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Redefining interiors and envelopes: hydrogen–silicate miscibility and its consequences for the structure and evolution of sub-Neptunes
Full text linkABSTRACT We present the first evolving interior structure model for sub-Neptunes that accounts for the miscibility between silicate magma and hydrogen. Silicate and hydrogen are miscible above ∼4000 K at pressures relevant to sub-Neptune interiors. Using the H–MgSiO phase diagram, we self-consistently couple physics and chemistry to determine the radial extent of the fully miscible interior. Above this region lies the envelope, where hydrogen and silicates are immiscible and exist in both gaseous and melt phases. The binodal surface, representing a phase transition, provides a physically/chemically informed boundary between a planet’s ‘interior’ and ‘envelope’. We find that young sub-Neptunes can store several tens of per cent of their hydrogen mass within their interiors. As the planet cools, its radius and the binodal surface contract, and the temperature at the binodal drops from ∼4000 to ∼3000 K. Since the planet’s interior stores hydrogen, its density is lower than that of pure-silicate. Gravitational contraction and thermal evolution lead to hydrogen exsolving from the interior into the envelope. This process slows planetary contraction compared to models without miscibility, potentially producing observable signatures in young sub-Neptune populations. At early times (∼10–100 Myr), the high temperature at the binodal surface results in more silicate vapour in the envelope, increasing its mean molecular weight and enabling convection inhibition. After Gyr of evolution, most hydrogen has exsolved, and the radii of miscible and immiscible models converge. However, the internal distribution of hydrogen and silicates remains distinct, with some hydrogen retained in the interior
JWST/NIRSpec insights into the circumnuclear region of Arp 220: A detailed kinematic study
Full text linkThe study of starburst and active galactic nuclei (AGN) feedback is crucial for understanding the regulation of star formation and the evolution of galaxies across cosmic time. Arp 220, the closest ultraluminous infrared galaxy (ULIRG), is in an advanced phase of a major merger with two distinct nuclei, and it shows evidence of multiphase (molecular, ionized, and neutral) and multiscale (from 5 kpc) outflows. Therefore, it represents an ideal system for investigating outflow mechanisms and feedback phenomena in detail. Using new JWST NIRSpec IFU observations, we investigated the spatially resolved gaseous (in both ionized and hot molecular phases) and stellar kinematics in the innermost 1 kpc. We decoupled the different gas kinematic components through multi-Gaussian fitting, identifying two multiphase outflows, each associated with one nucleus, with velocities up to ∼1000 km s −1 . We also resolved two counter-rotating discs around each nucleus embedded in a larger-scale rotational disk. We compute the total (including ionized, cold, and hot molecular) outflow mass (≈10 7 M ⊙ ), the mass rate (≈15 M ⊙ yr −1 ), and the energetics ( Ė out ≈ 10 42 erg s −1 ) for each nucleus, and we found that the ionized and hot molecular outflowing gas contribute around 2-30% of the total mass and the energy of the outflows, as inferred from the combination of multiwavelength information. We discuss the possible origin of the outflows, finding no compelling evidence to prefer a starburst- or AGN-driven scenario. Regardless of their nature, outflows in Arp 220 propagate in multiple directions from parsec to kiloparsec scales, potentially impacting a significant portion of the host galaxy. This contrasts with isolated systems where outflows typically follow a more collimated path or are limited to the central region of the galaxy and hence do not affect the interstellar medium throughout the entire galaxy. This study highlights the importance of investigating merging systems with multiwavelength facilities, including JWST/NIRSpec IFU, to obtain a comprehensive understanding of feedback mechanisms in galaxy evolution
Unraveling microglial spatial organization in the developing human brain with DeepCellMap, a deep learning approach coupled with spatial statistics
Full text linkMapping cellular organization in the developing brain presents significant challenges due to the multidimensional nature of the data, characterized by complex spatial patterns that are difficult to interpret without high-throughput tools. Here, we present DeepCellMap, a deep-learning-assisted tool that integrates multi-scale image processing with advanced spatial and clustering statistics. This pipeline is designed to map microglial organization during normal and pathological brain development and has the potential to be adapted to any cell type. Using DeepCellMap, we capture the morphological diversity of microglia, identify strong coupling between proliferative and phagocytic phenotypes, and show that distinct spatial clusters rarely overlap as human brain development progresses. Additionally, we uncover an association between microglia and blood vessels in fetal brains exposed to maternal SARS-CoV-2. These findings offer insights into whether various microglial phenotypes form networks in the developing brain to occupy space, and in conditions involving haemorrhages, whether microglia respond to, or influence changes in blood vessel integrity. DeepCellMap is available as an open-source software and is a powerful tool for extracting spatial statistics and analyzing cellular organization in large tissue sections, accommodating various imaging modalities. This platform opens new avenues for studying brain development and related pathologies
AI agents in service experience: towards autonomous and conscious agency
Full text linkPurpose Despite rapid advancements in AI and large language models (LLMs), there remains a critical gap in understanding how AI agents function as service actors and how they influence service processes and outcomes. This study addresses this gap by integrating AI agency and service experience dimensions, categorizing AI capabilities across six levels, from passive automation to fully conscious AI, and examining their impact on service workflows, human and multi-agent collaboration, and decision-making. Design/methodology/approach This research adopts a conceptual approach, drawing from literature on service experience and AI agency. It illustrates real-world applications of AI agents in service settings and outlines a future research agenda to explore the strategic and ethical implications of AI-driven service ecosystems. Findings AI agents transform service experiences by shaping action, collaboration, processes, outcomes, and learning. Automaticity AI enhances process efficiency through task automation but lacks adaptability, while Relational AI improves personalization in customer and employee engagement. Cognitive AI enables data-driven decision-making, whereas Autonomous AI optimizes workflows without human oversight. Innovator AI drives service transformation, generating novel solutions such as AI-driven drug discovery, while Conscious Organizational AI raises governance and ethical concerns for strategic decision makers. Originality/value This study advances AI agency theory in service experience, offering a structured framework to guide AI agent integration and its impact on context, process, collaboration, action, outcome and learning
Colouration evo-devo: the developmental basis of intra-specific variation in cichlid pigmentation
No full textUnderstanding why and how organisms diversify is a major goal of evolutionary biology. The fields of evolutionary developmental biology, evolutionary ecology, and population genetics have taken complementary approaches to this task, yet a lack of integration between these fields limits our understanding of the evolution of phenotypic diversity. Classical evo-devo tends to comprise comparative developmental biology between phylogenetically distant model organisms, while population genetics and evolutionary ecology studies often consider development as a ‘black-box’ between genotype and phenotype. Consequently, the role of development in the diversification of adaptive traits is not well understood. In this PhD thesis, I present a study of the development a trait exhibiting adaptive variation.
Cichlid egg-spots are a well-suited model for investigating the development of diversifying traits. Evolving under sexual selection, egg-spots are dense aggregations of xanthophores and iridophores on haplochromine cichlid anal fins, exhibiting remarkable inter- and intra-specific variation. In a population of the generalist species Astatotilapia calliptera from the Lake Malawi/Nyasa radiation, variation in egg-spots maintains signal visibility across different depths. A Genome Wide Association Study (GWAS) identified oca2, a gene required for pigment synthesis in melanophores, as a candidate associated with egg-spot number variation.
I present a study of A. calliptera egg-spot development and the developmental basis of intra-specific variation in egg-spot number. First, I characterise the development of egg-spots in embryo and juvenile stages in wild-type A. calliptera ‘kisiba/masoko’, describing a key role for iridophores initiating aggregations. I find consistent early development between littoral and benthic ecotypes, and identify developmental sources of variation between individuals, including developmental plasticity. Further, my results suggest differences in patterning rules from zebrafish stripe development, indicating evolutionary lability in pigment cell interactions.
To examine the developmental role of candidate genes for egg-spot variation, I review the application of CRISPR/Cas9 technology to cichlid fish, defining the state-of-the-art of cichlid genome editing and synthesising resources. Next I establish CRISPR/Cas9 editing in A. calliptera: I report efficient editing and germline transmission of mutations, and demonstrate the null mutant phenotypes of biallelic oca2 mutants, with amelanistic embryos and adults.
Finally, I examine the role of oca2 in the development of egg-spots. Comparing amelanistic and melanistic siblings, I find a higher number of egg-spots in oca2 null mutants. My comparison of juvenile development reveals delayed initial aggregations in oca2 null mutants followed by an increased number of iridophore clusters, indicating an effect on timing and an increased tendency to initiate new aggregations in amelanistic fins. Though growth patterns and egg-spot sizes do not differ, I find aggregations in amelanistic fins are more likely to occupy the proximal, faster-growing region of the fin. My findings not only validate the GWAS results, but also provide insights into the complexity of developmental divergence that underlies phenotypic divergence.
The results I present in this thesis provide a developmental connection between the genotypic, phenotypic, and environmental divergence in A. calliptera egg-spots. In particular, my work demonstrates the variety of mechanisms by which developmental processes transmit and integrate variation from both genetic and environmental sources, therefore contributing to our understanding of the interplay between these factors and highlighting the importance of studying development in micro- and eco-evolutionary contexts
AI-Augmented Co-Design in Healthcare: Log-Based Markers of Teamwork Behaviors and Collective Intelligence Outcomes.
Full text linkCo-design in healthcare settings requires teams to utilize each other's knowledge effectively, but practical guidance and simple methods for observing collaboration are often lacking. We tested whether a lightweight AI assistant that guides the process-and automatically logs who speaks, when, and how work progresses-can make teamwork easier to manage and easier to track. Six four-person teams completed the same five-phase session. The assistant nudged timing, turn-taking, and artifact hand-offs; all interactions were recorded in a shared workspace. We assessed usability and acceptance, expert-rated product quality (technical performance), perceived team performance, and self-rated technical contribution, and we summarized basic log signals of participation and pacing (e.g., turn-taking balance, average turn duration). Analyses were descriptive. All teams finished the protocol with complete logs. Outcomes were favorable (expert ratings averaged 4.18/5; perceived performance 6.14/7; self-rated contribution 4.08/5). Teams with more balanced participation and clearer pacing tended to report better performance, whereas simply having more turns did not. A process-guiding AI assistant can quantify teamwork behaviors as markers of collective intelligence and support reflection in everyday clinical co-design; future work will examine the generalizability of these findings across different sites
Efficient ab initio calculation of electronic stopping in disordered systems via geometry pre-sampling: Application to liquid water.
Full text linkKnowledge of the electronic stopping curve for swift ions, Se(v), particularly around the Bragg peak, is important for understanding radiation damage. Experimentally, however, the determination of such a feature for light ions is very challenging, especially in disordered systems such as liquid water and biological tissue. Recent developments in real-time time-dependent density functional theory (rt-TDDFT) have enabled the calculation of Se(v) along nm-sized trajectories. However, it is still a challenge to obtain a meaningful statistically averaged Se(v) that can be compared to observations. In this work, taking advantage of the correlation between the local electronic structure probed by the projectile and the distance from the projectile to the atoms in the target, we devise a trajectory pre-sampling scheme to select, geometrically, a small set of short trajectories to accelerate the convergence of the averaged Se(v) computed via rt-TDDFT. For protons in liquid water, we first calculate the reference probability distribution function (PDF) for the distance from the proton to the closest oxygen atom, ϕR(rp→O), for a trajectory of a length similar to those sampled experimentally. Then, short trajectories are sequentially selected so that the accumulated PDF reproduces ϕR(rp→O) to increasingly high accuracy. Using these pre-sampled trajectories, we demonstrate that the averaged Se(vp) converges in the whole velocity range with less than eight trajectories, while other averaging methods using randomly and uniformly distributed trajectories require approximately ten times the computational effort. This allows us to compare the Se(vp) curve to experimental data and assess widely used empirical tables based on Bragg's rule
Remote monitoring of wide-ranging real-world changes in adults following ADHD medication initiation.
Full text linkWhile attention-deficit/hyperactivity disorder (ADHD) medication is effective for core symptoms, its broader and progressive impacts remain underexplored. This study evaluated real-world changes in ADHD symptoms and impairments, co-occurring psychiatric symptoms, physical measures, and health behaviors following ADHD medication initiation in adults. Data were drawn from a remote monitoring cohort recruited from adult ADHD clinic waiting lists in the United Kingdom and Spain. Participants completed 4-weekly smartphone-based self-reports and continuously wore a wearable device to monitor behaviors such as physical activity and sleep. We additionally developed novel wearable-derived features to approximate restlessness. A subset of 176 participants with valid baseline (off-medication) and up to three 4-weekly on-medication assessments was included. Compared to the off-medication phase, the on-medication phase was significantly associated with improvements in ADHD symptoms and impairments, as well as reductions in depression, anxiety, irritability, and aggression. Additional changes included reduced alcohol use, healthier diet, elevated heart rate, lower blood pressure, reduced waist circumference, increased physical activity, less restlessness, and improved sleep quality. Several domains showed significant progressive changes, including continued improvements in ADHD symptoms, impairments, and irritability; rising heart rate; declining body weight; and delayed sleep timing. These findings suggest ADHD medication in adults is associated with broad real-world benefits alongside some potential concerns, such as elevated heart rate and delayed sleep. This study highlights the potential of remote monitoring technologies to capture multidimensional treatment responses in daily life and provides a foundation for future research to support both clinical care and self-management in ADHD
How air pollution makes firms less innovative: human capital and adaptive strategies
Full text linkThis paper studies the long-term effects of air pollution on firms’ human capital accumulation and the adaptive strategies they adopt in response. Leveraging a spatial regression discontinuity (RD) design based on China’s Huai River heating policy and utilizing a novel dataset with detailed firm-level human capital information, we show that air pollution significantly reduces the share of R&D staff with advanced degrees, particularly PhD and master’s degrees. To offset these challenges, firms in more polluted regions increasingly turn to external strategies, such as acquiring technology and collaborating with universities, as well as internal measures, including expanding welfare subsidies for R&D staff and investing in experimental instruments. However, despite these adaptive efforts, firms in polluted areas still generate fewer innovations than their counterparts in cleaner regions. Overall, our findings highlight the role of internal human capital in sustaining innovative capacity
GRB 250704B: An Off-axis Short GRB with a Long-lived Afterglow Plateau
Full text linkWe present a detailed multiwavelength afterglow study of the short gamma-ray burst (GRB) GRB 250704B, extensively monitored in optical and near-infrared bands. Its afterglow displays an unusually long duration plateau followed by an achromatic break and a steep decline, deviating from canonical GRB afterglows. While long plateaus are often explained by central engine activity, we find that for GRB 250704B an energy injection model requires unreasonable parameters. The afterglow is better explained by an off-axis power-law structured jet with a narrow core (θc ≈ 0 .° 7) viewed at a modest angle (θv ≈ 1 .° 9). A comparison with GRB 170817A shows that both events are consistent with the off-axis structured jet scenario, where the shape of the light curve is governed primarily by the geometry of the jet and the viewing angle rather than the energetics, microphysical parameters, or external density. Our results underscore the importance of incorporating the jet structure in GRB modeling