Surface seal image dataset of sterile barrier packaging.

This manuscript delineates the constitution of a dataset engineered to bolster research endeavours in the realm of automated inspection of seals pertinent to Medical Device Packaging. The compendium encompasses a total of 1200 images of medical device pouches, with an equitable distribution between intact seals and those exhibiting defects. Each image boasts dimensions of 3008 by 4110 by 3 pixels.

An Update on Pediatric Environmental Health Specialty Units: Activities and Impacts, 2015-19.

Objective: Pediatric Environmental Health Specialty Units (PEHSUs) address health concerns impacting children and their families related to environmental hazards by providing consultation and education to families, communities, and health care professionals. This analysis evaluated the productivity of the national PEHSU program.

Methods: PEHSUs reported data on services provided to US communities between October 1, 2014 and September 30, 2019.

Addressing Emerging Needs Through the COVID-19 and Children With Medical Complexity ECHO.

The COVID-19 and Children with Medical Complexity (CMC) Extension for Community Healthcare Outcomes (ECHO) was developed as a "just in time" learning format to respond to the vast number of challenges faced by health care clinicians, public health professionals, and families/caregivers of CMC during the coronavirus disease 2019 (COVID-19) pandemic. A unique aspect of the ECHO was the meaningful integration of family leaders who participated as faculty, learners, case study presenters, and guest lecturers. Another distinguishing feature of this ECHO was its inclusion within a Collaborative Improvement and Innovation Network.

Assessing the physiological effect of non-driving-related task performance and task modality in conditionally automated driving systems: A systematic review and meta-analysis.

In conditionally automated driving, the driver is free to disengage from controlling the vehicle, but they are expected to resume driving in response to certain situations or events that the system is not equipped to respond to. As the level of vehicle automation increases, drivers often engage in non-driving-related tasks (NDRTs), defined as any secondary task unrelated to the primary task of driving. This engagement can have a detrimental effect on the driver's situation awareness and attentional resources.

Assessing the physiological effect of non-driving-related task performance in conditionally automated driving systems: A systematic review and meta-analysis protocol.

Background: Level 3 automated driving systems involve the continuous performance of the driving task by artificial intelligence within set environmental conditions, such as a straight highway. The driver's role in Level 3 is to resume responsibility of the driving task in response to any departure from these conditions. As automation increases, a driver's attention may divert towards non-driving-related tasks (NDRTs), making transitions of control between the system and user more challenging.

C3I-SynFace: A synthetic head pose and facial depth dataset using seed virtual human models.

This article presents C3I-SynFace: a large-scale synthetic human face dataset with corresponding ground truth annotations of head pose and face depth generated using the iClone 7 Character Creator "Realistic Human 100" toolkit with variations in ethnicity, gender, race, age, and clothing. The data is generated from 15 female and 15 male synthetic 3D human models extracted from iClone software in FBX format. Five facial expressions - neutral, angry, sad, happy, and scared are added to the face models to add further variations.

DroneAttention: Sparse weighted temporal attention for drone-camera based activity recognition.

Human activity recognition (HAR) using drone-mounted cameras has attracted considerable interest from the computer vision research community in recent years. A robust and efficient HAR system has a pivotal role in fields like video surveillance, crowd behavior analysis, sports analysis, and human-computer interaction. What makes it challenging are the complex poses, understanding different viewpoints, and the environmental scenarios where the action is taking place.

3D face-model reconstruction from a single image: A feature aggregation approach using hierarchical transformer with weak supervision.

Convolutional Neural Networks (CNN) have gained popularity as the de-facto model for any computer vision task. However, CNN have drawbacks, i.e.

An Innovative Approach to Increase Lead Testing by Pediatricians in Children, United States, 2019-2021.

Opportunities for lead exposure are common in the United States. The American Academy of Pediatrics, in collaboration with the Centers for Disease Control and Prevention, launched the Increasing Capacity for Blood Lead Testing Extension for Community Healthcare Outcomes (ECHO) project to educate pediatricians on the importance of testing children for lead exposure and to assess practice behavior change. We found that two weeks to one month after receiving training, more than 80% of participants reported increased lead testing and practice changes.

The Power of Connections: AAP COVID-19 ECHO Accelerates Responses During a Public Health Emergency.

Context: Pediatric providers across the United States have sought guidance on how to care for the nation's children during the uncertain historic times of the COVID-19 pandemic. The health care community has been challenged by the unprecedented burden of caring for patients when they have evolving guidelines and limited information about the effects of the virus on children.

Program: In response, the American Academy of Pediatrics (AAP) rapidly launched a national initiative to increase child health professionals' knowledge, skills, and self-efficacy.

An efficient encoder-decoder model for portrait depth estimation from single images trained on pixel-accurate synthetic data.

Depth estimation from a single image frame is a fundamental challenge in computer vision, with many applications such as augmented reality, action recognition, image understanding, and autonomous driving. Large and diverse training sets are required for accurate depth estimation from a single image frame. Due to challenges in obtaining dense ground-truth depth, a new 3D pipeline of 100 synthetic virtual human models is presented to generate multiple 2D facial images and corresponding ground truth depth data, allowing complete control over image variations.

Development of Open-source Software and Gaze Data Repositories for Performance Evaluation of Eye Tracking Systems.

In this paper, a range of open-source tools, datasets, and software that have been developed for quantitative and in-depth evaluation of eye gaze data quality are presented. Eye tracking systems in contemporary vision research and applications face major challenges due to variable operating conditions such as user distance, head pose, and movements of the eye tracker platform. However, there is a lack of open-source tools and datasets that could be used for quantitatively evaluating an eye tracker's data quality, comparing performance of multiple trackers, or studying the impact of various operating conditions on a tracker's accuracy.

Deep neural network and data augmentation methodology for off-axis iris segmentation in wearable headsets.

A data augmentation methodology is presented and applied to generate a large dataset of off-axis iris regions and train a low-complexity deep neural network. Although of low complexity the resulting network achieves a high level of accuracy in iris region segmentation for challenging off-axis eye-patches. Interestingly, this network is also shown to achieve high levels of performance for regular, frontal, segmentation of iris regions, comparing favourably with state-of-the-art techniques of significantly higher complexity.

Performance Evaluation Strategies for Eye Gaze Estimation Systems with Quantitative Metrics and Visualizations.

An eye tracker's accuracy and system behavior play critical roles in determining the reliability and usability of eye gaze data obtained from them. However, in contemporary eye gaze research, there exists a lot of ambiguity in the definitions of gaze estimation accuracy parameters and lack of well-defined methods for evaluating the performance of eye tracking systems. In this paper, a set of fully defined evaluation metrics are therefore developed and presented for complete performance characterization of generic commercial eye trackers, when they operate under varying conditions on desktop or mobile platforms.

An end to end Deep Neural Network for iris segmentation in unconstrained scenarios.

With the increasing imaging and processing capabilities of today's mobile devices, user authentication using iris biometrics has become feasible. However, as the acquisition conditions become more unconstrained and as image quality is typically lower than dedicated iris acquisition systems, the accurate segmentation of iris regions is crucial for these devices. In this work, an end to end Fully Convolutional Deep Neural Network (FCDNN) design is proposed to perform the iris segmentation task for lower-quality iris images.

Dynamic Sensitivity of Corneal TRPM8 Receptors to Menthol Instillation in Dry Eye Versus Normal Subjects.

Purpose: To assess the sensitivity of corneal cold receptors to a known transient receptor potential melastatin 8 (TRPM8) agonist, menthol, in dry eye and normals, and to determine whether factors such as disease duration or age affect responses.

Methods: Dry eye disease (DED) (N = 33) and normal (N = 15) subjects were randomly assigned to receive Rohto Hydra (0.01% menthol) or Systane Ultra treatments (OU) in a prospective, double-blind, crossover study.

Variable Efficacy of Extended-release Mosquito Larvicides Observed in Catch Basins in the Northeast Chicago Metropolitan Area.

Since the mid-1990s, the North Shore Mosquito Abatement District (NSMAD) has applied extended-release formulations of mosquito larvicides to approximately 50,000 catch basins in the suburbs north of Chicago, IL, USA. This is performed as part of NSMAD's efforts to reduce local populations of the West Nile virus vector, Culex pipiens. Analyses from NSMAD's monitoring of larvicide-treated basins throughout the District over the 2014 and 2015 seasons suggest that larvicides intended to provide extended durations of control (30-180 days) failed to provide control for the maximum duration specified on the product label in approximately 25% of the District's basins.

Small-Scale Trials Suggest Increasing Applications of Natular™ XRT and Natular™ T30 Larvicide Tablets May Not Improve Mosquito Reduction in Some Catch Basins.

Stormwater catch basins are commonly treated with larvicides by mosquito control agencies to reduce local populations of mosquito species capable of transmitting West Nile virus. Recent evidence suggests that extended-release larvicides formulated to last up to 180 days in catch basins may not be effective in some basins due to chronic flushing, rapid dissolution, or burying of treatment in sump debris. To investigate if increasing the number of applications could improve effectiveness, a small study was performed over 13 weeks in 2015 to evaluate two extended-release larvicides (Natular™ XRT 180-day tablets and Natular™ T30 30-day tablets) and a larvicide oil (CocoBear™).

Permissiveness of human hepatoma cell lines for HCV infection.

Background: Although primary and established human hepatoma cell lines have been evaluated for hepatitis C virus (HCV) infection in vitro, thus far only Huh7 cells have been found to be highly permissive for infectious HCV. Since our understanding of the HCV lifecycle would benefit from the identification of additional permissive cell lines, we assembled a panel of hepatic and non-hepatic cell lines and assessed their ability to support HCV infection. Here we show infection of the human hepatoma cell lines PLC/PRF/5 and Hep3B with cell culture-derived HCV (HCVcc), albeit to lower levels than that achieved in Huh7 cells.

The rate of hepatitis C virus infection initiation in vitro is directly related to particle density.

To gain a more complete understanding of hepatitis C virus (HCV) entry, we initially assessed the rate at which HCV initiates productive attachment/infection in vitro and discovered it to be slower than most viruses. Since HCV, including cell culture-derived HCV (HCVcc), exhibits a broad-density profile (1.01-1.

On color texture normalization for active appearance models.

The extension of the standard grayscale active appearance model (AAM) techniques to color images is investigated. Prior work in this field has mainly focused on RGB color models which did not demonstrate noticeable benefits over grayscale models from the point of view of convergence accuracy. We improve on previous work by normalizing the color texture vector separately for intensity and chromaticity components.