67 research outputs found

    Solubilities of sub- and supercritical carbon dioxide in polyester resins

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    In supercritical carbon dioxide (CO2) assisted polymer processes the solubility of CO2 in a polymer plays a vital role. The higher the amount of CO2 dissolved in a polymer the higher is the viscosity reduction of the polymer. Solubilities Of CO2 in polyester resins based on propoxylated bisphenol (PPB) and ethoxylated bisphenol (PEB) have been measured using a magnetic suspension balance at temperatures ranging from 333 to 420 K and pressures up to 30 MPa. An optical cell has been used to independently determine the swelling of the polymers, which has been incorporated in the buoyancy correction. In both polyester resins, the solubility of CO, increases with increasing pressure and decreasing temperature as a result of variations in CO, density. The experimental solubility has been correlated to the Sanchez-Lacombe equation of state.</p

    A New Calibrated Bayesian Internal Goodness-of-Fit Method: Sampled Posterior p-Values as Simple and General p-Values That Allow Double Use of the Data

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    Background: Recent approaches mixing frequentist principles with Bayesian inference propose internal goodness-of-fit (GOF) p-values that might be valuable for critical analysis of Bayesian statistical models. However, GOF p-values developed to date only have known probability distributions under restrictive conditions. As a result, no known GOF p-value has a known probability distribution for any discrepancy function. Methodology/Principal Findings: We show mathematically that a new GOF p-value, called the sampled posterior p-value (SPP), asymptotically has a uniform probability distribution whatever the discrepancy function. In a moderate finite sample context, simulations also showed that the SPP appears stable to relatively uninformative misspecifications of the prior distribution. Conclusions/Significance: These reasons, together with its numerical simplicity, make the SPP a better canonical GOF p-value than existing GOF p-values

    Intravascular Ultrasound (IVUS): A Potential Arthroscopic Tool for Quantitative Assessment of Articular Cartilage

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    Conventional ultrasound examination of the articular cartilage performed externally on the body surface around the joint has limited accuracy due to the inadequacy in frequency used. In contrast to this, minimally invasive arthroscopy-based ultrasound with adequately high frequency may be a better alternative to assess the cartilage. Up to date, no special ultrasound transducer for imaging the cartilage in arthroscopic use has been designed. In this study, we introduced the intravascular ultrasound (IVUS) for this purpose. An IVUS system with a catheter-based probe (Ø ≈ 1mm) was used to measure the thickness and surface acoustical reflection of the bovine patellar articular cartilage in vitro before and after degeneration induced by enzyme treatments. Similar measurement was performed using another high frequency ultrasound system (Vevo) with a probe of much larger size and the results were compared between the two systems. The thickness measured using IVUS was highly correlated (r = 0.985, p < 0.001) with that obtained by Vevo. Thickness and surface reflection amplitude measured using IVUS on the enzymatically digested articular cartilage showed changes similar to those obtained by Vevo, which were expectedly consistent with previous investigations. IVUS can be potentially used for the quantitative assessment of articular cartilage, with its ready-to-use arthroscopic feature

    A System Dynamics Approach for Hospital Waste Management in a City in a Developing Country: The Case of Nablus, Palestine

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    Hospitals and health centers provide a variety of healthcare services and normally generate hazardous waste as well as general waste. General waste has a similar nature to that of municipal solid waste and therefore could be disposed of in municipal landfills. However, hazardous waste poses risks to public health, unless it is properly managed. The hospital waste management system encompasses many factors, i.e., number of beds, number of employees, level of service, population, birth rate, fertility rate, and not in my back yard (NIMBY) syndrome. Therefore, this management system requires a comprehensive analysis to determine the role of each factor and its influence on the whole system. In this research, a hospital waste management simulation model is presented based on the system dynamics technique to determine the interaction among these factors in the system using a software package, ithink. This model is used to estimate waste segregation as this is important in the hospital waste management system to minimize risk to public health. Real data has been obtained from a case study of the city of Nablus, Palestine to validate the model. The model exhibits wastes generated from three types of hospitals (private, charitable, and government) by considering the number of both inpatients and outpatients depending on the population of the city under study. The model also offers the facility to compare the total waste generated among these different types of hospitals and anticipate and predict the future generated waste both infectious and non-infectious and the treatment cost incurred

    Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

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    Introduction Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality. Methods Prospective cohort study in 109 institutions in 41 countries. Inclusion criteria: children &lt;18 years who were newly diagnosed with or undergoing active treatment for acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, retinoblastoma, Wilms tumour, glioma, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, medulloblastoma and neuroblastoma. Of 2327 cases, 2118 patients were included in the study. The primary outcome measure was all-cause mortality at 30 days, 90 days and 12 months. Results All-cause mortality was 3.4% (n=71/2084) at 30-day follow-up, 5.7% (n=113/1969) at 90-day follow-up and 13.0% (n=206/1581) at 12-month follow-up. The median time from diagnosis to multidisciplinary team (MDT) plan was longest in low-income countries (7 days, IQR 3-11). Multivariable analysis revealed several factors associated with 12-month mortality, including low-income (OR 6.99 (95% CI 2.49 to 19.68); p&lt;0.001), lower middle income (OR 3.32 (95% CI 1.96 to 5.61); p&lt;0.001) and upper middle income (OR 3.49 (95% CI 2.02 to 6.03); p&lt;0.001) country status and chemotherapy (OR 0.55 (95% CI 0.36 to 0.86); p=0.008) and immunotherapy (OR 0.27 (95% CI 0.08 to 0.91); p=0.035) within 30 days from MDT plan. Multivariable analysis revealed laboratory-confirmed SARS-CoV-2 infection (OR 5.33 (95% CI 1.19 to 23.84); p=0.029) was associated with 30-day mortality. Conclusions Children with cancer are more likely to die within 30 days if infected with SARS-CoV-2. However, timely treatment reduced odds of death. This report provides crucial information to balance the benefits of providing anticancer therapy against the risks of SARS-CoV-2 infection in children with cancer

    ICAR: endoscopic skull‐base surgery

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    Membrane technology for the regeneration of supercritical carbon dioxide

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