distribution of the variables. The IM were not significant. No significant correlation was found between the variables. The BoxMap identified eight municipalities with high CS rates. CONCLUSIONS: Even though it was not possible to identify a spatial pattern of CS rates, it was shown that eight municipalities deserve the attention of city managers.

Sensitivity, reliability and construct validity of GPS and accelerometers for quantifying peak periods of rugby competition.

Training prescription and monitoring of team-sport athletes rely on accurate quantification of player movement. Our aim was to determine the sensitivity, reliability and construct validity of measures derived from a wearable device incorporating Global Positioning System (GPS) and accelerometer technology to quantify the peak periods of rugby competition. Match movement data were collected from 30 elite and 30 sub-elite rugby union players across respective competitive seasons. Accelerometer and GPS measures were analysed using a rolling average to identify peak movement for epochs ranging from 5 to 600 seconds. General linear mixed modelling was used to quantify the effects of playing position and match-half on the peak movement and variabilities within and between players represented reliability of each measure. Mean positional differences and match-half changes were assessed via standardisation and magnitude-based decisions. Sensitivity of measures was quantified via evaluation of ("signal") and typical error of measurement ("noise"). GPS and accelerometer measures had poor sensitivity for quantifying peak movement across all epochs and both levels of rugby union competition (noise 4× to 5× the signal). All measures displayed correspondingly low reliability across most epochs and both levels of competition (ICC<0.50). Construct validity was evident in mean differences between playing positions and match halves that were consistent with expected activity profiles in rugby union. However, it was clear from the pattern of differences across epoch durations and levels of competition that GPS and accelerometer measures provided different information about player movement. The poor sensitivity and low reliability of GPS and accelerometer measures of peak movement imply that rugby union players need to be monitored across many matches to obtain adequate precision for assessing individuals. Although all measures displayed construct validity, accelerometers provided meaningful information additional to that of GPS. We recommend using accelerometers alongside GPS to monitor and prescribe match respresentative training.

Validity of Real-Time Ultra-wideband Global Navigation Satellite System Data Generated by a Wearable Microtechnology Unit.

Johnston, RD, Hewitt, A, and Duthie, G. Validity of real-time ultra-wideband global navigation satellite system data generated by a wearable microtechnology unit. J Strength Cond Res 34(7): 2071-2075, 2020-This study aimed to determine the validity of real-time ultra-wideband data generated by a wearable microtechnology unit during rugby league training sessions using a repeated-measures crossover study. Twenty-four semiprofessional rugby league players wore a commercially available microtechnology device (StatSports Apex, Newry, Northern Ireland) during 10 training sessions. Total distance; moderate-speed running (3.6-4.9 m·s); high-speed running (5.0-6.9 m·s); very high-speed running (≥7 m·s); maximum velocity (m·s); the number of high-intensity accelerations (≥2.78 m·s) and decelerations (≥-2.78 m·s); dynamic stress load (AU); and high metabolic load distance (m) were recorded in real time through an Apex beacon over a secured wireless network before being exported to a csv file at the end of the session. The data were then downloaded to a computer after event. To determine the validity of the real-time data, they were compared with the postevent downloaded data using coefficient of variation and Pearson's correlation coefficient. There was almost perfect agreement between real-time and postevent downloaded data for all variables reported. The overall bias effect size scores were all trivial, ranging from 0.00 for total distance and high-speed running up to -0.12 for maximal velocity; Pearson's correlations were either perfect or nearly perfect (r = 0.98-1.00). Irrespective of the movement speed, the data collected by these devices in real time show excellent levels of agreement with postevent downloaded data.

Intra- and Inter-Device Reliability of the Change-of-Direction Angles Using a Smartphone Application for Sailing.

The smartphone has recently become a commonly used tool for satellite navigation. The reliability of built-in smartphone Global Navigation Satellite Systems receivers was analyzed in terms of distance, velocity/speed and acceleration, but little is known about the accuracy of angular change-of-direction measurements. This might be important in the assessment of usefulness in sailing navigation. The aim of the study was to assess the reliability of the calculated change-of-direction angles, measured with the built-in smartphone Global Navigation Satellite Systems technology using the SoniSailing application. One individual completed five trials in an urban open space (sports ground), wearing six identical Samsung Galaxy J5 smartphones. The trials simulated an upwind sailing race (127 m), including two consecutive courses at 45° angle to the line of the tacking leg. To assess the reliability of change-of-direction angle measures the intra- and inter-device correlation coefficients were calculated. The analysis showed excellent reliability in change-of-direction angle measures-no less than 0.95 and 0.93 in case of correlation coefficients for inter- and intra-device, respectively. Correlation coefficients for average measures were no less than 0.99 in both cases. The study confirmed high reliability of the calculated change-of-direction angles, measured with the Global Navigation Satellite Systems technology using the SoniSailing application for smartphones.

Are safety and performance affected by navigation system display size, environmental illumination, and gender when driving in both urban and rural areas?

Driving with the aid of a navigation system could distract drivers. A high level of distraction influences driver performance and safety, leading to a possible increase in road crashes. The illumination level and size of the GPS display may influence the duration and frequency of a driver's glances, which in turn may affect driver distraction. In a simulated driving experiment requiring the use of a GPS, the GPS's display size and illumination level were examined, in light of the driver's experience and gender, to understand their effects on the performance and safety of young drivers on roads in urban and rural areas. Twenty young subjects, male and female between the ages of 18 and 29 years, participated in this experiment. Driving safety was evaluated by lateral control (number of pavement and lane line crossings), number of crashes, number of near misses, and the total time out of the lane. Driving performance was evaluated by the number of navigational errors, the total time making navigational errors, number of times the speed limit was exceeded and total amount of time speeding. These measures were analyzed using a repeated measures analysis of variance (ANOVA) model. Furthermore, the effects of the GPS display, considering the driving experience, were investigated with a simple linear regression. Findings suggest that driving with a small GPS display in an urban area leads to more navigational errors than driving with a large GPS display. Furthermore, more speed limit violations tend to occur in rural areas in the daytime than at night. Moreover, in urban areas, male drivers tend to have the highest number of crashes during the daytime. Furthermore, in rural areas, males tend to violate the speed limit more often and for longer periods of time during the daytime than at night and more than females do. Additionally, when navigating with a GPS system, young experienced drivers drive safer than inexperience drivers. The findings are of interest to designers and transportation researchers concerned with improving GPSs to enhance driving safety and performance.

The applicability of recreation-grade GNSS receiver (GPS watch, Suunto Ambit Peak 3) in a forested and an open area compared to a mapping-grade receiver (Trimble Juno T41).

Due to developments in global navigation satellite systems (GNSS) and the miniaturization of their components, the usage of Global Positioning System (GPS) is no longer restricted to professional applications, but has become available in various consumer type devices, such as wristwatches. These commercial devices, however, were primarily designed for tracking activities in predominately urban settings and their accuracy has not been tested in forested areas. In this study, we present an assessment of the positional accuracy of a GPS watch (Ambit Peak 3, Suunto, Finland) under different forest cover types, seasons and meteorological conditions within the Whitehall Forest GPS Test Site located in Athens, Georgia, USA. As a standard of comparison, the performance of the GPS watch measurements was juxtaposed to that of a mapping-grade receiver (Juno T41, Trimble Inc., USA). In this study, we analyzed the differences between the determined and control positions using root-mean-square-error (RMSE), along with the distribution of observed positions through the standard deviational ellipse. The results suggest that the seasonal variations contributed to a statistically significant impact on the RMSE values for the GPS watch. However, there were no statistically significant differences in horizontal position accuracy by forest cover-type when using the GPS watch. Furthermore, no significant differences were found in horizontal position accuracy during the leaf-off period between the RMSE values for the GPS watch and those of the mapping-grade receiver. Lastly, the positional accuracies for both types of receivers were found to be weakly, but significantly correlated with fluctuations in air temperature and absolute humidity.