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Two-year outcomes after selective early treatment of patent ductus arteriosus with ibuprofen in preterm babies: follow-up of Baby-OSCAR-a randomised controlled trial.
Get PDFBackgroundChildren born extremely preterm are at increased risk of developmental problems and respiratory morbidity due to patent ductus arteriosus (PDA). The objective of this study was to evaluate whether early treatment of a PDA ≥1.5 mm with ibuprofen improved neurodevelopmental and respiratory outcomes at 24 months of age, corrected for prematurity.MethodsBaby-OSCAR was a UK multi-center placebo-controlled masked randomized clinical trial in infants born 23+0-28+6 weeks' gestation. The main long-term outcome was survival without moderate or severe neurodevelopmental impairment at 24 months' corrected age, assessed using parent report primarily or classified by blinded end-point review committee where parent-reported data were not available. Other secondary outcomes included survival without respiratory morbidity and duration of oxygen supplementation. (ISRCTN Registry number ISRCTN84264977).FindingsFrom July 2015 through December 2020, 653 infants underwent randomization. At 24 months' corrected age, outcome data were available for 537 children: 263 in the ibuprofen group and 274 in the placebo group. Survival without moderate to severe neurodevelopmental impairment in the ibuprofen and placebo groups was 131/248 (53.0%) and 134/259 (51.9%) respectively; adjusted risk ratio 1.01 (95% confidence interval [CI] 0.86-1.18); p = 0.901. Survival without respiratory morbidity was 66/220 (30%) and 74/225 (32.9%) respectively; adjusted risk ratio 0.89 (95% CI 0.68-1.18). Median duration of oxygen supplementation from randomization was 76.0 and 78.0 days, respectively; adjusted median difference -1.5 (-13.8 to 10.9).InterpretationWe found no evidence of an improvement in neurodevelopmental and respiratory outcomes at 24 months' corrected age, after selective early treatment of a PDA ≥1.5 mm with ibuprofen in children born extremely preterm.FundingThis study was funded by the National Institute for Health Research (NIHR) Health Technology Assessment Programme (11/92/15)
Advancements in hydrometallurgical processes for rare earth elements recovery from coal ash
Get PDFRecent advancements in the hydrometallurgical extraction of rare earth elements (REEs) from coal ash have transformed the landscape of REEs recovery. This review critically synthesizes the latest developments and emphasizes key innovations. Coal ash, often overlooked, has emerged as a promising REEs reservoir due to its remarkable ability to retain these valuable elements during coal burning. Researchers have shifted their focus from feasibility studies to pilot-scale production, recognizing the potential of this unconventional source. Various hydrometallurgical techniques, including acid leaching, ion exchange, and solvent extraction, are explored as efficient methods for REEs recovery. Notably, acid leaching, when combined with additives, alkaline pretreatment, or thermal pretreatment, yields promising results. REEs find applications in renewable energy, security technologies, consumer goods, and national defense. Understanding the chemistry in coal is crucial for efficient extraction. Evaluating the global distribution of REEs informs strategic decisions. Hydrometallurgical procedures emerge as effective, affordable, and environmentally friendly technologies for REEs extraction from coal ash. This study bridges the gap between scientific advancements and practical implementation, positioning REEs as critical resources for a sustainable future
Bi-Level Low-Carbon Scheduling of Active Distribution Networks with Multiple Technical Virtual Power Plants in the Integrated Electricity and Carbon Markets
No full textAs the integration of distributed energy resources (DERs) accelerates, optimizing active distribution networks (ADNs) for low-carbon operations has become essential for decarbonizing power systems. This paper proposes a bi-level optimization model aimed at achieving low-carbon scheduling of ADNs interacting with multiple technical virtual power plants (TVPPs) in the integrated electricity and carbon markets. The upper-level problem seeks to minimize ADN costs, including expenses associated with energy procurement and carbon emissions. The lower-level problem maximizes VPP economic benefits by optimizing their power generation, demand response, and trading strategies. To enhance carbon accountability, the dynamic emission factors (DEFs) are developed, encompassing both generation-based and trading-based emission factors. The generation-based DEF quantifies emissions based on the output of distributed generators, while the trading-based DEF allocates emissions for ADN-VPP power exchanges, preventing double-counting and ensuring accurate carbon cost assessments. The bi-level model is then reformulated as a single-level mixed-integer linear programming (MILP) problem using Karush-Kuhn-Tucker (KKT) optimality conditions, Fortuny-Amat transformation, McCormick Envelop method, and the strong duality theorem. Case studies conducted on a modified IEEE 33-bus test system demonstrate that the proposed approach can effectively reduce carbon emissions by 7.93% and further reduce total operational cost considering carbon price, achieving both economic and environmental objectives. These findings underscore the potential of integrating low-carbon strategies into ADN management for more sustainable and resilient power systems
When Madness Matters: The limits and affordances of representing madness in contemporary biopics of historical royal women
No full textThis chapter explores three contemporaneous biopics of royal women: Spencer, (2021: Dir: Pablo Larrain), Corsage (2022, Dir: Marie Kreutzer) and The Favourite (2018, Dir: Yorgos Lanthimos). The three films share striking similarities in their content (all follow a single European royal woman across a short period of time, attending particularly to her mental distress or madness) and their approach (presenting less idealised versions of royal womanhood). We argue that all three films encourage a complex closeness to their protagonists and their experiences of madness, mental distress, and mental illness, which are more commonly represented through frameworks of disgust, bewilderment, and othering. We explore how the films draw on cinematic techniques, contemporary conceptual frameworks, and agentic revisionings to accomplish this compelling and unusual closeness, and we analyse its politics. Specifically, we suggest that while the approach these films take to madness can be deeply meaningful, it can also be limited in its ability to make a radical intervention into the politics of madness through its focus on women of extreme privilege, its reliance on glamour and aestheticizing, and its individualisation of systemic and collective issues
The other side of the coin: Speculation in bearish natural gas markets
Get PDFThis paper analyses the speculative behaviour of traders in natural gas markets. We test for mild explosiveness in natural gas futures prices using the method proposed by Phillips et al. (2015a) and employ a multinomial logistic regression to determine whether changes in trader positions drive these explosive episodes. Our findings indicate that changes in short positions held by money managers increase the probability of negative explosiveness in futures prices. Our Granger causality analysis reveals that changes in positions held by money managers (pure speculators) precede changes in spot and futures prices, as well as the incentive to hold inventories during bearish market phases. This supports the notion that speculators might influence natural gas price dynamics in bearish conditions. However, our analysis does not provide evidence of a similar impact on futures prices during bullish phases. In fact, our results suggest that long positions taken by speculators reduce the probability of explosive price increases
Assessment of Landscape Risks and Ecological Security Patterns in the Tarim Basin, Xinjiang, China
Get PDFEcological risk refers to the potential threat that landscape changes pose to ecosystem structure, function, and service sustainability, while ecological security emphasizes the ability of regional ecosystems to maintain stability and support human well-being. Developing an Ecological Security Pattern (ESP) provides a strategic approach to balance ecological protection and sustainable development. This study investigates the spatial and temporal dynamics of landscape ecological risk in the Tarim Basin and surrounding urban areas in the Xinjiang Uygur Autonomous Region, China, from 2000 to 2020. Using a combination of the InVEST model, landscape connectivity index, and circuit theory-based modeling, we identify ecological source areas and simulate ecological corridors. Ecological source areas are categorized by their ecological value and connectivity: primary sources represent high ecological value and strong connectivity, secondary sources have moderate ecological significance, and tertiary sources are of relatively lower priority but still vital for regional integrity. The results show a temporal trend of ecological risk declining between 2000 and 2010, followed by a moderate increase from 2010 to 2020. High-risk zones are concentrated in the central Tarim Basin, reflecting intensified land-use pressures and weak ecological resilience. The delineated ecological protection zones include 61,702.9 km2 of primary, 146,802.5 km2 of secondary, and 36,141.2 km2 of tertiary ecological source areas. In total, 95 ecological corridors (23 primary, 37 secondaries, and 35 tertiary) were identified, along with 48 pinch points and 56 barrier points that require priority attention for ecological restoration. Valuable areas refer to those with high ecological connectivity and service provision potential, while vulnerable areas are characterized by high ecological risk and landscape fragmentation. This study provides a comprehensive framework for constructing ESPs in arid inland basins and offers practical insights for ecological planning in desert–oasis environments
BcQLM: Efficient Vision-Language Understanding with Distilled Q-Gated Cross-Modal Fusion
Get PDFAs multimodal large language models (MLLMs) advance, their large-scale archi-tectures pose challenges for deployment in resource-constrained environments. In the age of large models, where energy efficiency, computational scalability and environmental sustainability are paramount, the development of lightweight and high-performance models is critical for real-world applications. As such, we propose a lightweight MLLM framework for end-to-end visual question answering. Our proposed approach centres on BreezeCLIP, a compact yet powerful vision-language encoder optimised for efficient multimodal understanding. With only 1.2 billion parameters overall, our model significantly reduces computational cost while achieving performance comparable to standard-size MLLMs. Experiments conducted on multiple datasets further validate its effectiveness in balancing accuracy and efficiency. The modular and extensible design enables generalisation to broader multimodal tasks. The proposed lightweight vision-language framework is denoted as BcQLM (BreezeCLIP-enhanced Q-Gated Multimodal Language Model). It offers a promising path toward deployable MLLMs under practical hardware constraints. The source code is available at https://github.com/thico0224/BcQLM
On the Entropy-Based Localization of Inequality in Probability Distributions
Get PDFWe present a novel method for localizing inequality within probability distributions by applying a recursive Hahn decomposition to the degree of uniformity—a measure derived from the exponential of Shannon entropy. This approach partitions the probability space into disjoint regions exhibiting progressively sharper deviations from uniformity, enabling structural insights into how and where inequality is concentrated. To demonstrate its broad applicability, we apply the method to both standard and contextualized systems: the discrete binomial and continuous exponential distributions serve as canonical cases, while two hypothetical examples illustrate domain-specific applications. In the first, we analyze localized risk concentrations in disease contraction data, revealing targeted zones of epidemiological disparity. In the second, we uncover stress localization in a non-uniformly loaded beam, demonstrating the method’s relevance to physical systems with spatial heterogeneity. This decomposition reveals aspects of structural disparity that are often obscured by scalar summaries. The resulting recursive tree offers a multi-scale representation of informational non-uniformity, capturing the emergence and localization of inequality across the distribution. The framework may have implications for understanding entropy localization, transitions in informational structure, and the dynamics of heterogeneous systems
A straightforward route to hexagonal-boron nitride fibers
Get PDFAdvanced fibers enable the fabrication of structures and composites for applications reliant on lightweight, oxidation resistant, mechanically strong, and electrically insulating materials, e.g. in all forms of land, air, and space transportation and in applications within extreme environments. Hexagonal boron nitride (h-BN) fibers harness these advantages, and in addition, offer ultra-high-strength-to-weight ratio and low density. Yet, existing precursors for polymer-derived BN fibers are limited to insoluble and air/moisture sensitive polyborazylenes, hindering fiber production at scale. In this contribution, we report a reliable, controllable, and scalable synthesis methodology for producing pure micro- and nano-h-BN fibers, offering a competitive alternative to NASA’s energy-intensive h-BN nanotubes production. The single-source precursor, N-methyl polyaminoborane (PMeAB), plays a pivotal role in this process. The catalytic, and scalable, synthesis of PMeAB with controlled molecular weights (Mw = 110,500–290,500 g·mol−1) enables the production of h-BN fibers by electrospinning method and thermolysis under ammonia. PMeAB molecular weight and concentration were identified as key factors dictating the viscosity and surface tension, and thus influencing the overall spinnability of the PMeAB solution. We reveal that the subsequent formation of a cross-linked intermediate during PMeAB thermolysis is essential to retain the fibrous morphology during the conversion to h-BN fibers. Comprehensive characterization demonstrated the purity and homogeneity of the h-BN fibers, with ~ 97 at.% of B and N contents combined throughout the fiber body. This newly disclosed route to h-BN fibers offers a route to potentially valuable multifunctional filler material for advanced lightweight composites suitable for applications in extreme environments
Lowermost Mantle Flow at Thermochemical Piles Constrained by Shear Wave Anisotropy: Insights From Combined Geodynamic and Mantle Fabric Simulations at Global Scale
Get PDFPlain Language Summary: Seismic waves travel differently depending on direction, a phenomenon called seismic anisotropy. This effect is especially common in the lowermost mantle, around the edges of Large Low‐Shear‐Velocity Provinces (LLSVPs), which are massive structures. Understanding this anisotropy can provide clues about how the deep mantle deforms. We simulate mantle convection over the past 250 million years, focusing on how subducted plates influence mantle flow and plume generation from the deep mantle. Our models treat LLSVPs as chemically distinct regions that form from an initially 100 km thick layer. Our results show that most of the lowermost mantle remains isotropic. However, regions where LLSVP piles form show strong anisotropy, with vertically polarized shear waves traveling faster. Our findings match seismic observations of the D″ layer. Our models suggest that most of the anisotropy is concentrated at LLSVP edges rather than within their interiors. We also find that LLSVPs are about 100 times more compositionally viscous than the surrounding mantle. Overall, our models provide new insights into how the deep mantle flows and how LLSVPs interact with surrounding material, helping to explain observed patterns of seismic anisotropy
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