This paper introduces a distributed online learning coverage control algorithm based on sparse Gaussian process regression for addressing the problem of multi-robot area coverage and source localization in unknown environments. Considering the limitations of traditional Gaussian process regression in handling large datasets, this study employs multiple robots to explore the task area to gather environmental information and approximate the posterior distribution of the model using variational free energy methods, which serves as the input for the centroid Voronoi tessellation algorithm. Additionally, taking into consideration the localization errors, and the impact of obstacles, buffer factors and centroid Voronoi tessellation algorithms with separating hyperplanes are introduced for dynamic robot task area planning, ultimately achieving autonomous online decision-making and optimal coverage. Simulation results demonstrate that the proposed algorithm ensures the safety of multi-robot formations, exhibits higher iteration speed, and improves source localization accuracy, highlighting the effectiveness of model enhancements.

Carbon storage in saline aquifers is a prominent geological method for reducing CO2 emissions. However, salt precipitation within these aquifers can significantly impede CO2 injection efficiency. This study examines the mechanisms of salt precipitation during CO2 injection into fractured matrices using pore-scale numerical simulations informed by microfluidic experiments. The analysis of varying initial salt concentrations and injection rates revealed three distinct precipitation patterns, namely displacement, breakthrough and sealing, which were systematically mapped onto regime diagrams. These patterns arise from the interplay between dewetting and precipitation rates. An increase in reservoir porosity caused a shift in the precipitation pattern from sealing to displacement. By incorporating pore structure geometry parameters, the regime diagrams were adapted to account for varying reservoir porosities. In hydrophobic reservoirs, the precipitation pattern tended to favour displacement, as salt accumulation occurred more in larger pores than in pore throats, thereby reducing the risk of clogging. The numerical results demonstrated that increasing the gas injection rate or reducing the initial salt concentration significantly enhanced CO2 injection performance. Furthermore, identifying reservoirs with high hydrophobicity or large porosity is essential for optimising CO2 injection processes.

While researchers often study message features like moral content in text, such as party manifestos and social media posts, their quantification remains a challenge. Conventional human coding struggles with scalability and intercoder reliability. While dictionary-based methods are cost-effective and computationally efficient, they often lack contextual sensitivity and are limited by the vocabularies developed for the original applications. In this paper, we present an approach to construct “vec-tionaries” that boost validated dictionaries with word embeddings through nonlinear optimization. By harnessing semantic relationships encoded by embeddings, vec-tionaries improve the measurement of message features from text, especially those in short format, by expanding the applicability of original vocabularies to other contexts. Importantly, a vec-tionary can produce additional metrics to capture the valence and ambivalence of a message feature beyond its strength in texts. Using moral content in tweets as a case study, we illustrate the steps to construct the moral foundations vec-tionary, showcasing its ability to process texts missed by conventional dictionaries and to produce measurements better aligned with crowdsourced human assessments. Furthermore, additional metrics from the vec-tionary unveiled unique insights that facilitated predicting downstream outcomes such as message retransmission.

This study investigates the effects of fat emulsion-based early parenteral nutrition in patients following hemihepatectomy, addressing a critical gap in clinical knowledge regarding parenteral nutrition after hemihepatectomy. We retrospectively analysed clinical data from 274 patients who received non-fat emulsion-based parenteral nutrition (non-fatty nutrition group) and 297 patients who received fat emulsion-based parenteral nutrition (fatty nutrition group) after hemihepatectomy. Fat emulsion-based early parenteral nutrition significantly reduced levels of post-operative aspartate aminotransferase, total bilirubin and direct bilirubin, while minor decreases in red blood cell and platelet counts were observed in the fatty nutrition group. Importantly, fat emulsion-based early parenteral nutrition shortened lengths of post-operative hospital stay and fasting duration, but did not affect the incidence of short-term post-operative complications. Subgroup analyses revealed that the supplement of n-3 fish oil emulsions was significantly associated with a reduced inflammatory response and risk of post-operative infections. These findings indicate that fat emulsion-based early parenteral nutrition enhances short-term post-operative recovery in patients undergoing hemihepatectomy.

We have developed an interactive system comprising a soft wearable robot hand and a wireless task board, facilitating the interaction between the hand and regular daily objects for task-oriented training in stroke rehabilitation. A ring-reinforced soft actuator (RSA) to accommodate different hand sizes and enable flexion and extension movements was introduced in this paper. Individually controlled finger actuators assist stroke patients during various grasping tasks. A wireless task board was developed to support the training, allowing for the placement of training objects and seamless interaction with the soft robotic hand. Evaluation with seven stroke subjects shows significant improvements in upper limb functions (FMA), hand-motor abilities (ARAT, BBT), and maximum grip strengths after 20 sessions of this task-oriented training. These improvements were observed to persist for at least 3 months post-training. The results demonstrate its potential to enhance stroke rehabilitation and promote hand-motor recovery. This lightweight, user-friendly interactive system facilitates frequent hand practice and easily integrates into regular rehabilitation therapy routines.

Sleep value is the relative worth individuals assign to sleep. We previously found that individual differences in several sleep value subfactors relate to demographic, health and sleep variables. Given the pivotal role values play in health behavior and the positive association between sleep value and sleep disturbance, individual differences in sleep value may influence vulnerability/resilience to sleep and circadian disturbance. This survey study (N = 455) aimed to establish the latent factor structure of sleep value and identify whether sleep value profiles relate to demographic and sleep characteristics. Factor analysis on the Sleep Valuation Item Bank 2.0 identified five factors (wanting, prioritizing, devaluing, appreciating and preferring). Latent profile analyses revealed five distinct sleep value profiles (unconcerned, appreciative, devalue, ambivalent priority and concerned). Depression, sleep disturbance and sleep-related impairment were highest among those who highly value sleep (concerned profile) and lowest among those who neither value nor devalue sleep (unconcerned profile). Findings suggest sleep value is a complex aspect of sleep health rather than a “more is better” construct and highlight that individual differences in sleep value profiles may be associated with vulnerability/resilience to sleep disturbance.

Expert drivers possess the ability to execute high sideslip angle maneuvers, commonly known as drifting, during racing to navigate sharp corners and execute rapid turns. However, existing model-based controllers encounter challenges in handling the highly nonlinear dynamics associated with drifting along general paths. While reinforcement learning-based methods alleviate the reliance on explicit vehicle models, training a policy directly for autonomous drifting remains difficult due to multiple objectives. In this paper, we propose a control framework for autonomous drifting in the general case, based on curriculum reinforcement learning. The framework empowers the vehicle to follow paths with varying curvature at high speeds, while executing drifting maneuvers during sharp corners. Specifically, we consider the vehicle’s dynamics to decompose the overall task and employ curriculum learning to break down the training process into three stages of increasing complexity. Additionally, to enhance the generalization ability of the learned policies, we introduce randomization into sensor observation noise, actuator action noise, and physical parameters. The proposed framework is validated using the CARLA simulator, encompassing various vehicle types and parameters. Experimental results demonstrate the effectiveness and efficiency of our framework in achieving autonomous drifting along general paths. The code is available at https://github.com/BIT-KaiYu/drifting.

This research challenges the conventional wisdom that value-driven protests in China are exceedingly rare and face harsh state repression. Drawing on a hand-coded, multi-source dataset of over 3,100 protests in three Chinese megacities from 2014 to 2016, we identify 67 protests that reveal a hitherto unknown underbelly of everyday, value-driven contention. Qualitatively, we identify three main forms of contentious performances. Quantitatively, we show how value-driven protesters combine non-disruptive tactics with ambitious targets and virtually never extract concessions. Surprisingly, we find that such protests are less often policed and repressed than other protests. They are also never met with violence from non-state actors. We provide three interpretations for the counter-intuitive finding on repression. This study shows that the Chinese state coexists with a non-negligible amount of explicitly regime-critical contention. It adopts a containment strategy, tolerating a certain extent of value-driven performances when the risk of spill-over into wider society is limited.

Melting and solidification in periodically time-modulated thermal convection are relevant for numerous natural and engineering systems, for example, glacial melting under periodic sun radiation and latent thermal energy storage under periodically pulsating heating. It is highly relevant for the estimation of melt rate and melt efficiency management. However, even the dynamics of a solid–liquid interface shape subjected to a simple sinusoidal heating has not yet been investigated in detail. In this paper, we offer a better understanding of the modulation frequency dependence of the melting and solidification front. We numerically investigate periodic melting and solidification in turbulent convective flow with the solid above and the melted liquid below, and sinusoidal heating at the bottom plate with the mean temperature equal to the melting temperature. We investigate how the periodic heating can prevent the full solidification, and the resulting flow structures and the quasi-equilibrium interface height. We further study the dependence on the heating modulation frequency. As the frequency decreases, we found two distinct regimes, which are ‘partially solid’ and ‘fully solid’. In the fully solid regime, the liquid freezes completely, and the effect of the modulation is limited. In the partially solid regime, the solid partially melts, and a steady or unsteady solid–liquid interface forms depending on the frequency. The interface height can be derived based on the energy balance through the interface. In the partially solid regime, the interface height oscillates periodically, following the frequency of modulation. Here, we propose a perturbation approach that can predict the dependency of the oscillation amplitude on the modulation frequency.

Decimetre-scale carbonaceous macrofossils from the Mesoproterozoic Gaoyuzhuang Formation in the Yanshan Range are known as the current oldest unambiguous evidence of macroscopic multicellular eukaryotes. Here, we reported a new SIMS zircon age of 1588.8 ± 6.5 Ma from a volcanic tuff in the Qianxi County of Hebei Province, about 11 m above the macrofossil’s horizon. This new age provides a direct age constraint on the macroscopic eukaryotic fossils from the Gaoyuzhuang Formation. It indicates that macroscopic life with the moderate diversity and certain morphological complexity had already evolved at the beginning of the Mesoproterozoic, and implies a possibility of discovering macroscopic eukaryotes in earlier rocks. This study also calls for a stratigraphic framework to integrate biological and environmental studies in different regions for a better understanding of the evolution of multicellular organisms and environmental change during this important period.

Cryogenic carbon capture (CCC) is an innovative technology to desublimate $\text {CO}_2$ out of industrial flue gases. A comprehensive understanding of $\text {CO}_2$ desublimation and sublimation is essential for widespread application of CCC, which is highly challenging due to the complex physics behind. In this work, a lattice Boltzmann (LB) model is proposed to study $\text {CO}_2$ desublimation and sublimation for different operating conditions, including the bed temperature (subcooling degree $\Delta T_s$), gas feed rate (Péclet number $Pe $) and bed porosity ($\psi$). The $\text {CO}_2$ desublimation and sublimation properties are reproduced. Interactions between convective $\text {CO}_2$ supply and desublimation/sublimation intensity are analysed. In the single-grain case, $Pe $ is suggested to exceed a critical value $Pe _c$ at each $\Delta T_s$ to avoid the convection-limited regime. Beyond $Pe _c$, the $\text {CO}_2$ capture rate ($v_c$) grows monotonically with $\Delta T_s$, indicating a desublimation-limited regime. In the packed bed case, multiple grains render the convective $\text {CO}_2$ supply insufficient and make CCC operate under the convection-limited mechanism. Besides, in small-$\Delta T_s$ and high-$Pe $ tests, $\text {CO}_2$ desublimation becomes insufficient compared with convective $\text {CO}_2$ supply, thus introducing the desublimation-limited regime with severe $\text {CO}_2$ capture capacity loss ($\eta _d$). Moreover, large $\psi$ enhances gas mobility while decreasing cold grain volume. A moderate porosity $\psi _c$ is recommended for improving the $\text {CO}_2$ capture performance. By analysing $v_c$ and $\eta _d$, regime diagrams are proposed in $\Delta T_s$–$Pe $ space to show distributions of convection-limited and desublimation-limited regimes, thus suggesting optimal conditions for efficient $\text {CO}_2$ capture. This work develops a viable LB model to examine CCC under extensive operating conditions, contributing to facilitating its application.

In 2017, Brosseau & Vlahovska (Phys. Rev. Lett, vol. 119, no. 3, 2017, p. 034501) found that, in a strong electric field, a weakly conductive, low-viscosity droplet immersed in a highly conductive, high-viscosity medium formed a lens shape, and liquid rings continuously detached from its equatorial plane and subsequently broke up into satellite droplets. This fascinating multiphase electrohydrodynamic (EHD) phenomenon is known as droplet equatorial streaming. In this paper, based on the unified lattice Boltzmann method framework proposed by Luo et al. (Phil. Trans. R. Soc. A Math. Phys. Engng Sci, vol. 379, no. 2208, 2021, p. 20200397), a novel lattice Boltzmann (LB) model is constructed for multiphase EHD by coupling the Allen–Cahn type of multiphase LB model and two new LB equations to solve the Poisson equation of the electric field and the conservation equation of the surface charge. Using the proposed LB model, we successfully reproduced, for the first time, the complete process of droplet equatorial streaming, including the continuous ejection and breakup of liquid rings on the equatorial plane. In addition, it is found that, under conditions of high electric field strength or significant electrical conductivity contrast, droplets exhibit fingering equatorial streaming that was unknown before. A power-law relationship is discovered for droplet total charge evolution and a theoretical model is then proposed to describe the droplet radius and height over time. The breakup of liquid rings is found to be dominated by capillary instability, while the breakup of liquid fingers is governed by the end-pinching mechanism. Finally, a phase diagram is constructed for fingering equatorial streaming and ring equatorial streaming, and a criterion equation is established for the phase boundary.

This paper proposes an air-filled substrate integrated waveguide (AFSIW) bandpass filter with a miniaturized non-resonant node (NRN). The NRN structure is introduced between the three resonators, and its size is smaller than the resonator size, which can realize the NRN structure’s miniaturization and reduce the model’s size. The NRN size of this filter is 41% of the NRN size of the existing AFSIW filter. This filter also introduces a transmission zero (TZ) above the passband. The measured results show that the filter’s center frequency is 20.73 GHz, and the bandwidth is 0.86 GHz. The insertion loss in the passband is 0.95 dB, and the return loss is better than 23 dB. Due to the TZ in the upper stopband, the AFSIW filter obtained good selectivity.

In previous research, several computational methods have been proposed to analyse the navigation, transportation safety and collision risks of maritime vessels. The objective of this study is to use Automatic Identification System (AIS) data to assess the collision risk between two vessels before an actual collision occurs. We introduce the concept of an angle interval in the model to enable real-time response to vessel collision risks. When predicting collision risks, we consider factors such as relative distance, relative velocity and phase between the vessels. Lastly, the collision risk is divided into different regions and represented by different colours. The green region represents a low-risk area, the yellow region serves as a cautionary zone and the red region indicates a high-alert zone. If a signal enters the red region, the vessel's control system will automatically intervene and initiate evasive manoeuvres. This reactive mechanism enhances the safety of vessel operations, ensuring the implementation of effective collision avoidance measures.

Nitrate is linked to chronic human illness and to a variety of environmental problems, and continues to be a contaminant of concern in soils and natural waters. Improved methods for nitrate abatement, thus, are still needed. The purpose of this study was to assess the potential for redox-modified, iron-bearing clay minerals to act as nitrate decontamination agents in natural environments. The model clay mineral tested was ferruginous smectite (sample SWa-1) exchanged with either sodium (Na+) or polydiallyldimethylammonium chloride (poly-DADMAC). Structural iron (Fe) in SWa-1 was in either the oxidized or reduced state. Little nitrate uptake was observed in the Na+-SWa-1, which was attributed to coulombic repulsion between the basal surfaces of the smectite and the nitrate anion. The addition of the DADMAC to the SWa-1 reversed the electrostatic charge manifested at the smectite surface from negative to positive, as measured by the zeta (ζ) potential. The positively charged poly-DADMAC-SWa-1 yielded high nitrate uptake due to coulombic attraction in both the oxidized and reduced states of the Fe in the SWa-1. The presence of reduced structural Fe(II) in the positively charged poly-DADMAC-SWa-1 enabled a chemical reduction reaction with the nitrate to produce nitrite. The amounts of nitrite found in solution, however, failed to account for all of the Fe(II) oxidized, so other N reduction products may also have formed or perhaps nitrite was also present in the adsorbed phase. The effects of other complexities, such as polymer configuration at the surface, also need further investigation. The results do clearly establish abiotic nitrate reduction to nitrite and possibly other reduction products. The combination of bacterial activity in soils and sediments, which is known to reduce structural Fe in smectites, and the abundance of organic cations in soil organic matter creates an environment where reversed-charge smectite could exist in nature. This represents a potentially effective system for mitigating harmful effects of nitrate in soils, sediments, groundwater, and surface water.