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Influence of mesoscale eddies on the distribution of phytoplankton chlorophyll-a concentration in the East China Sea
No full textThe main purpose of this study is to investigate the influence of mesoscale eddies on the distribution of phytoplankton chlorophyll-a (Chl-a) concentration in the East China Sea. Mesoscale eddies (radius > 20 km) were identified using sea current data from the Copernicus Marine Environment Monitoring Service (CMEMS) GLORYS12V1 reanalysis (0.08° grid, 24-h intervals) via a vector geometry algorithm, and validated against sea level anomaly (SLA) assembled by Haiyang-2 (HY-2) altimeters and Chl-a from Haiyang-1C (HY-1C) Level-3 (L-3) (2023–2024). The CMEMS-based eddies show good consistency with SLA data for radii >100 km. Seasonal analysis of SLA/Eddy Kinetic Energy (EKE) and Chl-a cross-correlations indicate the strongest negative relationships in winter, suggesting that lower sea surface temperatures enhance phytoplankton sensitivity to eddy-induced dynamics. Results further reveal that mixed layer depth (MLD) strongly regulates Chl-a in cyclonic eddies (CEs), while its effect is weaker inside anticyclonic eddies (AEs) but more variable at their peripheries. Four interaction mechanisms were analysed – eddy stirring, eddy trapping, eddy-induced Ekman pumping and eddy intensification – classified as horizontal or vertical processes. Vertical mechanisms exhibit stronger links to Chl-a anomalies than horizontal ones. Notably, AEs exhibit peak Chl-a concentrations and vorticity in the upper-right quadrant, whereas CEs show maxima in the upper-left quadrant. Overall, the findings highlight eddy polarity, seasonality and vertical coupling as key drivers of phytoplankton distribution, underscoring the utility of high-resolution reanalysis for resolving ecological processe
AutoMedTS: Automated Modeling of Physiological Time Series for Surgical Suturing Action Recognition
No full textIn laparoscopic surgical training and evaluation, real-time recognition of surgical actions with transparency outputs is crucial for automated, objective, and immediate instructional feedback to support skills improvement. However, we face challenges due to limited dataset sizes and variability in surgical environments. This study presents AutoMedTS, an end-to-end automated machine learning framework customized for medical time-series data, enabling rapid deployment using surgical suturing trajectories collected from both expert and novice surgeons. The proposed method features key improvements including: (i) a novel temperature-scaled Softmax resampling technique effectively addressing severe class imbalance, and (ii) an uncertainty-aware ensemble selection mechanism ensuring robust predictions across surgeons with varying skill levels. Additionally, the approach emphasizes model transparency to meet the high standards of reliability and transparency required in medical applications. Compared to deep learning methods, traditional machine learning models not only facilitate efficient rapid deployment but also offer significant transparency advantages. Experimental results demonstrate that our method provides fast, stable, and reliable real-time surgical action recognition in clinical training environments. Code and data are publicly available at https://github.com/baobingzhang/AutoMedTS
The role of structural compartmentalization in carbon storage site selection in Permian (Rotliegend Group) reservoirs in the Southern North Sea
No full textThe Southern North Sea (SNS) gas basin is a key area for CO2 storage projects in the UK. Many of the now-depleted Permian (Rotliegend) Leman Sandstone Formation fields are being re-evaluated as carbon stores. However, the reservoir is known to be highly faulted, often leading to field compartmentalization. This has historically impacted field development and production, and will challenge suitability for CO2 storage by limiting site capacity, requiring a high number of injector wells, and increasing capital costs. It is necessary to understand the nature of these pressure compartments - and whether any individual culmination can house sufficient capacity - before devising a carbon storage development programme. The highly compartmentalized Indefatigable (Inde) Field was evaluated as a case study. A static model of the field was constructed using 3D seismic and well log data, and subsequently used to calculate the CO2 capacity of each of the 12 compartments. Five compartments were found to have capacities larger than 10 Mt, with the large Main Horst found to host 51% of total CO2 capacity. A sequential filling-and-sealing storage site development plan is suggested based on the evaluation and ranking of these compartments
Dynamic Mechanical Properties of Polymer Dispersed–Silica Nanoparticle Composites
No full textA series of nanocomposites were prepared by dispersing various silica nanoparticles in polystyrene (PS) and poly(methyl methacrylate) (PMMA) and analyzed by differential scanning calorimetry (DSC) and dynamic mechanical thermal analysis (DMTA). Colloidally dispersed silica nanoparticles and structured fumed silica were used in the synthesis, leading to well-dispersed systems. A detailed investigation was conducted into the thermal and dynamic mechanical behavior of the nanocomposites. The findings of this study demonstrate that the incorporation of filler particles increases the glass transition temperature (Tg) and suppresses polymer flow, resulting in an extended rubbery plateau. Significant reinforcement as evidenced by an increased plateau modulus above Tg was only observed for samples containing fumed silica. While neat PMMA begins to flow and deform irreversibly above 150 °C, the fumed silica/–polymer hybrid materials remain stable up to 240 °C, exceeding the polymer’s Tg by over 100 °C. The polymer nanocomposites exhibited slight mechanical damping at high temperature as evidenced by a surprisingly low tan δ (<0.1). Compared to the structured fumed silica hybrids, colloidally dispersed silica had very slight effect on polymer reinforcement.</p
Shining a Light on Benzo[c][1,2,5]thiadiazole Photocatalysts
No full textThe benzo[c][1,2,5]thiadiazole (BTZ) group is a strongly electron accepting unit that has primarily been investigated for application in photovoltaic systems or as fluorescent bioimaging agents or sensors. The strongly electron accepting nature of the BTZ group, in combination with its excellent photostability and options for chemical derivatisation, has kindled interest within the photochemistry community with regards to using this unit as a prospective building block in π-conjugated electron donor-acceptor photocatalysts. The aim of this review is to highlight the research surrounding the development of photocatalytic systems based on the BTZ group. This will include discussing chemical reactions that can be used to synthesise or derivatise the BTZ motif, as well as highlighting methods that have been used to alter the structural, photophysical or optoelectronic properties of electron donor-BTZ electron acceptor systems. Subsequent discussion of the photocatalytic applications will span both homogeneous photocatalysts (molecules, molecular cages and linear polymers) and heterogeneous materials (such as crosslinked organic polymers, covalent organic frameworks, and metal-organic frameworks) containing the BTZ group and structurally related groups
Beyond growth: Reshaping fisheries for a wellbeing economy
No full textContemporary fisheries have been shaped by a paradigm of perpetual growth, characterized by increasing global production and consumption. While this growth has driven economic benefits and technological progress, it has jeopardized the sustainability of marine ecosystems, with implications for the long-term livelihoods and wellbeing of fishers, consumers and resource dependent coastal populations worldwide. This paper advocates for a shift beyond growth towards a wellbeing economy. It considers how five fundamental principles intrinsic to a wellbeing economy - purpose, nature, fairness, participation and dignity - can help reorient the fisheries sector. The paper then provides ten actionable recommendations for reshaping the composition and structure of economic activity in fisheries to enhance societal wellbeing and equity within ecological boundaries. In a world grappling with the consequences of unchecked economic growth, this paper offers insights into fostering a regenerative fisheries system that safeguards human prosperity and environmental integrity.<br/
Women’s Bargaining Power and Children’s Nutritional Status: Evidence from Indonesia
No full textChild stunting is a serious challenge in Indonesia, one of the largest middle-income countries in the world. Beyond the influence of bio-behavioral determinants, mothers’ bargaining power in the household is expected to have an overarching contribution to stunting, particularly as the primary caregivers of their children. Using a dataset from the fifth wave of the Indonesia Family Life Survey (IFLS-5), this study examines whether and to what extent a mother’s bargaining power influences children’s nutritional status. The study uses the instrumental variables method to correct the potential endogeneity of the mother’s bargaining power. Results suggest that children of mothers with higher intrahousehold bargaining power have a lower prevalence of stunting and better anthropometric outcomes. However, other members of the household matter, in the sense that improved outcomes are evidenced when the mother exercises her choice in decision making in a more consensual manner, by consultation with other household members.HIGHLIGHTS- In Indonesia, higher women’s bargaining power enhances child nutritional long-term outcomes.- Child nutrition improves when women make decisions jointly with other family members.- Boys appear to be the main beneficiaries of mothers’ higher bargaining power.- Policies to increase women’s agency need to consider family support and social norms
A novel kinetically-driven approach to forming columnar {110}-textured lithium metal anodes with extended cycle life
No full textConstructing {110}‐textured lithium (Li) metal anodes is a promising strategy to extend battery life. While preparation of such anodes has been the subject of a few studies, their focus has been exclusively on thermodynamically‐driven (equilibrium) strategies. Through a systematic screening of bath conditions, the study reported here identifies a novel kinetically‐driven protocol that enhances the volume fraction of {110} texture by more than fivefold compared to equilibrium approaches. The protocol involves Li deposition at high current densities or low temperatures in a commonly used LiNO3‐containing ether‐based electrolyte. Columnar {110}‐oriented grains are formed through a growth rate selection process arising from the stronger electronic coupling and faster electron transfer rate between Li(110) and Li+ cations compared to other lattice planes. LiNO3 plays a crucial role by inhibiting the deposition on the Li(110) plane less than the other planes. Simple bath condition adjustments yield optimized {110}‐textured Li anodes with improved plating/stripping homogeneity that suppresses dendrite formation and electrolyte consumption, resulting in extended cycle life in lean‐electrolyte full cells. This kinetically‐driven approach offers mechanistic insight into Li texture formation and a promising route to high‐performance Li metal anodes
A Hybrid Approach to Music Recommendations for Improving ADHD Productivity
No full textThis study explores the development of a web application designed to enhance focus, motivation, and productivity in individuals with ADHD by inte-grating music recommendation algorithms, task management tools, and note-taking features. Music recommendations were generated using a hybrid approach combining Collaborative Filtering and Content-based Filtering to create tailored playlists based on tracks users “liked” during the procedure. The application was evaluated through a systematic framework using the Pomodoro Technique, where twenty ADHD-diagnosed students (aged 18+) completed two 20-minute sessions, each followed by a 5-minute break in between. In the first session, participants were asked to listen to one of three pre-selected playlists (Lo-Fi, Classical, Binaural Beats) and indicated their preferences by liking tracks while performing focused tasks. Using participants’ selections from the first session, the recommendation model generated a personalized "For You" playlist during the break, which they engaged with under identical condi-tions in the second session. A mixed-methods analysis was then used to combine quantitative data from Likert scale ratings and qualitative feedback from open-ended responses and structured questionnaires. The results of this study revealed significant improvements in all key areas, supporting the effectiveness of personalized music recommendations in academic and professional settings. Future work will focus on refining the application and expanding the recommendation system to accommodate a broader range of musical preferences
A fractional partition of unity finite element method for transient anomalous diffusion problems
No full textA fractional partition of unity finite element method is proposed for the solution of the transient anomalous diffusion equation. The Caputo integro-differential operator is employed to represent the fractional time-derivative in these problems. To approximate the Caputo fractional derivative, we propose a new numerical differentiation formula using quadratic splines. For the spatial discretization, we implement an enriched finite element method on unstructured meshes. In the present study, a category of exponential functions incorporating fractional orders is introduced as enrichment functions to refine the finite element approximation. These functions are designed to capture the fractional characteristics of the solution more effectively. By integrating these enrichment functions through the partition of unity framework, the method utilizes prior knowledge of the fractional problem, leading to a substantial enhancement in approximation accuracy while preserving the fundamental advantages of the traditional finite element method. Consequently, the proposed approach delivers precise numerical solutions even with coarse meshes and requires significantly fewer degrees of freedom compared to conventional finite element techniques. Moreover, the mesh resolution remains unaffected by variations in the fractional order, allowing for a consistent mesh structure regardless of changes in fractional parameters. Through extensive numerical simulations, we consistently verify the effectiveness of the proposed technique in achieving high levels of accuracy. This approach not only ensures reliable and precise results but also broadens the applicability of the finite element method, making it more capable of handling time-fractional transient diffusion problems that have traditionally been challenging for standard methods
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