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Obsolescence in Command, Control, Communications, Computers, Cyber, Intelligence, Surveillance and Reconnaissance (C5ISR) systems is a challenge that often frustrates practitioners. Obsolescence challenges require solutions many times over the life cycle [...]

BackgroundThe burden of pediatric critical illness and resource utilization by children with critical illness in resource limited settings (RLS) are largely unknown. Without specific data that captures key aspects of critical illness, disease presentation, and resource utilization for pediatric populations in RLS, development of a contextual framework for appropriate, evidence-based interventions to guide allocation of limited but available resources is challenging. We present this methods paper which describes our efforts to determine the prevalence, etiology, hospital outcomes, and resource utilization associated with pediatric acute, critical illness in RLS globally.MethodsWe will conduct a prospective, observational, multicenter, multinational point prevalence study in sixty-one participating RLS hospitals from North, Central and South America, Africa, Middle East and South Asia with four sampling time points over a 12-month period. Children aged 29 days to 14 years evaluated for acute illness or injury in an emergency department) or directly admitted to an inpatient unit will be enrolled and followed for hospital outcomes and resource utilization for the first seven days of hospitalization. The primary outcome will be prevalence of acute critical illness, which Global PARITY has defined as death within 48 hours of presentation to the hospital, including ED mortality; or admission/transfer to an HDU or ICU; or transfer to another institution for a higher level-of-care; or receiving critical care-level interventions (vasopressor infusion, invasive mechanical ventilation, non-invasive mechanical ventilation) regardless of location in the hospital, among children presenting to the hospital. Secondary outcomes include etiology of critical illness, in-hospital mortality, cause of death, resource utilization, length of hospital stay, and change in neurocognitive status. Data will be managed via REDCap, aggregated, and analyzed across sites.DiscussionThis study is expected to address the current gap in understanding of the burden, etiology, resource utilization and outcomes associated with pediatric acute and critical illness in RLS. These data are crucial to inform future research and clinical management decisions and to improve global pediatric hospital outcomes.

Obsolescence is a major challenge that affects all Command, Control, Communications, Computers, Cyber, Intelligence, Surveillance and Reconnaissance (C5ISR) systems. A proactive obsolescence management approach focusing on the planning and execution [...]

The Eagle Marsh Nature Preserve and Fox Island County Park bat communities were surveyed in 2018 and 2019 as a follow-up to the 2014 Indiana Academy of Science Bioblitz. We surveyed using acoustic detectors in the summer of 2018 and mist-nets in 2019, to confirm acoustic survey results. Sampling at 16 sites over 64 acoustic detector nights and 29 net nights, resulted in 6,390 bat call sequences and 50 captured bats. Nine bat species were detected in the acoustic survey, resulting in a Shannon Index of 1.43 [+ or -] 0.13 and an evenness of 0.64 [+ or -] 0.06 (averaged between the two automated identification programs). However, two Myotis spp. may have been misidentified by the automated identification software. In the mistnet survey, four bat species (including the state endangered and federally threatened northern long-eared bat, Myotis septentrionalis) were captured in four sites (two sites that weren't sampled with acoustics), resulting in a Shannon Index of 0.75 and an evenness of 0.54. Results suggest that Eagle Marsh and Fox Island hosts a healthy diversity of bat species, thus justifying restoration efforts and the need for additional conservation efforts in this part of the state. Keywords: Myotis septentrionalis, community ecology, biodiversity survey, restoration, northern long-eared bat, bat diversity, Eagle Marsh, Fox Island, INTRODUCTION Ecological community surveys provide population and presence/absence data across different taxa, and help gauge community health (Elton & Miller 1954). These survey data can then be used to justify [...]

Driver characteristics have been linked to the frequency and severity of car crashes. Among these, age and gender have been shown to impact both the possibility and severity of a crash. Previous studies have used standard ordered probit (OP) models to analyze crash data, and some research has suggested heteroskedastic ordered probit (HETOP) could provide improved model fit. The objective of this paper is to evaluate potential improvements of the heteroskedastic ordered probit (HETOP) model compared to the standard ordered probit (OP) model in crash analysis, by examining the effect of gender across age on injury severity among drivers. This paper hypothesizes that the HETOP model can provide a better fit to crash data, by allowing heteroskedasticity in the distribution of injury severity across driver age and gender. Data for 20,222 crashes were analyzed for North Carolina from 2016 to 2018, which represents the state with the highest number of fatalities per 100 million vehicle miles traveled amongst available crash data from the Highway Safety Information System. Darker lighting conditions, severe road surface conditions, and less severe weather were associated with increased injury severity. For driver demographics, the probability of severe injuries increased with age and for male drivers. Moreover, the variance of severity increased with age disproportionately within and across genders, and the HETOP was able to account for this. The results of the two applied approaches revealed that HETOP model outperformed the standard OP model when measuring the effects of age and gender together in injury severity analysis, due to the heteroskedasticity in injury severity within gender and age. The HETOP statistical method presented in this paper can be more broadly applied across other contexts and combinations of independent variables for improved model prediction and accuracy of causal variables in traffic safety. [ABSTRACT FROM AUTHOR]

Drivers with a Commercial Driver's License (CDL) experience higher rates of fatal and serious injury crashes compared to non-commercial drivers. Emotional Intelligence (EI) has shown to be a significant predictor of dangerous driving among non-commercial drivers. However, there is limited research investigating EI within commercial drivers. This paper investigates the relationship between drivers' EI and dangerous driving behaviors, and how this differs between commercial (N = 595) and non-commercial (N = 615) drivers. A survey was conducted, where EI was measured using Trait Emotional Intelligence Questionnaire, and risky driving using Dula Dangerous Driving Questionnaire. Analyses confirmed (1) commercial drivers have lower EI than non-commercial (ANCOVA, p <.01); (2) commercial drivers are more likely to report more dangerous driving behaviors (MANCOVA, p <.01); and (3) lower EI is associated with increased dangerous driving, and these effects are strongest amongst commercial drivers (linear regression, p <.001). Promoting and improving EI can help prevent dangerous driving and reduce crash risk. [ABSTRACT FROM AUTHOR]

Shared electric scooters (e-scooters) offer a potential strategy to mitigate environmental concerns and congestion. However, successfully addressing these issues with e-scooters requires adoption across a diverse array of consumers. Understanding the differences between users and non-users can improve shared e-scooter appeal, operation and safety. The objective of this paper is to compare shared e-scooter users and non-users in terms of their perceptions on safety, trip behaviors, other shared modes, risk propensity and willingness to adopt technology. A survey was conducted involving 210 (51.3%) users and 199 (48.7%) non-users of shared e-scooters. Binary logistic regression and chi-squared tests were performed. The results reveal that users demonstrated a higher risk propensity and were more likely to be early adopters of new technologies. Non-users tended to place higher importance on helmet use, while users have an overall increased feeling of safety associated with riding e-scooters in vehicle lanes, on sidewalks and being passed by e-scooters as a pedestrian. Overall, users also have a more positive perception of e-scooter sanitary levels than non-users, and a more positive perception on the sanitary levels and usability of e-scooters over e-bicycles. These findings can provide guidance to urban planners, municipal authorities and micromobility providers in developing infrastructure and policies to better support micromobility adoption. [ABSTRACT FROM AUTHOR]

This study aims to identify expectations and perceptions of Passenger Air Vehicles (PAVs). Specifically, (1) what are the initial perceptions of PAVs by the public, and (2) what are the differences between early and laggard adopters of PAVs. The emergence of Urban Air Mobility presents an opportunity to increase transportation capacity in densely populated metropolitan areas. However, successful integration is largely dependent on adoption and acceptance from communities. A survey of 407 respondents across the United States provides insights from potential users. The Technology Adoption Life Cycle and Technology Acceptance Model are used to characterize adopter profiles and rates of adoption. Respondents not only expect the same level of safety standards as conventional aircraft (i.e., seatbelts, air quality), but even more feedback (i.e., displays on current and projected flight operations). PAVs are not an immediate replacement for daily trips once available. In-cabin noise is not a crucial deterrent to ridership. Earlier PAV adopters are trusting of the technology, willing to pay more to ride, and exhibit overall riskier behaviors. Later PAV adopters need more feedback in-flight and a pilot on-board. PAV manufacturers, operators, and policymakers can utilize these findings to incorporate crucial design elements needed for PAVs to satisfy user expectations. These findings identify priorities that should be targeted in relative timeframes to satisfy near-term and long-term PAV users appropriately. [ABSTRACT FROM AUTHOR]