OAK (Online Access to Knowledge) Commons (Young Harris College)
Not a member yet
33676 research outputs found
Sort by
Insufficient respiratory hazard identification in the Safety Data Sheets for cleaning and disinfection products used in healthcare organisations across England and Wales
No full textBackground Exposure to cleaning and disinfection products has been associated with respiratory disorders such as asthma in cleaning and healthcare workers. Safety Data Sheets (SDSs) provide information on hazardous chemicals that are present in products to help users with risk assessment and implement appropriate control measures. However, they have potential limitations in identifying respiratory hazards due to a lack of regulatory test methods for respiratory sensitisation and irritation of chemicals.Methods SDSs were first used to identify chemicals on the database as respiratory sensitisers and irritants. A quantitative structure-activity relationship (QSAR) model and an asthmagen list established by the Association of Occupational and Environmental Clinics (AOEC) were used toidentify potential respiratory sensitisers and irritants (by the AOEC list only) in the cleaning and disinfection products.Results From a total of 459 cleaning and disinfection products used in healthcare organisations across England and Wales, 35 respiratory sensitisers not labelled as such on the SDS were identified by QSAR or AOEC. Only 2% of cleaning and disinfection products contained at least one respiratory sensitiser as identified by their SDSs; this was increased to 37.7% of products when the QSAR or theAOEC list was used.Conclusions A significantly higher proportion of cleaning products contain respiratory hazardous chemicals, particularly respiratory sensitisers than would be expected from the information provided by SDSs alone. Cleaners and health care workers may therefore be insufficiently protected
Novel eco-efficient process for methyl methacrylate production
No full textMethyl methacrylate (MMA) is an essential chemical used as raw material for the production of other methacrylates and poly-MMA. There are various chemistry routes, available or not at industrial scale, to produce MMA. These routes use the same or different raw materials, and present common chemistry and processing steps. Many of these routes though, have as final step the esterification of methacrylic acid (MAA) with methanol (MeOH) to obtain MMA. However, there is no complete process described in the literature for this final esterification step. This paper is the first to propose a solid-based catalytic process for MMA production starting from MAA and MeOH, in a continuous reaction-separation-recycle (RSR) system. In this specific case, the RSR system is more suitable than reactive distillation due to the unfavorable ranking of boiling points and also due to the presence of several potentially hindering azeotropes. This work also provides an original framework for simulation of other MMA processes, by deriving detailed equilibrium and kinetic parameters based on literature experimental data. Rigorous process simulations are carried out in Aspen Plus and Aspen Plus Dynamics for the design and control of the new process. The flowsheet consists mainly of a fixed-bed tubular reactor followed by a sequence of three distillation columns coupled with a decanter. The results show that the process is technically feasible, cost effective in terms of total annualized costs, and with excellent sustainability metrics, requiring only 2.05 MJ/kg of MMA produced
Group Decision Making with Hesitant Fuzzy Linguistic Preference Relations Based on Modified Extent Measurement
No full textPhotons, Protons, SBRT, Brachytherapy- What is leading the charge for the management of prostate cancer? A Perspective From the GU Editorial Team
No full textThe Relation between Rheumatoid Arthritis and Diabetes Mellitus: a Systematic Review and Meta-Analysis
No full textObjectives This systematic review and meta-analysis was conducted to investigate the relationship between rheumatoid arthritis (RA) and the incidence of diabetes mellitus (DM). Methods A comprehensive search was conducted up to March 10, 2020 in Medline (via Ovid), Embase (via Ovid) and Web of science core collection to identify cohort studies comparing the risk of DM incidence in people with RA with the general population. The I2 statistic was used to test heterogeneity. Pooled relative risks (RR) were calculated using random-effects models. Publication bias was assessed using funnel plot, Egger’s test and Begg’s test. Results The initial search provided 3,669 articles. Of those, five journal articles and two conference abstracts comprising 1,629,854 participants were included in this study. The funnel plot showed potential publication bias, proven by Egger’s test (-3.15, P<0.01), but not Begg’s test (-0.05, P=1.00). Heterogeneity was observed in I2 test (I2=96%, P<0.01). We found that RA was associated with a higher risk of DM incidence (pooled RR 1.23; 95% CI 1.07-1.40). Exploration of potential sources of heterogeneity found significant heterogeneity among different countries or regions (P=0.002), but heterogeneity was not significant for differing study designs (P=0.30). Sensitivity analyses confirmed that the association between rheumatoid arthritis and diabetes mellitus incidence was robust. Conclusion RA is associated with an increased risk of diabetes incidence. This finding supports the notion that inflammatory pathways are involved in the pathogenesis of diabetes. More intensive intervention to target diabetes risk factors should be considered in people with RA
Operational optimization of cyclic gas pipeline network with consideration of thermal hydraulics
No full textFollowing the rapidly increasing global demand for natural gas, many countries are launching projects to expand gas pipeline networks (GPNs). As a result, more cyclic GPNs are under construction with more rigorous physical constraints required, bringing new challenges to GPNs optimization. This paper proposes a novel nonconvex mixed-integer nonlinear programming (MINLP) formulation for operational optimization of the cyclic GPN with simultaneous consideration of thermal hydraulics and flow direction reversibility, which has not been explored in the literature. To solve the proposed MINLP model, a three-level decomposition algorithm is proposed to generate an approximate solution, from which the flow direction is extracted and used to fix all discrete variables in the original MINLP model to construct two-stage NLP models. The NLP models are then solved to improve solution feasibility and quality. The computational results show that the proposed approach outweighs several state-of-the-art commercial MINLP solvers with better solutions and shorter computational time
Experiences of acute mental health inpatient care in the UK: From admission to readmission
No full textEight service users with experiences of psychosis were interviewed about the support provided by mental services before, during and after acute mental health inpatients admissions in the UK. All participants had at least one other admission to an acute mental health ward in the preceding six months. Interviews were analysed using Interpretative Phenomenological Analysis. Three themes were identified: 1) Quality of therapeutic relationships, 2) Adjusting to sudden shifts in care, 3) Struggling without the ward environment. Although participants acknowledged positive care experiences within their narratives, significant challenges were evident in the abilities of services to effectively meet service users’ needs across the care pathway. Findings highlight the importance of consistent support centred on service users’ needs at all stages of care. Service users need support to build autonomy and coping skills to sustain meaningful recovery within the community and reduce the likelihood of readmission
Drone Mobile Networks: Performance Analysis under 3D Tractable Mobility Models
No full textReliable wireless communication networks are a significant but challenging mission for post-disaster areas and hotspots in the era of information. However, with the maturity of unmanned aerial vehicle (UAV) technology, drone mobile networks have attracted considerable attention as a prominent solution for facilitating critical communications. This paper provides a system-level analysis for drone mobile networks ona finite three-dimensional (3D) space. Our aim is to explore the fundamental performance limits of drone mobile networks taking into account practical considerations. Most existing works on mobile drone networks use simplified mobility models (e.g., fixed height), but the movement of the drones in practice is significantly more complicated, which leads to difficulties in analyzing the performance of the drone mobile networks. Hence, to tackle this problem, we propose a stochastic geometry-based framework with a number of different mobility models including a randomBrownian motion approach. The proposed framework allows to circumvent the extremely complex reality model and obtain upper and lower performance bounds for drone networks in practice. Also, we explicitly consider certain constraints, such as the smallscale fading characteristics relying on line-of-sight (LOS) and non line-of-sight (NLOS) propagation, and multi-antenna operations. The validity of the mathematical findings is verified via Monte-Carlo (MC) simulations for various network settings. In addition, the results reveal some design guidelines and important trends for the practical deployment of drone networks
Approximate models for the lattice thermal conductivity of alloy thermoelectrics
No full textThermoelectric generators (TEGs) convert waste heat to electricity and are a leading contender for improving energy efficiency at a range of scales. Ideal TE materials show a large Seebeck effect, high electrical conductivity, and low thermal conductivity. Alloying is a widely-used approach to engineering the heat transport in TEs, but despite many successes the underlying mechanisms are poorly understood. In previous work, first-principles modelling has successfully been used to study the thermodynamics of alloy formation and to investigate its effect on the electronic structure and phonon spectrum. However, it has so far only been possible to examine qualitatively the impact of alloying on the lattice thermal conductivity. In this work, we develop and test two new approaches to addressing this. The constant relaxation-time approximation (CRTA) assumes the primary effect of alloying is on the phonon group velocities, and allows the thermal conductivity to be calculated assuming a suitable constant lifetime. Alternatively, setting the three-phonon interaction strengths to a constant further enables an assessment of how changes to the phonon frequency spectrum influence the lifetimes. We test both approaches for the Pnma Sn(S1-xSex) alloy system and are able to account for the substantially-reduced thermal conductivity measured in experiments
