Ground Transportation Research Articles

Cumulatively Anticipative Car-Following Model with Enhanced Safety for Autonomous Vehicles in Mixed Driver Environments

The contribution of autonomous vehicles to traffic is one of the key aspects of future ground transportation in smart cities. Autonomous vehicles are able to provide many benefits, but some benefits can only provide advantages if these vehicles comprise a large percent of on the road/driven vehicles, which may take decades. Until then, the robotic drivers in autonomous vehicles will share the same road system with human divers in a mixed-driver environment where the majority of road accidents for autonomous vehicles are associated with the operational inconsistency of human drivers. In this paper, a cumulatively anticipative car-following model (which considers cumulative influences from multiple preceding vehicles) is developed to potentially improve the safety of autonomous vehicles in mixed-driver environments that benefit from enhanced communication between the autonomous vehicles and other components in the transportation system. Through intensive simulations (200 simulations), this study comprehensively evaluates four models including the cumulative anticipative car-following model, the Wiedemann 99 model, adaptive cruise control, and the cooperative adaptive cruise control model. Across 10 scenarios and five speed limits (24.59–33.53 m/s), the cumulative anticipative car-following model consistently demonstrates superior conflict reduction, with average, maximum, and minimum conflict percentages ranging from 77.69% to 91.97% against the Wiedemann 99 model, 67.00% to 93.94% against the adaptive cruise control model, and 69.17% to 93.25% against the cooperative adaptive cruise control model. Notably, the cooperative adaptive cruise control model exhibits suboptimal performance, especially in mixed-driver settings. The cumulative anticipative car-following model also enhances vehicle mobility, reducing average stops by up to 93.54%, 91.74%, 92.04%, 88.60%, and 91.35% in comparison to the other three models at speeds of 24.59 m/s, 26.82 m/s, 29.06 m/s, 31.29 m/s, and 33.53 m/s. Overall, the cumulative anticipative car-following model holds significant potential for conflict reduction and traffic enhancement.

Comparison of helicopter and ground transportation in pediatric trauma patients.

Decision making regarding transportation mode after a traumatic injury may have a significant impact on outcomes, due to differences in time to definitive care. The objective of this study was to determine if transport mode had an impact on in-hospital mortality and discharge disposition in pediatric trauma patients. Data were abstracted from the National Trauma Data Bank from 2007 to 2016 comparing helicopter and ground transportation modes effects on mortality and discharge outcomes. The primary outcome was in-hospital death, while the secondary outcome was discharge home without services (DCHWOS). Analyses included logistic regression modeling and propensity score matching. Significant variables from univariate analysis were included in the multivariate, propensity-matched regression model. Pediatric trauma patients transported by helicopter had lower odds of mortality (OR 0.69 [0.64,0.75]) and higher odds of DCHWOS (1.29 [1.20,1.39]). There were no differences in overall mechanism, but individual injury patterns showed higher odds of mortality. Critical decisions regarding triage of patients by different modes of transport occur every day. This study supports the current literature on the topic and shows a potential additional benefit of a meaningful discharge outcome for those transported by helicopter. This study may impact prehospital triage decision making process for pediatric trauma patients on mortality. Prehospital transport mode may contribute to pediatric trauma discharge outcomes. Highlights the need for future research regarding non-clinical data that is unable to be abstracted from national databases (e.g., family dynamics, insurance status, weather, access to post-discharge resources).

Inferring intercity freeway truck volume from the perspective of the potential destination city attractiveness

Accurately inferring the spatiotemporal distribution of freeway traffic volume is one of the bottleneck problems for intelligent management of ground transportation. Although the accuracy of the widely used machine learning-based approaches has been improving, these methods on freeway traffic flow inference tend to become more and more complex and unexplainable, and sometimes even contradict the constraints of freeway access. From the perspective of the potential destination city attractiveness, this study proposes a new method to infer freeway truck volume. First, considering the spatial scope and direction constraints of road transportation, a restricted area search method for potential destination cities of freeway traffic trips is proposed. Second, a freeway traffic inference model was constructed by combining distance and the angle-weighted socioeconomic statistics of each potential destination city. Finally, the Shapley additive explanation value was used to explain how the potential destination city attraction affects the freeway traffic flow. The results show that the proposed method only used 10 indicators; however, the prediction results were closer to the true value, and the computational efficiency improved by 3–10 times over the baseline method. The variables related to spatiotemporal heterogeneity were the most significant variable group, followed by the industrial structure of potential destination cities.

SP surveys to estimate Airport Shuttle demand in an Urban Air Mobility context

Electric vertical take-off and landing vehicles (eVTOL) are expected to be the key drivers for Urban Air Mobility (UAM) scenarios, by satisfying on-demand air travel needs in the short or mid-term. Despite the high number of eVTOL prototypes, nowadays only few studies have focused on UAM travel demand estimation, in particular Airport Shuttle demand estimation. The aim of this work is to use Stated Preference methods to collect data necessary to understand the main features of the potential UAM Airport Shuttle trip demand, also by calibrating some discrete choice models. Data were collected by both on-line surveys and face-to-face interviews, which captured mainly the Italian context. Three different Multinominal Logit models and a Mixed Logit model have been calibrated in order to identify the main variables driving people's choices for Airport Shuttle services. The results show the positive impact of income, air travel frequency and shared ride in increasing the willingness to use Airport Shuttle services. On the other hand, user that still prefers the ground transportation modes to reach the airport, high ratio between the number of cars and the driving licenses per family unit and the lack of experience with autonomous systems (i.e., driving assistance systems) seem to have a negative impact on people intention to use Airport Shuttle services.

Enhancing Data Discretization for Smoother Drone Input Using GAN-Based IMU Data Augmentation

This study investigates the use of generative adversarial network (GAN)-based data augmentation to enhance data discretization for smoother drone input. The goal is to improve unmanned aerial vehicles’ (UAVs) performance and maneuverability by incorporating synthetic inertial measurement unit (IMU) data. The GAN model is employed to generate synthetic IMU data that closely resemble real-world IMU measurements. The methodology involves training the GAN model using a dataset of real IMU data and then using the trained model to generate synthetic IMU data. The generated synthetic data are then combined with the real data for data discretization. The resulting improved data discretization is evaluated using statistical metrics and a similarity evaluation. The improved data discretization demonstrates enhanced drone performance in terms of flight stability, control accuracy, and smoothness of movements when compared to standard data discretization methods. These results highlight the potential of GAN-based data augmentation for enhancing data discretization and improving drone performance. The proposition of improved data discretization offers a tangible benefit for the successful integration of Advanced Air Mobility (AAM) systems. Enhancing the accuracy and reliability of data acquisition and processing in UAS makes UAS operations safer and more reliable. This improvement is crucial for achieving the goal of automated and autonomous operations in diverse settlement environments, encompassing multiple mobility modes such as ground and air transportation.

A rapid approach to evaluating ground surface conditions for shale gas extraction in mountainous areas

Ground surface conditions, regarding the engineering, eco-environmental, and economic constraints, are crucial for shale gas extraction in the mountainous areas. A novel approach has thus been proposed to perform a rapid and integrated evaluation of ground surface conditions on a regional scale. The southeastern margin of the Sichuan Basin, China’s primary shale gas exploitation target, serves as an example to demonstrate the execution of this approach. Critical metrics for ground surface condition evaluation, including geomorphology, land utilization, water supply, and transportation conditions, were obtained from published GIS and remote sensing data. Different ratings were assigned to facilitate a quantitative evaluation of the metrics, and the composite index was calculated based on the ratings. The study area was first filtered using a composite index threshold determined from the calculated values at the existing well sites. The contiguous regions with the sufficient dimensions within the screened area were further selected as the final potential targets. The overall assessment recommended that only 10.99%, 7.61%, and 4.86% of the study area be deemed marginally, moderately, and highly suitable for potential shale gas extraction sites, respectively. These results suggest that this approach can enable efficient and accurate ground surface condition evaluations beyond the actual field surveys, while excluding the most unsuitable areas for further shale gas extraction site selection.

Calculation of fracture number and length formed by methane deflagration fracturing technology

The innovative Methane in-situ deflagration fracturing technology offers several benefits. It can prevent formation pollution and eliminates the need for complex treatment procedures for backflow materials. Additionally, it reduces ground transportation expenses and is poised to become a highly effective and eco-friendly waterless fracturing technology. This paper suggests methods for determining the number and length of fractures in oil and gas well stimulation, considering the main influencing factors. The fracture number is calculated using mass conservation principles, while the fracture length is determined using the crack propagation model. The fracturing experiments with large-sized samples were conducted to verify the technical feasibility of the new fracturing technology and fill the gap in large-scale physical model experimental research for deflagration fracturing technology. Following the experiment, compare experimental data with calculated data, and analyze the factors that affect the fracture number and length. The results indicate that both methods are highly feasible and possess strong predictive accuracy. It is advised that to enhance the fracturing effect on formations with high crustal stress, it is beneficial to appropriately increase the peak pressure, reduce the pressure rate, and increase the fracturing time while ensuring that the wellbore remains undamaged. Moreover, these proposed methods are versatile and adaptable, making them suitable for explosive fracturing within hydraulically fractured formations and high-energy gas fracturing technology.

Carbon Monitor Europe near-real-time daily CO2 emissions for 27 EU countries and the United Kingdom

With the urgent need to implement the EU countries pledges and to monitor the effectiveness of Green Deal plan, Monitoring Reporting and Verification tools are needed to track how emissions are changing for all the sectors. Current official inventories only provide annual estimates of national CO2 emissions with a lag of 1+ year which do not capture the variations of emissions due to recent shocks including COVID lockdowns and economic rebounds, war in Ukraine. Here we present a near-real-time country-level dataset of daily fossil fuel and cement emissions from January 2019 through December 2021 for 27 EU countries and UK, which called Carbon Monitor Europe. The data are calculated separately for six sectors: power, industry, ground transportation, domestic aviation, international aviation and residential. Daily CO2 emissions are estimated from a large set of activity data compiled from different sources. The goal of this dataset is to improve the timeliness and temporal resolution of emissions for European countries, to inform the public and decision makers about current emissions changes in Europe.

Bilevel Optimal Scheduling of Electric Bus Fleets in Regional Integrated Electricity–Gas–Heat Energy Systems

Proliferation of electric buses (EBs) is widely acknowledged as a viable solution to reduce carbon emissions while addressing the demands of ground transportation. This paper investigates how to optimally schedule EBs in regions where heterogeneous energy resources, such as electricity, gas, and heat, are integrated as a regional integrated energy system (RIES). A novel bi-level optimal scheduling framework considering EBs’ operation schedules and vehicle-to-grid (V2G) responses is proposed in this work. Firstly, instead of charging-by-need (e.g., low SOC), this paper considers charging-by-scheduling (e.g., low electricity price) to optimize regional energy cost by explicitly incorporating coupled constraints from EB operation schedules, renewable energy generations, gas network models, and heat supply demands. The upper level scheduling strategy is formed to minimize the operation cost of the entire RIES. Secondly, EB operation strategies and energy generation & heat conversion devices (e.g., CHP, electric boilers, and gas boilers) are further optimized in the lower level to minimize fluctuation in the total electrical load. Finally, numerical simulation results of coordinated scheduling of EB charging, renewable integration, and gas supply to meet electrical and heat demands under different scenarios are compared and analyzed. Simulation results based on five scenarios show that the bi-level model and the two-stage optimal scheduling method can realize the optimal operation cost and reduce the electrical load fluctuation of the system.

Autoignition enhancement of ammonia spray under engine-relevant conditions via hydrogen addition: Thermal, chemical, and charge cooling effects

With the growing trend of decarbonization in ground transportation, low and zero-carbon fuels have attracted extensive research interest. Liquid ammonia is a promising alternative fuel due to its relatively high volumetric energy density, mature production and distribution infrastructure, convenience of storage, and zero carbon emissions. However, ammonia combustion also suffers from low flame speed and weak chemical reactivity. In this work, we computationally investigate the suitable engine-relevant thermochemical conditions for auto-ignition of constant volume ammonia spray, as well as its spray dynamics, vaporization, flash boiling effects, and emissions. The simulation is first validated by comparing it against available experimental data from a vaporizing ammonia spray and is then extended to chemically reactive conditions. Results show that ammonia sprays under engine-relevant conditions (60 bar and 1200 K) can only successfully auto-ignite for cases with ambient hydrogen addition, through enhancement of thermal condition and chemical reactivity. A chemical flux analysis is conducted to further understand the important species and reactions that promote ammonia auto-ignition from hydrogen, which potentially can be introduced via H2 solubility, exhaust gas recirculation, and onboard ammonia thermal decomposition. Furthermore, results have indicated that charge cooling effects can further decrease the temperature in the flow field and make auto-ignition more difficult. This study provided useful insights for the application of ammonia as a zero-carbon diesel fuel for ground transportation.

39 Certified Burn Center Access in the United States: The Geospatial and Transport Cost of Transfer

Abstract Introduction Specialized burn centers are critical in minimizing burn-associated morbidity and mortality. However, American Burn Association (ABA)-verified burn centers are unequally distributed across the US, and fewer verified centers are available for pediatric patients relative to adults. The economic burden of transport to verified centers represents a significant proportion of the already high cost of burn-associated care. The present study aims to quantify inequitable burn care access in the contiguous US due to age group and locality as a function of physical proximity and transportation cost. Methods County-level distances (n=3,106) to the nearest ABA-verified adult or pediatric burn center were determined and mapped. Distances were then analyzed separately for rural (n = 1440) and urban (n = 1666) counties for both adult and pediatric burn centers. Distance calculations for each population were combined with transport cost data (2022 CMS Ambulance fee Schedules) to determine the average cost of transport for each patient population (adult vs. pediatric, urban vs. rural). Results 59 Adult and 43 Pediatric ABA-verified centers were identified from the ABA burn center directory. Pediatric patients reside 30.57 miles (p < 0.001) further than adults from the nearest center, accounting for a 10.5% - 15.9% transport cost increase. Transport costs increased dramatically between urban and rural counties, with rural patients facing a cost increase of 32.7% and 80.88% for ground and air transportation, respectively. Conclusions Physical proximity to burn care may appear to differ only modestly across age and region. However, the seemingly marginal increase in distance significantly impacts the cost of patient transport. The present study highlights both physical and economic barriers to burn care access faced by rural and pediatric patients. Increasing ABA burn center certification in targeted areas across the US may decrease the disparities in access to burn care faced by these groups. Applicability of Research to Practice Identify areas that may benefit from expansion of certified burn-care access and additional provider education.

A comprehensive study for the identification of the requirements for an optimal H2 combustion engine

As part of the fight against global warming and to achieve greenhouse gas emission targets, it is crucial to reduce the carbon footprint of ground transportation. Mobility needs are continuously growing with increase in population. All these factors will lead to an upsurge in the energy demand for the mobility in the very next future. Consequently, the diversification of low carbon energy sources is urgently required. Hydrogen can be used for mobility solution in its two energy conversion mechanisms: The Fuel Cell technology or the Internal Combustion Engine (ICE). The latter option, studied in the present work, offers the advantages of current fossil fuel engines – existing and proven technology, lifetime, controlled cost – with a very low carbon footprint. The overall objective of the study is to define the specifications of a dedicated Hydrogen direct injection combustion system for ground transportation application with the best fuel efficiency and lower raw emissions, to minimize the aftertreatment needs. A complete experimental and numerical study was carried out to get valuable information on various phenomena occurring throughout the engine cycle. The very first step of the study consisted in performing experimental investigations. For this purpose, an all metal single cylinder engine originally designed for gasoline spark ignited combustion (tumble air motion, gasoline direct injection) was modified for hydrogen direct injection combustion. The gas-gas injection was experimentally studied in the High Pressure/High Temperature vessel available at IFPEN. Those experiments were used to calibrate the 3D CFD numerical approach. Based on a 0D pre-study (boundary conditions) and using the injection modeling calibration introduced before, 3D CFD simulations have been then carried out with specific hydrogen kinetics properties. Finally, this comprehensive study highlights the specificities of ICE running with hydrogen. It provides indications and guidelines for further developments and optimization of hydrogen combustion engines.

Mass production of unvouchered records fails to represent global biodiversity patterns.

The ever-increasing human footprint even in very remote places on Earth has inspired efforts to document biodiversity vigorously in case organisms go extinct. However, the data commonly gathered come from either primary voucher specimens in a natural history collection or from direct field observations that are not traceable to tangible material in a museum or herbarium. Although both datasets are crucial for assessing how anthropogenic drivers affect biodiversity, they have widespread coverage gaps and biases that may render them inefficient in representing patterns of biodiversity. Using a large global dataset of around 1.9 billion occurrence records of terrestrial plants, butterflies, amphibians, birds, reptiles and mammals, we quantify coverage and biases of expected biodiversity patterns by voucher and observation records. We show that the mass production of observation records does not lead to higher coverage of expected biodiversity patterns but is disproportionately biased toward certain regions, clades, functional traits and time periods. Such coverage patterns are driven by the ease of accessibility to air and ground transportation, level of security and extent of human modification at each sampling site. Conversely, voucher records are vastly infrequent in occurrence data but in the few places where they are sampled, showed relative congruence with expected biodiversity patterns for all dimensions. The differences in coverage and bias by voucher and observation records have important implications on the utility of these records for research in ecology, evolution and conservation research.

D98. Access to Certified Burn Centers in The United States: The Geospatial and Transport Cost of Transfer

PURPOSE: Although ABA-verified burn centers are critical in minimizing burn-associated morbidity and mortality, disparities in burn care access remain – particularly for rural and pediatric patients. The present study quantifies inequitable burn care access as a function of physical proximity and assesses its impact on burn-associated transport costs. METHODS: County-level distances (n=3,106) to the nearest ABA-verified adult (n=59) or pediatric (n=43) burn center were determined and mapped. Average per mile transport cost for each population (urban vs. rural) was estimated from CMS ambulance fee schedules. Total transport cost was determined based on county-level distance calculations, and cost burden was compared between cohorts. RESULTS: Pediatric patients reside 30.57 miles (p < 0.001) further than adults from the nearest center, accounting for a 10.5% - 15.9% transport cost increase. Transport costs increased dramatically between urban and rural counties, with rural patients facing a cost increase of 32.7% and 80.88% for ground and air transportation, respectively. CONCLUSION: Physical proximity to burn care may appear to differ only modestly across age and region. However, the seemingly marginal increase in distance significantly impacts the cost of patient transport. The present study highlights both physical and economic barriers to access faced by rural and pediatric burn patients. Increasing ABA burn center certification in targeted areas across the US may decrease the disparities in access to burn care faced by these groups.

Drone-Assisted Secure Healthcare with AI/ML Algorithm and Big Data Analytics for 6G Wireless Communication in the Future

Over the next ten years, expect to witness the emergence of a Sixth Era (6G) of innovation owing to the explosive expansion of 5G applications and rising demand for even faster communication solutions. Many researchers predicted that the 6G remote arrangement standard may appear around 2030. The Sixth Era (6G) organization, which is anticipated to be the next major amusement changer in the media transmission sector, is now the focus of attention in both academia and business. The use of rambles in healthcare will further help to lower healthcare expenditures. The need for expensive ground transportation is eliminated by using rambles to deliver the medical supplies. Additionally, the use of rambles in the inquiry and collecting of therapeutic information will reduce the need for expensive human labour. As the information gathered can be easily and swiftly analysed, this will also reduce the time and costs associated with therapeutic drugs. Long-term improvements in healthcare outcomes and lower healthcare expenditures will follow from this. Numerous organizing hubs and terminal devices provide services for use in the healthcare industry, but this requires a spine system to consider the time-consuming advantage. For future 6G age healthcare frameworks using ramble by machine learning computations with big data. Without being explicitly altered, the framework may provide the ability to memorize and advance spontaneously through machine learning from experience. AI can accurately recognize data, treatment approaches, and generally produces superior, quiet outcomes. It is essential to verify their quality and identify the appropriate linkages for big data analytics to be useful inside the healthcare industry. to ship haematological supplies, defibrillators, and immunizations via drone. The reference layered communication system for hubs and devices in real-time communication, which is part of the suggested approach, demonstrates cutting-edge healthcare application for persuasive treatment and clever integration of benefit provided by 6G distant systems.

Rapid increase in tropospheric ozone over Southeast Asia attributed to changes in precursor emission source regions and sectors

Observations indicate that tropospheric ozone (O3) concentrations over Southeast Asia have been increasing rapidly since the 1990s. Here, we quantify source contributions from geographical regions and emission sectors of the two distinct types of O3 precursors, i.e., nitrogen oxides (NOx) and volatile organic compounds (VOCs), to the increase in tropospheric O3 in Southeast Asia during 1990–2019 using an O3 source tagging technique implemented in a global chemistry-climate model. The results show that although local anthropogenic emission of NOx in Southeast Asia only contributes 18% of the annual averaged near-surface O3 concentration, the increase in local NOx emission dominates the increasing trend of O3 concentration in Southeast Asia, accounting for 107% of the regional averaged trend of 1.07 ppb decade−1. Increases in NOx emissions from East Asia and South Asia explain 29% of the increasing trend, but 9% is offset by the emission reduction in North America. The vertical O3 trends in the troposphere contributed by individual source regions are consistent with those near the surface. Ground transportation is responsible for 79% of the rapid O3 increase, followed by 39% contribution from international shipping. Because an increase in anthropogenic NOx emissions enhances the O3 production efficiency by VOCs, the increase in O3 concentrations in Southeast Asia is thereby largely contributed by methane and biogenic VOCs.

Global Consumption Speed of Jet Fuel/Air Flames and the Impact of Fuel Chemistry

ABSTRACT Large hydrocarbon fuels are used for ground and air transportation and will be for the foreseeable future. A key parameter when burning these fuels is the turbulent consumption speed, which is the velocity at which fuel and air are consumed through a turbulent flame front. Such information can be useful as a model input parameter and for validation of modeled results. In this study, turbulent consumption speeds were measured for three jet-like fuels using a premixed turbulent Bunsen burner. The burner was used to independently control turbulence intensity, unburned temperature, and equivalence ratio. Each fuel had similar heat releases (within 2%), laminar flame speeds (within 5–15%), and adiabatic flame temperatures. Despite this similarity, for constant Re D and turbulence intensity, A2 fuel (i.e. jet-A) has the highest turbulent flame speeds and remains stable (i.e. without tip quenching) at lower ϕ than the other fuels. In contrast the C1 fuel, which consists of heavily-branched alkanes, contains no aromatics and has a relatively high average molecular weight, has the slowest turbulent flame speeds and is the most prone to tip quenching. The C1 fuel has the highest stretch sensitivity, in general, as indicated by calculated Markstein numbers. This work shows that turbulent flame speeds and tip stability of multi-component large hydrocarbon fuels can be sensitive to the chemical class of its components.

An Electric Vehicle Assisted Charging Mechanism for Unmanned Aerial Vehicles

The global greenhouse effect and air pollution problems have been deteriorating in recent years. The power generation in the future is expected to shift from fossil fuels to renewables, and many countries have also announced the ban on the sale of vehicles powered by fossil fuels in the next few decades, to effectively alleviate the global greenhouse effect and air pollution problems. In addition to electric vehicles (EVs) that will replace traditional fuel vehicles as the main ground transportation vehicles in the future, unmanned aerial vehicles (UAVs) have also gradually and more recently been widely used for military and civilian purposes. The recent literature estimated that UAVs will become the major means of transport for goods delivery services before 2040, and the development of passenger UAVs will also extend the traditional human ground transportation to low-altitude airspace transportation. In recent years, the literature has proposed the use of renewable power supply, battery swapping, and charging stations to refill the battery of UAVs. However, the uncertainty of renewable power generation cannot guarantee the stable power supply of UAVs. It may even be very possible that a large number of UAVs need to be charged during the same period, causing congestion in charging stations or battery swapping facilities and delaying the arranged schedules of UAVs. Although studies have proposed the method of that employing moving EVs along with wireless charging technology in order to provide electricity to UAVs with urgent needs, the charging schemes are still oversimplified and have many restrictions. In addition, different charging options should be provided to fit the individual need of each UAV. In view of this, this work attempts to meet the mission characteristics and needs of various UAVs by providing an adaptive flight path and charging plan attached to individual UAVs, as well as reducing the power load of the renewable power generation during the peak period. We ran a series of simulations for the proposed flight path and charging mechanism to evaluate its performance. The simulation results revealed that the solutions proposed in this work can be used by UAV operators to fit the needs of each individual UAV.

Regional Burn Review: Neither Parkland nor Brooke Formulas Reach 85% Accuracy Mark for Burn Resuscitation.

Prolonged resuscitation can result in burn wound conversion and other complications. Our team switched from using Parkland (PF) to modified Brooke formula (BF) in January 2020. Secondary to difficult resuscitations using BF, we sought to review our data to identify factors associated with resuscitation requiring greater than predicted resuscitation with either formula, defined as 25% or more of predicted, hereafter referred to as over-resuscitation. Patients admitted to the burn unit between 1/1/2019 and 8/29/2021 for a burn injury with a percentage of total body surface area (%TBSA) ≥15% were included. Subjects <18 years, or weighing <30kg, and those who died or had care withdrawn within 24h of admission were excluded. Demographics, injury information, and resuscitation information were collected. Univariate and multivariate analyses were performed to identify factors associated with over-resuscitation by either formula. P < 0.05 was considered significant. Sixty-four patients were included; 27 were resuscitated using BF and 37 using PF. No significant differences were observed in demographics and burn injury between the groups. Patients required a median 3.59mL/kg/%TBSA for BF and 3.99mL/kg/%TBSA for PF to reach maintenance (p = 0.32). Over-resuscitation was more likely to occur when using BF compared to PF (59.3% vs. 32.4%, p = 0.043). Over-resuscitation was associated with longer time to reach maintenance (OR = 1.179 [1.042-1.333], p = 0.009) and arrival via ground transportation (OR = 10.523 [1.171-94.597], p = 0.036). Future studies are warranted to identify populations in which BF underperforms and sequelae associated with prolonged resuscitation.

The Omicron Lineages BA.1 and BA.2 (Betacoronavirus SARS-CoV-2) Have Repeatedly Entered Brazil through a Single Dispersal Hub.

Brazil currently ranks second in absolute deaths by COVID-19, even though most of its population has completed the vaccination protocol. With the introduction of Omicron in late 2021, the number of COVID-19 cases soared once again in the country. We investigated in this work how lineages BA.1 and BA.2 entered and spread in the country by sequencing 2173 new SARS-CoV-2 genomes collected between October 2021 and April 2022 and analyzing them in addition to more than 18,000 publicly available sequences with phylodynamic methods. We registered that Omicron was present in Brazil as early as 16 November 2021 and by January 2022 was already more than 99% of samples. More importantly, we detected that Omicron has been mostly imported through the state of São Paulo, which in turn dispersed the lineages to other states and regions of Brazil. This knowledge can be used to implement more efficient non-pharmaceutical interventions against the introduction of new SARS-CoV variants focused on surveillance of airports and ground transportation.