Strong Constraints Research Articles

Century-long timelines of herbarium genomes predict plant stomatal response to climate change

Dissecting plant responses to the environment is key to understanding whether and how plants adapt to anthropogenic climate change. Stomata, plants’ pores for gas exchange, are expected to decrease in density following increased CO2 concentrations, a trend already observed in multiple plant species. However, it is unclear whether such responses are based on genetic changes and evolutionary adaptation. Here we make use of extensive knowledge of 43 genes in the stomatal development pathway and newly generated genome information of 191 Arabidopsis thaliana historical herbarium specimens collected over 193 years to directly link genetic variation with climate change. While we find that the essential transcription factors SPCH, MUTE and FAMA, central to stomatal development, are under strong evolutionary constraints, several regulators of stomatal development show signs of local adaptation in contemporary samples from different geographic regions. We then develop a functional score based on known effects of gene knock-out on stomatal development that recovers a classic pattern of stomatal density decrease over the past centuries, suggesting a genetic component contributing to this change. This approach combining historical genomics with functional experimental knowledge could allow further investigations of how different, even in historical samples unmeasurable, cellular plant phenotypes may have already responded to climate change through adaptive evolution.

Asymmetric Sea Surface Salinity Response to Global Warming: “Fresh Gets Fresher but Salty Hesitates”

AbstractEfforts to detect long‐term changes in global mean evaporation minus precipitation over the ocean remain ambiguous. Here we define an ad hoc sea surface salinity index to assess the observed and simulated intensification of the freshwater flux pattern over the global ocean and, thus, of the overall water cycle. A recent salinity reconstruction shows a long‐term amplification of the climatological patterns, thereby supporting the popular “fresh gets fresher, salty gets saltier” paradigm. Unlike in a previous study, no systematic underestimation of this amplification is found in the latest generation of global climate models. Yet, the “fresh gets fresher” paradigm is much more robust than its “salty gets saltier” counterpart and the proposed salinity index does not yet provide a strong constraint on the model‐dependent projected intensification of the global water cycle intensification along the 21st century.

Generalized dualities for heterotic and type I strings

We define generalized dualities for heterotic and type I strings based on consistent truncations to half-maximal gauged supergravities in more than three dimensions. The latter are constructed from a generalized Scherk-Schwarz ansatz in heterotic double field theory that satisfies the strong constraint. Necessary and sufficient conditions on the resulting embedding tensor are discussed, showing that only certain gaugings, called geometric, can arise from this procedure. For all of them, we explicitly construct the internal geometry and gauge potentials. In general, this construction is not unique and permits different uplifts which are used to define generalized T-duality. Two examples are worked out underlying the utility of our approach to explore new dualities and uplifts of half-maximal gauged supergravities.

Climatic variation allows montane willows to escape an adaptive trade-off.

Adaptive responses to climate change, based on heritable variation in stress tolerance, may be important for plant population persistence. It is unclear which populations will mount the strongest future adaptive responses. It may be fruitful to identify populations that have escaped trade-offs among performance traits, which can hinder adaptation. Barring strong genetic constraints, the extent of trade-offs may depend on spatial relationships among climate variables shaping different traits. Here, we test for climate-driven ecotypic variation and trade-offs among drought and freezing sensitivity, and growth, for Lemmon's willow (Salix lemmonii) in a common garden study of 90 genotypes from 38 sites in the Sierra Nevada, USA. Salix lemmonii exhibits ecotypic variation in leaf turgor loss point, a measure of drought sensitivity, from -0.95 to -0.74 MPa along a gradient of spring snowpack. We also find variation in spring freezing sensitivity with minimum May temperature. However, we find no trade-off, as the climatic gradients shaping these traits are spatially uncorrelated in our study region, despite being negatively correlated across the Sierra Nevada. Species may escape adaptive trade-offs in geographic regions where climate variables are spatially decoupled. These regions may represent valuable reservoirs of heritable adaptive phenotypic variation.

Behaviours of rip cosmological models in f(Q,C) gravity

In this study, the Universe's rip cosmology theories have been provided for the f(Q,C) gravity theory, where Q and C stand for the non-metricity scalar and boundary term. We assume f(Q,C)=αQn+βC and analyze the nature of the physical parameters for the Little Rip (LR), Big Rip (BR) and Pseudo Rip (PR) models. In the LR and PR models, the EoS parameter exhibits phantom characteristics but remains closely aligned with the ΛCDM line. The non-metricity term Q has direct effect on the rip models. After investigating the energy conditions, we recognise that our model violates the strong energy constraint. Avoiding singularity situations has been noted in all of these accelerated models. The characteristics of the jerk and snap parameters have been investigated. Our model provides an effective description of the Universe's evolutionary history and fits well with contemporary cosmic data.

A radical solution to the Hubble tension problem

The Hubble tension has proven to be stubbornly persistent, despite widespread efforts to relax it. As a possible resolution of this problem we propose a radical alternative to the way in which cosmological models are viewed. Specifically, we consider building cosmological models from spaces that exhibit intrinsic symmetries, rather than as space-times with explicit symmetry. This change in perspective allows statistical homogeneity and isotropy to be maintained, while relaxing some strong mathematical constraints that the standard approach imposes. We show that a Hubble tension arises naturally in our new approach, and that (as a corollary) a prediction can be made for the radial component of the Baryon Acoustic Oscillations. Our prediction appears to be consistent with the DESI first-year data release, which has otherwise been interpreted as evidence for dynamical dark energy.

Rapid kilonova evolution: Recombination and reverberation effects

Kilonovae (KNe) are one of the fastest types of optical transients known, cooling rapidly in the first few days following their neutron-star merger origin. We show here that KN spectral features go through rapid recombination transitions, with features due to elements in the new ionisation state emerging quickly. Due to time-delay effects of the rapidly expanding KN, a ‘wave’ of these new features passing though the ejecta should be a detectable phenomenon. In particular, isolated line features will emerge as blueshifted absorption features first, gradually evolving into P Cygni features and then pure emission features. In this analysis, we present the evolution of individual exposures of the KN AT2017gfo observed with VLT/X-shooter, which together comprise X-shooter’s first epoch spectrum (1.43 days post-merger). The spectra of these ‘sub-epochs’ show a significant evolution across the roughly one hour of observations, including a decrease in the blackbody temperature and photospheric velocity. The early cooling is even more rapid than that inferred from later photospheric epochs and suggests that a fixed power-law relation between the temperature and time does not describe the data. The cooling constrains the recombination wave, where a Sr II interpretation of the AT2017gfo ∼1 μm feature predicts both a specific timing for the feature emergence and its early spectral shape, including the very weak emission component observed at about 1.43 days. This empirically indicates a strong correspondence between the radiation temperature of the blackbody and the ejecta’s electron temperature. Furthermore, this reverberation analysis suggests that temporal modelling is important for interpreting individual spectra and that higher-cadence spectral series, especially when concentrated at specific times, can provide strong constraints on KN line identifications and the ejecta physics. Given the use of such short-timescale information, we lay out improved observing strategies for future KN monitoring.

Ionized gas in quiescent galaxies: Temperature measurement and constraint on the ionization source

In non-star-forming, passively evolving galaxies, regions with emission lines dominated by low-ionization species are classified as low-ionization emission regions (LIERs). The ionization mechanism behind such regions has long been a mystery. Active galactic nuclei (AGNs), which were once believed to be the source, have been found not to be the dominant mechanism, especially in regions distant from the galaxy nuclei. The remaining candidates, photoionization by post-asymptotic giant branch (pAGB) stars and interstellar shocks can only be distinguished with in-depth analysis. As the temperature predictions of these two models differ, temperature measurements can provide strong constraints on this puzzle. We selected a sample of 2795 quiescent red-sequence galaxies from the Sloan Digital Sky Survey IV (SDSS-IV) Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. We divided the sample spectra into three groups based on the flux ratio, and utilized stacking techniques to improve the signal-to-noise ratio of the observed spectra. We determined the temperature of and through their temperature-sensitive emission line ratios. Subsequently, we compared the measured temperatures with predictions from different models. The results demonstrate consistency with the interstellar shock model with pre-shock density n = 1 $ and solar metallicity, thus supporting shocks as the dominant ionization source of LIERs. Additionally, we also find that the interstellar dust extinction value measured through the Balmer decrement appears to be larger than that implied by the forbidden line ratios of low-ionization lines.

Non-relativistic limits of bosonic and heterotic Double Field Theory

The known stringy non-relativistic (NR) limit of the universal NS-NS sector of supergravity has a finite Lagrangian due to non-trivial cancellations of divergent parts coming from the metric and the B-field. We demonstrate that in Double Field Theory (DFT) and generalised geometry these cancellations already happen at the level of the generalised metric, which is convergent in the limit c → ∞, implying that the NR limit can be imposed before solving the strong constraint. We present the c-expansion of the generalised metric, which reproduces the Non-Riemannian formulation of DFT at the (finite) leading order, and the c-expansion of the generalised frame, which contains divergences. We also extend this approach to the non-Abelian gauge field of Heterotic DFT assuming a convergent expansion for the O(D, D + n) generalised metric. From this proposal, we derive a novel c-expansion for the bosonic part of the heterotic supergravity which is, by construction, compatible with O(D, D)-symmetry.

Efficient Study Design and Analysis of Longitudinal Dose-Response Data Using Fractional Polynomials.

Correctly characterising the dose-response relationship and taking the correct dose forward for further study is a critical part of the drug development process. We use optimal design theory to compare different designs and show that using longitudinal data from all available timepoints in a continuous-time dose-response model can substantially increase the efficiency of estimation of the dose-response compared to a single timepoint model. We give theoretical results to calculate the efficiency gains for a large class of these models. For example, a linearly growing Emax dose-response in a population with a between/within-patient variance ratio ranging from 0.1 to 1 measured at six visits can be estimated with between 1.43 and 2.22 times relative efficiency gain, or equivalently, with 30% to a 55% reduced sample size, compared to a single model of the final timepoint. Fractional polynomials are a flexible way to incorporate data from repeated measurements, increasing precision without imposing strong constraints. Longitudinal dose-response models using two fractional polynomial terms are robust to mis-specification of the true longitudinal process while maintaining, often large, efficiency gains. These models have applications for characterising the dose-response at interim or final analyses.

A warm dark matter cosmogony may yield more low-mass galaxy detections in 21-cm surveys than a cold dark matter one

ABSTRACT The 21-cm spectral line widths, $w_{50}$, of galaxies are an approximate tracer of their dynamical masses, such that the dark matter halo mass function is imprinted in the number density of galaxies as a function of $w_{50}$. Correcting observed number counts for survey incompleteness at the level of accuracy needed to place competitive constraints on warm dark matter (WDM) cosmological models is very challenging, but forward-modelling the results of cosmological hydrodynamical galaxy formation simulations into observational data space is more straightforward. We take this approach to make predictions for an ALFALFA-like survey from simulations using the EAGLE galaxy formation model in both cold (CDM) and WDM cosmogonies. We find that for WDM cosmogonies more galaxies are detected at the low-$w_{50}$ end of the 21-cm velocity width function than in the CDM cosmogony, contrary to what might naïvely be expected from the suppression of power on small scales in such models. This is because low-mass galaxies form later and retain more gas in WDM cosmogonies (with EAGLE). While some shortcomings in the treatment of cold gas in the EAGLE model preclude placing definitive constraints on WDM scenarios, our analysis illustrates that near-future simulations with more accurate modelling of cold gas will likely make strong constraints possible, especially in conjunction with new 21-cm surveys such as WALLABY.

Hybrid Optimal Power System Recovery and Load Pick-Up With DGAllocation In Electrical Power System

The increasing demand for electricity, the expansion of complex power networks, and the operation of power systems near their capacity have heightened the risk of power outages. Consequently, control room operators must develop comprehensive restoration plans to minimize recovery time. Key steps in power system restoration include starting non-black-start units with black-start units and initiating load pick-up. This process requires identifying the shortest route between nodes to expedite repairs. This research presents an expert plan employing the Modified Cuckoo Search algorithm (MCSA) to determine optimal pathways. Additionally, it explores the optimal allocation of distributed generators (DG) to enhance the system's voltage profile and reduce power losses using particle swarm optimization (PSO). The results demonstrate that DG significantly reduces losses during recovery. The study prioritizes the restoration of DGs with strong black start capability, considering network and DG constraints. The effectiveness of the proposed restoration approach is validated through MATLAB simulations on theIEEE 39-bus system.

Prospects for heavy neutral lepton searches at short and medium baseline reactor experiments

Heavy neutrinos with masses in the MeV range can in principle simultaneously explain the light neutrino masses and the origin of baryonic matter in the universe. The strongest constraints on their properties come from their potential impact on the formation of light elements in the early universe. Since these constraints rely on assumptions about the cosmic history, independent checks in the laboratory are highly desirable. In this paper, we discuss the opportunity to search for heavy neutrinos within the MeV mass range in short and medium baseline reactor neutrino experiments, using the SoLid, JUNO and TAO experiments as examples. These experiments can give the currently strongest upper bound on the mixing between the light electron neutrinos and the heavy neutrino in the 2–9 MeV mass range.

Supply chain risks and corporate innovation strategy: from the perspective of breakthrough innovation and incremental innovation

ABSTRACT This paper investigates the impact of supply chain risks on corporate innovation in China. Our findings indicate that firms with high supply chain risks are more inclined towards incremental innovation rather than breakthrough innovation. This relationship is further strengthened by high customer concentration and strong financial constraints, and it is more pronounced in industries characterized by higher levels of competitiveness and within the high-tech sector. Furthermore, the influence of supply chain risks on corporate innovation is jointly driven by supply and demand risks. Crucially, strategic adjustments in response to supply chain risks not only improve operational performance but also enhance the stability of customer relationships.

Bat Rhinacoviruses Related to Swine Acute Diarrhoea Syndrome Coronavirus Evolve under Strong Host and Geographic Constraints in China and Vietnam.

Swine acute diarrhoea syndrome coronavirus (SADS-CoV; Coronaviridae, Rhinacovirus) was detected in 2017 in Guangdong Province (China), where it caused high mortality rates in piglets. According to previous studies, SADS-CoV evolved from horseshoe bat reservoirs. Here, we report the first five Rhinacovirus genomes sequenced in horseshoe bats from Vietnam and their comparisons with data published in China. Our phylogenetic analyses provided evidence for four groups: rhinacoviruses from Rhinolphus pusillus bats, including one from Vietnam; bat rhinacoviruses from Hainan; bat rhinacoviruses from Yunnan showing a divergent synonymous nucleotide composition; and SADS-CoV and related bat viruses, including four rhinacoviruses from Vietnam sampled in Rhinolophus affinis and Rhinolophus thomasi. Our phylogeographic analyses showed that bat rhinacoviruses from Dien Bien (Vietnam) share more affinities with those from Yunnan (China) and that the ancestor of SADS-CoVs arose in Rhinolophus affinis circulating in Guangdong. We detected sequencing errors and artificial chimeric genomes in published data. The two SADS-CoV genomes previously identified as recombinant could also be problematic. The reliable data currently available, therefore, suggests that all SADS-CoV strains originate from a single bat source and that the virus has been spreading in pig farms in several provinces of China for at least seven years since the first outbreak in August 2016.

Topology Optimization of Anisotropic Materials with Smooth Fiber Orientation

In the concurrent optimization of topology and fiber orientation, the design of smooth fiber helps to maintain the stability of numerical calculation and the compatibility of the manufacturing process. However, the improvement of fiber continuity is often accompanied by a significant decrease in the overall structural stiffness. Aiming at this problem, this paper proposes a topology optimization method for anisotropic materials with smooth fiber orientation. This method improves the smoothness of fiber orientation and reduces stiffness loss by introducing a fiber angle constraint strategy and adaptive filtering technology. The fiber angle constraint strategy integrates the created angle constraint function into the Method of Moving Asymptotes (MMA) to complete the strong constraint of the angle. This strategy quantifies the continuity of the fiber and effectively improves the continuity of the fiber. At the same time, the application of adaptive filtering technology can adjust a reasonable fiber angle distribution on the basis of smoothing fibers, thereby enhancing the stiffness of the overall structure. In addition, this paper shows the complete optimization process and MATLAB code implementation and verifies the effectiveness of the method through a series of numerical examples, that is, on the basis of improving fiber continuity, the stiffness of the whole structure is guaranteed, and then the effective balance between the two is realized.

Occurrence Rates of Exosatellites Orbiting 3–30 M Jup Hosts from 44 Spitzer Light Curves

We conduct a comprehensive search for transiting exomoons and exosatellites within 44 archival Spitzer light curves of 32 substellar worlds with estimated masses ranging between 3 and 30 M Jup. This sample’s median host mass is 16 M Jup, inclusive of 14 planetary-mass objects, among which one is a wide-orbit exoplanet. We search the light curves for exosatellite signatures and implement a transit injection-recovery test, illustrating our survey’s capability to detect >0.7 R ⊕ exosatellites. Our findings reveal no substantial (>5σ) evidence for individual transit events. However, an unusual fraction of light curves favor the transit model at the 2–3σ significance level, with fitted transit depths consistent with terrestrial-sized (0.7–1.6 R ⊕) bodies. Comparatively, fewer than 2.2% of randomly generated normal distributions from an equivalent sample size exhibit a similar prevalence of outliers. Should one or two of these outliers represent a real exosatellite transit, it would imply an occurrence rate of η=0.61−0.34+0.49 short-period terrestrial exosatellites per system, consistent with the known occurrences rates for both solar system moons and mid-M dwarf exoplanets. We explore alternative astrophysical interpretations for these outliers, underscoring that transits are not the only plausible explanation. For orbital periods <0.8 days, the typical duration of the light curves, we constrain the occurrence rate of sub-Neptunes to η < 0.35 (95% confidence) and, if none of the detected outlier signals are real, the occurrence rate of terrestrial (∼Earth-sized) exosatellites to η < 0.51 (95% confidence). Forthcoming JWST observations of substellar light curves will enable the detection of sub-Io-sized exosatellites, allowing for much stronger constraints on this exosatellite population.

Eccentricity dynamics of wide binaries – II. The effect of stellar encounters and constraints on formation channels

ABSTRACT Gaia wide stellar binaries (separations $\sim 10^3{\!-\!}10^{4.5}$ au) are observed to have a superthermal eccentricity distribution function (DF), well-fit by $P(e) \propto e^\alpha$ with $\alpha \sim 1.2$. In a previous paper, we proved that this DF cannot have been produced by Galactic tidal torques starting from any realistic DF that was not already superthermal. Here, we consider the other major dynamical effect on wide binaries: encounters with passing stars. We derive and solve the Fokker–Planck equation governing the evolution of binaries in semimajor axis and eccentricity under many weak, impulsive, penetrative stellar encounters. We show analytically that these encounters drive the eccentricity DF towards thermal on the same time-scale as they drive the semimajor axes a towards disruption, $t_\mathrm{dis}\sim 4\, \mathrm{Gyr}\, (a/10^4\, \mathrm{AU})^{-1}$. We conclude that the observed superthermal DF must derive from an even more superthermal (i.e. higher $\alpha$) birth distribution. This requirement places strong constraints on the dominant binary formation channels. A testable prediction of our theory is that $\alpha$ should be a monotonically decreasing function of binary age.

The infall region as a complementary probe to cluster abundance

ABSTRACT Galaxy cluster abundance measurements provide a classic test of cosmology. They are most sensitive to the evolved amplitude of fluctuations, usually expressed as $S_8 = \sigma _8\sqrt{\Omega _{\rm m}/0.3}$. Thus, abundance constraints exhibit a strong degeneracy between $\sigma _8$ and $\Omega _{\rm m}$, as do other similar low-redshift tests such as cosmic shear. The mass distribution in the infall region around galaxy clusters, where material is being accreted from the surrounding field, also exhibits a cosmological dependence, but in this case it is nearly orthogonal to the $S_8$ direction in the $\Omega _{\rm m}$–$\sigma _8$ plane, making it highly complementary to halo abundance or cosmic shear studies. We explore how weak-lensing measurements of the infall region might be used to complement abundance studies, considering three different tests. The splashback radius is a prominent feature of the infall region; we show that detection of this feature in lensing data from the Euclid survey could independently constrain $\Omega _{\rm m}$ and $\sigma _8$ to $\pm 0.05$. Another feature, the depletion radius where the bias reaches a minimum, also shows cosmological dependence, though it is challenging to observe in practice. The strongest constraints come from direct measurements of the shear profile in the infall region at 2–$4\, r_{200{\rm c}}$. Combining the latter with abundance constraints such as those reported from SRG$/$eROSITA should reduce the area of the error contours by an estimated factor of 1.2 using a sample of clusters observed by the UNIONS survey, or a factor of 3 using clusters observed by the Euclid Wide survey over a broader range of redshift.

Edge Private Graph Neural Networks with Singular Value Perturbation

Graph neural networks (GNNs) play a key role in learning representations from graph-structured data and are demonstrated to be useful in many applications. However, the GNN training pipeline has been shown to be vulnerable to node feature leakage and edge extraction attacks. This paper investigates a scenario where an attacker aims to recover private edge information from a trained GNN model. Previous studies have employed differential privacy (DP) to add noise directly to the adjacency matrix or a compact graph representation. The added perturbations cause the graph structure to be substantially morphed, reducing the model utility. We propose a new privacy-preserving GNN training algorithm, Eclipse, that maintains good model utility while providing strong privacy protection on edges. Eclipse is based on two key observations. First, adjacency matrices in graph structures exhibit low-rank behavior. Thus, Eclipse trains GNNs with a low-rank format of the graph via singular values decomposition (SVD), rather than the original graph. Using the low-rank format, Eclipse preserves the primary graph topology and removes the remaining residual edges. Eclipse adds noise to the low-rank singular values instead of the entire graph, thereby preserving the graph privacy while still maintaining enough of the graph structure to maintain model utility. We theoretically show Eclipse provide formal DP guarantee on edges. Experiments on benchmark graph datasets show that Eclipse achieves significantly better privacy-utility tradeoff compared to existing privacy-preserving GNN training methods. In particular, under strong privacy constraints (𝜖 &lt; 4), Eclipse shows significant gains in the model utility by up to 46%. We further demonstrate that Eclipse also has better resilience against common edge attacks (e.g., LPA), lowering the attack AUC by up to 5% compared to other state-of-the-art baselines.