Abrasion is one of the key mechanisms by which coke undergoes degradation in the blast furnace. Abrasion in coke refers to its surface breakage, and it occurs when lumps of coke move against each other as they descend the furnace. In industry, abrasion is assessed using tumble drum testing. However, tumble drum indices do not provide a measure of pure abrasion; rather, different breakage mechanisms occur during the test, including volume breakage and asperity breakage. To this end, we previously developed an approach using tribological testing of coke specimens to examine their resistance to pure abrasive wear and linked the mechanisms by which abrasion took place to coke microstructural and microtextural features, and thereby the properties of the parent coal(s) used to make the cokes. The key objectives of this present study were to: (i) investigate whether correlations exist between abrasion resistance measured using tribological testing and conventional coke quality indices, namely tumble drum indices-which is one of the novel aspects of this work; (ii) link the mechanisms of wear to coke microtextural components and the rank and maceral composition of the parent coal or blend; (iii) conduct a preliminary evaluation of whether partially pre-reacting coke samples with H2O affects their abrasion resistance compared to pre-reacting samples with CO2. This last objective contributes to a broader research aim of improving understanding of the coke quality requirements for effective operation of hydrogen-enriched blast furnaces. Key findings of the present study include: Some positive correlation was observed between the coefficient of friction (COF) of a coke at the end of tribological testing under ambient conditions and its measured ASTM Hardness or I600. This trend is a tentative observation requiring further validation. In addition, the mechanisms of abrasive wear under ambient conditions were correlated with parent coal rank. For coke from mid-rank coal, the reactive maceral derived components (RMDC) appeared to have a high fracture toughness based on SEM image analysis. For coke from the high-rank coal, which showed a higher degree of RMDC anisotropy, the main mechanisms of abrasion were delamination and ploughing. Finally, increased abrasive wear was observed for the samples pre-reacted with H2O than for those pre-reacted with CO2. The impact of the different gasification conditions on all six cokes will be subject of a follow-up paper.
Wire Arc Additive Manufacturing (WAAM) has emerged as one of the most practical and scalable technologies for fabricating large metal components. With high deposition rate and cost efficiency, WAAM is increasingly used in aerospace, marine, and other high-value industries. Conventional WAAM systems, based on commercial welding equipment and industrial robots, are limited in controlling material microstructure, mechanical properties, and geometric accuracy. As the demands for higher performance in fabricated parts continue to rise, process-oriented system innovations have become a key development trend. These modifications directly manipulate arc behaviour, wire feeding, thermal fields, and in-situ deformation, providing more effective regulation of molten pool dynamics and solidification patterns. Approaches such as multi-wire feeding, hybrid arc-laser configurations, external field assistance, and in-situ thermal or mechanical treatments have achieved improved structural uniformity, reduced defects, and higher deposition efficiency. Despite this rapid progress, the diversity and complexity of independently developed systems have led to a fragmented research landscape. This review synthesizes these innovations, evaluates their mechanisms and effectiveness, and maps them to key research objectives. It then provides critical insights of current research, discusses existing issues and highlights future opportunities to guide the development of high-performance, structurally reliable, and industrially deployable WAAM systems.
OBJECTIVE:To update, synthesise and provide meta-analytical evidence of the associations between domain-specific physical activity (PA) and mental health and mental ill-health outcomes. DESIGN:Systematic review and multilevel meta-analysis. DATA SOURCES:In March 2024, we systematically searched five databases. ELIGIBILITY CRITERIA:Methods employed replicated those of a previous review in 2017. All studies examining associations between domain-specific PA and specified mental health outcomes were included. RESULTS:372 studies met inclusion criteria and 361 were included in the meta-analysis. Across the 372 studies (combined sample size of 3 323 711), 338 examined leisure-time PA, 54 work-related PA, 72 transport-related PA, 44 household PA, 5 school sport and 8 physical education. Multilevel meta-analyses showed that leisure-time PA (r=0.205, 95% CI 0.157 to 0.253), transport-related PA (r=0.138, 95% CI 0.042 to 0.231) and household PA (r=0.096, 95% CI 0.025 to 0.165) were positively associated with mental health. Leisure-time PA (r=-0.149, 95% CI -0.189 to -0.11) and school sport (r=-0.096, 95% CI -0.115 to -0.077) were inversely associated with mental ill health. However, work-related PA (r=0.134 95% CI 0.069 to 0.199) was positively associated with mental ill health. CONCLUSION:The direction of the association between PA and mental health/mental ill health is dependent on the domain in which PA occurs. Promoting PA for leisure purposes is likely to yield the greatest benefits for both promoting mental health and preventing mental ill health. As such, leisure-time PA should be prioritised in messaging, guidelines and interventions/programmes designed to support mental health through PA. PROSPERO REGISTRATION NUMBER:CRD42024510303.
We compared temporal variability in dust and loess accretion in New Zealand's South Island with glacial activity in the central Southern Alps, considered the main mechanism of silt production, in (i) a proximal loess deposit at Barrhill, Rakaia River and (ii) a distal dust record from a peat mire in Central Otago. We applied novel luminescence dating approaches at Barrhill, targeting both polymineral silt and K-feldspar sand. Results demonstrated loess accretion began from similar to 8.5 +/- 1.7 ka, with accumulation rates increasing by 7 times after similar to 2 ka, before decreasing toward the present. In the peat record, trace-element geochemistry was used to distinguish New Zealand-sourced dust from Australian dust. Like Barrhill, deposition of New Zealand-sourced dust increased by similar to 4 times from similar to 3 ka, while also recording high deposition during the Little Ice Age. Changing dustiness in both records is attributed to climate-modulated sediment production. At Barrhill, this was linked directly to glacial advances in the Rakaia catchment, while in the more distal peat mire it likely resulted from enhanced periglacial activity. Together, both records demonstrate that dustiness closely tracks glacial variability in the South Island, highlighting potential for further detailed studies of dust production and glacial dynamics from New Zealand's loess.
This study explores how AI-Driven disclosure strategies on climate finance influence investors' perceptions and decisions, focusing on perceived sustainability value and authenticity. Based on 449 responses from Vietnam, using partial least squares structural equation modeling (PLS-SEM), the findings show five dimensions of AI-Driven climate disclosures positively affect perceived sustainability value and perceived authenticity. Sustainability value enhances financial sustainability and climate finance investment, while authenticity only predicts financial sustainability. Sustainable finance dynamics showed limited but surprising moderating effects. By integrating signaling theory and the SOR framework, the study contributes to emerging literature by demonstrating how AI-driven disclosure strategies can enhance investor understanding of climate information, support more credible sustainability signaling, and improve the effectiveness of climate-related financial decision-making. The findings offer implications for organizations and policymakers aiming to advance transparency, reduce information risk, and promote sustainable finance.
