Time parallelization, also known as PinT (parallel-in-time), is a new research direction for the development of algorithms used for solving very large-scale evolution problems on highly parallel computing architectures. Despite the fact that interesting theoretical work on PinT appeared as early as 1964, it was not until 2004, when processor clock speeds reached their physical limit, that research in PinT took off. A distinctive characteristic of parallelization in time is that information flow only goes forward in time, meaning that time evolution processes seem necessarily to be sequential. Nevertheless, many algorithms have been developed for PinT computations over the past two decades, and they are often grouped into four basic classes according to how the techniques work and are used: shooting-type methods; waveform relaxation methods based on domain decomposition; multigrid methods in space–time; and direct time parallel methods. However, over the past few years, it has been recognized that highly successful PinT algorithms for parabolic problems struggle when applied to hyperbolic problems. We will therefore focus on this important aspect, first by providing a summary of the fundamental differences between parabolic and hyperbolic problems for time parallelization. We then group PinT algorithms into two basic groups. The first group contains four effective PinT techniques for hyperbolic problems: Schwarz waveform relaxation (SWR) with its relation to tent pitching; parallel integral deferred correction; ParaExp; and ParaDiag. While the methods in the first group also work well for parabolic problems, we then present PinT methods specifically designed for parabolic problems in the second group: Parareal; the parallel full approximation scheme in space–time (PFASST); multigrid reduction in time (MGRiT); and space–time multigrid (STMG). We complement our analysis with numerical illustrations using four time-dependent PDEs: the heat equation; the advection–diffusion equation; Burgers’ equation; and the second-order wave equation.

The whitefly Bemisia tabaci (Hemiptera: Aleyrodidae) is economically one of the most threatening pests in tomato cultivation, which not only causes direct damage but also transmits many viruses. Breeding whitefly-resistant tomato varieties is a promising and environmentally friendly method to control whitefly populations in the field. Accumulating evidence from tomato and other model systems demonstrates that flavonoids contribute to plant resistance to herbivorous insects. Previously, we found that high flavonoid-producing tomato line deterred whitefly oviposition and settling behaviours, and was more resistant to whiteflies compared to the near-isogenic low flavonoid-producing tomato line. The objective of the current work is to describe in detail different aspects of the interaction between the whitefly and two tomato lines, including biochemical processes involved. Electrical penetration graph recordings showed that high flavonoid-producing tomato reduced whitefly probing and phloem-feeding efficiency. We also studied constitutive and induced plant defence responses and found that whitefly induced stronger reactive oxygen species accumulation through NADPH oxidase in high flavonoid-producing tomato than in low flavonoid-producing tomato. Moreover, whitefly feeding induced the expression of callose synthase genes and resulted in callose deposition in the sieve elements in high flavonoid-producing tomato but not in low flavonoid-producing tomato. As a consequence, whitefly feeding on high flavonoid-producing tomato significantly decreased uptake of phloem and reduced its performance when compared to low flavonoid-producing tomato. These results indicate that high flavonoid-producing tomato provides phloem-based resistance against whitefly infestation and that the breeding of such resistance in new varieties could enhance whitefly management.

This study examined global trends in influenza-associated lower respiratory infections (LRIs) deaths from 1990 to 2019 using data from the GBD 2019. The annual percentage change (APC) and average annual percentage change (AAPC) were used to analyze age-standardized death rates (ASDR). Globally, the ASDR of influenza-associated LRIs was 3.29/100,000 in 2019, which was higher in the African region (6.57/100,000) and among adults aged 70 years and older (29.88/100,000). The ASDR of influenza-associated LRIs decreased significantly from 1990 to 2019 (AAPC = −1.88%, P < 0.05). However, it was significantly increased among adults aged 70 years and older during 2017–2019 (APC = 2.31%, P < 0.05), especially in Western Pacific Region and South-East Asia Regions. The ratio of death rates between adults aged 70 years and older and children aged under 5 years increased globally from 1.63 in 1990 to 5.34 in 2019, and the Western Pacific Region experienced the most substantial increase, with the ratio soaring from 1.83 in 1990 to 12.98 in 2019. Despite a decline in the global ASDR of influenza-associated LRIs, it continues to impose a significant burden, particularly in the African, Western Pacific regions and among the elderly population.

Silicified microfossils are reported from nine stratigraphic sections of the Ediacaran Doushantuo Formation deposited in shelf margin, slope, and basin environments in Hunan Province of South China. These microfossils include sphaeromorphic and acanthomorphic acritarchs (15 genera and 29 species, including three new acanthomorph species, Bullatosphaera? colliformis n. sp., Eotylotopalla inflata n. sp., and Verrucosphaera? undulata n. sp.), multicellular algae, tubular microfossils, and other problematic forms, representing major fossil groups similar to those from the Doushantuo Formation in more proximal facies (e.g., inner shelf and shelf lagoon). A database of the abundance and occurrences of Doushantuo acanthomorphs is assembled and analyzed using quantitative and data-visualization methods (e.g., rarefaction analysis, non-parametric multidimensional scaling, and network analysis). The results show that, at the genus and species levels, taxonomic richness of Doushantuo acanthomorphs exhibits considerable variation among facies, but this variation is largely due to sampling and taphonomic biases. The results also show that numerous acanthomorph taxa have broad facies distribution, affirming their biostratigraphic value. The analysis confirms that acanthomorphs in the Weng'an biota of shelf margin facies are composed of a mixture of Member II and Member III assemblages of shelf-lagoon facies in the Yangtze Gorges area. The study shows the biostratigraphic potential of acanthomorphs in the establishment of regional biozones using the first appearance datum of widely distributed taxa, highlighting the importance of continuing exploration of under-sampled Doushantuo sections in slope and basinal facies.

UUID: http://zoobank.org/6fc92858-4054-4117-8043-1f06cfe77155

Nonlinear compression experiments based on multiple solid thin plates are conducted in an ultra-high peak power Ti:sapphire laser system. The incident laser pulse, with an energy of 80 mJ and a pulse width of 30.2 fs, is compressed to 10.1 fs by a thin-plate based nonlinear compression. Significant small-scale self-focusing is observed as ring structures appear in the near-field of the output pulse at high energy. Numerical simulations based on the experimental setup provide a good explanation for the observed phenomena, offering quantitative predictions of the spectrum, pulse width, dispersion and near- and far-field distributions of the compressed laser pulse.

Biped wall-climbing robots (BWCRs) serve as viable alternatives to human workers for inspection and maintenance tasks within three-dimensional (3D) curtain wall environments. However, autonomous climbing in such environments presents significant challenges, particularly related to localization and navigation. This paper presents a pioneering navigation framework tailored for BWCRs to navigate through 3D curtain wall environments. The framework comprises three essential stages: Building Information Model (BIM)-based map extraction, 3D climbing path planning (based on our previous work), and path tracking. An algorithm is developed to extract a detailed 3D map from the BIM, including structural elements such as walls, frames, and ArUco markers. This generated map is input into a proposed path planner to compute a viable climbing motion. For path tracking during actual climbing, an ArUco marker-based global localization method is introduced to estimate the pose of the robot, enabling adjustments to the target foothold by comparing desired and actual poses. The conducted experiments validate the feasibility and efficacy of the proposed navigation framework and associated algorithms, aiming to enhance the autonomous climbing capability of BWCRs.

We study the melting process of a solid under microgravity, driven solely by lateral vibrations that are perpendicular to the applied temperature gradient due to the absence of gravity-induced convection. Using direct numerical simulations with the phase-field method, we examine two-dimensional vibration-induced melting in a square cavity over four orders of magnitude of vibrational Rayleigh numbers, $10^5\le Ra_{{vib}}\le 10^9$. Our results show that as melting progresses, the flow structure transitions from a periodic-circulation regime with diffusion-dominated heat transfer to a columnar regime with vibroconvection. The mean height of the liquid–solid interface follows a power-law dependency with time, $\bar {\xi } \sim \tilde t^{1/(2-2\alpha )}$, where $\alpha = 0$ in the periodic-circulation regime and $\alpha = 1/2$ in the columnar regime. We further observe that within the columnar regime, the morphological evolution of the liquid–solid interface is influenced by the interaction of columnar thermal plumes in the central regions and the peripheral flow near the sidewalls. Specifically, we offer a comprehensive analysis of the plume merging behaviour, which is governed by the aspect ratio ($\bar {\xi }$) of the liquid layer and the intensity of vibration, quantified by the effective vibrational Rayleigh number $Ra_{vib}^{eff}$. We identify the relationship between the number of columnar plumes $K_m$ and $Ra_{vib}^{eff}$, finding that $K_m \sim \bar {\xi }^{-1} (Ra_{vib}^{eff})^{\gamma }$ with the fitting scaling exponent $\gamma = 0.150 \pm 0.025$. We subsequently quantify the characteristics of the interface roughness amplitude evolution in microgravity vibroconvection. Our results indicate that the roughness amplitude exhibits a power-law dependence on the mean height of the liquid layer. Drawing from the Stefan boundary condition, we theoretically deduce this dependence under the assumption of a non-uniform heat flux distribution at the interface, where the theory is corroborated by our numerical simulations.

We report on an improved ytterbium-doped yttrium aluminum garnet thin-disk multi-pass amplifier for kilowatt-level ultrafast lasers, showcasing excellent beam quality. At a repetition rate of 800 kHz, the 6.8 ps, 276 W seed laser is amplified up to an average power of 1075 W, corresponding to a pulse energy of 1.34 mJ. The 36-pass amplifier is designed as a compact mirror array in which the beam alternately propagates between the mirrors and the disk by a quasi-collimated state. We adopted a quasi-collimated propagation to confine stray and diffracted light by the slight curvature of the disk, which enables us to achieve an outstanding extraction efficiency of up to 57% with excellent beam quality in stable laser operation at high power. The beam quality at 1075 W was measured to be M2 < 1.51. Furthermore, stability testing was demonstrated with a root-mean-square power fluctuation of less than 1.67% for 10 min.

Depression is one of the major mental disorders, which seriously endangers human health, brings a serious burden to patients’ families. In this study, we intended to further explore the antidepressant-like effect and possible molecular mechanisms of Salidroside (SAL). We built corticosterone (CORT)-induced depressive mice model and used behavioural tests to evaluate depression behaviour. To explore the molecular mechanisms of SAL, we employed a variety of methods such as immunofluorescence, western blot, pharmacological interference, etc. The results demonstrated that SAL both at 25 mg/kg and 50 mg/kg can reduce immobility time in the tail suspension test (TST). At the same time, SAL treatment could restore the reduced sugar water intake preference in the sucrose preference test (SPT) in CORT-induced depressive mice and reduce the immobility time in TST and forced swimming experiments (FST). In addition, SAL treatment reversed the reduction in the number of Ki-67, BrdU, and NeuN in the hippocampus due to CORT treatment. SAL treatment also restored the expression of SIRT1, PGC-1α, brain-derived neurotrophic factor (BDNF) and other proteins in the hippocampus. In addition, after blocking SIRT1 signalling with EX527, we found that the treatment with SAL failed to reduce the immobility time in TST and FST, the level of SIRT1 and PGC-1α activity were correspondingly downregulated, and the expression of DCX and Ki-67 in the hippocampus failed to be activated. These findings suggested that SAL exerts antidepressant-like effects by promoting hippocampal neurogenesis through the SIRT1/PGC-1α signalling pathway.

Let G and H be two vertex disjoint graphs. The join $G+H$ is the graph with $V(G+H)=V(G)+V(H)$ and $E(G+H)=E(G)\cup E(H)\cup \{xy\;|\; x\in V(G), y\in V(H)\}$. A (finite) linear forest is a graph consisting of (finite) vertex disjoint paths. We prove that for any finite linear forest F and any nonnull graph H, if $\{F, H\}$-free graphs have a $\chi $-binding function $f(\omega )$, then $\{F, K_n+H\}$-free graphs have a $\chi $-binding function $kf(\omega )$ for some constant k.

Thanks to its real-time computation efficiency, deep reinforcement learning (DRL) has been widely applied in motion planning for mobile robots. In DRL-based methods, a DRL model computes an action for a robot based on the states of its surrounding obstacles, including other robots that may communicate with it. These methods always assume that the environment is attack-free and the obtained obstacles’ states are reliable. However, in the real world, a robot may suffer from obstacle localization attacks (OLAs), such as sensor attacks, communication attacks, and remote-control attacks, which cause the robot to retrieve inaccurate positions of the surrounding obstacles. In this paper, we propose a robust motion planning method ObsGAN-DRL, integrating a generative adversarial network (GAN) into DRL models to mitigate OLAs in the environment. First, ObsGAN-DRL learns a generator based on the GAN model to compute the approximation of obstacles’ accurate positions in benign and attack scenarios. Therefore, no detectors are required for ObsGAN-DRL. Second, by using the approximation positions of the surrounding obstacles, ObsGAN-DRL can leverage the state-of-the-art DRL methods to compute collision-free motion commands (e.g., velocity) efficiently. Comprehensive experiments show that ObsGAN-DRL can mitigate OLAs effectively and guarantee safety. We also demonstrate the generalization of ObsGAN-DRL.

Under certain conditions, we construct a countable Markov partition for pointwise hyperbolic diffeomorphism $f:M\rightarrow M$ on an open invariant subset $O\subset M$, which allows the Lyapunov exponents to be zero. From this partition, we define a symbolic extension that is finite-to-one and onto a subset of O that carries the same finite f-invariant measures as O. Our method relies upon shadowing theory of a recurrent-pointwise-pseudo-orbit that we introduce. As a canonical application, we estimate the number of closed orbits for f.

This study proposes a novel super-resolution (or SR) framework for generating high-resolution turbulent boundary layer (TBL) flow from low-resolution inputs. The framework combines a super-resolution generative adversarial neural network (SRGAN) with down-sampling modules (DMs), integrating the residual of the continuity equation into the loss function. The DMs selectively filter out components with excessive energy dissipation in low-resolution fields prior to the super-resolution process. The framework iteratively applies the SRGAN and DM procedure to fully capture the energy cascade of multi-scale flow structures, collectively termed the SRGAN-based energy cascade reconstruction framework (EC-SRGAN). Despite being trained solely on turbulent channel flow data (via ‘zero-shot transfer’), EC-SRGAN exhibits remarkable generalization in predicting TBL small-scale velocity fields, accurately reproducing wavenumber spectra compared to direct numerical simulation (DNS) results. Furthermore, a super-resolution core is trained at a specific super-resolution ratio. By leveraging this pretrained super-resolution core, EC-SRGAN efficiently reconstructs TBL fields at multiple super-resolution ratios from various levels of low-resolution inputs, showcasing strong flexibility. By learning turbulent scale invariance, EC-SRGAN demonstrates robustness across different TBL datasets. These results underscore the potential of EC-SRGAN for generating and predicting wall turbulence with high flexibility, offering promising applications in addressing diverse TBL-related challenges.

We report the unified constitutive law of vibroconvective turbulence in microgravity, i.e. $Nu \sim a^{-1} Re_{os}^\beta$ where the Nusselt number $Nu$ measures the global heat transport, $a$ is the dimensionless vibration amplitude, $Re_{os}$ is the oscillational Reynolds number and $\beta$ is the universal exponent. We find that the dynamics of boundary layers plays an essential role in vibroconvective heat transport and the $Nu$-scaling exponent $\beta$ is determined by the competition between the thermal boundary layer (TBL) and vibration-induced oscillating boundary layer (OBL). Then a physical model is proposed to explain the change of scaling exponent from $\beta =2$ in the TBL-dominant regime to $\beta = 4/3$ in the OBL-dominant regime. Our finding elucidates the emergence of universal constitutive laws in vibroconvective turbulence, and opens up a new avenue for generating a controllable effective heat transport under microgravity or even microfluidic environment in which the gravity effect is nearly absent.