In gas evolving electrolysis, bubbles grow at electrodes due to a diffusive influx from oversaturation generated locally in the electrolyte by the electrode reaction. When considering electrodes of micrometre size resembling catalytic islands, direct numerical simulations show that bubbles may approach dynamic equilibrium states at which they neither grow nor shrink. These are found in undersaturated and saturated bulk electrolytes during both pinning and expanding wetting regimes of the bubbles. The equilibrium is based on the balance of local influx near the bubble foot and global outflux. To identify the parameter regions of bubble growth, dissolution and dynamic equilibrium by analytical means, we extend the solution of Zhang & Lohse (2023 J. Fluid Mech. vol. 975, R3) by taking into account modified gas fluxes across the bubble interface, which result from a non-uniform distribution of dissolved gas. The Damköhler numbers at equilibrium are found to range from small to intermediate values. Unlike pinned nanobubbles studied earlier, for micrometre-sized bubbles the Laplace pressure plays only a minor role. With respect to the stability of the dynamic equilibrium states, we extend the methodology of Lohse & Zhang (2015a Phys. Rev. E vol. 91, 031003(R)) by additionally taking into account the electrode reaction. Under contact line pinning, the equilibrium states are found to be stable for flat nanobubbles and for microbubbles in general. For unpinned bubbles, the equilibrium states are always stable. Finally, we draw conclusions on how to possibly enhance the efficiency of electrolysis.

Emission line galaxies (ELGs) are crucial for cosmological studies, particularly in understanding the large-scale structure of the Universe and the role of dark energy. ELGs form an essential component of the target catalogue for the Dark Energy Spectroscopic Instrument (DESI), a major astronomical survey. However, the accurate selection of ELGs for such surveys is challenging due to the inherent uncertainties in determining their redshifts with photometric data. In order to improve the accuracy of photometric redshift estimation for ELGs, we propose a novel approach CNN–MLP that combines convolutional neural networks (CNNs) with multilayer perceptrons (MLPs). This approach integrates both images and photometric data derived from the DESI Legacy Imaging Surveys Data Release 10. By leveraging the complementary strengths of CNNs (for image data processing) and MLPs (for photometric feature integration), the CNN–MLP model achieves a $\sigma_{\mathrm{NMAD}}$ (normalised median absolute deviation) of 0.0140 and an outlier fraction of 2.57%. Compared to other models, CNN–MLP demonstrates a significant improvement in the accuracy of ELG photometric redshift estimation, which directly benefits the target selection process for DESI. In addition, we explore the photometric redshifts of different galaxy types (Starforming, Starburst, AGN, and Broadline). Furthermore, this approach will contribute to more reliable photometric redshift estimation in ongoing and future large-scale sky surveys (e.g. LSST, CSST, and Euclid), enhancing the overall efficiency of cosmological research and galaxy surveys.

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by chronic inflammation of the synovial membrane, leading to cartilage destruction and bone erosion. Due to the complex pathogenesis of RA and the limitations of current therapies, increasing research attention has been directed towards novel strategies targeting fibroblast-like synoviocytes (FLS), which are key cellular components of the hyperplastic pannus. Recent studies have highlighted the pivotal role of FLS in the initiation and progression of RA, driven by their tumour-like transformation and the secretion of pro-inflammatory mediators, including cytokines, chemokines and matrix metalloproteinases. The aggressive phenotype of RA-FLS is marked by excessive proliferation, resistance to apoptosis, and enhanced migratory and invasive capacities. Consequently, FLS-targeted therapies represent a promising avenue for the development of next-generation RA treatments. The efficacy of such strategies – particularly those aimed at modulating FLS signalling pathways – has been demonstrated in both preclinical and clinical settings, underscoring their therapeutic potential. This review provides an updated overview of the pathogenic mechanisms and functional roles of FLS in RA, with a focus on critical signalling pathways under investigation, including Janus kinase/signal transducer and activator of transcription (JAK/STAT), mitogen-activated protein kinase (MAPK), nuclear factor kappa B (NF-κB), Notch and interleukin-1 receptor-associated kinase 4 (IRAK4). In addition, we discuss the emerging understanding of FLS-subset-specific contributions to immunometabolism and explore how computational biology is shaping novel targeted therapeutic strategies. A deeper understanding of the molecular and functional heterogeneity of FLS may pave the way for more effective and precise therapeutic interventions in RA.

In gas evolving electrolysis, bubbles grow at electrodes due to a diffusive influx from oversaturation generated locally in the electrolyte by the electrode reaction. When considering electrodes of micrometre size resembling catalytic islands, direct numerical simulations show that bubbles may approach dynamic equilibrium states at which they neither grow nor shrink. These are found in under- and saturated bulk electrolytes during both pinning and expanding wetting regimes of the bubbles. The equilibrium is based on the balance of local influx near the bubble foot and global outflux. To identify the parameter regions of bubble growth, dissolution and dynamic equilibrium by analytical means, we extend the solution of Zhang & Lohse (2023) J. Fluid Mech. 975, R3, by taking into account modified gas fluxes across the bubble interface, that result from a non-uniform distribution of dissolved gas. The Damköhler numbers at equilibrium are found to range from small to intermediate values. Unlike pinned nano-bubbles studied earlier, for micrometre-sized bubbles the Laplace pressure plays only a minor role. With respect to the stability of the dynamic equilibrium states, we extend the methodology of Lohse & Zhang (2015a) Phys. Rev. E 91 (3), 031003(R), by additionally taking into account the electrode reaction. Under contact line pinning, the equilibrium states are found to be stable for flat nano-bubbles and for micro-bubbles in general. For unpinned bubbles, the equilibrium states are always stable. Finally, we draw conclusions on how to possibly enhance the efficiency of electrolysis.

Asian corn borer, Ostrinia furnacalis Guenée (Lepidoptera: Crambidae), is a major pest in corn production, and its management remains a significant challenge. Current control methods, which rely heavily on synthetic chemical pesticides, are environmentally detrimental and unsustainable, necessitating the development of eco-friendly alternatives. This study investigates the potential of the entomopathogenic nematode Steinernema carpocapsae as a biological control agent for O. furnacalis pupae, focusing on its infection efficacy and the factors influencing its performance. We conducted a series of laboratory experiments to evaluate the effects of distance, pupal developmental stage, soil depth, and light conditions on nematode attraction, pupal mortality and sublethal impacts on pupal longevity and oviposition. Results demonstrated that S. carpocapsae exhibited the highest attraction to pupae at a 3 cm distance, with infection declining significantly at greater distances. Younger pupae (<12 h old), were more attractive to nematodes than older pupae, and female pupae were preferred over males. Nematode infection was highest on the head and thorax of pupae, with a significant reduction in infection observed after 24 h. Infection caused 100% mortality in pupae within 2 cm soil depth, though efficacy was reduced under light conditions. Sublethal effects included a significant reduction in the longevity of infected adults and a decrease in the number of eggs laid by infected females compared to controls. These findings underscore the potential of S. carpocapsae as an effective biocontrol agent for sustainable pest management in corn production, offering a viable alternative to chemical pesticides.

We present a practical verification method for safety analysis of the autonomous driving system (ADS). The main idea is to build a surrogate model that quantitatively depicts the behavior of an ADS in the specified traffic scenario. The safety properties proved in the resulting surrogate model apply to the original ADS with a probabilistic guarantee. Given the complexity of a traffic scenario in autonomous driving, our approach further partitions the parameter space of a traffic scenario for the ADS into safe sub-spaces with varying levels of guarantees and unsafe sub-spaces with confirmed counter-examples. Innovatively, the partitioning is based on a branching algorithm that features explainable AI methods. We demonstrate the utility of the proposed approach by evaluating safety properties on the state-of-the-art ADS Interfuser, with a variety of simulated traffic scenarios, and we show that our approach and existing ADS testing work complement each other. We certify five safe scenarios from the verification results and find out three sneaky behavior discrepancies in Interfuser which can hardly be detected by safety testing approaches.

To evaluate the variations in COVID-19 case fatality rates (CFRs) across different regions and waves, and the impact of public health interventions, social and economic characteristics, and demographic factors on COVID-19 CFRs, we collected data from 30 countries with the highest incidence rate in three waves. We summarized the CFRs of different countries and continents in each wave through meta-analysis. Spearman’s correlation and multiple linear regression were employed to estimate the correlation between influencing factors and reduction rates of CFRs. Significant differences in CFRs were observed among different regions during the three waves (P < 0.001). An association was found between the changes in fully vaccinated rates (rs = 0.41), population density (rs = 0.43), the proportion of individuals over 65 years old (rs = 0.43), and the reduction rates of case fatality rate. Compared to Wave 1, the reduction rates in Wave 2 were associated with population density (β = 0.19, 95%CI: 0.05–0.33) and smoking rates (β = −4.66, 95%CI: −8.98 – −0.33), while in Wave 3 it was associated with booster vaccine rates (β = 0.60, 95%CI: 0.11–1.09) and hospital beds per thousand people (β = 4.15, 95%CI: 1.41–6.89). These findings suggest that the COVID-19 CFRs varied across different countries and waves, and promoting booster vaccinations, increasing hospital bed capacity, and implementing tobacco control measures can help reduce CFRs.

We report a numerical investigation of a previously noticed but less explored flow state transition in two-dimensional turbulent Rayleigh–Bénard convection. The simulations are performed in a square domain over a Rayleigh number range of $10^7 \leq Ra \leq 2 \times 10^{11}$ and a Prandtl number range of $0.25 \leq Pr \leq 20$. The transition is characterized by the emergence of multiple satellite eddies with increasing $Ra$, which orbit around and interact with the main vortex roll in the system. Consequently, the main roll is squeezed to a smaller size compared with the domain and wanders around in the bulk region irregularly and extensively. This is in sharp contrast to the flow state before the transition, which is featured by a domain-sized circulatory roll with its vortex centre ‘condensed’ near the domain's centre. Detailed velocity field analysis reveals that there exists an abrupt increase in the energy fluctuations of the Fourier modes during the transition. Based on this phase-transition-like signal, the critical condition for the transition is found to follow a scaling relation as $Ra_t \sim Pr^{1.41}$ where $Ra_t$ is the critical Rayleigh number for the transition. This scaling relation is quantitatively explained by a phenomenological model grounded on the bistability behaviour (i.e. spontaneous and stochastic switching between the two flow states) observed at the edge of the transition. The model can also account for the effects of aspect ratio on the transition reported in the literature (van der Poel et al., Phys. Fluids, vol. 24, 2012).

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.

Flexible electronics researchers have been conducting studies to explore the response of flexible stretchable electrodes to strain. The regulation of strain response in current flexible stretchable electrodes relies primarily on altering the material system, interfacial adhesion, or electrode structure. However, modifying the material system or interfacial adhesion can negatively disrupt the stretchable electrode preparation process, making commercialization a significant challenge. Additionally, the material system may be inadequate in extreme environments such as high temperatures. Hence a systematic structural design approach is crucial for effective response modulation of stretchable electrodes. One potential solution is the design of fibre structures from the micro to macro scale. This article focuses on discussing how the response of stretchable electrodes can be modulated by fibres in different states. The discussion includes fibres on elastic films, fibres directly constituting fibrous membranes at the microscopic level, and fibres constituting metamaterials at the fine level. The modulation can be achieved by altering the orientation of the fibres, the geometrical structure of the fibres themselves, and the geometrical structure formed between the fibres. Additionally, the article analyses the current situation of stretchable electrodes in extreme environments such as high temperatures. It also reviews the development of ceramic fibre membranes that can be stretched in high-temperature environments. The authors further discuss how the stretchability of ceramic fibre membranes can be improved through the structuring of ceramic fibre membranes with metamaterials. Ultimately, the goal is to realize stretchable electrodes that can be used in extreme environments such as high temperatures.

An enhanced wideband tracking method for characteristic modes (CMs) is investigated in this paper. The method consists of three stages, and its core tracking stage (CTS) is based on a classical eigenvector correlation-based algorithm. To decrease the tracking time and eliminate the crossing avoidance (CRA), we append a commonly used eigenvalue filter (EF) as the preprocessing stage and a novel postprocessing stage to the CTS. The proposed postprocessing stage can identify all CRA mode pairs by analyzing their trajectory and correlation characteristics. Subsequently, it can predict corresponding CRA frequencies and correct problematic qualities rapidly. Considering potential variations in eigenvector numbers at consecutive frequency samples caused by the EF, a new execution condition for the adaptive frequency adjustment in the CTS is introduced. Finally, CMs of a conductor plate and a fractal structure are investigated to demonstrate the performance of the proposed method, and the obtained results are discussed.

Montmorillonite (Mnt)-based solid acids have a wide range of applications in catalysis and adsorption of pollutants. For such solid acids, the acidic characteristic often plays a significant role in these applications. The objective of the current study was to examine the effects of H3PO4-activation and supporting WO3 on the textural structure and surface acidic properties of Mnt. The Mnt-based solid acid materials were prepared by H3PO4 treatment and an impregnation method with a solution of ammonium metatungstate (AMT) and were examined as catalysts in the dehydration of glycerol to acrolein. The catalysts were characterized by nitrogen adsorption-desorption, powder X-ray diffraction (XRD), Fourier-transform infrared (FTIR) spectroscopy, scanning electronic microscopy (SEM), X-ray photoelectron spectroscopy (XPS), diffuse reflectance ultraviolet-visible (DR UV-Vis) spectroscopy, temperature programmed desorption of NH3 (NH3-TPD), diffuse reflectance Fourier-transform infrared (DR FTIR) spectroscopy of adsorbed pyridine, and thermogravimetric (TG) analyses. The phosphoric acid treatment of Mnt created Brönsted and Lewis acid sites and led to increases in specific surface areas, porosity, and acidity. WO3 species influenced total acidity, acid strength, the numbers of Brönsted and Lewis acid sites, and catalytic performances. A high turnover frequency (TOF) value (31.2 h−1) based on a maximal 60.7% yield of acrolein was reached. The correlation of acrolein yield with acidic properties indicated that the cooperative role of Brönsted and Lewis acid sites was beneficial to the formation of acrolein and a little coke deposition (<3.3 wt.%). This work provides a new idea for the design of solid acid catalysts with cooperative Brönsted and Lewis acidity for the dehydration of glycerol.

Lower limb exoskeletons (LLEs) have demonstrated their potential in delivering quantified repetitive gait training for individuals afflicted with gait impairments. A critical concern in robotic gait training pertains to fostering active patient engagement, and a viable solution entails harnessing the patient’s intrinsic effort to govern the control of LLEs. To address these challenges, this study presents an innovative online gait learning approach with an appropriate control strategy for rehabilitation exoskeletons based on dynamic movement primitives (DMP) and an Assist-As-Needed (AAN) control strategy, denoted as DMP-AAN. Specifically tailored for post-stroke patients, this approach aims to acquire the gait trajectory from the unaffected leg and subsequently generate the reference gait trajectory for the affected leg, leveraging the acquired model and the patient’s personal exertion. Compared to conventional AAN methodologies, the proposed DMP-AAN approach exhibits adaptability to diverse scenarios encompassing varying gait patterns. Experimental validation has been performed using the lower limb rehabilitation exoskeleton HemiGo. The findings highlight the ability to generate suitable control efforts for LLEs with reduced human-robot interactive force, thereby enabling highly patient-controlled gait training sessions to be achieved.

All-fiber coherent beam combiners based on the self-imaging effect can achieve a near-perfect single laser beam, which can provide a promising way to overcome the power limitation of a single-fiber laser. One of the key points is combining efficiency, which is determined by various mismatches during fabrication. A theoretical model has been built, and the mismatch error is analyzed numerically for the first time. The mismatch errors have been numerically studied with the beam quality and combining efficiency being chosen as the evaluation criteria. The tolerance of each mismatch error for causing 1% loss is calculated to guide the design of the beam combiners. The simulation results are consistent with the experimental results, which show that the mismatch error of the square-core fiber is the main cause of the efficiency loss. The results can provide useful guidance for the fabrication of all-fiber coherent beam combiners.