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The spontaneous self-assembly of multicellular ensembles into living materials with synergistic structure and function remains a considerable challenge in biotechnology and synthetic biology. Here, we exploit the aqueous two-phase separation of dextran-in-PEG emulsion micro-droplets for the capture, spatial organization and immobilization of algal cells or algal/bacterial cell communities to produce discrete multicellular spheroids capable of both aerobic (oxygen producing) and hypoxic (hydrogen producing) photosynthesis in daylight under air. We show that localized oxygen depletion results in hydrogen production from the core of the algal microscale reactor, and demonstrate that enhanced levels of hydrogen evolution can be achieved synergistically by spontaneously enclosing the photosynthetic cells within a shell of bacterial cells undergoing aerobic respiration. Our results highlight a promising droplet-based environmentally benign approach to dispersible photosynthetic microbial micro-reactors comprising segregated cellular micro-niches with dual functionality, and provide a step towards photobiological hydrogen production under aerobic conditions. The development of techniques capable of orchestrating the assembly of living cells into multicellular ensembles with synergistic and function is challenge. Here, the authors construct algal or algal/bacterial cells-based core shell-like structure based on aqueous two-phase system for synergic photosynthetic H 2 production.

Stress stimulation-mediated liquid-liquid phase separation is a key activity in living organisms, but its biophysical characteristics are poorly understood. Here, we report a UV-light stress stimulation behaviour in a binary community of synthetic protocells of condensates and proteinosomes, showing that condensates could behave like Condensate Pumps to enable a stepwise controlled transmembrane mass transfer regardless of the permeability barrier of proteinosomes. The stimulation mechanism of interfacial tension-induced proteinosome deformation and transient high osmotic pressure arisen by the dissociation of condensate is proposed. Accordingly, under UV-light stress stimulation, unexpected characteristics could be triggered by transmembrane pumping oversized biomacromolecules into proteinosomes including liquid-liquid reentrant phase separation, DNA unwinding, and protein synthesis. Therefore, our results not only reveal unique physical principles and potential characteristics of macromolecular assemblies at droplet-membrane interface but also highlight a pathway for transmembrane transport of biomacromolecules which is anticipated to serve as a powerful technique to inducing higher-order behaviour in synthetic protocells community. Stress stimulation-mediated liquid-liquid phase separation is an essential feature of living organisms, but its biophysical characteristics are poorly understood. Here, the authors report a UV-light stress stimulation behaviour in a binary community of synthetic protocells of condensates and proteinosomes, showing that condensates could behave like condensate pumps to enable a stepwise controlled transmembrane mass transfer regardless of the permeability barrier of proteinosomes.

We describe a smart hybrid system that integrates a temperature-sensitive polymer and photothermal material. The system enables algae to produce hydrogen under both low and high light intensities (100–2000 μmol photons·m–2·s–1).Algae-based hydrogen production, which relies only on sunlight and water, offers a green alternative that provides clean, low-carbon energy for sustainable development.High light intensity typically damages algae and halts hydrogen production. Our system dynamically regulates light exposure, protecting algal cells and sustaining hydrogen generation for 25 days.This self-regulating, energy-efficient system works without external power and reduces carbon emissions, paving the way for scalable outdoor biohydrogen production. Cleaner, lower carbon energy is needed for more sustainable development. Algal production of hydrogen directly from water and sunlight is a promising route toward such sustainable energy. However, algae can only produce hydrogen continuously in weak light. We developed a hybrid system using a designed thermosensitive material, poly(N-isopropylacrylamide)-co-poly(butyl acrylate) (PNIPAM-BA), and a photothermal material, graphene oxide (GO), to dynamically sense light intensity. This system regulates the entry of incident light to protect the activity of algal hydrogenase, which enables algae to efficiently produce hydrogen through photosynthesis across a range of light intensities (100–2000 μmol photons·m–2·s–1). Even under the standard maximum solar intensity of 2000 μmol photons·m–2·s–1, we achieved continuous hydrogen production over 25 days with an average hydrogen production rate of 17.53 μmol H2 (mg chlorophyll)–1 h–1. Thus, this study addresses the challenge of continuous hydrogen production by algae under high light intensity, greatly advancing prospects for large-scale outdoor hydrogen production. [Display omitted] The proposed algae/polymer hybrid system demonstrates significant technological advances in photosynthetic hydrogen production under high light intensities. While laboratory-scale results showcase sustained hydrogen production over 25 days with high efficiency, several challenges must be addressed for large-scale implementation. These include ensuring uniform light distribution in larger photobioreactors, preventing oxygen accumulation that can inhibit hydrogenase activity, and maintaining consistent environmental conditions across diverse reactor regions. To overcome these barriers, innovative reactor designs, real-time automation for oxygen and temperature control, and efficient gas exchange systems will be crucial. In addition, the scalability of the light-regulating capability of the hybrid system and its long-term stability require further validation. While these discussions involve some level of speculation, they are grounded in the experimental outcomes outlined in this study, which underscore the potential for a low-carbon transition enabled by scalable, algae-based hydrogen production systems. We developed a smart algae/polymer hybrid system that enabled sustained photosynthetic hydrogen production under high light intensities (100–2000 μmol photons·m-2·s-1), overcame photoinhibition and oxygen-related challenges, and advances outdoor large-scale green hydrogen production.

Among many e-commerce platforms, collaborative filtering recommendation algorithm is currently the most widely used recommendation technology. In order to alleviate the deficiencies of the traditional user-based collaborative filtering algorithm in cold start and recommendation accuracy, this paper proposes a collaborative filtering recommendation algorithm based on user characteristics and user interests. The similarity of the algorithm in this paper is composed of user score similarity, user attribute feature similarity and user interest similarity, in which user registration information is used to extract attribute features to calculate user feature similarity; use the number of user evaluations of project attributes to measure users' interest in different project attributes, use the similarity calculation formula to calculate the interest similarity value between users. The user attribute feature similarity and user interest similarity are combined with the user rating similarity to obtain the final similarity for recommendation. Finally, a simulation experiment is performed on the MovieLens movie data set. Through the experimental results, it can be seen that the improved collaborative filtering algorithm based on user characteristics and user interests not only solves the cold start problem, but also improves the recommendation accuracy.

Nowadays, variable frequency AC generation system is widely used on more electric aircraft because of their advantages of simple structure, high power density, and high reliability. However, a variable frequency system has a wide range of operating speeds and frequencies, and its exciter field is designed to be highly saturated at low speed. Under the condition of a saturated exciter field at high speed, the generator can produce a very high voltage, which will cause damage to aircraft utilization equipment, leading to catastrophic failures. Therefore, to protect the safety of the aircraft, transient voltage regulation performance and voltage protection design are critical in the system design of variable frequency AC generation. This paper focuses on the design of voltage regulation and protection of variable frequency electrical power systems that can meet airworthiness requirements.

As an emerging field of robotics, magnetic-field-controlled soft microrobot has broad application prospects for its flexibility, locomotion diversity as well as remote controllability. Magnetic soft microrobots can perform multimodal locomotion under the control of a magnetic field, which may have potential applications in precision medicine. However, previous researches mainly focus on new locomotion in a relatively ideal environment, lacking exploration on the ability of magnetic microrobot locomotion to resist external disturbances and proceed in a nonideal environment. Here, a porous silica-doped soft magnetic microrobot is constructed for enhanced stability of multimodal locomotion in the nonideal biological environment. Porous silica spheres are doped into NdFeB-silicone elastomer base, improving adhesion properties as well as refining the comprehensive mechanical properties of the microrobot. Multimodal locomotions are achieved, and the influence of porous silica doping on the stability of each locomotion in nonideal environment is explored in depth. Motions in nonideal circumstances such as climbing, loading, current rushing, wind blowing, and obstacle hindering are conducted successfully with porous silica doping. Such a stability-enhanced multimodal locomotion system can be used in biocatalysis as well as thrombus removal, and its prospect for precision medicine is highlighted by in vivo demonstration of multimodal locomotion with nonideal disturbance.

Circular RNA (CircRNA) is a type of non-coding RNAs in which both ends are covalently linked. Researchers have demonstrated that many circRNAs can act as biomarkers of diseases. However, traditional experimental methods for circRNA-disease associations identification are labor-intensive. In this work, we propose a novel method based on the heterogeneous graph neural network and metapaths for circRNA-disease associations prediction termed as HMCDA. First, a heterogeneous graph consisting of circRNA-disease associations, circRNA-miRNA associations, miRNA-disease associations and disease-disease associations are constructed. Then, six metapaths are defined and generated according to the biomedical pathways. Afterwards, the entity content transformation, intra-metapath and inter-metapath aggregation are implemented to learn the embeddings of circRNA and disease entities. Finally, the learned embeddings are used to predict novel circRNA-disase associations. In particular, the result of extensive experiments demonstrates that HMCDA outperforms four state-of-the-art models in fivefold cross validation. In addition, our case study indicates that HMCDA has the ability to identify novel circRNA-disease associations.

Diagnosing agricultural machinery faults is critical to agricultural automation, and identifying vibration signals from faulty bearings is important for agricultural machinery fault diagnosis and predictive maintenance. In recent years, data–driven methods based on deep learning have received much attention. Considering the roughness of the attention receptive fields in Vision Transformer and Swin Transformer, this paper proposes a Shift–Deformable Transformer (S–DT) network model with multi–attention fusion to achieve accurate diagnosis of composite faults. In this method, the vibration signal is first transformed into a time–frequency graph representation through continuous wavelet transform (CWT); secondly, dilated convolutional residual blocks and efficient attention for cross–spatial learning are used for low–level local feature enhancement. Then, the shift window and deformable attention are fused into S–D Attention, which has a more focused receptive field to learn global features accurately. Finally, the diagnosis result is obtained through the classifier. Experiments were conducted on self–collected datasets and public datasets. The results show that the proposed S–DT network performs excellently in all cases. With a slight decrease in the number of parameters, the validation accuracy improves by more than 2%, and the training network has a fast convergence period. This provides an effective solution for monitoring the efficient and stable operation of agricultural automation machinery and equipment.

The impact of emotions on intuitive and analytical thinking has been widely studied. Most research suggests that negative emotions enhance analytical processing. However, there are studies indicating that the sense of certainty associated with disgust can stimulate intuitive processing. Despite these findings, the neuroelectrophysiological evidence supporting the role of disgust in promoting intuitive processing remains unexplored. This study aimed to investigate the neuroelectrophysiological mechanisms by which disgust promotes intuitive processing. A total of 54 participants were recruited and randomly assigned to specific emotion groups. Emotional states were induced by exposing participants to disgust and fear videos designed to evoke specific dimensions of certainty and uncertainty. Event-related potentials (ERP) and the Cognitive Reflection Test (CRT) were utilized as experimental materials to measure participants' responses. The results demonstrated that disgust facilitated intuitive thinking, as evidenced by the lowest accuracy in behavioral outcomes. ERP findings showed that disgust led to smaller N2 and larger P3b amplitudes under conditions of conflict. These results suggest that disgust reduces individuals' conflict-detection ability, resulting in a stronger sense of certainty in intuitive but incorrect answers. This study provides neuroelectrophysiological evidence that disgust enhances intuitive thinking. The findings offer a new perspective on the influence of emotions on dual-process thinking, highlighting the role of disgust in shaping intuitive and analytical thought processes.

In the field of visual graphic design, complexity plays a crucial role in visual information processing, and it is assumed to be an absolute quantity based on the number of the presenting features and components. However, it remains unclear whether the visual order of the constituent elements in graphical symbol complexity affects cognitive processing, especially memory processing. Our research innovatively generated four groups of novel, meaningless graphical symbols (complex and ordered, complex and disordered, simple and ordered, and simple and disordered) and experimentally manipulated the level of complexity and order in these stimuli. Before the formal experiment, a five-point scale was used to further rule out differences between objective and subjective definitions of these graphical symbols on ratings of complexity, order, concreteness, and familiarity. Then, we used a cue-recall task to compare subjects’ memory performance of those four graphical symbol groups. The analytical results showed a significant interaction between visual order and graphical symbol complexity, with the complexity effect appearing only when the stimuli were in disordered condition and disappearing once the stimuli were ordered. In addition, this study conducted a practical application validation to confirm that increasing the level of visual order is an effective way to improve user experience while maintaining the same level of complexity. The findings can serve as a reference for graphical symbol design, graphic design, and visual communication design.