Impact of Aspiration in the Assessing Process of Pediatric Lung Disease

This study aimed at analyzing the impact of Aspiration in the assessing process of pediatric lung disease, as the affected children will frequently encounter a situation where swallowing is insecure and aspiration is likely. Besides analyzing the Aspiration of foreign matter into the airways and lungs that can cause a wide spectrum of pulmonary disorders with various presentations. And discussing the type of syndrome resulting from aspiration depends on the quantity and nature of the aspirated material, the chronicity, and the host responses. Considering that Aspiration is most likely to occur in subjects with a decreased level of consciousness, compromised airway defense mechanisms, dysphagia, gastroesophageal reflux, and recurrent vomiting

A Framework for Advanced Video Traces: Evaluating Visual Quality for Video Transmission Over Lossy Networks

Conventional video traces (which characterize the video encoding frame sizes in bits and frame quality in PSNR) are limited to evaluating loss-free video transmission. To evaluate robust video transmission schemes for lossy network transport, generally experiments with actual video are required. To circumvent the need for experiments with actual videos, we propose in this paper an advanced video trace framework. The two main components of this framework are (i) advanced video traces which combine the conventional video traces with a parsimonious set of visual content descriptors, and (ii) quality prediction schemes that based on the visual content descriptors provide an accurate prediction of the quality of the reconstructed video after lossy network transport. We conduct extensive evaluations using a perceptual video quality metric as well as the PSNR in which we compare the visual quality predicted based on the advanced video traces with the visual quality determined from experiments with actual video. We find that the advanced video trace methodology accurately predicts the quality of the reconstructed video after frame losses.</p

Modeling the performance of healthcare construction projects

Purpose Healthcare-sector projects are some of the most complex in modern practice due to their reliance on high-tech components and the level of precision they must maintain. Existing literature in healthcare performance specifically is scarce, but there is a recent increasing trend in both healthcare construction and a corresponding trend in related literature. No previously existing study has derived weights (relative importance) of performance metric in an objective, data-based manner. The purpose of this paper is to present a newly developed mathematical model that derives these weights, free of subjectivity that is common in other literature. Design/methodology/approach This paper’s model considers 17 exceptional projects and 19 average projects, and reveals the weights (or relative importance) of ten performance metrics by comparing how projects relate to one another in terms of each metric individually. It solves an eigenvalue problem that maximizes the difference between average and exceptional project performances. Findings The most significant weight, i.e. the performance metric which has the greatest impact on healthcare project performance, was request for information per million dollars with a weight of 16.07 percent. Other highly weighted metrics included construction speed and schedule growth at 13.08 and 12.23 percent, respectively. Rework was the least significant metric at 3.61 percent, but not all metrics of quality had low ratings. Deficiency issues per million dollars was weighted at 11.61 percent, for example. All weights derived by the model in this paper were validated statistically to ensure their applicability as comparison and assessment tools. Originality/value There is no widely accepted measure of project performance specific to healthcare construction. This study’s contribution to the body of knowledge is its mathematical model which is a landmark effort to develop a single, objective, unified project performance index for healthcare construction. Furthermore, this unified score presents a user-friendly avenue for contractors to standardize their productivity tracking – a missing piece in the practices of many contractors. </jats:sec

Palliative care management of head and neck cancer patients among otolaryngology surgeons: a novel national survey assessing knowledge, decision making, perceived confidence and training in the UK

AbstractObjectiveManagement of head and neck cancer patients provides unique challenges. Palliation serves to optimise quality-of-life by alleviating suffering and maintaining dignity. Prompt recognition and management of suffering is paramount to achieving this. This study aimed to assess perceived confidence, knowledge and adequacy of palliative training among UK-based otolaryngologists.MethodEight multiple-choice questions developed by five palliative care consultants via the Delphi method were distributed over five weeks. Knowledge, perceived confidence and palliative exposure among middle-grade and consultant otolaryngologists were assessed, alongside training deficits.ResultsOverall, 145 responses were collated from middle-grade (n = 88, 60.7 per cent) and consultant (n = 57, 39.3 per cent) otolaryngologists. The mean knowledge score was 5 out of 10, with 22.1 per cent (n = 32) stating confidence in palliative management. The overwhelming majority (n = 129, 88.9 per cent) advocated further training.ConclusionA broad understanding of palliative care, alongside appropriate specialist involvement, is key in meeting the clinical needs of palliative patients. Curriculum integration of educational modalities such as simulation and online training may optimise palliative care.</jats:sec

A data-driven approach for identifying project manager competency weights

Competent project managers (PMs) are the backbone of any construction project. It is extremely important to constantly develop and enhance their competencies. However, to establish effective training and development plans for PMs, the relative importance of the key competencies that define a PM’s performance should be first understood. Instead of subjectively weighting the relative importance of differing competencies, this paper aims at developing an automated model that uses real-life data to compute the PM competency weights. The rationale behind the model is to maximize the distance in a higher dimensional space between average and exceptional PM performances. The model solves an eigenvalue problem, and identifies a single data-based weight for each competency. The model is generic and can be applied to various research settings to alleviate the problems associated with opinion-based assessment and reduce individuals’ subjectivity. Findings within this paper reveal the most critical competencies that enable PMs to perform their roles in construction projects exceptionally. </jats:p