Global Positioning System Research Articles

Environmental Suitability Predictions for the Distribution and Potential Cultivation of Artemisia afra in South Africa

Cultivation is advocated as a solution for the sustainable exploitation of medicinal plants. Understanding environmental factors influencing plant species distribution will eliminate the indiscriminate introduction of medicinal plants to inappropriate cultivation regions. This study investigated environmental conditions for the distribution of Artemisia afra and mapped out potential areas for its cultivation in South Africa. Soil samples were collected for analysis in the Free State Province in South Africa. To identify suitable environmental conditions for the natural distribution of A. afra, the South African National Botanical Institute database and physically collected Global Positioning System points were used in a maximum entropy model. Monthly long-term average interpolated weather surfaces were used to estimate the effect of climate change on future climate suitability for A. afra distribution. Sixty-one percent of soil samples from different A. afra populations were clay loam soils with a slightly acidic to neutral pH. The carbon source utilization, Shannon Weaver Index, and species richness were positively correlated with one group of fourteen soil samples, and species evenness was positively correlated with the second group, consisting of four samples. Climate change will only affect the distribution of A. afra in the very long term. The current study provides critical information for identifying suitable cultivation areas for A. afra while supporting conservation efforts from an ecological point of view.

Near Real Time Crop Health Status Monitoring and Mapping using Sentinel Satellite Image in Menjar Shenkora District, Ethiopia

Agricultural monitoring systems must provide timely and standardized information on crop production, status, and yield, from sub-regional to national scales. Accurate monitoring and mapping of vegetation condition and health are vital for managing crops, assessing damage, and predicting yields. Crop health monitoring is one of the important items for tracking the general health status of any crop. In this regard, remote sensing and GIS play a crucial role for monitoring crop health, providing current information that traditional methods like field surveys and sampling questionnaires struggle to obtain. Effective cropland mapping techniques are essential for regular crop monitoring. This type of monitoring demands frequents continuous data with high time and space resolution. Near real-time crop monitoring uses technologies like the Sentinel-2 satellite mission, offering a consistent 5-day revisit cycle and freely accessible data. This opens new doors for delivering timely updates and monitoring parcel-based crop health and conditions in real-time. Therefore, this study used satellite images, Global Positioning System (GPS) collected data, and parcel-based socioeconomic data. GPS and socioeconomic data were employed to validate the satellite-based near real-time crop monitoring results. Vegetation Condition Index (VCI) and the Normalized Difference Vegetation Index (NDVI) were used to evaluate crop health at different stages of the growing season and to generate time series data for crop phenology respectively. NDVI time series data was used to generate crop phenology information for four main crops: Teff, wheat, onion, and sorghum. The crop type maps for these crops at the study sites were validated with an overall accuracy of 79.26% and a Kappa value of 0.737. Additionally, the results from the current research and the field-collected data were consistent in providing information about the onset, greening, maturity, and senescence dates of each crop. These findings highlight the effectiveness of the satellite-based system for real-time agricultural crop monitoring using Sentinel-2 observations across various sites and time frames. Moreover, it helps to fill the gaps of traditional crop monitoring methods with those based on satellite technology. This system is particularly valuable for early warning purpose in areas like the current study site, where conventional crop monitoring methods and inputs are limited.

A reinforcement learning model for autonomous vehicles with realistic car simulation in urban using unity

Abstract Simulator training with reinforcement learning (RL) for autonomous vehicles (AVs) offers advantages over supervised learning. However, transferring the learned behaviours to the real world is a challenging task due to the inconsistencies between the data captured by the vehicle's sensors in the simulated environment and the real world. Additionally, some of the sensors that the AVs rely on are sensitive to weather and lighting conditions. Our proposed model addresses the challenges of sensor data disparity and environmental variation. It utilizes three sensing components which are radio detection and ranging (RADAR), inertial measurement units (IMUs), and global positioning systems (GPSs) to overcome the addressed drawbacks. The proposed model incorporates a carefully designed reward system and prioritizes computational efficiency by using fewer number of sensors and ensures safe and efficient driving. The chosen sensors enable easier knowledge transfer from the simulator to the real-world due to their consistent data representation. The model leverages the Unity engine and ML agent to train AVs for both urban and highway environments. The experimental results show that our suggested model effectively trained AVs to navigate through complex urban areas without collisions while keeping them in their lanes. The demonstration video is provided in the following link: https://youtu.be/YCOjli7lrCM

Integrating accelerometry, GPS, GIS and molecular data to investigate mechanistic pathways of the urban environmental exposome and cognitive outcomes in older adults: a longitudinal study protocol

IntroductionMaintaining cognitive health in later life is a global priority. Encouraging individuals to make health behaviour changes, such as regular physical activity, and providing supportive urban environments can help maintain...

Evaluation of the regional ionosphere using final, ultra-rapid, and rapid ionosphere products

Abstract The ionosphere plays a critical role in radio wave propagation, impacting satellite-based communication and navigation systems. This study evaluates near-real-time ionosphere maps (NRTIMs) derived from dual-frequency Global Positioning System (GPS) observations and validates them against established ionosphere models. Using dual-frequency Global Navigation Satellite System (GNSS) technology, the research mitigates ionospheric errors by measuring phase delays at L1 and L2 frequencies. Global ionosphere maps (GIMs) generated by the International GNSS Service (IGS) provide essential ionospheric corrections. Our approach combines accurate GPS observations with regional modeling to enhance GNSS positioning accuracy. The results demonstrate the effectiveness of the developed MATLAB algorithm in estimating ionospheric delays, showing strong convergence with GIMs. The results show a significant convergence between the Regional Ionosphere Modeling of RIM, IGS (Final Ionosphere Product), IGU (Ultra Rapid Ionosphere Product), and IGR (Rapid Ionosphere Product), as the highest average values during the 77th DOY of winter 2020 at the CPVG station were 14.753 TECU for RIM and 14.736, 14.7373 and 14.731 TECU at the CPVG station for IGS, IGU, and IGR while the average was for RIM, IGS, IGU, and IGR are respectively lower, with the lowest average values during the 190th DOY of autumn 2020 at station IZMI with a value of 3.5472 TECU for RIM, 3.5541, 3.5421 and 3.5624 TECU at IZMI station for IGS, IGU, and IGR respectively. By achieving strong agreement with existing GIMs and providing high-frequency results, the algorithm improves the reliability of GPS systems by effectively monitoring envelope disturbances. Ionic and dilute.

Use of Accelerometry and Global Positioning System (GPS) to Describe Children's Park-Based Physical Activity Among Racial and Ethnic Minority Youth.

Parks are one component of the built environment to promote regular physical activity (PA) among youth. This study investigated differences in park-based PA among youth based on demographics and park features in racially or ethnically diverse communities. In 2017-2018, parks were selected in majority Asian (n = 3), Latino (n = 5), and Black (n = 4) neighborhoods in North Carolina (n = 6) and New York (n = 6). Researchers recruited parents/caregivers of 5-10-year-olds to participate. Children wore an Actigraph GT3 + waist accelerometer and a QStarz GPS unit and were instructed to play normally for at least 15min. Evenson cut-points were used to classify PA levels as sedentary, light, moderate, and vigorous. Chi-squared tests and non-parametric Kruskal-Wallis tests were used to examine differences in PA intensity minutes (sedentary, light, moderate-to-vigorous) across study location and demographic variables. Youth participated from NY (n = 200) and NC (n = 157). Overall, most park-based PA was spent in light intensity (59.9%), followed by moderate-to-vigorous intensity (32.4%). Females, compared to male participants, spent more time in sedentary behavior (9.0%, 6.1%) and less time in moderate-to-vigorous PA (26.6%, 38.1%). Participants who identified as Black (32.9% MVPA), Latino (35.8%), and Other (39.8%) spent higher percentages of time in moderate-to-vigorous PA than Asian (26.6%) and non-Hispanic White (21.3%) participants. The highest proportion of moderate-to-vigorous PA occurred on swing sets (46%) and basketball courts (45%). Racial and ethnic, sex, and activity area differences in park-based PA indicate that diverse youth use parks uniquely; these factors should be considered in designing parks for various ages and backgrounds.

Red fox home ranges, activity patterns, and resource selection on an Atlantic barrier island

AbstractRelatively little is known about red fox (Vulpes vulpes) spatial ecology on barrier islands, where semi‐linear habitat distribution and aquatic barriers may affect terrestrial movements. Because red foxes often are a predator of imperiled shorebirds in these ecosystems, and predation is often managed along with other factors such as habitat limitation, this information is needed to inform effective holistic management. The goals of this study were to describe red fox spatial ecology in a barrier island ecosystem and compare these findings to the existing literature on red fox space use in other coastal settings. We used global positioning system (GPS) collar data collected from 2015–2018 from 31 red foxes to estimate sizes of home ranges and core‐use areas, describe daily activity patterns, and investigate within‐home‐range resource selection among red foxes on Fire Island, New York, USA. Twenty‐two of 31 red foxes maintained distinct home ranges throughout the monitoring period, while 9 were transient, regularly traveling through the home ranges of other red foxes and among management units across the island. Observed GPS‐collared red fox home range sizes (95% time local convex hull [t‐LoCoH] isopleths) ranged from 10 ha to 659 ha, averaging 59 ± 7 ha (SE) among resident foxes and 447 ± 46 ha among transient foxes. Core‐use areas (50% t‐LoCoH isopleths) ranged from <1 ha to 268 ha, averaging 10 ± 1 ha among resident foxes and 67 ± 27 ha among transient foxes. Hourly minimum movement rates varied across the diel cycle and among individuals, averaging 216 m/hour ± 9 m/hour, and were highest 13–22 hours after sunrise. Within‐home‐range resource selection varied among activity periods. For example, red foxes selected areas closer than expected to vegetation based on availability during the daytime and twilight hours but farther than expected from vegetation at night. We recommend vegetation management in and around shorebird nesting areas to reduce daytime resting sites and hunting cover for red foxes while improving suitability for use by nesting shorebirds. We also suggest coordination of predator management activities across agencies in this situation and in others where predators regularly cross management unit boundaries. Overall, we found that many aspects of red fox space use in the study area, such as smaller average home ranges compared to those in other ecosystems, were similar to that of red foxes in other coastal settings; additional research is needed to determine whether this holds true in other barrier island systems.

Dynamic Bidirectional Associations Between Global Positioning System Mobility and Ecological Momentary Assessment of Mood Symptoms in Mood Disorders: Prospective Cohort Study.

Although significant research has explored the digital phenotype in mood disorders, the time-lagged and bidirectional relationship between mood and global positioning system (GPS) mobility remains relatively unexplored. Leveraging the widespread use of smartphones, we examined correlations between mood and behavioral changes, which could inform future scalable interventions and personalized mental health monitoring. This study aims to investigate the bidirectional time lag relationships between passive GPS data and active ecological momentary assessment (EMA) data collected via smartphone app technology. Between March 2020 and May 2022, we recruited 45 participants (mean age 42.3 years, SD 12.1 years) who were followed up for 6 months: 35 individuals diagnosed with mood disorders referred by psychiatrists and 10 healthy control participants. This resulted in a total of 5248 person-days of data. Over 6 months, we collected 2 types of smartphone data: passive data on movement patterns with nearly 100,000 GPS data points per individual and active data through EMA capturing daily mood levels, including fatigue, irritability, depressed, and manic mood. Our study is limited to Android users due to operating system constraints. Our findings revealed a significant negative correlation between normalized entropy (r=-0.353; P=.04) and weekly depressed mood as well as between location variance (r=-0.364; P=.03) and depressed mood. In participants with mood disorders, we observed bidirectional time-lagged associations. Specifically, changes in homestay were positively associated with fatigue (β=0.256; P=.03), depressed mood (β=0.235; P=.01), and irritability (β=0.149; P=.03). A decrease in location variance was significantly associated with higher depressed mood the following day (β=-0.015; P=.009). Conversely, an increase in depressed mood was significantly associated with reduced location variance the next day (β=-0.869; P<.001). These findings suggest a dynamic interplay between mood symptoms and mobility patterns. This study demonstrates the potential of utilizing active EMA data to assess mood levels and passive GPS data to analyze mobility behaviors, with implications for managing disease progression in patients. Monitoring location variance and homestay can provide valuable insights into this process. The daily use of smartphones has proven to be a convenient method for monitoring patients' conditions. Interventions should prioritize promoting physical movement while discouraging prolonged periods of staying at home.

The Influence of Lower-Limb Strength and Power on the Speed and Heat Results of Professional Brazilian Surfers.

To correlate speed and heat scores with anthropometric variables and lower-limb strength and power in professional surfers. A total of 19 men participated in simulated competitions on different days. All surfed waves were scored, and each athlete's best 2 were used for their total heat score. Speed values were extracted by global positioning system and adjusted by Z score. Squat jump, countermovement jump, and drop jump were executed. Anthropometric variables and 1-repetition maximum (1RM) in the half squat were measured. Pearson product-moment correlation was used to analyze the relationships. Height had a significant (P < .05) inverse association with speed indicators (r = -.36 to - .68), and body mass index had a moderate association with maximum wave speed of the highest score. Significant correlations with moderate to large magnitudes were found between maximum speed and vertical jumps (r = .46 to .56), average speed and vertical jumps (r = .48 to .59), and both maximum and average speed with 1RM (r = .52-.53). Athletes' best score and total heat score showed moderate to large associations with vertical jumps and 1RM (r = .48-.64), whereas second scores were correlated with the reactive strength index of the drop jump (r = .48) and 1RM (r = .51). Shorter surfers with lower center of gravity and those with superior lower-limb strength and power achieved greater speed and higher scores. Accordingly, surf coaches may consider prescribing dynamic strength and balance training based on an athlete's profile to improve performance.

Return to Performance of a Soccer Player with an Adductor Longus Injury: A Case Report

Context: There is limited information on the quantification of external load and reconditioning programs during adductor longus injuries in soccer. Case Presentation: This case report describes a male professional soccer player (LaLiga) returning to performance following an adductor longus muscle injury during the 2022/2023 season. The player suffered the injury during a change of direction in a match. The injury was confirmed by ultrasound after 48 h, and the previously validated rehabilitation and reconditioning program was applied to the injured player. This case report has focused on the development of the on-field reconditioning program and the quantification of the load during this phase. The goal of this case report was to return the player to pre-injury loads using global positioning systems (GPS). Variables such as total distance, distances covered at different speeds and metabolic load variables were quantified during the injury process, with the aim of increasing them through training and reaching at least 75% of the game load. Therefore, objective performance criteria for making return-to-play decisions based on the use of GPS was determined. In addition, the return to play (RTP) was on the 20th day after the injury, and then four RTPs were recorded in the following 6 weeks after the injury occurred, without re-injury. Conclusions: The approach to the competition performance profile, through the quantification of the external load during the rehabilitation process of the injured player, allowed us a safe return to competition and continued competition with a 6-week follow-up.

Wolf density and predation patterns in the Canadian High Arctic

AbstractThe Arctic wolf (Canis lupus arctos) is a predator of muskoxen (Ovibos moschatus), Arctic hares (Lepus arcticus), and endangered Peary caribou (Rangifer tarandus pearyi) in the Canadian High Arctic. Although Arctic wolves potentially affect the dynamics of muskoxen and Peary caribou populations, knowledge about their abundance, distribution, and predation patterns is limited. Inuit and Inuvialuit communities value these species for sociocultural and subsistence reasons, and community members are concerned about how interactions among these species and their environment may change in a warming, unpredictable Arctic. We conducted a study from 2014–2018 of wolves in the rolling tundra of central Ellesmere Island (Fosheim Peninsula) and eastern Axel Heiberg Island. This area supported relatively high densities of muskoxen and Arctic hares, and previously supported Peary caribou, although caribou were mostly absent in the area during our study. We deployed global positioning system (GPS) radio‐collars on 10 adult wolves in 6 packs on Ellesmere and Axel Heiberg islands to describe wolf density and predation patterns. Wolves were neither nomadic nor migratory; they remained on territories year‐round, with summer densities of 2.5–8.0 adult wolves/1,000 km2 and 3.7–10.4 wolves/1,000 km2 including pups. Based on a ground search of 312 of 868 location clusters over a 340‐day period, wolves in a focal study pack killed approximately 0.12 muskoxen/day, equivalent to a predation rate of 5.5–17.0% of the estimated muskox population (older than 10 months old). This predation rate is likely sustainable given that calves and yearlings rather than reproductive adults comprised most documented kills, and that muskox populations can increase at rates up to 20%. The kill rate for this pack also implied a biomass intake deficit of 0.82–1.63 kg/wolf/day that could have been offset by each wolf consuming 115–228 Arctic hares annually. The decline of Peary caribou in the study area precluded any assessment of wolf predation influences on their population, but annual telemetry data confirming the year‐round presence of a wolf–ungulate–hare system with relatively high wolf densities suggests that apparent competition could present a challenge to Peary caribou recovery efforts.

Performance of GNSS space service for geostationary autonomous operations

Abstract The geostationary orbit (GEO) belt hosts a substantial number of high-value satellites, making the study of autonomous navigation within this area significant. Features of autonomous operations such as patrolling the GEO belt and frequent manoeuvres at a certain location make real-time positioning using the Global Navigation Satellite System (GNSS) valuable. This paper studies the performance of positioning with GNSS considering main lobe and side lobe signals at different longitudes in the GEO belt. The research delves into the visibility and Position Dilution of Precision (PDOP) across the GEO belt, analysing the performance of the Global Positioning System (GPS), GLObalnaya NAvigatsionnaya Sputnikovaya Sistema (GLONASS) in Russian, BeiDou Navigation Satellite System (BDS), Galileo Navigation Satellite System (Galileo) and multi-systems. In particular, this paper investigates the impact of asymmetric constellations of mixed GEO, Inclined Geosynchronous Orbit (IGSO) and Medium Earth Orbit (MEO) satellites. The study reveals that BDS hybrid constellation provides long-term stable signal coverage over the GEO space above North America and Atlantic Ocean, where GEO signals are more sustainable while IGSO signals have wider coverage. This advantage positions BDS favourably in terms of performance in these regions.

On the ability to study regional hydrometeorological changes using GPS and GRACE measurements

Recently, an ongoing rise in temperature for both land and ocean areas is recorded resulting from the Earth’s warming climate. As a result, droughts we observe are getting more frequent, longer and more severe, exerting sustained impacts on humans, ecosystems leading to famine, poverty, mass migration, or agricultural and economic losses. The changes in climate are successfully monitored by analyzing Total Water Storage (TWS). For years, TWS has been successfully determined using geodetic techniques, such as gravity field variations observed by the Gravity Recovery and Climate Experiment (GRACE) missions or station position changes monitored by the Global Positioning System (GPS). As well, geodetic-derived data can be applied successfully to study of hydrometeorological events. To quantify droughts characteristics at different temporal and spatial scales, we recalculate the vertical displacements to Drought Severity Indices (DSI). We find that DSI based on GPS and GRACE are positively correlated at over 80% of stations around the world, highlighting both Americas and Europe as the most correlated areas. To validate results, we compare DSI based on GPS/GRACE with the Global Land Water Storage (GLWS) hydrological model, the traditional climate indices, and temperature anomalies. We show that GPS-DSIs are strongly temporally consistent with both the Standardized Precipitation Index (SPI) and the Soil Moisture Index (SMI) climate indices at 85% of stations, indicating weakly correlated areas at mid-latitudes. We further show a high potential of geodetic data to assess drought characteristics within climate zones as well as global studies. We note that moderate conditions dominate for all climate zones, for which dry moderate conditions are observed for 40% of the months analyzed. As a result, we note warning conditions at least 52% of global stations with extreme drying DSI trends above a value of 2–3 per year. We note that the global water changes are dominated by 9 month droughts at over 72% of stations, indicating the average drought duration around 12, 14, and 15 months for GPS-, GRACE-, and GLWS-DSI, respectively. The obtained results from geodetic measurements more reliably characterize the type and phase of drought, as well as how these droughts cascade into freshwater, enabling appropriate mitigation strategies.

Machine Learning Based Localization of LoRa Mobile Wireless Nodes Using a Novel Sectorization Method

Indoor localization of wireless nodes is a relevant task for wireless sensor networks with mobile nodes using mobile robots. Despite the fact that outdoor localization is successfully performed by Global Positioning System (GPS) technology, indoor environments face several challenges due to multipath signal propagation, reflections from walls and objects, along with noise and interference. This results in the need for the development of new localization techniques. In this paper, Long-Range Wide-Area Network (LoRaWAN) technology is employed to address localization problems. A novel approach is proposed, based on the preliminary division of the room into sectors using a Received Signal Strength Indicator (RSSI) fingerprinting technique combined with machine learning (ML). Among various ML methods, the Gated Recurrent Unit (GRU) model reached the most accurate results, achieving localization accuracies of 94.54%, 91.02%, and 85.12% across three scenarios with a division into 256 sectors. Analysis of the cumulative error distribution function revealed the average localization error of 0.384 m, while the mean absolute error reached 0.246 m. These results demonstrate that the proposed sectorization method effectively mitigates the effects of noise and nonlinear signal propagation, ensuring precise localization of mobile nodes indoors.

Improved Computerized Ionospheric Tomography Based on GPS and PALSAR Data

AbstractDue to factors such as the uneven distribution of ground receiving stations and the lack of effective observation rays, Global Positioning System (GPS)‐based computerized ionospheric tomography (CIT) is typically of low quality and requires additional data sources. Recently, Faraday rotation angle (FRA) retrieval using the Phased Array L‐band Synthetic Aperture Radar (PALSAR) full‐pol data have emerged as a reliable technique for ionospheric detection. Similar to the total electron content (TEC), the FRA is the integral effect of the electron density and geomagnetic field, with the geomagnetic field being accurately estimated by the International Geomagnetic Reference Field (IGRF) model. Therefore, this paper proposes a 3‐D secondary CIT algorithm by integrating PALSAR and GPS data: first, the product of the electron density values obtained from GPS‐based CIT and the magnitude of geomagnetic field in corresponding voxel obtained from IGRF is used as the initial value. Then, the iterative algorithm is improved by using the FRA obtained from PALSAR data, rather than TEC, as the input for the second iteration, avoiding the approximation error caused by converting FRA into TEC. The geomagnetic field information is then separated by using the IGRF model, and the reconstructed spatial distribution is finally obtained. Experimental verification shows that the FRA can compensate for the lack of GPS observation rays to a certain extent and improve the accuracy of the reconstructed electron density. The results also indicate that the PALSAR can provide an effective and feasible data source for CIT.

A Global Combination of Geodetic Techniques at the Observation Level: New Perspectives on the Terrestrial Reference Frame

AbstractWe describe the development and assessment of a new terrestrial reference frame (TRF) based on a combination of geodetic techniques at the observation level over the period 2010–2022. Included in the solution are observations from the Global Positioning System (GPS), Satellite Laser Ranging (SLR) and Very Long Baseline Interferometry (VLBI). A key feature of our solution strategy is the use of space ties in low‐Earth orbit to connect SLR to GPS. Though the resulting TRF solution is based on only 12.6 years of data, it is competitive with the international (ITRF2020) standard in terms of fundamental frame parameters (origin and scale) and their temporal evolution, both linear and seasonal. The relative rates of origin (3D) and scale (at Earth's surface) are 0.2 mm and 0.1 mm respectively. Absolute scale and 3D origin (at epoch 2015.0) both differ by 2–3 mm. In addition to station positions and velocities, our combined solution includes Earth orientation parameters (EOP), low‐degree zonal coefficients (J2 and J3) of the geopotential and precise orbit solutions for all participating satellites (GPS, GRACE and GRACE Follow‐on tandems, Jason 2 and 3, and LAGEOS 1 and 2). We discuss potential benefits of our solution strategy and characterize the impacts of our new TRF on estimates of geocenter motion and sea level change from satellite altimetry.

Development of a high-resolution ionospheric VTEC model over Nigeria using spherical harmonics with orthogonal transformation solution

Abstract One important ionosphere element that impacts radio signal transmission is the Vertical Total Electron Content (VTEC). Accurate estimation of VTEC is important for diverse applications such as satellite positioning, space weather forecasting, satellite communication. In regions with a sparse network of receivers, especially Nigeria, the spatial and temporal resolutions of the Global Ionospheric Maps (GIM) regularly provided by the International GNSS Service (IGS), Center for Orbit Determination in Europe (CODE), and the International Reference Ionosphere (IRI) are limited. This limits their potential to uncover local ionospheric phenomena in such areas. To address this limitation, we have developed a VTEC model for estimating high temporal-resolution VTEC and Differential Code Bias (DCB) over Nigeria using spherical harmonic expansions with an orthogonal transformation solution. Our novel method makes use of GNSS measurements from the Global Positioning System (GPS) and Global Navigation Satellite System (GLONASS) to precisely estimate VTEC and DCB. GNSS datasets in Receiver Independent EXchange (RINEX), satellite orbit (SP3) and Ionospheric Exchange (IONEX) formats from 2011 across 9 GNSS receivers in the Nigerian Geodetic Network sampled at 30-second intervals were used for this study. For this investigation, code pseudo-range observations were also smoothed using carrier phase observations. To assure data quality, we also carried out several preprocessing procedures utilizing the Melbourne-Wubbena linear and geometry-free linear combinations using an internal ITB-GNSSTEC FORTRAN application based on batch processing and least squares approaches. To validate our model, we compared the estimates with the IGS, CODE, and IRI-2020 models. Results demonstrated strong agreement with the other models with a standard deviation between 2.80 and 6.50 TECU and a correlation coefficient of not less than 0.92 at the evaluation stations. Notably, the new model aligned more closely with CODE and IGS than the IRI model. Also, the new model enabled the detection of local ionospheric VTEC post-sunset enhancement missed by GIM models. Our model also showed a strong positive correlation with the other models for quiet and disturbed days of geomagnetic activity. In Conclusively, this research has developed a high-resolution VTEC method for areas with sparse distribution of GNSS receivers, achieving a temporal resolution of 10 minutes. The ionospheric modeling in areas like Nigeria with sparse GNSS networks has greatly benefited from this research. The approach improves the precision of GNSS-based applications, such as location and navigation, by precisely calculating VTEC and DCBs. It also addresses the issue of sparse observational data in equatorial regions, offering insightful information for atmospheric and geodetic research.

Sex-Specific Variation in Foraging Behavior is Related to Telomere Length in a Long-Lived Seabird.

Foraging during breeding is a demanding activity linked to breeding investment and possibly constrained by individual quality. Telomere length, the protective nucleoproteins located at the ends of the chromosomes, is considered a trait reflecting somatic maintenance and individual quality. Therefore, foraging effort and parental investment may be positively related to telomere length, if individuals with longer telomeres are of better quality and thus able to maintain better body condition and allocate more resources to parental activities. In the brown booby (Sula leucogaster), we investigated if telomere length is related to body mass (a proxy of condition) and whether variation in foraging behavior and provisioning effort is related to telomere length or body mass. Then, we explored whether variation in foraging and provisioning influences the chick mass growth rate. In 34 pairs nesting in Isla de San Jorge, in the Gulf of California, México, we sampled their blood to estimate telomere length, measured their body mass, and for 10 days, recorded their foraging behavior via global positioning system (GPS) loggers and their chick provisioning rate and chicks' mass growth rate. We found a positive relationship between parents' body mass and telomere length. Body mass did not affect foraging behavior. Females with longer telomeres were more prone to travel longer distances toward offshore and deeper waters than females with shorter telomeres. In contrast, males with longer telomere lengths performed more nearshore foraging trips than males with shorter telomeres. The chick provisioning rate was unrelated to telomere length or body mass, but females fed the chick at a rate 2.4 times greater than males. Females' offshore foraging, but not males', was positively related to chick mass growth rate. Our results suggest that individual quality, indicated by telomere length, is an important driver of sex-specific, between-individual variation in foraging behavior, indirectly affecting offspring condition.

Strong Relativistic Electron Flux Events in GPS Orbit

AbstractRelativistic electrons cause internal charging on satellites and are a significant space weather hazard. In this study we analyze approximately 20 years of data from the US Global Positioning System (GPS) satellite NS41 to determine the conditions associated with the largest daily averaged fluxes of = 2.0 MeV relativistic electrons. The largest flux events at = 4.5 and = 6.5 were associated with moderate to strong CME‐driven geomagnetic storms. However, the majority of the 50 largest flux events at = 4.5 (30 out of 50) and = 6.5 (37 out of 50) were associated with high speed solar wind streams from coronal holes. Both solar drivers are thus very important for relativistic electron flux enhancements in GPS orbit. The 1 in 3 year flux level was not exceeded following any of the 15 largest geomagnetic storms as monitored by the index, showing that the largest geomagnetic storms, most often associated with extreme space weather, do not result in significantly larger relativistic electron flux events in GPS orbit.

A low-cost localization method in autonomous vehicle by applying light detection and ranging technology

The autonomous platform uses global positioning system (GPS) to localize the vehicle. In addition, light detection and ranging (LIDAR) and the high precision camera help to identify the turns in the road. The proposed system can help to determine the road turns with higher accuracy without utilizing LIDAR and high-precision camera technology. This research aims to implement a cost-effective simultaneous localization system that can reduce the cost by half for any autonomous vehicle. The existing system is more complex due to the inclusion of LIDAR technology. In contrast, the proposed approach uses beacon communication between vehicles and infrastructure and long-range (LoRa) for vehicle-to-vehicle (V2V) and vehicle to infrastructure (V2I) communication. The simulation result illustrates that the proposed approach provides better performance.