A review of imaging in the diagnosis and management of complicated paediatric pneumonia.

Paediatric pneumonia and its complications present substantial health and economic challenges. While chest radiographs are commonly used as the initial imaging modality for diagnosing uncomplicated pneumonia, they are less effective for complicated cases. In response, various imaging techniques, such as lung ultrasound, computed tomography (CT), and chest MRI, have been integrated into clinical practice to enhance diagnosis and guide management decisions.

Real-time risk estimation for active road safety: Leveraging Waymo AV sensor data with hierarchical Bayesian extreme value models.

Near-miss traffic risk estimation using Extreme Value Theory (EVT) models within a real-time framework offers a promising alternative to traditional historical crash-based methods. However, current approaches often lack comprehensive analysis that integrates diverse roadway geometries, crash patterns, and two-dimensional (2D) vehicle dynamics, limiting both their accuracy and generalizability. This study addresses these gaps by employing a high-fidelity, 2D time-to-collision (TTC) near-miss indicator derived from autonomous vehicle (AV) sensor data.

The negative Binomial-Lindley model with Time-Dependent Parameters: Accounting for temporal variations and excess zero observations in crash data.

Crash counts are non-negative integer events often analyzed using crash frequency models such as the negative binomial (NB) distribution. However, due to their random and infrequent nature, crash data usually exhibit unique characteristics, such as excess zero observations that the NB distribution cannot adequately model. The negative binomial-Lindley (NBL) and random parameters negative binomial-Lindley (RPNBL) models have been proposed to address this limitation.

Analyzing fatal crash patterns of recidivist drivers across genders and age Groups: A hazard-based duration approach.

Identifying factors that significantly affect drivers that are repeatedly involved in traffic violations or non-fatal crashes (defined here as recidivist drivers) is very important in highway safety studies. This study sought to understand the relationship between a set of variables related to previous driving violations and the duration between a previous non-fatal crash and a subsequent fatal crash, taking into account the age and gender of the driver. By identifying the characteristics of this unique driver population and the factors that influence the duration between their crash events strategies can be put in place to prevent the occurrence of future and potentially fatal crashes.

Estimating the effectiveness of marked sidewalks: An application of the spatial causality approach.

Various safety enhancements and policies have been proposed to enhance pedestrian safety and minimize vehicle-pedestrian accidents. A relatively recent approach involves marked sidewalks delineated by painted pathways, particularly in Asia's crowded urban centers, offering a cost-effective and space-efficient alternative to traditional paved sidewalks. While this measure has garnered interest, few studies have rigorously evaluated its effectiveness.

Classification of autonomous vehicle crash severity: Solving the problems of imbalanced datasets and small sample size.

Only a few researchers have shown how environmental factors and road features relate to Autonomous Vehicle (AV) crash severity levels, and none have focused on the data limitation problems, such as small sample sizes, imbalanced datasets, and high dimensional features. To address these problems, we analyzed an AV crash dataset (2019 to 2021) from the California Department of Motor Vehicles (CA DMV), which included 266 collision reports (51 of those causing injuries). We included external environmental variables by collecting various points of interest (POIs) and roadway features from Open Street Map (OSM) and Data San Francisco (SF).

Beyond 1D and oversimplified kinematics: A generic analytical framework for surrogate safety measures.

This paper presents a generic analytical framework tailored for surrogate safety measures (SSMs) that is versatile across various highway geometries, capable of encompassing vehicle dynamics of differing dimensionality and fidelity, and suitable for dynamic, real-world environments. The framework incorporates a generic vehicle movement model, accommodating a spectrum of scenarios with varying degrees of complexity and dimensionality, facilitating the estimation of future vehicle trajectory evolution. It establishes a generic mathematical criterion to denote potential collisions, characterized by the spatial overlap between a vehicle and any other entity.

Vein of Galen Aneurysmal Malformation: A Case Report.

Vein of Galen aneurysmal malformation is a relatively rare disease in which failure of the median prosencephalic vein of Markowski to involute early in gestation leads to a grossly dilated deep cerebral vein with multiple arterial feeders, causing a large arteriovenous shunt which leads to high-output cardiac failure. We describe a case of a term neonate who presented to a tertiary neonatal centre on day one of life with history, symptoms, and signs consistent with perinatal asphyxia; however, in the context of worsening multi-organ dysfunction and cardiomegaly, the infant was found to have a severe vein of Galen aneurysmal dilatation leading to high-output cardiac failure. The patient was transferred to a tertiary paediatric hospital and underwent a total of four coiling procedures to embolise the multiple feeder arteries supplying the aneurysmal malformation.

Functional screening in human HSPCs identifies optimized protein-based enhancers of Homology Directed Repair.

Homology Directed Repair (HDR) enables precise genome editing, but the implementation of HDR-based therapies is hindered by limited efficiency in comparison to methods that exploit alternative DNA repair routes, such as Non-Homologous End Joining (NHEJ). In this study, we develop a functional, pooled screening platform to identify protein-based reagents that improve HDR in human hematopoietic stem and progenitor cells (HSPCs). We leverage this screening platform to explore sequence diversity at the binding interface of the NHEJ inhibitor i53 and its target, 53BP1, identifying optimized variants that enable new intermolecular bonds and robustly increase HDR.

Exploring the spatial relationship of e-bike and motorcycle crashes: Implications for risk reduction.

Introduction: Electric bicycles, or e-bikes, have become very popular over the past decade. In order to reduce the risk of crashes, it is necessary to understand the contributing factors. While several researchers have examined these elements, few have considered the spatial heterogeneity between crashes and environmental variables, such as Points of Interest (POI).

Assessing the collective safety of automated vehicle groups: A duration modeling approach of accumulated distances between crashes.

Ideally, the evaluation of automated vehicles would involve the careful tracking of individual vehicles and recording of observed crash events. Unfortunately, due to the low frequency of crash events, such data would require many years to acquire, and potentially place the motorized public at risk if defective automated technologies were present. To acquire information on the safety effectiveness of automated vehicles more quickly, this paper uses the collective crash histories of a group of automated vehicles, and applies a duration modeling approach to the accumulated distances between crashes.

Illuminating protein space with a programmable generative model.

Three billion years of evolution has produced a tremendous diversity of protein molecules, but the full potential of proteins is likely to be much greater. Accessing this potential has been challenging for both computation and experiments because the space of possible protein molecules is much larger than the space of those likely to have functions. Here we introduce Chroma, a generative model for proteins and protein complexes that can directly sample novel protein structures and sequences, and that can be conditioned to steer the generative process towards desired properties and functions.

Stability of factors influencing walking-along-the-road pedestrian injury severity outcomes under different lighting conditions: A random parameters logit approach with heterogeneity in means and out-of-sample predictions.

Pedestrians walking along the road's edge are more exposed and vulnerable than those on designated crosswalks. Often, they remain oblivious to the imminent perils of potential collisions with vehicles, making crashes involving these pedestrians relatively unique compared to others. While previous research has recognized that the surrounding lighting conditions influence traffic crashes, the effect of different lighting conditions on walking-along-the-road pedestrian injury severity outcomes remains unexplored.

Examining the performance of engineering treatment evaluation methodologies using the hypothetical treatment and actual treatment settings.

The selection of treatment evaluation methodology is paramount in determining reliable crash modification factors (CMFs) for engineering treatments. A lack of ground truth makes it cumbersome to examine the performance of treatment evaluation methodologies. In addition, a sound methodological framework is critical for evaluating the performances of treatment evaluation methodologies.

MqsR is a noncanonical microbial RNase toxin that is inhibited by antitoxin MqsA via steric blockage of substrate binding.

The MqsRA toxin-antitoxin system is a component of the Escherichia coli stress response. Free MqsR, a ribonuclease, cleaves mRNAs containing a 5'-GC-3' sequence causing a global shutdown of translation and the cell to enter a state of dormancy. Despite a general understanding of MqsR function, the molecular mechanism(s) by which MqsR binds and cleaves RNA and how one or more of these activities is inhibited by its cognate antitoxin MqsA is still poorly understood.

Finite mixture Negative Binomial-Lindley for modeling heterogeneous crash data with many zero observations.

Crash data are often highly dispersed; it may also include a large amount of zero observations or have a long tail. The traditional Negative Binomial (NB) model cannot model these data properly. To overcome this issue, the Negative Binomial-Lindley (NB-L) model has been proposed as an alternative to the NB to analyze data with these characteristics.

Costs of Specialist Referrals From Employer-Sponsored Integrated Health Care Clinics Are Lower Than Those From Community Providers.

Background: There have been very few published studies of referral management among commercially insured populations and none on referral management from employer-sponsored health centers.

Objective: Describe the referral management system of an integrated employer-sponsored health care system and compare specialist referral rates and costs of specialist visits between those initiated from employer-sponsored health clinics and those initiated from community providers.

Design: Retrospective, comparative cohort study using multivariate analysis of medical claims comparing care initiated in employer-sponsored health clinics with propensity-matched controls having specialist referrals initiated by community providers.

Employer-Sponsored Health Centers Provide Access to Integrated Care via a Hybrid of Virtual and In-Person Visits.

Since the explosion of telemedicine resulting from the SARS-CoV2 pandemic, employers have been particularly interested in virtual primary care as a novel means of expanding primary care services. The purpose of this study is to describe a model of integrated care delivered both in-person and virtually at employer-sponsored health centers nationwide. The key outcomes of this analysis were the proportion of all care delivered in-person and virtually by clinical discipline, the types of care and member satisfaction for care delivered in-person and virtually, and a description of the use of multiple clinical disciplines by the employee population.

Pediatric empyema: Are ultrasound characteristics at the time of intervention predictive of reintervention?

Background: Parapneumonic effusions and empyema are the most frequent complication of pediatric pneumonia. Interventions include chest drain and fibrinolytics (CDF) or thoracoscopic surgery. CDF is considered less invasive, and more cost-effective though with higher rates of reintervention.

Derivation of the Empirical Bayesian method for the Negative Binomial-Lindley generalized linear model with application in traffic safety.

The expected crash frequency is the long-term average crash count for a specific site. It is extensively used to systematically evaluate the crash risk associated with roadway elements. To estimate the expected crashes, the Empirical Bayesian (EB) approach is typically employed.

Alcohol-impaired motorcyclists versus car drivers: A comparison of crash involvement and legal consequence from adjudication data.

Introduction: Driving under the influence (DUI) increases the probability of motor-vehicle collisions, especially for motorcycles with less protections. This study aimed to identify commonalities and differences between criminally DUI offenses (i.e.

Application of different negative binomial parameterizations to develop safety performance functions for non-federal aid system roads.

Safety performance functions (SPFs) are the main building blocks in understanding the relationships between crash risk factors and crash frequencies. Many research efforts have focused on high-volume roadways that typically experience more crashes. A few studies have documented SPFs for non-federal aid system (NFAS) roads including rural minor collectors, rural local roads, and urban local roads.

Toward a crowdsourcing solution to identify high-risk highway segments through mining driving jerks.

Traffic crashes have become a leading cause of preventable deaths globally. Identifying high-risk segments not only benefits safety specialists to better understand crash patterns but also reminds road users to be aware of driving risks. This study reports on a new crowdsourcing solution to identify high-risk highway segments by analyzing driving jerks.

A visual approach for defining the spatial relationships among crashes, crimes, and alcohol retailers: Applying the color mixing theorem to define the colocation pattern of multiple variables.

In traffic safety studies, the few scholars who have focused on analyzing disaggregated data obtained results that have been either difficult to explain or demonstrate because they did not provide clear visual maps or utilize statistical tests to quantify the spatial relationships. In order to increase the use of such disaggregated spatial methods for use in traffic safety studies, the current study documents the application of a new RGB (red, green, blue) model which combines the color additive theorem and the kernel density map (KDE) to define crash colocation patterns and the coincidence spaces of related variables. This study contributes to the literature in three major ways: (1) a new RGB model was established and applied in the field of traffic safety; (2) the variable dimensions were expanded from two to three; and, (3) the dimension of uncertainty was also included.

Examining driver distraction in the context of driving speed: An observational study using disruptive technology and naturalistic data.

Considering the number of people who have been involved in crashes associated with driver distractions, it is important to understand the characteristics of distracted driving on public roadways. While experiments have indicated that driver distractions are associated with slower driving speeds, the methodologies tend to have limited external validity. Observational studies are often conducted under limited circumstances - be it time or location.