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Abstract Swarm systems consist of a large number of interacting individuals, which exhibit complex behavior despite having simple interaction rules. However, crafting individual motion policies that can manifest desired collective behaviors poses a significant challenge due to the intricate relationship between individual policies and swarm dynamics. This paper addresses this issue by proposing an imitation learning method, which derives individual policies from collective behavior data. The approach leverages an adversarial imitation learning framework, with a deep attention network serving as the individual policy network. Our method successfully imitates three distinct collective behaviors. Utilizing the ease of analysis provided by the deep attention network, we have verified that the individual policies underlying a certain collective behavior are not unique. Additionally, we have analyzed the different individual policies discovered. Lastly, we validate the applicability of the proposed method in designing policies for swarm robots through practical implementation on swarm robots.

Abstract Environmental stimuli not only alter gene expression profiles but also induce structural changes in cells. How distinct nuclear bodies respond to cellular stress is poorly understood. Here, we identify a subnuclear organelle named the nucleolar stress body (NoSB), the formation of which is induced by the inhibition of rRNA transcription or inactivation of rRNA processing and maturation in C. elegans. NoSB does not colocalize with other previously described subnuclear organelles. We conduct forward genetic screening and identify a bZIP transcription factor, named nucleolar stress response-1 (NOSR-1), that is required for NoSB formation. The inhibition of rRNA transcription or inactivation of rRNA processing and maturation increases nosr-1 expression. By using transcriptome analysis of wild-type animals subjected to different nucleolar stress conditions and nosr-1 mutants, we identify that the SR-like protein NUMR-1 (nuclear localized metal responsive) is the target of NOSR-1. Interestingly, NUMR-1 is a component of NoSB and itself per se is required for the formation of NoSB. We conclude that the NOSR-1/NUMR-1 axis likely responds to nucleolar stress and mediates downstream stress-responsive transcription programs and subnuclear morphology alterations in C. elegans.

Abstract Germ granules are biomolecular condensates present in most animal germ cells. One function of germ granules is to help maintain germ cell totipotency by organizing mRNA regulatory machinery, including small RNA-based gene regulatory pathways. The C. elegans germ granule is compartmentalized into multiple subcompartments whose biological functions are largely unknown. Here, we identify an uncharted subcompartment of the C. elegans germ granule, which we term the E granule. The E granule is nonrandomly positioned within the germ granule. We identify five proteins that localize to the E granule, including the RNA-dependent RNA polymerase (RdRP) EGO-1, the Dicer-related helicase DRH-3, the Tudor domain-containing protein EKL-1, and two intrinsically disordered proteins, EGC-1 and ELLI-1. Localization of EGO-1 to the E granule enables synthesis of a specialized class of 22G RNAs, which derive exclusively from 5’ regions of a subset of germline-expressed mRNAs. Defects in E granule assembly elicit disordered production of endogenous siRNAs, which disturbs fertility and the RNAi response. Our results define a distinct subcompartment of the C. elegans germ granule and suggest that one function of germ granule compartmentalization is to facilitate the localized production of specialized classes of small regulatory RNAs.

Summary: The nucleolus is the most prominent membraneless organelle within the nucleus. How the nucleolar structure is regulated is poorly understood. Here, we identified two types of nucleoli in C. elegans. Type I nucleoli are spherical and do not have visible nucleolar vacuoles (NoVs), and rRNA transcription and processing factors are evenly distributed throughout the nucleolus. Type II nucleoli contain vacuoles, and rRNA transcription and processing factors exclusively accumulate in the periphery rim. The NoV contains nucleoplasmic proteins and is capable of exchanging contents with the nucleoplasm. The high-order structure of the nucleolus is dynamically regulated in C. elegans. Faithful rRNA processing is important to prohibit NoVs. The depletion of 27SA2 rRNA processing factors resulted in NoV formation. The inhibition of RNA polymerase I (RNAPI) transcription and depletion of two conserved nucleolar factors, nucleolin and fibrillarin, prohibits the formation of NoVs. This finding provides a mechanism to coordinate structure maintenance and gene expression.

Temperature greatly affects numerous biological processes in all organisms. How multicellular organisms respond to and are impacted by hypothermic stress remains elusive. Here, we found that cold-warm stimuli induced depletion of the RNA exosome complex in the nucleoli but enriched it in the nucleoplasm. To further understand the function and mechanism of cold-warm stimuli, we conducted forward genetic screening and identified ZTF-7, which is required for RNA exosome depletion from nucleoli upon transient cold-warm exposure in C. elegans. ZTF-7 is a putative ortholog of human ZNF277 that may contribute to language impairments. Immunoprecipitation followed by mass spectrometry (IP-MS) found that ZTF-7 interacted with RPS-2, which is a ribosomal protein of the small subunit and participates in pre-rRNA processing. A partial depletion of RPS-2 and other proteins of the small ribosomal subunit blocked the cold-warm stimuli-induced reduction of exosome subunits from the nucleoli. These results established a novel mechanism by which C. elegans responds to environmental cold-warm exposure.

Quantifying canopy light interception provides insight into the effects of plant spacing, canopy structure, and leaf orientation on radiation distribution. This is essential for increasing crop yield and improving product quality. Canopy light interception can be quantified using 3-dimensional (3D) plant models and optical simulations. However, virtual 3D canopy models (VCMs) have often been used to quantify canopy light interception because realistic 3D canopy models (RCMs) are difficult to obtain in the field. This study aims to compare the differences in light interception between VCMs and RCM. A realistic 3D maize canopy model (RCM) was reconstructed over a large area of the field using an advanced unmanned aerial vehicle cross-circling oblique (CCO) route and the structure from motion-multi-view stereo method. Three types of VCMs (VCM-1, VCM-4, and VCM-8) were then created by replicating 1, 4, and 8 individual realistic plants constructed by CCO in the center of the corresponding RCM. The daily light interception per unit area (DLI), as computed for the 3 VCMs, exhibited marked deviation from the RCM, as evinced by the relative root mean square error (rRMSE) values of 20.22%, 17.38%, and 15.48%, respectively. Although this difference decreased as the number of plants used to replicate the virtual canopy increased, rRMSE of DLI for VCM-8 and RCM still reached 15.48%. It was also found that the difference in light interception between RCMs and VCMs was substantially smaller in the early stage (48 days after sowing [DAS]) than in the late stage (70 DAS). This study highlights the importance of using RCM when calculating light interception in the field, especially in the later growth stages of plants.

The non-uniform growth and development of crops within Chinese Solar Greenhouses (CSG) is directly related to the micro-light climate within canopy. In practice, reflective films are used to improve micro-light climate within plant canopy by homogenizing light distribution and so increasing total plant light interception. However, as to our knowledge, the contributions to light distribution within canopy have not been investigated for passive reflector like reflective films. Field experiments dealing with light conditions and growth behavior over time, are complicated to carry out, time-consuming and hard to control, while however, accurate measurements of how reflective films influence the micro-light climate of canopy are an essential step to improve the growth conditions for any crop. Here, we propose a supplementary light strategy using reflective films to improve light distribution within plant canopy. Based on the example of CSG, a 3D greenhouse model including a detailed 3D tomato canopy structure was constructed to simulate the influence of supplementary reflective films to improve micro-light climate. Comparison of measured solar radiation intensity with predicted model data demonstrated that the model could precisely predict light radiation intensity over time with different time points and positions in the greenhouse. A series of reflective film configurations were investigated based on features analysis of light distribution in the tomato canopy on sunny days using the proposed model. The reflective film configuration scheme with the highest impact significantly improved the evenness of horizontal and vertical light distribution in tomato canopy. The strategy provided here can be used to configure reflective films that will enhance light conditions in CSG, which can be applied and extended in different scenarios.

The depth control problem of autonomous underwater vehicle (AUV) by using deep reinforcement learning method was mainly studied.Different from the traditional control algorithm, the deep reinforcement learning method allows the AUV to learn the control law independently, avoiding the artificial establishment of accurate model and design control law.The deep deterministic policy gradient method was used to design two neural networks: actor and critic.Actor neural network enabled agents to make corresponding control actions.Critic neural network was used to estimate the action-value function in reinforcement learning.The AUV depth control was conducted by training of actor and critic neural networks.The effectiveness of the algorithm was proved by simulation on OpenAI Gym.

Abstract Background Extra-pelvic intravenous leiomyomatosis (IVL) extending into inferior vena cava (IVC) or heart (i.e. intracardiac leiomyomatosis, ICL) is an extremely rare benign disease. No consensus has been reached on the optimal surgical strategy. The aim of this study is to introduce four types of one-stage surgical strategies including less invasive options and a guideline to select patient-specific strategy for this disease. Methods Twenty-four patients of extra-pelvic IVLs receiving one-stage resections at the Zhongshan Hospital from July 2011 to November 2019 were reviewed retrospectively. Base on the initial experiences of the indiscriminate choices of tumor thrombectomies through sterno-laparotomy under cardiopulmonary bypass (CPB) in 6 ICLs, an anatomy-based guideline for four types of surgical strategies was developed and applied for the next 18 patients. Results Under the direction of guideline, tumor thrombectomies through single laparotomy were applied without CPB in 2 ICLs and 4 IVLs confined in IVC, or with CPB in 7 ICLs. Guideline-directed double-incisions with CPB were applied in only 5 ICLs, including 1 receiving mini-thoracotomy and 4 receiving sternotomy because of tumor adherences with right atriums in 2 and with pulmonary arteries in 2. All 24 patients accomplished one-stage panhysterectomy, bilateral adnexectomy and complete resections of intracaval and intracardiac tumors. For residual pelvic intravenous tumors in 19 patients, 17 received macroscopically complete resections while the other 2 failed because of high risk of hemorrhage. Intraoperative blood losses, operation time and hospitalization expense in the single-laparotomy non-CPB group were significantly lesser than the other groups. In CPB groups, inpatient stay and hospitalization expense in the single-incision group were significantly lesser than the double-incisions group. All patients were alive and free of recurrences during a mean follow-up of 35.4 ± 27.2 months (range, 1–100 months). The pelvic tumor residues in 2 patients remained unchanged for 51 and 52 months since operation, respectively. Conclusions For various extra-pelvic IVLs, the 4 types of surgical strategies including less invasive options are feasible, providing these are selected by a guideline base on the tumor extension and morphology. The proposed guideline is believed to accommodate more patients receiving less invasive surgery without compromising the curative effect.

Determine the level of significance of planting strategy and plant architecture and how they affect plant physiology and dry matter accumulation within greenhouses is essential to actual greenhouse plant management and breeding. We thus analyzed four planting strategies (plant spacing, furrow distance, row orientation, planting pattern) and eight different plant architectural traits (internode length, leaf azimuth angle, leaf elevation angle, leaf length, leaflet curve, leaflet elevation, leaflet number/area ratio, leaflet length/width ratio) with the same plant leaf area using a formerly developed functional–structural model for a Chinese Liaoshen-solar greenhouse and tomato plant, which used to simulate the plant physiology of light interception, temperature, stomatal conductance, photosynthesis, and dry matter. Our study led to the conclusion that the planting strategies have a more significant impact overall on plant radiation, temperature, photosynthesis, and dry matter compared to plant architecture changes. According to our findings, increasing the plant spacing will have the most significant impact to increase light interception. E–W orientation has better total light interception but yet weaker light uniformity. Changes in planting patterns have limited influence on the overall canopy physiology. Increasing the plant leaflet area by leaflet N/A ratio from what we could observe for a rose the total dry matter by 6.6%, which is significantly better than all the other plant architecture traits. An ideal tomato plant architecture which combined all the above optimal architectural traits was also designed to provide guidance on phenotypic traits selection of breeding process. The combined analysis approach described herein established the causal relationship between investigated traits, which could directly apply to provide management and breeding insights on other plant species with different solar greenhouse structures.

In order to further improve the utilization of solar energy in Chinese Solar Greenhouse (CSG), this paper systematically studied the effects of orientation and structure on solar radiation interception in CSG. A solar radiation model has been developed based on the previous research, which taking solar motion law, meteorological data, and optical properties of materials into consideration. The established model was used to optimize the orientation and structure of CSG. The analysis of structure considered two major structural parameters, which are the ridge height and the horizontal projection of the rear roof. Moreover, the widely used Liao-Shen type Chinese solar greenhouse (CSG-LS) has been taken as the prototype in the present research, and the measured data of the typical clear day was used for the model validation. The results showed that the ridge height has a remarkable influence on the solar energy captured by CSG-LS. Compared with the optimization of a single factor, the comprehensive optimization of orientation and structure can increase the solar radiation interception of the rear wall by 3.95%. Considering the limiting factor of heat storage-release capacity and the shading effect on the greenhouse structure, the optimal lighting construction of the CSG-LS (with a span of 9.0 m) was specified as 7~9° from south to west of azimuth angle, 4.5~4.7 m ridge height, and 1.4~1.6 m horizontal projection of the rear roof at 42°N latitude. The proposed solar radiation model can provide scientific guidance for the CSG-LS construction in different areas.

With the continuous use of resources, solar energy is expected to be the most used sustainable energy. To improve the solar energy efficiency in Chinese Solar Greenhouses (CSG), the effect of CSG orientation on intercepted solar radiation was systematically studied. By using a 3D CSG model and a detailed crop canopy model, the light environment within CSG was optimized. Taking the most widely used Liao-Shen type Chinese solar greenhouse (CSG-LS) as the prototype, the simulation was fully verified. The intercepted solar radiation of the maintenance structures and crops was used as the evaluation index. The results showed that the highest amount of solar radiation intercepted by the maintenance structures occurred in the CSG orientations of 4–6° south to west (S-W) in 36.8° N and 38° N areas, 8–10° S-W in 41.8° N areas, and 2–4° south to east (S-E) in 43.6° N areas. The solar radiation intercepted by the crop canopy displayed the highest value at an orientation of 2–4° S-W in 36.8° N, 38° N, 43.6° N areas, and 4–6° S-W in the 41.8° N area. Furthermore, the proposed model could provide scientific guidance for greenhouse crop modelling.

A continuous control set model predictive power control strategy for an indirect matrix converter is proposed in this paper. The load reactive power, the load active power, and the input reactive power are controlled simultaneously. This control strategy can obtain output waveforms with fixed switching frequency. Additionally, an optimal switching sequence is proposed to simplify the commutations of the indirect matrix converter. To suppress the input filter resonance, an active damping method is proposed. Experimental results prove that the proposed method features controllable input reactive power, controllable load active and reactive power, fixed switching frequency output waveforms, zero-current switching operations, and effectively suppresses input filter resonance.

This paper proposes a vector modulation-based model predictive current control strategy for a two-stage matrix converter. The switching frequency is kept constant by fixing the switching instantly. The control scheme controls the source reactive power on the input side and output currents on the output side. Besides, the advantage of the proposed strategy compared with conventional model predictive control is firstly proved using the principle of vector synthesis and the law of sines in the vector distribution area. Moreover, to ensure zero-current switching operations and reduce the switching losses, an optimal switching sequence is proposed and implemented. Furthermore, considering that the input filter resonance is easier to be inspired by the model predictive control, compared with conventional linear control strategies, an innovative active damping technique is proposed to suppress the input filter resonance. To assess the performance of the proposed method, simulation and experimental results are demonstrated, showing that the control system features both good steady-state and transient performance.

This paper proposes a novel model predictive current control scheme for two-stage matrix converter. The switching frequency is kept constant by fixing the switching instant. The control strategy achieves to control source reactive power in the input side and output currents in the output side. In addition, the advantage of the proposed strategy compared with conventional model predictive control is firstly proved using the principle of vector synthesis and the law of sines in the vector distribution area. Moreover, a zero-current switching sequence is proposed and implemented to insure zero-current switching operations and reduce the switching losses. Furthermore, in order to suppress the input filter resonance, which is easier to be inspired by the model predictive control, compared with traditional control strategies, an innovative active damping technique is proposed and implemented. Finally, both simulation and experiment are implemented to verify the performance of the proposed strategy. The results demonstrate that the control system features both good steady and transient performance.

Despite the substantial efforts to elucidate the role of early brain injury in subarachnoid hemorrhage (SAH), an effective pharmaceutical therapy for patients with SAH continues to be unavailable. This study aims to reveal the role of necroptosis after SAH, and explore whether the disruption of the blood–brain barrier (BBB) and RIP3-mediated necroptosis following SAH in a rat SAH model are altered by necrostatin-1 via its selective inhibition of receptor-interacting protein kinase 1 (RIP1). Sixty-five rats were used in the experiments. The SAH model was established using endovascular perforation. Necrostatin-1 was intracerebroventricularly injected 1 h before SAH induction. The neuroprotective effects of necrostatin-1 were evaluated with multiple methods such as magnetic resonance imaging (MRI) scanning, immunohistochemistry, propidium iodide (PI) labeling, and western blotting. Pretreatment with necrostatin-1 attenuated brain swelling and reduced the lesion volume on T2 sequence and ventricular volume on MRI 72 h after SAH induction. Albumin leakage and the degradation of tight junction proteins were also ameliorated by necrostatin-1 administration. In addition, necrostatin-1 decreased the number of PI-positive cells in the basal cortex, reduced the levels of the RIP3 and MLKL proteins, and inhibited the production of the pro-inflammatory cytokines IL-1β, IL-6, and TNF-α. Based on the findings from the present study, the selective RIP1 inhibitor necrostatin-1 functioned as a neuroprotective agent after SAH by attenuating brain swelling and BBB disruption. Moreover, the necrostatin-1 pretreatment prevented SAH-induced necroptosis by suppressing the activity of the RIP3/MLKL signaling pathway. These results will provide insights into new drugs and pharmacological targets to manage SAH, which are worth further study.

Summary: piRNAs play significant roles in suppressing transposons and nonself nucleic acids, maintaining genome integrity, and defending against viral infections. In C. elegans, piRNA precursors are transcribed in the nucleus and are subjected to a number of processing and maturation steps. The biogenesis of piRNAs is not fully understood. We use functional proteomics in C. elegans and identify a piRNA biogenesis and chromosome segregation (PICS) complex. The PICS complex contains TOFU-6, PID-1, PICS-1, TOST-1, and ERH-2, which exhibit dynamic localization among different subcellular compartments. In the germlines, the PICS complex contains TOFU-6/PICS-1/ERH-2/PID-1, is largely concentrated at the perinuclear granule zone, and engages in piRNA processing. During embryogenesis, the TOFU-6/PICS-1/ERH-2/TOST-1 complex accumulates in the nucleus and plays essential roles in chromosome segregation. The functions of these factors in mediating chromosome segregation are independent of piRNA production. We speculate that differential compositions of PICS factors may help cells coordinate distinct cellular processes. : Zeng et al. use functional proteomics and identify a PICS complex that promotes Piwi-interacting RNA (piRNA) production in C. elegans. This work reports that the PICS complex acts in the 5′ end processing of piRNA precursors. This PICS complex also shuttles between the nucleus and cytoplasm and promotes chromosome segregation in embryos. Keywords: piRNA, TOFU-6, PID-1, TOST-1, PICS-1, ERH-2, chromosome segregation, perinuclear granule

This article deals with fault isolation issue for the redundant thrusters of frame-structure unmanned underwater vehicles (UUVs). Consistency check is adopted to accomplish this task while solving the reformed control input equations that are produced after getting rid of some fault-free terms from the given equations. Specially selected column vectors from the given control matrix together with the corresponding hypothetical thrust output faults are taken as the known/unknown elements for these equations. Redundant relations among the thrusters support the vector selection, which are revealed by analyzing the maximally linearly independent vectors of the given control matrix. Simulation with faulty thrusters under redundancy in a frame-structure unmanned underwater vehicle illustrates the effectiveness of the proposed methodologies.

Motion planning is a crucial, basic issue in robotics, which aims at driving vehicles or robots towards to a given destination with various constraints, such as obstacles and limited resource. This paper presents a new version of rapidly exploring random trees (RRT), that is, liveness-based RRT (Li-RRT), to address autonomous underwater vehicles (AUVs) motion problem. Different from typical RRT, we define an index of each node in the random searching tree, called “liveness” in this paper, to describe the potential effectiveness during the expanding process. We show that Li-RRT is provably probabilistic completeness as original RRT. In addition, the expected time of returning a valid path with Li-RRT is obviously reduced. To verify the efficiency of our algorithm, numerical experiments are carried out in this paper.

Cooperative localization (CL) is considered a promising method for underwater localization with respect to multiple autonomous underwater vehicles (multi-AUVs). In this paper, we proposed a CL algorithm based on information entropy theory and the probability hypothesis density (PHD) filter, aiming to enhance the global localization accuracy of the follower. In the proposed framework, the follower carries lower cost navigation systems, whereas the leaders carry better ones. Meanwhile, the leaders acquire the followers’ observations, including both measurements and clutter. Then, the PHD filters are utilized on the leaders and the results are communicated to the followers. The followers then perform weighted summation based on all received messages and obtain a final positioning result. Based on the information entropy theory and the PHD filter, the follower is able to acquire a precise knowledge of its position.

Online path planning (OPP) for unmanned aerial vehicles (UAVs) is a basic issue of intelligent flight and is indeed a dynamic multi-objective optimization problem (DMOP). In this paper, an OPP framework is proposed in the sense of model predictive control (MPC) to continuously update the environmental information for the planner. For solving the DMOP involved in the MPC we propose a dynamic multi-objective evolutionary algorithm based on linkage and prediction (LP-DMOEA). Within this algorithm, the historical Pareto sets are collected and analysed to enhance the performance. For intelligently selecting the best path from the output of the OPP, the Bayesian network and fuzzy logic are used to quantify the bias to each optimization objective. The DMOEA is validated on three benchmark problems characterized by different changing types in decision and objective spaces. Moreover, the simulation results show that the LP-DMOEA overcomes the restart method for OPP. The decision-making method for solution selection can assess the situation in an adversarial environment and accordingly adapt the path planner.

The occurrence and development of tumors are closely associated with abnormalities in the immune system's structure and function, with tumor immunotherapy being intricately linked to the tumor microenvironment (TME). Early studies on lymphocytes within the TME primarily concentrated on T cells. However, as research has advanced, the multifaceted roles of tumor-infiltrating B cells (TIL-Bs) in tumor immunity, encompassing both anti-tumor and pro-tumor effects, have garnered increasing attention. This paper explored the composition of the TME and the biological characteristics of TIL-Bs, investigating the dual roles within the TME to offer new insights and strategies for tumor immunotherapy.