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Introduction: Needle decompression of a tension pneumothorax can be a lifesaving procedure. It requires an adequate needle length to reach the chest wall to rapidly remove air. With adult obesity exceeding one third of the United States population in 2010, we sought to evaluate the proper catheter length that may result in a successful needle decompression procedure. Advance Trauma Life Support (ATLS) currently recommends a 51 millimeter (mm) needle, while the needles stocked in our emergency department are 46 mm. Given the obesity rates of our patient population, we hypothesize these needles would not have a tolerable success rate of 90%. Methods: We retrospectively reviewed 91 patient records that had computed tomography of the chest and measured the chest wall depth at the second intercostal space bilaterally. Results: We found that 46 mm needles would only be successful in 52.7% of our patient population, yet the ATLS recommended length of 51 mm has a success rate of 64.8%. Therefore, using a 64 mm needle would be successful in 79% percent of our patient population. Conclusion: Use of longer length needles for needle thoracostomy is essential given the extent of the nation’s adult obesity population. [West J Emerg Med. 2013;14(6):650-652.]

Migration-induced land degradation is a challenging environmental issue in Sub-Saharan Africa. The need for expansion due to urban development has raised the question of effective sustainable measures. Understanding migration and land degradation links is paramount for sustainable urban development and resource use. This is particularly true in Nigeria, where elevated migration levels frequently result in accelerated land degradation due to urban expansion. Given the need to understand the impact of migration on land degradation in the Savannah Region of Nigeria (SRN), this study introduces a novel approach by integrating remote sensing data (NDVI, NDBI) with local community perceptions (mixed-methods approach) to assess the impact of migration on land degradation in four migration destination communities located in two local government areas (LGAs) (Sabon Gari East and Sabon Gari West of Fagge LGA; Zuba and Tungamaje of Gwagwalada LGA). We conducted focus group discussions and a semi-structured survey with 360 household heads to obtain a comprehensive view of perceptions. Our findings revealed that 41.1% and 29.5% of the respondents agreed and strongly agreed that migration significantly contributes to land degradation. We analysed the spatiotemporal patterns of the Normalised Difference Vegetation Index (NDVI) and the Normalised Difference Built-Up Index (NDBI) acquired from Landsat 8 datasets for 2014 to 2023. While increasing NDBI values were observed in all communities, a slight decrease in NDVI was noted in Sabon Gari East and Tungamaje. Our analyses highlighted activities leading to land degradation such as land pressure due to built-up expansion at Sabon Gari East, Sabon Gari West, and Tungamaje, and deforestation at Zuba. Based on the varying challenges of migration-induced land degradation, we recommend adequate community participation in suggesting targeted interventions and policies to foster various adaptive capacities and sustainable environments within SRN communities and Sub-Saharan Africa. [ABSTRACT FROM AUTHOR]

Aerial vehicles are increasingly relying on connectivity to cellular networks, with 5G new radio (NR) and 6G technologies deemed critical for the next generation of indoor and outdoor positioning systems. Conventional time of arrival approaches require time synchronisation between base stations and vehicles, and a clock bias greater than 30 ns can result in a positioning inaccuracy above 10 m. This work, thereby, proposes an integrated positioning technique based on RF fingerprinting using ray-tracing data and reinforced with machine learning. The system leverages advanced sensing technologies, NR communications, and AI-driven random forests to enhance the precision and reliability of air vehicle positioning, contributing to safer and more efficient air travel and autonomous flight operations. The developed solution is evaluated in a representative urban canyon environment, in which the performance of conventional radio-based positioning systems is often degraded. Notably, a supervised learning algorithm based on the received signal strength and time of arrival is shown to exhibit an accuracy of under 3 m in 75% of the areas studied. [ABSTRACT FROM AUTHOR]

Spatial information about plant health and productivity are essential when assessing the progress towards Sustainable Development Goals such as life on land and zero hunger. Plant health and productivity are strongly linked to a plant's phenological progress. Remote sensing, and since the launch of Sentinel-1 (S1), specifically, radar-based frameworks have been studied for the purpose of monitoring phenological development. This study produces insights into how crop phenology shapes S1 signatures of PolSAR features and InSAR coherence of wheat, canola, sugar beet. and potato across multiple years and orbits. Hereby, differently smoothed time series and a base line of growing degree days are stacked to estimate the patterns of occurrence of extreme values and break points. These patterns are then linked to in situ observations of phenological developments. The comparison of patterns across multiple orbits and years reveals that a single optimized fit hampers the tracking capacities of an entire season monitoring framework, as does the sole reliance on extreme values. VV and VH backscatter intensities outperform all other features, but certain combinations of phenological stage and crop type are better covered by a complementary set of PolSAR features and coherence. With regard to PolSAR features, alpha and entropy can be replaced by the cross-polarization ratio for tracking certain stages. Moreover, a range of moderate incidence angles is better suited for monitoring crop phenology. Also, wheat and canola are favored by a late afternoon overpass. In sum, this study provides insights into phenological developments at the landscape level that can be of further use when investigating spatial and temporal variations within the landscape. [ABSTRACT FROM AUTHOR]

Climate change is affecting the snow cover conditions on a global scale, leading to changes in the extent and duration of snow cover as well as variations in the start and end of snow cover seasons. These changes can have a paramount impact on runoff and water availability, especially in catchments that are characterized by nival runoff regimes, e.g., the Syr Darya in Central Asia. This time series analyses of daily MODIS snow cover products and in situ data from hydrological stations for the time series from 2000 through 2022 reveal the influences of changing snow cover on the runoff regime. All catchments showed a decrease in spring snow cover duration of −0.53 to −0.73 days per year over the 22-year period. Catchments located farther west are generally characterized by longer snow cover duration and experience a stronger decreasing trend. Runoff timing was found to be influenced by late winter and spring snow cover duration, pointing towards earlier snowmelt in most of the regions, which affects the runoff in some tributaries of the river. The results of this study indicate that the decreasing snow cover duration trends lead to an earlier runoff, which demands more coordinated water resource management in the Syr Darya catchment. Further research is recommended to understand the implications of snow cover dynamics on water resources in Central Asia, crucial for agriculture and hydropower production. [ABSTRACT FROM AUTHOR]