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Rational design of robust Cu@Ag core-shell nanowires for wearable electronics applications
No full textCopper nanowires (CuNWs) have shown great potential as transparent electrodes for cost-effective wearable electronics. However, its unsatisfactory electrical conductivity and intrinsic susceptibility to oxidation hinder practical applications. To address these issues, herein, ultra-stable Cu@Ag core–shell NWs have been designed via a facile galvanic replacement method for wearable applications. The thermal stability of the NWs is significantly enhanced after introducing Ag, and superior stability is achieved with a more uniform Ag coating. The structural integrity of the percolation networks is basically maintained after 5 days’ annealing treatment at a high temperature (≥150 °C). The devices based on core–shell NWs show reliable heating performance, and can further be used for defrosting and heating water/ice applications. Owing to optimized contact between Ag-coated NWs, the devices exhibit excellent mechanical performance under repetitive bending. Based on above structural design, the resultant strain sensors show high sensitivity, good repeatability and a wide sensing range, which are capable to detect various hand gestures and communicate with Morse code. Furthermore, the fabricated core–shell NWs show robust antibacterial activity, which is essential for wearable healthcare applications, outperforming that of pristine CuNWs. This work provides a promising way for the design of high-performance metal NWs for advanced wearable electronics
Review of chemical models and applications in Geant4-DNA: Report from the ESA BioRad III Project
No full textA chemistry module has been implemented in Geant4-DNA since Geant4 version 10.1 to simulate the radiolysis of water after irradiation. It has been used in a number of applications, including the calculation of G-values and early DNA damage, allowing the comparison with experimental data. Since the first version, numerous modifications have been made to the module to improve the computational efficiency and extend the simulation to homogeneous kinetics in bulk solution. With these new developments, new applications have been proposed and released as Geant4 examples, showing how to use chemical processes and models. This work reviews the models implemented and application developments for modeling water radiolysis in Geant4-DNA as reported in the ESA BioRad III Project
Pre-implementation context and implementation approach for a nursing and midwifery clinician researcher career pathway: A qualitative study
No full textAim: To describe the pre-implementation context and implementation approach, for a clinician researcher career pathway. Background: Clinician researchers across all health disciplines are emerging to radically influence practice change and improve patient outcomes. Yet, to date, there are limited clinician researcher career pathways embedded in clinical practice for nurses and midwives. Methods: A qualitative descriptive design was used. Data Sources: Data were collected from four online focus groups and four interviews of health consumers, nursing and midwifery clinicians, and nursing unit managers (N = 20) between July 2022 and September 2023. Results: Thematic and content analysis identified themes/categories relating to: Research in health professionals' roles and nursing and midwifery, and Research activity and culture (context); with implementation approaches within coherence, cognitive participation, collective action and reflexive monitoring (Normalization Process Theory). Conclusions: The Pathway was perceived to meet organizational objectives with the potential to create significant cultural change in nursing and midwifery. Backfilling of protected research time was essential. Implications for the Profession and/or Patient Care: The Pathway was seen as an instrument to empower staff, foster staff retention and extend research opportunities to every nurse and midwife, while improving patient experiences and outcomes. Impact: Clinicians, consumers and managers fully supported the implementation of clinician researchers with this Pathway. The Pathway could engage all clinicians in evidence-based practice with a clinician researcher leader, effect practice change with colleagues and enhance patient outcomes. Reporting Method: This study adheres to relevant EQUATOR guidelines using the COREG checklist. Patient or Public Contribution: Health consumers involved in this research as participants, did not contribute to the design or conduct of the study, analysis or interpretation of the data, or in the preparation of the manuscript
Appraisal of Urban Waterlogging and Extent Damage Situation after the Devastating Flood
No full textThe rapid urbanization in Pakistan frequently leads to urban waterlogging due to storms. The event often leads to significant harm to the environment, people, and urban economies. Early identification of rainstorm events and urban waterlogging disasters is essential in reducing associated damages. Twitter (X), a widely used global microblogging platform, offers a large amount of real-time tweets that can be used for immediate monitoring purposes. This study introduces a method for recognizing microblogs with information about urban rainstorms and waterlogging and uses blog posts to assess the waterlogging risk. In light of the preliminary examination of microblog content, we determine the efficacy of cluster and support vector machine methods for classification. In addition to text vector attributes, we incorporate sentiment aspects to improve the precision and clarity of our results. We also constructed a lexicon for waterlogging severity to evaluate the risk of waterlogging based on the content of Tweets. Afterward, we generate a risk map using ArcGIS, with findings suggesting that SVM is suitable for detecting rainstorms and waterlogging events in real time. The waterlogging location aligns with the findings of the hazard assessment. The proposed risk assessment method can be a precise tool for promptly addressing emergencies
Methane mitigation via the nitrite-DAMO process induced by nitrate dosing in sewers
No full textNitrate or nitrite-dependent anaerobic methane oxidation (n-DAMO) is a microbial process that links carbon and nitrogen cycles as a methane sink in many natural environments. This study demonstrates, for the first time, that the nitrite-dependent anaerobic methane oxidation (nitrite-DAMO) process can be stimulated in sewer systems under continuous nitrate dosing for sulfide control. In a laboratory sewer system, continuous nitrate dosing not only achieved complete sulfide removal, but also significantly decreased dissolved methane concentration by ∼50 %. Independent batch tests confirmed the coupling of methane oxidation with nitrate and nitrite reduction, revealing similar methane oxidation rates of 3.68 ± 0.5 mg CH4 L−1 h−1 (with nitrate as electron acceptor) and 3.57 ± 0.4 mg CH4 L−1 h−1 (with nitrite as electron acceptor). Comprehensive microbial analysis unveiled the presence of a subgroup of the NC10 phylum, namely Candidatus Methylomirabilis (n-DAMO bacteria that couples nitrite reduction with methane oxidation), growing in sewer biofilms and surface sediments with relative abundances of 1.9 % and 1.6 %, respectively. In contrast, n-DAMO archaea that couple methane oxidation solely to nitrate reduction were not detected. Together these results indicated the successful enrichment of n-DAMO bacteria in sewerage systems, contributing to approx. 64 % of nitrite reduction and around 50 % of dissolved methane removal through the nitrite-DAMO process, as estimated by mass balance analysis. The occurrence of the nitrite-DAMO process in sewer systems opens a new path to sewer methane emissions
Flexocatalysis of nanoscale titanium dioxide
No full textPiezocatalysis emerges as a distinctive approach for producing free radicals to drive catalysis. However, the piezoelectric effect exclusively manifests in non-centrosymmetric materials, which largely constraints the use of materials with centrosymmetry. To address this challenge, the concept of flexocatalysis is explored to bypass the structural constraints of materials by harnessing strain-gradient-induced polarization, taking advantage of universality of flexoelectricity. As an exemplar of flexocatalysis, centrosymmetric rutile titanium dioxide (TiO2) nano particles are selected due to its high permittivity, non-toxicity, biocompatibility, and wide-ranging utility. The effectiveness of flexocatalysis in generating free radicals (·H, and ·OH) is validated through hydrogen generation (∼2380 μmolg−1h−1 in pure water) and Rhodamine B dye degradation. Additionally, the size effect on flexoelectricity is examined both experimentally and theoretically, revealing that materials at nanoscale exhibit greatly enhanced flexoelectricity that can rival the traditional piezoelectricity. This work endows TiO2 with novel capabilities and broadens material's selection in mechanochemistry applications
Electricity market crisis in Europe and cross border price effects: A quantile return connectedness analysis
No full textAs the interconnection of the European electricity markets and integration of renewables progresses, there is little known about interconnectedness across them at times of market turbulence. The electricity crisis of 2021 and 2023 were significant events that can also provide lessons in the behaviour of integrated markets with high renewables under stress. Despite the impacts of the COVID-19 pandemic and the Russia-Ukraine war on the European energy market, little is known about their effects on the transmission of risks between the electricity markets. We employ the quantile connectedness approach to quantify the return connectedness between eleven key European markets, as well as the natural gas and carbon markets. We then examine the effect of the two crises on the interconnectedness. We find significant return interconnectedness, driven by spillover effects, among the markets. Analysis of connectedness across quantiles shows that the spillover effects are much stronger at tail ends of conditional distribution. Moreover, our results reveal opposite effects from crises on market interconnectedness. While the COVID-19 pandemic reduced the interconnectedness, the Russia-Ukraine war intensified the return shock transmission. Finally, we find that the natural gas and carbon markets are net recipients of return shocks across the quantiles
Implementation of a day-stay joint replacement pathway in an Australian regional public hospital: A descriptive study
No full textObjective: To describe the implementation, feasibility and safety of a day-stay joint replacement pathway in a regional public hospital in Australia. Method: Over a 12-month pilot period, a prospective descriptive analysis of consecutive patients undergoing total knee and hip arthroplasty was conducted. The number of eligible day-stay patients, proportion of successful same-day discharges and reasons for same-day failure to discharge were recorded. Outcome measures captured for all joint replacements across this period included length of stay (LoS), patient reported outcomes, complications and patient satisfaction. The implementation pathway as well as patient and staff identified success factors derived from interviews were outlined. Results: Forty-one/246 (17%) patients booked for joint replacement surgery were eligible for day-stay and 21/41 (51%) achieved a successful same-day discharge. Unsuccessful same-day discharges were due to time of surgery too late in the day (7/20), no longer meeting same-day discharge criteria (11/20) and declined discharge same-day (2/20). Over the implementation period 65% (162/246) of all patients were discharged with a LoS of 2 days or less. Patient satisfaction for the day-stay pathway was high. Complication rates and patient-reported outcomes were equivalent across LoS groups. Conclusion: The day-stay joint replacement surgery pathway was feasible to implement, safe and acceptable to patients. Day-stay pathways have potential patient and system-level efficiency benefits
Effects of YSZ and CA6 additives on densification and thermal shock resistance of Al2O3-MgO-CaO-Y2O3 refractories
No full textTo achieve high-quality and stable production of modern clean steel, novel Al2O3-MgO-CaO-Y2O3 refractories with enhanced sintering properties and thermo-mechanical properties were synthesized by introducing YSZ and CA6 as the reinforcers. A sintering reaction mechanism involving the Al2O3-MgO-CaO-Y2O3 quaternary system is proposed. The results show that the sintering process in the Al2O3-MgO-CaO-Y2O3 quaternary system was characterized by the sequential formation of Al5Y3O12→YAlO3→Y4Al2O9→Y2O3 in three distinct stages, resulting in the predominant phases of Al5Y3O12 and MgAl2O4. The YSZ addition on Al2O3-MgO-CaO-Y2O3 refractories promotes the complete reaction between Y2O3 and CaAl4O7, fostering the formation of additional Al5Y3O12, which significantly enhances the densification, leading to improvements in both compressive strength and thermal shock resistance. The addition of CA6 promotes the generation of more Al5Y3O12, which forms numerous pores during the three stages of the sintering process, and the distribution of these pores is uncontrollable. Therefore, based on the sintering reaction mechanism of the Al2O3-MgO-CaO-Y2O3 quaternary system, a low-cost and enforceable reinforcement strategy for Al2O3-MgO-CaO-Y2O3 refractories is proposed, which is expected to focus on the application of YSZ in Al2O3-MgO-CaO-Y2O3 refractories for clean steel smelting
Phase-resolved wave prediction with varying buoy positions in the field using machine learning-based methods
No full textSurface wave predictions for several wave periods in advance are crucial for optimizing a wide range of offshore applications. This work focuses on the potential application in active control of wave energy converters (WECs), which can dramatically enhance the efficiency of power generation. Field tests were conducted in the Southern Ocean of Albany, Western Australia. We compared two prediction models: a physics-based algebraic model and a machine learning-based Artificial Neural Network (ANN) model. Although the standard ANN model is found to achieve better prediction accuracy than the algebraic model for highly directional spreading waves, the prediction performance of the model is greatly reduced due to varying buoy positions, leading to phase offset in predictions. To overcome this limitation, phase correction and partition methods have been incorporated with physical insights into a purely data-driven ANN model. The modified ANN model significantly reduced the prediction error in peaks and troughs compared to the standard ANN model. This study demonstrates that both physics-based and machine learning-based models can work in parallel to provide more accurate predictions, thereby enhancing the practical value of wave prediction for WECs