Large Domain Research Articles

Self-adaptive smoothing model for cardinality estimation

Abstract Cardinality estimation is a crucial component in query optimizers. After decades of research, employing autoregressive models for cardinality estimation has demonstrated remarkable accuracy. However, when queries involve attributes with large domain sizes, autoregressive model-based estimators struggle to accurately capture the data distribution, leading to poor performance. Furthermore, these models often exhibit significant errors when handling queries with low-selectivity predicates. To address these challenges, we propose a self-adaptive cardinality estimator named AdaCard. Initially, we employ a self-adaptive smoothing factor selection strategy to variably adjust the original data, thereby mitigating the impact of large domain sizes. Secondly, to correct errors stemming from Monte Carlo sampling, we utilize resampling to refine the handling of low-selectivity predicates, thereby improving accuracy. Through evaluation using four real-world benchmarks, we compared AdaCard with mainstream baselines. The final results show that our estimator has the lowest tail estimation error and improves accuracy by nearly 10$\times $ over the second-best method, with similar latency and model size.

3D chromatin maps of a brown alga reveal U/V sex chromosome spatial organization.

Nuclear three dimensional (3D) folding of chromatin structure has been linked to gene expression regulation and correct developmental programs, but little is known about the 3D architecture of sex chromosomes within the nucleus, and how that impacts their role in sex determination. Here, we determine the sex-specific 3D organization of the model brown alga Ectocarpus chromosomes at 2 kb resolution, by mapping long-range chromosomal interactions using Hi-C coupled with Oxford Nanopore long reads. We report that Ectocarpus interphase chromatin exhibits a non-Rabl conformation, with strong contacts among telomeres and among centromeres, which feature centromere-specific LTR retrotransposons. The Ectocarpus chromosomes do not contain large local interactive domains that resemble TADs described in animals, but their 3D genome organization is largely shaped by post-translational modifications of histone proteins. We show that the sex determining region (SDR)within the U and V chromosomes are insulated and span the centromeres andwe link sex-specific chromatin dynamics and gene expression levels to the 3D chromatin structure of the U and V chromosomes. Finally, we uncover the unique conformation of a large genomic region on chromosome 6 harboring an endogenous viral element, providing insights regarding the impact of a latent giant dsDNA virus on the host genome's 3D chromosomal folding.

A Unified Model for Chinese Cyber Threat Intelligence Flat Entity and Nested Entity Recognition

In recent years, as cybersecurity threats have become increasingly severe and cyberattacks have occurred frequently, higher requirements have been put forward for cybersecurity protection. Therefore, the Named Entity Recognition (NER) technique, which is the cornerstone of Cyber Threat Intelligence (CTI) analysis, is particularly important. However, most existing NER studies are limited to recognizing single-layer flat entities, ignoring the possible nested entities in CTI. On the other hand, most of the existing studies focus on English CTIs, and the existing models performed poorly in a limited number of Chinese CTI studies. Given the above challenges, we propose in this paper a novel unified model, RBTG, which aims to identify flat and nested entities in Chinese CTI effectively. To overcome the difficult boundary recognition problem and the direction-dependent and distance-dependent properties in Chinese CTI NER, we use Global Pointer as the decoder and TENER as the encoder layer, respectively. Specifically, the Global Pointer layer solves the problem of the insensitivity of general NER methods to entity boundaries by utilizing the relative position information and the multiplicative attention mechanism. The TENER layer adapts to the Chinese CTI NER task by introducing an attention mechanism with direction awareness and distance awareness. Meanwhile, to cope with the complex feature capture of hierarchical structure and dependencies among Chinese CTI nested entities, the TENER layer solves the problem by following the structure of multiple self-attention layers and feed-forward network layers superimposed on each other in the Transformer. In addition, to fill the gap in the Chinese CTI nested entity dataset, we further apply the Large Language Modeling (LLM) technique and domain knowledge to construct a high-quality Chinese CTI nested entity dataset, CDTinee, which consists of six entity types selected from STIX, including nearly 4000 entity types extracted from more than 3000 threatening sentences. In the experimental session, we conduct extensive experiments on multiple datasets, and the results show that the proposed model RBTG outperforms the baseline model in both flat NER and nested NER.

Atypical phase transition, twinning and ferroelastic domain structure in bis(ethylenediammonium) tetrabromozincate(II) bromide, [NH3(CH2)2NH3]2[ZnBr4]Br2

Single-crystal growth, differential thermal analysis (DTA), derivative thermogravimetry (DTG), differential scanning calorimetry (DSC), X-ray structural studies and polarized microscopy observations of bis(ethylenediammonium) tetrabromozincate(II) bromide [NH3(CH2)2NH3]2[ZnBr4]Br2 are presented. A reversible phase transition is described. At room temperature, the complex crystallizes in the monoclinic system. In some cases, the single crystals are twinned into two or more large domains of ferroelastic type with domain walls in the (100) crystallographic plane. DTA and DTG measurements show chemical stability of the crystal up to ∼538 K. In the DSC studies, a reversible isostructural phase transition was revealed at ∼526/522 K on heating/cooling run, respectively. Optical observation on the heating run reveals that at the phase transition the plane of twinning (domain wall) does not disappear and additionally the appearance of a new domain structure of ferroelastic type with domain walls in the planes (101), (101), (100) and (001) is observed. The domain structure pattern is preserved after cooling to the room-temperature phase and the symmetry of this phase is unchanged.

Dynamic Adaptive and Fully Unstructured Tetrahedral Gridding: Application to CO2 Sequestration with Consideration of Full Fluid Compressibility

Numerical simulations of complex subsurface flow problems and geomechanics will advance enormously by dynamic adaptive gridding. Only a small part of a large domain where sharp changes occur may require fine gridding. In this work, we introduce a methodology to carry out dynamic adaptive gridding for large-scale flow problems. The algorithm allows 2D and 3D unstructured gridding with consideration of full fluid compressibility in single-phase, and two-phase compositional flow. We divide a triangular element into four and a tetrahedron element into eight which creates hanging nodes at each level of refinement. The handing nodes are eliminated by splitting extra elements. As a result, a transition region exists between the fine and coarse grid regions of the domain. We have applied the method to CO2 sequestration in subsurface aquifers. The conditions are selected such that gravity fingers develop from density increase by the dissolution of CO2 in the aqueous phase. The selected examples include large domains where neither systematic studies nor dynamic adaptive gridding have been reported in the past. Results from comparison with uniform gridding reveal a speedup of up to three orders of magnitude in 3D.

Integrated Biochemical and Computational Methods for Deciphering RNA‐Processing Codes

ABSTRACTRNA processing involves steps such as capping, splicing, polyadenylation, modification, and nuclear export. These steps are essential for transforming genetic information in DNA into proteins and contribute to RNA diversity and complexity. Many biochemical methods have been developed to profile and quantify RNAs, as well as to identify the interactions between RNAs and RNA‐binding proteins (RBPs), especially when coupled with high‐throughput sequencing technologies. With the rapid accumulation of diverse data, it is crucial to develop computational methods to convert the big data into biological knowledge. In particular, machine learning and deep learning models are commonly utilized to learn the rules or codes governing the transformation from DNA sequences to intriguing RNAs based on manually designed or automatically extracted features. When precise enough, the RNA codes can be incredibly useful for predicting RNA products, decoding the molecular mechanisms, forecasting the impact of disease variants on RNA processing events, and identifying driver mutations. In this review, we systematically summarize the biochemical and computational methods for deciphering five important RNA codes related to alternative splicing, alternative polyadenylation, RNA localization, RNA modifications, and RBP binding. For each code, we review the main types of experimental methods used to generate training data, as well as the key features, strategic model structures, and advantages of representative tools. We also discuss the challenges encountered in developing predictive models using large language models and extensive domain knowledge. Additionally, we highlight useful resources and propose ways to improve computational tools for studying RNA codes.

Ultrafast Time-Domain Spectroscopy Reveals Coherent Vibronic Couplings upon Electronic Excitation in Crystalline Organic Thin Films.

The coherent coupling between electronic excitations and vibrational modes of molecules largely affects the optical and charge transport properties of organic semiconductors and molecular solids. To analyze these couplings by means of ultrafast spectroscopy, highly ordered crystalline films with large domains are particularly suitable because the domains can be addressed individually, hence allowing azimuthal polarization-resolved measurements. Impressive examples of this are highly ordered crystalline thin films of perfluoropentacene (PFP) molecules, which adopt different molecular orientations on different alkali halide substrates. Here, we report polarization-resolved time-domain vibrational spectroscopy with 10 fs time resolution and Raman spectroscopy of crystalline PFP thin films grown on NaF(100) and KCl(100) substrates. Coherent oscillations in the time-resolved spectra reveal vibronic coupling to a high-frequency, 25 fs, in-plane deformation mode that is insensitive to the optical polarization, while the coupling to a lower-frequency, 85 fs, out-of-plane ring bending mode depends significantly on the crystalline and molecular orientation. Comparison with calculated Raman spectra of isolated PFP molecules in vacuo supports this interpretation and indicates a dominant role of solid-state effects in the vibronic properties of these materials. Our results represent a first step toward uncovering the role of anisotropic vibronic couplings for singlet fission processes in crystalline molecular thin films.

A microphase-separated structure of polystyrene-b-polyisoprene-b-polystyrene triblock copolymers prepared via shear-press and injection molding methods during uniaxial deformation

The influence of the preparation method on the initial structure and deformation behavior of polystyrene (PS) - polyisoprene (PI) - PS (SIS) triblock copolymer elastomers was investigated using small-angle X-ray scattering (SAXS) and wide-angle X-ray diffraction (WAXD). Shear pressing (SP) and injection molding (IM) were used as the preparation methods. The samples exhibited a microphase-separated structure, in which the PS cylinders were packed in a hexagonal lattice for the entire sample. SP-SIS possessed a higher degree of microphase separation (DMPS) and an ordering of a microphase-separated structure (OMPSS), and lower degree of the PS cylinder orientation (DCO) than IM-SIS. Uniaxial tensile testing was performed along the parallel (//) and perpendicular (–|) directions to the PS cylinder orientation combining in situ SAXS/WAXD measurements. Young’s modulus and tensile strength of IM-SIS were lager and smaller than those of SP-SIS. A change in the PS cylinder orientation, which occurs for –| stretching, of IM-SIS occurred at larger strain than SP-SIS, indicating that the orientation of highly ordered PS cylinders are difficult to be changed due to their larger domains. It was found that the DCO relates to Young's modulus, yielding, and change in the PS cylinder orientation, while the OMPSS and DMPS relate to tensile strength.

Massively Parallel Screening of Toll/Interleukin-1 Receptor (TIR)-Derived Peptides Reveals Multiple Toll-Like Receptors (TLRs)-Targeting Immunomodulatory Peptides.

Toll-like receptors (TLRs) are critical regulators of the immune system, and altered TLR responses lead to a variety of inflammatory diseases. Interference of intracellular TLR signaling, which is mediated by multiple Toll/interleukin-1 receptor (TIR) domains on all TLRs and TLR adapters, is an effective therapeutic strategy against immune dysregulation. Peptides that inhibit TIR-TIR interactions by fragmenting interface residues have potential as therapeutic decoys. However, a systematic method for discovering TIR-targeting moieties has been elusive, limiting exploration of the vast, unsequenced space of the TIR domain family. A comprehensive parallel screening method is developed to uncover novel TIR-binding peptides derived from previously unexplored surfaces on a wide range of TIR domains. A large peptide library is constructed, named TIR surfacesome, by tiling surface sequences of the large TIR domain family and screening against MALTIR and MyD88TIR, TIRs of two major TLR adaptor proteins, resulting in the discovery of hundreds of TIR-binding peptides. The selected peptides inhibited TLR signaling and demonstrated anti-inflammatory effects in macrophages, and therapeutic potential in mouse inflammatory models. This approach may facilitate the development of TLR-targeted therapeutics.

Distributed intelligence in industrial and automotive cyber–physical systems: a review

Cyber–physical systems (CPSs) are evolving from individual systems to collectives of systems that collaborate to achieve highly complex goals, realizing a cyber–physical system of systems (CPSoSs) approach. They are heterogeneous systems comprising various autonomous CPSs, each with unique performance capabilities, priorities, and pursued goals. In practice, there are significant challenges in the applicability and usability of CPSoSs that need to be addressed. The decentralization of CPSoSs assigns tasks to individual CPSs within the system of systems. All CPSs should harmonically pursue system-based achievements and collaborate to make system-of-system-based decisions and implement the CPSoS functionality. The automotive domain is transitioning to the system of systems approach, aiming to provide a series of emergent functionalities like traffic management, collaborative car fleet management, or large-scale automotive adaptation to the physical environment, thus providing significant environmental benefits and achieving significant societal impact. Similarly, large infrastructure domains are evolving into global, highly integrated cyber–physical systems of systems, covering all parts of the value chain. This survey provides a comprehensive review of current best practices in connected cyber–physical systems and investigates a dual-layer architecture entailing perception and behavioral components. The presented perception layer entails object detection, cooperative scene analysis, cooperative localization and path planning, and human-centric perception. The behavioral layer focuses on human-in-the-loop (HITL)-centric decision making and control, where the output of the perception layer assists the human operator in making decisions while monitoring the operator’s state. Finally, an extended overview of digital twin (DT) paradigms is provided so as to simulate, realize, and optimize large-scale CPSoS ecosystems.

A frequency-independent absorption function surrogate for perfectly matched layer in exterior acoustics

In many engineering applications, the solution of acoustic wave problems in the infinite domain is required over a broad frequency range with densely sampled increments. In order to achieve efficient numerical simulations via a spatial discretization, e.g. finite element method, additional artificial absorbing boundaries are necessary to truncate the computational domain into appropriate bounded sizes. One of the most commonly used non-reflecting techniques to attenuate propagating waves is known as the perfectly matched layer. However, the system matrices arising from the finite element treatment of the Helmholtz equation in the absorbing layers are frequency-dependent, implying that they must be formed and inverted at each frequency of interest. Such a procedure is rather troublesome for frequency sweeps. To address this, a surrogate of perfectly matched layers is proposed, which enables the corresponding system matrices to be independent of the frequency. Moreover, it avoids the use of a relatively large computational domain and relatively thick enclosed layers at low frequencies, thus improving the ability of perfectly matched layers across the entire frequency range. After that, an adaptive projection-based model order reduction scheme is further developed to reduce the computational complexity of exterior acoustic systems. A robust error indicator based on the relative error of two constructed reduced order models is accordingly introduced. The performance of the present solution framework is discussed and compared with other implementation strategies, in the context of multi-frequency solution of two-dimensional test models with single or multiple scatterers.

Modelling of planetary accretion and core-mantle structure formation

Abstract We advance a thermodynamically consistent model of self-gravitational accretion and differentiation in planets. The system is modeled in actual variables as a compressible thermoviscoelastic fluid in a fixed, sufficiently large domain. The supply of material to the accreting and differentiating system is described as a bulk source of mass, volume, impulse, and energy localized in some border region of the domain. Mass, momentum, and energy conservation, along with constitutive relations, result in an extended compressible Navier–Stokes-Fourier-Poisson system. The centrifugal and Coriolis forces are also considered. After studying some single-component setting, we consider a two-component situation, where metals and silicates mix and differentiate under gravity, eventually forming a core-mantle structure. The energetics of the models are elucidated. Moreover, we prove that the models are stable, in that self-gravitational collapse is excluded. Eventually, we comment on the prospects of devising a rigorous mathematical approximation and existence theory.

DAR-DRL: A dynamic adaptive routing method based on deep reinforcement learning

Mobile-centric wireless networks offer users a diverse range of services and experiences. However, existing intelligent routing methods often struggle to make suitable routing decisions during dynamic network changes, significantly limiting transmission performance. This paper proposes a dynamic adaptive routing method based on Deep Reinforcement Learning (DAR-DRL) to effectively address these challenges. First, to accurately model network state information in complex and dynamically changing routing tasks, we introduce a link-aware graph learning model (LA-GNN) that efficiently senses network information of varying structures through a hierarchical aggregated message-passing neural network. Second, to ensure routing reliability in dynamic environments, we design a hop-by-hop routing strategy featuring a large acceptance domain and a reliability guarantee reward function. This mechanism adaptively avoids routing holes and loops across various network scenarios while enhancing the robustness of routing under dynamic conditions. Experimental results demonstrate that the proposed DAR-DRL method achieves the network routing task with shorter end-to-end delays, lower packet loss rates, and higher throughput compared to existing mainstream methods across common dynamic network scenarios, including cases with dynamic traffic variations, random link failures (small topology changes), and significant topology alterations.

Estimating plant β-diversity using airborne and spaceborne imaging spectroscopy

ABSTRACT The increasing threats to grassland ecosystems from land-use/land-cover change, disturbances, and invasive species underscore the importance of monitoring grassland plant diversity. While most remote sensing studies have mainly focused on quantifying α-diversity (diversity within communities), less attention has been given to remotely estimating β-diversity (diversity between communities) in naturally-assembled grasslands. In this study, we used remote sensing to map plant β-diversity in a naturally-assembled grassland managed using prescribed fire and grazing in a North American tallgrass prairie ecosystem within the US Southern Great Plains. We aimed to assess the impact of time since fire on the relationship between in situ plant β-diversity and remotely–sensed β-diversity, also known as spectral β-diversity. We collected in situ observations at 60 m × 60 m, 120 m × 120 m, 180 m × 180 m, and 240 m × 240 m plots, alongside airborne and spaceborne DESIS imaging spectroscopy data with spatial resolutions of 1 m and 30 m, respectively. To assess how management practices influenced β-diversity, we grouped our in situ observations into three categories based on time since fire, including recently-burned (burn age <1 year), transitional (burn age of 1–2 years), and unburned (burn age >2 years). Our findings showed that the association between in situ and spectral β-diversity was strongly influenced by time since fire. Excluding plots with high soil cover (≥50%) improved our remote estimation of β-diversity, despite soil exposure effects. Our study demonstrated that remote sensing of β-diversity in grassland ecosystems is influenced by spatial scale, time since fire, and soil exposure, all of which can be addressed with scale-appropriate imaging spectrometry. This study also highlighted the capability of spaceborne imaging spectrometers to estimate β-diversity of grassland ecosystems across large spatial domains.

Thousands of planetesimals: Simulating the streaming instability in very large computational domains

The streaming instability is a mechanism whereby pebble-sized particles in protoplanetary discs spontaneously come together in dense filaments, which collapse gravitationally to form planetesimals upon reaching the Roche density. The extent of the filaments along the orbital direction is nevertheless poorly characterised, due to a focus in the literature on small simulation domains where the behaviour of the streaming instability on large scales cannot be determined. We present here computer simulations of the streaming instability in boxes with side lengths up to $6.4$ scale heights in the plane. This is $32$ times larger than typically considered simulation domains and nearly a factor $1,000$ times the volume. We show that the azimuthal extent of filaments in the non-linear state of the streaming instability is limited to approximately one gas scale height. The streaming instability will therefore not transform the pebble density field into axisymmetric rings; rather the non-linear state of the streaming instability appears as a complex structure of loosely connected filaments. Including the self-gravity of the pebbles, our simulations form up to $4,000$ planetesimals. This allows us to probe the high-mass end of the initial mass function of planetesimals with much higher statistical confidence than previously. We find that this end is well-described by a steep exponential tapering. Since the resolution of our simulations is moderate -- a necessary trade-off given the large domains -- the mass distribution is incomplete at the low-mass end. When putting comparatively less weight on the numbers at low masses, at intermediate masses we nevertheless reproduce the power-law shape of the distribution established in previous studies.

Recent developments in tornado theory and observations.

This article critically reviews research on tornado theory and observations over the last decade. From the theoretical standpoint, the major advances have come through improved numerical-simulation models of supercell convective storms, which contain the tornado's parent circulation. These simulations are carried out on a large domain (to capture the supercell's circulation system), but with high grid resolution and improved representations of sub-grid physics (to capture the tornado). These simulations offer new insights into how and why tornadoes form in some supercells, but not others. Observational advances have come through technological improvements of mobile Doppler radars capable of rapid scanning and dual-polarization measurements, which offer a much more accurate view of tornado formation, tornado structure, and the tornado's place within its parent supercell.

The lysosomal lipid transporter LIMP-2/SCARB2 is part of lysosome-endoplasmic reticulum STARD3-VAPB-dependent contact sites.

SCARB2/LIMP-2 is an abundant lysosomal membrane protein. Previous studies have shown LIMP-2 functions as a virus receptor, a chaperone for lysosomal enzyme targeting, and a lipid transporter. The large luminal domain of LIMP-2 contains a hydrophobic tunnel that enables transport of phospholipids, sphingosine and cholesterol from the lysosomal lumen to the membrane. The question about the fate of the lipids after LIMP-2-mediated transport is largely unexplored. To elucidate whether LIMP-2 is part of contact sites between lysosomes and the endoplasmic reticulum (ER), we performed a proximity-based interaction screen. This revealed that LIMP-2 interacts with the endosomal protein STARD3 and the ER-resident protein VAPB. Using imaging and co-immunoprecipitation, we demonstrated colocalization and physical interaction between LIMP-2 and these proteins. Moreover, we found that interaction of LIMP-2 with VAPB required the presence of STARD3. Our findings suggest that LIMP-2 is part of ER-lysosome contact sites, possibly facilitating cholesterol transport from the lysosomal to the ER membrane. This suggests a novel mechanism for inter-organelle communication and lipid trafficking mediated by LIMP-2.

A conserved peptide-binding pocket in HyNaC/ASIC ion channels

The only known peptide-gated ion channels-FaNaCs/WaNaCs and HyNaCs-belong to different clades of the DEG/ENaC family. FaNaCs are activated by the short neuropeptide FMRFamide, and HyNaCs by Hydra RFamides, which are not evolutionarily related to FMRFamide. The FMRFamide-binding site in FaNaCs was recently identified in a cleft atop the large extracellular domain. However, this cleft is not conserved in HyNaCs. Here, we combined molecular modeling and site-directed mutagenesis and identified a putative binding pocket for Hydra-RFamides in the extracellular domain of the heterotrimeric HyNaC2/3/5. This pocket localizes to only one of the three subunit interfaces, indicating that this trimeric ion channel binds a single peptide ligand. We engineered an unnatural amino acid at the putative binding pocket entrance, which allowed covalent tethering of Hydra RFamide to the channel, thereby trapping the channel in an open conformation. The identified pocket localizes to the same region as the acidic pocket of acid-sensing ion channels (ASICs), which binds peptide ligands. The pocket in HyNaCs is less acidic, and both electrostatic and hydrophobic interactions contribute to peptide binding. Collectively, our results reveal a conserved ligand-binding pocket in HyNaCs and ASICs and indicate independent evolution of peptide-binding cavities in the two subgroups of peptide-gated ion channels.

Efficient Modeling of Spatial Extremes over Large Geographical Domains

Various natural phenomena exhibit spatial extremal dependence at short spatial distances. However, existing models proposed in the spatial extremes literature often assume that extremal dependence persists across the entire domain. This is a strong limitation when modeling extremes over large geographical domains, and yet it has been mostly overlooked in the literature. We here develop a more realistic Bayesian framework based on a novel Gaussian scale mixture model, with the Gaussian process component defined by a stochastic partial differential equation yielding a sparse precision matrix, and the random scale component modeled as a low-rank Pareto-tailed or Weibull-tailed spatial process determined by compactly-supported basis functions. We show that our proposed model is approximately tail-stationary and that it can capture a wide range of extremal dependence structures. Its inherently sparse structure allows fast Bayesian computations in high spatial dimensions based on a customized Markov chain Monte Carlo algorithm prioritizing calibration in the tail. We fit our model to analyze heavy monsoon rainfall data in Bangladesh. Our study shows that our model outperforms natural competitors and that it fits precipitation extremes well. We finally use the fitted model to draw inference on long-term return levels for marginal precipitation and spatial aggregates.

A coherent view of Li depletion and angular momentum transport to explain the Li plateau – from Population II to Population I stars

Context. The discrepancy between the predictions of Big Bang nucleosynthesis and the lithium abundance observed in the oldest stars of our Galaxy, known as the cosmological lithium problem, has long been regarded as a challenge to the fields of both cosmology and astrophysics. Aims. In light of recent theoretical advances concerning the transport of chemicals and angular momentum in Population I low-mass stars, we re-examine the stellar depletion hypothesis to explain the lithium plateau, which spans a wide range of metallicities over a specific range of stellar effective temperature. Methods. We computed stellar evolution models with the code STAREVOL, including the same input physics that enable self-consistent reproduction of the Li depletion in the Sun and stars in open clusters, while accounting for internal rotation consistent with asteroseismic constraints. In addition to atomic diffusion and parametric turbulence, which were considered in previous studies of Li depletion along the plateau, our models include rotation-induced hydrodynamical processes and additional parametric viscosity for the transport of angular momentum as well as penetrative convection with a rotational dependence, and magnetic braking. Results. As in the case of Pop I stars, the mixing obtained with the current prescriptions for vertical and horizontal shear turbulence induced by rotation is insufficient to reproduce the Li constraints, and parametric turbulence is required. Even if the nature of the turbulence has yet to be identified, we show that the compactness of Pop II low-mass dwarf stars shall naturally lead to similar Li depletion over a large domain in the [Fe/H]–Teff plane, resulting in a plateau with little dispersion. We calibrated the efficiency of the turbulence to fit the abundance of Li in Pop II stars selected from the GALAH DR3 spectroscopic survey and from an homogeneous reanalysis of abundances from the literature. This calibration also enables the reproduction of lithium and magnesium trends in post-turnoff stars of the globular cluster NGC 6752. The same stellar structure considerations consistently explain the observed change of Li depletion and the dispersion regime for [Fe/H] above −1.5 dex, that is, at the transition in metallicity between Pop II to Pop I stars. Conclusions. Our results provide new constraints to the physical processes that transport chemicals and angular momentum in stellar interiors. They offer a comprehensive way to reproduce the observed Li patterns in low-mass dwarf stars across the entire Galactic metallicity range covered by spectroscopic surveys, including the most Fe-poor regime, as supported by the Li value in the non-CEMP star that lies on the plateau at [Fe/H] below −5.8 dex. Our careful analysis of the other very metal-poor stars with lower Li abundances supports the environmental origin of the so-called meltdown regime. Finally, the expected plateau-to-scatter transition pattern further supports the stellar solution to the cosmological problem.