19684 research outputs found
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Glove breach occurrence during surgical procedures:the benefits of double/indicator system gloves
No full textBackground: The use of gloves during surgery aims at preventing surgical site infections (SSIs) and to protect both staff and patients from cross-contamination. Aim: To assess the rate of surgical glove breaches, whether these pose an increased risk of infection, and, if so, how might this be overcome (using double/indicator system glove techniques). Methods: A scoping review was undertaken to address the primary research questions identified in the objectives. The search strategy was as follows: ‘surgical AND gloves AND perforations’ with a search date from January 1st, 1970 to July 31st, 2024 using the PubMed database. The articles were screened independently by two separate reviewers using the PRISMA-Scr checklist methodology. Findings: The initial search identified 343 articles that were then screened to provide 129 articles for full review. The results showed that surgical glove perforations are frequently reported to various levels in a variety of different surgical procedures, but that importantly a high proportion of glove breaches go undetected. The incidence of these perforations varies, but analysis of the data indicates that orthopaedic, oral/maxillofacial and obstetrics/gynaecology were pertaining the highest levels, probably due to the use of mechanical procedures that can easily damage the gloves. Increased levels of bacterial transmission and SSIs are associated with increased frequency of surgical glove perforations. The use of indicator system gloves demonstrated significant benefits in terms of identification of surgical glove breaches. Conclusion: In high-risk surgical procedures the use of an indicator system provides both surgeon and patient added protection with the perforation/breach detection helping prevent bacterial transmission and cross-infection.</p
Comparative analysis to assess the effects of hydrogen injection techniques on performance and emission characteristics of a compression-ignition engine
No full textThe need to decarbonise transportation has driven research into hydrogen as an alternative fuel for compression ignition engines. This study uses 1D combustion simulations to evaluate hydrogen injection strategies in a diesel engine with a 30 % hydrogen energy share (HES), including port fuel injection, gaseous direct injection (GDI), and blending liquid hydrogen with diesel. Performance metrics such as brake power, torque, brake thermal efficiency (BTE), brake specific fuel consumption (BSFC), brake mean effective pressure (BMEP), heat transfer rate (HTR) and emissions were analysed. Liquid fuels maintain power and torque, while port and direct injections reduce them by 10 % and 15 % due to uneven pressure rise and incomplete energy conversion. BTE remains stable with liquid fuels. However, it drops by up to 17.3 % and 15 % at 1500 rpm with port and direct injection but stabilises at higher speeds. Injection of liquid fuels has little effect on BMEP and HTR, while direct and port injections lower BMEP by 9.6 % and 14 % but increase HTR by over 70 % at high speeds. Port injection achieves the highest emissions reduction, cutting NOx by 54.4 % and CO by 99 %. Liquid fuels offer the best efficiency-performance trade-off, while port and direct injections prioritise emissions reduction at the cost of power. Furthermore, brake power and NOx emissions were evaluated across multiple engine loads (25 %, 50 %, 75 %, and 100 %) to capture load-dependent effects of hydrogen injection strategies
Finding Treblinka:Forensic and Archaeological Discoveries
No full textFinding Treblinka challenges the long-held belief that Treblinka, the second-deadliest extermination camp operated by Nazi Germany in occupied Poland, was completely destroyed. Even though Nazis demolished buildings, exhumed and burned victims’ bodies, and planted trees to obscure the site, Caroline Sturdy Colls uncovers what still lies beneath the surface and what this material evidence reveals about the camp’s operations, evolution, and afterlife.Sturdy Colls combines archival insight through newly uncovered and unpublished documents, photographs, maps, and testimonies with the first non-invasive archaeological surveys and excavations ever conducted at Treblinka. Developed in accordance with Jewish burial law (Halacha), her methods allow for ethical access to Holocaust landscapes long considered off limits to archaeologists and offer powerful material counterpoint to the myth of Treblinka’s disappearance. Sturdy Colls not only demonstrates that traces of atrocity continue to shape how we remember and understand the Holocaust, but also how archaeology can confront absence with presence, silence with proof. Finding Treblinka reveals how genocide inscribes itself into the land, and how, with the right tools, we can still read it.<br/
Particle Deposition rate constants:a DPM approach for particles in pipe flow
No full textThis study focuses on the use of the discrete phase model (DPM) to determine the deposition constant of particles flowing in a horizontal pipe. A population balance modelling of the particle deposition in a 500 m pipe was also carried out. The deposition constant was found to be nonlinear to both the location of the pipe and particle size. It was also interesting to see that the constant is substantially higher at the inlet of the pipe then gradually decreases along the axial direction of the flow. The change of deposition constant in particle size was found to be exponentially dependent. Population balance modelling results showed that the thickness of particle deposit decreases with the flow towards outlet of the pipe. Deposition mainly takes place at the nearside of the inlet of the pipe
Morphological Convolution Undecimated Wavelet:A Novel Frequency Demodulation Analysis Method for Bearing Fault Diagnosis
No full textThe morphological undecimated wavelet (MUW) is an efficient feature extraction algorithm for bearing fault diagnosis. Currently, the researched MUW is mainly focused on background noise cancellation and transient impulse extraction but has not been exploited for frequency demodulation. This article proposed a novel frequency demodulation analysis method named morphological convolution undecimated wavelet (MCUW) for bearing fault diagnosis. First, the morphological difference convolution operator (MDCO) is developed, which fully employs the transient impulse enhancement properties of the difference operator and the combined morphological filter-hat transform (CMFHT) operator, as well as the random noise cancellation performance of the convolution operator. Subsequently, the MDCO is utilized into the MUW to produce the MCUW for frequency demodulation to extract the bearing frequency features. Finally, the simulated scenarios and experiment signals are implemented to evaluate the MCUW performance. The analysis results illustrate that the MCUW can efficiently extract fault features and its performance is better than other well-advanced algorithms
Guest Editorial: Criminology in Post-Violence Transitions:Exploring the Intersections between Human Rights, Grassroots Activism, Transitional Justice, Memory, and Criminology
No full textFocused parameter study of dye removal from PET textiles using Cyrene:Toward sustainable textile recycling
No full textPolyester is the most widely used textile fibre, accounting for around 54% of global fibre production. However, less than 1% of clothing is recycled into new textiles, largely due to dyes that reduce the quality of recovered fibres. This study aimed to improve textile-to-textile recycling by optimising a sustainable dye extraction method using Cyrene™, a biodegradable solvent, under mild conditions. The Taguchi method was used to identify the best combination of solvent ratio, treatment time, and fabric loading for removing two anthraquinone disperse dyes—CI Disperse Red 60 and CI Disperse Blue 56—from polyester fabrics dyed at low and high temperatures. The optimal conditions were a 75:25 Cyrene-to-water ratio, 30 minutes of treatment, and 10% fabric loading. Dye removal ranged from 70 to 96% for low-temperature dyed fabrics and 70–75% for high-temperature dyed fabrics, based on two anthraquinone disperse dyes; while not broadly generalisable, the results align with commonly understood consistency in dye–fibre interactions within similar dye classes. The results show that Cyrene™ can effectively extract dyes without harsh chemicals, improving the recyclability of polyester textiles. This supports a circular economy by enhancing fibre quality and reducing environmental impact.</p
Remaining useful life prediction of lithium-ion batteries by leveraging end-of-charge characteristics
No full textPredicting the Remaining Useful Life (RUL) of lithium-ion batteries (LIBs) is crucial for ensuring their reliable performance and extending their lifespan, especially in applications such as electric vehicles (EVs). Traditional RUL prediction methods mainly focus on battery capacity degradation, but obtaining accurate capacity data in real-world settings is often challenging, leading to limited prediction accuracy. To address this issue, our study experimentally investigates the degradation behavior of EV LIBs by analysing variations in Constant-Current (C[sbnd]C) and Constant-Voltage (C[sbnd]V) charging durations at different stages of battery ageing. The results show significant changes in the rate of current decrease during the C[sbnd]V charging stage and the increase in Open Circuit Voltage (OCV) during the C[sbnd]C charging stage, resulting in varied charging times across degradation stages. Given the challenges posed by partial charging and uncertain degradation rates in practical scenarios, we propose a novel RUL prediction method. This method utilizes the C[sbnd]V charging characteristic, which is less affected by partial charging, and integrates Bayesian theory with real-time monitoring data to dynamically update model parameters, enhancing prediction accuracy. Our approach offers a practical, data-driven solution for more reliable LIB RUL prediction, providing a new tool for battery health management in EV applications.</p
Robust data envelopment analysis models for efficiency evaluation with new uncertainty sets
No full textThe integration of robust optimisation (RO) techniques and data envelopment analysis (DEA) models results in a methodology called robust DEA. This methodology aims to tackle uncertain data and ensure robust and reliable efficiency measures. In applying RO approaches, the selection of the uncertainty set plays a pivotal role since it determines the trade-off between achieving optimal objective and ensuring a high probability of constraint feasibility, a concept well-known as the price of robustness. This trade-off can be adjusted using a robust parameter based on managers’ risk preferences. Like RO, robust DEA aims to protect the deterministic DEA models against data uncertainty within a user-specified uncertainty set, providing a probability bound on constraint feasibility. Despite recent advancements in the RO approaches, robust DEA models are still in their early stages of development, accentuating the need for further research, especially in the application of new types of uncertainty sets. To address the identified research gap, this study aims to develop two novel robust DEA models considering recently introduced uncertainty sets—namely, variable budgeted and order statistic uncertainty sets—to improve the flexibility and generality of the existing robust DEA models. We discuss in depth how the existing robust DEA models under budgeted uncertainty sets represent a special case of the proposed robust DEA models in this paper when the robust parameter is appropriately selected. Finally, we present a case study on EU banks to illustrate the efficacy and applicability of the proposed models, which show a robust evaluation strategy for management in uncertain environments
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