Large Language Models (LLMs) and Evolutionary Computation (EC) are increasingly being combined to support automated optimization, algorithm design, and adaptive decision-making. This survey reviews the bidirectional interaction between these two paradigms and examines how their complementary strengths can be leveraged in hybrid intelligent systems. First, we analyze how EC can enhance LLM-based systems through prompt optimization, hyperparameter tuning, and architecture search. Second, we review how LLMs can improve EC by supporting metaheuristic design, surrogate reasoning, adaptive operator control, and heuristic generation. We further discuss emerging co-adaptive frameworks in which LLMs and EC interact through iterative feedback loops. Beyond summarizing recent developments, the survey provides a structured perspective on interaction mechanisms, application patterns, and methodological challenges, including computational cost, reproducibility, interpretability, benchmarking, and generalization. The paper concludes by outlining open research questions and future directions for developing more robust, transparent, and scalable LLM-EC systems.
Africa is increasingly being exposed to the negative impacts of climate and environmental change, while having less capacity to respond compared to other continents. The vulnerability partially results from unprecedented demographic growth, urbanization, and industrialization. However, the continent has still largely been underserved by the broader Earth system science (ESS) community, as evidenced by the limited amount of ESS data and research that cover Africa compared to other areas of the world. Here, we present the recent University Corporation for Atmospheric Research (UCAR) Africa Initiative that aims to enhance environmental sustainability in Africa by fostering international collaborative research partnerships coled by African scientists. Specifically, we outline urgent challenges and opportunities identified through an international workshop in six areas of ESS, namely, 1) air quality and health, 2) weather, 3) climate, 4) land and water, 5) social science perspectives, and 6) developing equitable collaboration and sustainable infrastructure. We highlight examples of successful partnerships and conclude with recommendations to advance collaborative, actionable ESS research that addresses Africa's critical environmental challenges.
Abstract Transcription–replication conflicts (TRCs) arise when DNA replication forks encounter actively transcribing RNA polymerases, creating a major threat to genome stability. These conflicts, which can occur in different orientations, disrupt replication fork progression, impair transcriptional fidelity and reshape the chromatin landscape. In this review, we discuss emerging conceptual insights into how cells coordinate replication and transcription in space and time to minimise such encounters, and we highlight the central role of RNA polymerase II dynamics in both preventing and resolving TRCs. We further describe how TRCs engage a broad network of genome maintenance pathways that regulate R-loops, stabilize stalled forks and maintain chromatin integrity. Importantly, elevated or mismanaged TRCs create vulnerabilities that many cancers exploit, positioning conflict-resolution mechanisms as attractive therapeutic targets. Finally, we examine current challenges in detecting and analysing these transient, dynamic events and underscore the need for improved imaging and sequencing technologies to study the genome’s molecular “traffic jams”. A deeper mechanistic understanding of TRCs will be crucial for harnessing them in precision oncology and clarifying their broader roles in genome regulation.
Context. High-mass stars and star clusters form from the fragmentation of massive dense clumps driven by gravity, turbulence, and magnetic fields. The extent to which each of these agents impacts the fragmentation depending on the clump mass, density, and evolutionary stage is still largely unknown. Aims. The ALMA evolutionary study of high-mass protocluster formation in the GALaxy (ALMAGAL) project, with similar to 1000 clumps observed at similar to 1000 au resolution, allows a statistically significant characterization of the fragmentation process over a large range of clump physical parameters and evolutionary stages. Our goal is to characterize where and how the dense cores revealed by ALMA are distributed in massive potentially cluster-forming clumps to trace how fragmentation is initially set and how it proceeds before gas dispersal due to stellar feedback. Methods. We characterized the spatial distribution of dense cores in the 514 ALMAGAL clumps that host at least four cores, using a set of quantitative descriptors that we evaluated against the clump bolometric luminosity-to-mass ratio, which we adopted as an indicator of the evolution of the system. We measured the separations between cores with the minimum spanning tree (MST) method, which we compared with the predictions of gravitational fragmentation from Jeans theory. We investigated whether cores have specific arrangements using the Q parameter or variations due to their masses with the mass segregation ratio, Lambda(MSR). Results. ALMAGAL cores are distributed throughout the entire area of the clump, usually arranged in elliptical groups with an axis ratio e similar to 2.2, although high values with e >= 5 are also observed. We found a single characteristic core separation per clump in similar to 76% of cases, suggesting that multiple fragmentation lengths may be frequently present. Typical core separations are compatible with the clump-averaged thermal Jeans length,lambda(th)(J). However, we found an additional population of cores, typical of low-fragmented and young clumps, which are on average more widely separated with l approximate to 3 & times; lambda(th)(J). By stacking the distributions of the core separations in clumps of similar evolutionary stage, we also found that the separation decreases on average from l similar to 22 000 au in younger systems to l similar to 7000 au in more evolved ones. The ALMAGAL cores are typically distributed in fractal-type subclusters, while centrally concentrated patterns appear only at later stages, but we do not observe a progressive transition between these configurations with evolution. Finally, we also found 110 ALMAGAL systems with a signature of mass segregation, with an occurrence that increases with evolution.
Measuring galaxy rotation curves is critical for inferring the properties of dark-matter haloes in the Lambda cold dark matter (Lambda CDM) paradigm. We present HI rotation curves and mass models for 20 galaxies from the MIGHTEE survey. Using extended H I kinematics, we construct resolved mass models that include stellar, gaseous, and dark-matter components. Stellar masses are derived using 3.6 mu m imaging under fixed mass-to-light ratio (Upsilon(*) = M/L) assumptions and are complemented, for the first time for a H I-selected sample, by spatially resolved M/L, obtained from multiwavelength spectral energy distribution fitting. We examine the ratio of baryonic to observed rotation velocity (V-bar/V-obs) at the characteristic radius R-2.2. Adopting a fixed Upsilon(*) = 0.5M((R))/L-(R) yields a clear dependence of V-2.2 /V-obs on galaxy luminosity, while adopting Upsilon(*) = 0.2M((R))/L-(R) substantially weakens this trend. In contrast, the resolved M/L analysis preserves the luminosity dependence while modifying the stellar contribution on a galaxy-by-galaxy basis, providing a more accurate representation of the underlying relation. We model the dark-matter haloes using Navarro-Frenk-White profiles and find that the different assumptions for a fixed a M/L systematically shift galaxies relative to the theoretical stellar-to-halo mass and baryonic-to-halo mass relations, while the spatially varying M/L yields the closest agreement with theoretical benchmarks within Lambda CDM. We therefore demonstrate that future investigations of the dark matter properties of galaxies using rotation curves need to account for varying M/L across individual galaxy profiles and between galaxies in order to obtain accurate measurements of the dark matter, and therefore test Lambda CDM.
