Explore the vast range of titles available.

Self-balancing robots, with their compact size, are capable of achieving high agility. Small wheel-legged self-balancing robots have demonstrated significant potential across various applications. However, expanding small self-balancing robots to larger sizes to serve as personal transport tools is a more attractive and impactful direction than further miniaturization or confinement to niche laboratory demonstrations. This paper presents the development of a small self-balancing robot, which is then scaled up to a larger version designed to carry human passengers as a self-balancing wheelchair. A unified control framework, built around a shared core of online model-updating LQR for balance and PD for steering, is applied to both robots. This core is supplemented with platform-specific modules, such as a dedicated leg controller for the wheel-legged robot, to handle distinct dynamic maneuvers. The LQR controller is implemented for balance control in both robots. Additionally, a dedicated leg controller is applied exclusively to the small wheel-legged robot to enable dynamic maneuvers, such as jumping. A series of experiments conducted with the final prototypes validate the effectiveness of the control systems and highlight the robots’ application potential.

Background We have proved fecal microbiota transplantation (FMT) is an efficacious remedy to mitigate acute radiation syndrome (ARS); however, the mechanisms remain incompletely characterized. Here, we aimed to tease apart the gut microbiota-produced metabolites, underpin the therapeutic effects of FMT to radiation injuries, and elucidate the underlying molecular mechanisms. Results FMT elevated the level of microbial-derived indole 3-propionic acid (IPA) in fecal pellets from irradiated mice. IPA replenishment via oral route attenuated hematopoietic system and gastrointestinal (GI) tract injuries intertwined with radiation exposure without precipitating tumor growth in male and female mice. Specifically, IPA-treated mice represented a lower system inflammatory level, recuperative hematogenic organs, catabatic myelosuppression, improved GI function, and epithelial integrity following irradiation. 16S rRNA gene sequencing and subsequent analyses showed that irradiated mice harbored a disordered enteric bacterial pattern, which was preserved after IPA administration. Notably, iTRAQ analysis presented that IPA replenishment retained radiation-reprogrammed protein expression profile in the small intestine. Importantly, shRNA interference and hydrodynamic-based gene delivery assays further validated that pregnane X receptor (PXR)/acyl-CoA-binding protein (ACBP) signaling played pivotal roles in IPA-favored radioprotection in vitro and in vivo. Conclusions These evidences highlight that IPA is a key intestinal microbiota metabolite corroborating the therapeutic effects of FMT to radiation toxicity. Owing to the potential pitfalls of FMT, IPA might be employed as a safe and effective succedaneum to fight against accidental or iatrogenic ionizing ARS in clinical settings. Our findings also provide a novel insight into microbiome-based remedies toward radioactive diseases. 5xbhwSC1V4FsDQpg8AwjrS Video abstract.

Background The global prevalence of autoimmune hepatitis (AIH) is increasing due in part to the lack of effective pharmacotherapies. Growing evidence suggests that fibroblast growth factor 4 (FGF4) is crucial for diverse aspects of liver pathophysiology. However, its role in AIH remains unknown. Therefore, we investigated whether FGF4 can regulate M1 macrophage and thereby help treat liver inflammation in AIH. Methods We obtained transcriptome-sequencing and clinical data for patients with AIH. Mice were injected with concanavalin A to induce experimental autoimmune hepatitis (EAH). The mechanism of action of FGF4 was examined using macrophage cell lines and bone marrow-derived macrophages. Results We observed higher expression of markers associated with M1 and M2 macrophages in patients with AIH than that in individuals without AIH. EAH mice showed greater M1-macrophage polarization than control mice. The expression of M1-macrophage markers correlated positively with FGF4 expression. The loss of hepatic Fgf4 aggravated hepatic inflammation by increasing the abundance of M1 macrophages. In contrast, the pharmacological administration of FGF4 mitigated hepatic inflammation by reducing M1-macrophage levels. The efficacy of FGF4 treatment was compromised following the in vivo clearance of macrophage populations. Mechanistically, FGF4 treatment activated the phosphatidylinositol 3-kinase (PI3K)–protein kinase B (AKT)-signal pathway in macrophages, which led to reduced M1 macrophages and hepatic inflammation. Conclusion We identified FGF4 as a novel M1/M2 macrophage-phenotype regulator that acts through the PI3K–AKT-signaling pathway, suggesting that FGF4 may represent a novel target for treating inflammation in patients with AIH.

Background The Forkhead box M1 factor (FOXM1) is a crucial activator for cancer cell proliferation. While FOXM1 has been shown to promote hepatocellular carcinoma (HCC) progression, its transcriptional mechanisms remain incompletely understood. Methods We performed an in-house tissue microarray on 313 HCC and 37 non-HCC tissue samples, followed by immunohistochemical staining. Gene chips and high throughput sequencing data were used to assess FOXM1 expression and prognosis. To identify candidate targets of FOXM1, we comprehensively reanalyzed 41 chromatin immunoprecipitation followed by sequencing (ChIP-seq) data sets. We predicted FOXM1 transcriptional targets in HCC by intersecting candidate FOXM1 targets with HCC overexpressed genes and FOXM1 correlation genes. Enrichment analysis was employed to address the potential mechanisms of FOXM1 underlying HCC. Finally, single-cell RNA sequencing analysis was performed to confirm the transcriptional activity of FOXM1 on its predicted targets. Results This study, based on 4235 HCC tissue samples and 3461 non-HCC tissue samples, confirmed the upregulation of FOXM1 in HCC at mRNA and protein levels (standardized mean difference = 1.70 [1.42, 1.98]), making it the largest multi-centered study to do so. Among HCC patients, FOXM1 was increased in Asian and advanced subgroups, and high expression of FOXM1 had a strong ability to differentiate HCC tissue from non-HCC tissue (area under the curve = 0.94, sensitivity = 88.72%, specificity = 87.24%). FOXM1 was also shown to be an independent exposure risk factor for HCC, with a pooled hazard ratio of 2.00 [1.77, 2.26]. The predicted transcriptional targets of FOXM1 in HCC were predominantly enriched in nuclear division, chromosomal region, and catalytic activity acting on DNA. A gene cluster encoding nine transcriptional factors was predicted to be positively regulated by FOXM1, promoting the cell cycle signaling pathway in HCC. Finally, the transcriptional activity of FOXM1 and its targets was supported by single-cell analysis of HCC cells. Conclusions This study not only confirmed the upregulation of FOXM1 in HCC but also identified it as an independent risk factor. Moreover, our findings enriched our understanding of the complex transcriptional mechanisms underlying HCC pathogenesis, with FOXM1 potentially promoting HCC progression by activating other transcription factors within the cell cycle pathway.

The existence of clearance in the joint causes positional deviation and reduces the accuracy of robotics, in which nonlinear factors such as friction and lubrication inside the joint seriously affect its dynamic behaviors. On the other hand, the effectiveness of control algorithms is largely dependent on the dynamic complexity of the robotics, while its complexity analysis is an important prerequisite for achieving high-performance control. In this paper, we provide a method for analyzing the dynamic complexity of a planar manipulator with clearance and lubrication in joints based on a nonlinearity measure. The influences of joint parameters such as friction coefficient, lubricant viscosity, and gap radius are quantified on the dynamic complexity of the kinetics, which can identify the collision state of the joints effectively in the robot’s motion. First, a dynamical model of a planar manipulator is established by integrating the contact-separation model and the force model at the joint, and a method for calculating the dynamic complexity based on the nonlinearity measure is proposed. Second, the effects of different joint parameters on the dynamic behaviors of the robotic system are analyzed, and the relationships between the lubricant viscosity, gap radius, and the dynamic complexity under different friction coefficients are established to analyze the impacts of the joint parameters on the dynamic complexities. The results show that the dynamic complexity of the robotic system can be decreased significantly by using the small gap radius and high viscosity of the lubricant, which can help to realize the better control performance. Especially, this method is more sensitive to state changes such as the collision state of the joint relative to the sample entropy method.

Real‐time monitoring and accurate prediction of photovoltaic (PV) power generation operation parameters are essential to ensure stable operation. In this paper, a set of online PV power generation parameter measurement and monitoring devices characterized by simple structure, high sampling accuracy, small data fluctuations, and ease of measurement, are designed. Sensors based on the zero‐flux principle are employed in the real‐time collection of the output electrical signals in the process of PV power generation, realizing the accurate collection of electric parameter signals. Next, the basic structure and working principle of PV cells are analyzed, a mathematical model of PV cells for engineering purposes is established, a wavelet neural network is selected to predict the short‐term PV power generation, and particle swarm optimization and adding momentum are used to optimize the weight of wavelet neural network (WNN) as well as the parameters of the wavelet basis function. Finally, the historical power generation data and meteorological data of the power station are taken as the training samples to train and simulate the prediction sub‐models of different weather types to verify the effectiveness and accuracy of the PV power generation short‐term prediction model for optimizing the WNN based on the particle swarm optimization algorithm. The research results of this paper can realize real‐time monitoring of the output parameters and accurate prediction and evaluation of power generation during the operation of the PV‐power‐generation system. This paper concentrates on the short term prediction of photovoltaic (PV) power generation, the wavelet neural network (WNN) prediction algorithm was used to conduct short‐term prediction of PV‐power generation, and the particle swarm optimization (PSO) was used to optimize the learning rate and weight of WNN. The results showed that the PSO‐WNN‐based prediction model was found to be more effective for the short‐term prediction of PV power generation, and the predicted values were closer to the actual power generation data.

To investigate the influence of thermal effects on the hydrogen desorption performance of the metal hydride hydrogen storage system, a two-dimensional numerical model was established based on a small metal hydride hydrogen storage tank, and its accuracy was verified by the temperature variations in the reaction zone of the hydrogen storage tank during hydrogen desorption. In addition, the influence of the heat transfer medium on the heat and mass transfer performance of the hydrogen desorption reaction was analyzed. An external heat transfer bath was added to simulate the thermal effect of the model during the hydrogen desorption reaction. The temperature and type of heat transfer medium in the heat transfer bath were modified, and the temperature and reaction fraction variations in each zone of the hydrogen storage model were analyzed. The results showed that under heat transfer water flow, the reaction rate in the center region of the hydrogen storage tank was gradually lower than that in the wall region. The higher the temperature of water flow, the shorter the total time required for the hydrogen desorption reaction and the shortening amplitude is reduced. The variations in the temperature and hydrogen storage capacity during hydrogen desorption were similar, with water and oil as the heat transfer medium, under the same flow rate and heat transfer temperature, however, the heat transfer time and hydrogen desorption time of water were about 10% and 5% shorter than that of oil, respectively. When the air was used as the heat transfer medium, the heat transfer rate of the air convection in the channel was lower than the heat transfer rate of the tank wall, reducing the temperature difference between the air and alloy on both sides of the wall, decreasing heat transfer efficiency, and significantly prolonging the time required for hydrogen desorption.

Methods based on vibration analysis are currently regarded as the most conclusive means for fault diagnosis and health prognostics in rotary machinery. However, changing working conditions mean that the vibration signals originating from rotary machinery exhibit different levels of complexity. This complexity leads to increased difficulty in constructing health indicators (HIs). In this paper, we propose a multiscale Tsallis permutation entropy (MTPE) to construct the HIs of rotary machinery under different working conditions. MTPE values are a function of an entropy index and scale, which have the universality for handling the complexity of a permutated time series. The health condition of the rotary machinery was effectively represented by the MTPEs in conditional monitoring; the initial point of the unhealthy stage was found using the 3σ interval. This was set as the alarm threshold according to the varying HI trend. Once this was established, dividing the stages into two-stage health stages (HS) was straightforward. Using a rolling bearing, a run-to-failure experiment was conducted and results suggested that the proposed method effectively assessed the status of the rotary machinery. Taken together, this study provided a novel complexity measure based on a methodology for constructing the HIs of rotary machinery and enriches conditional monitoring theory.

Accidental or iatrogenic ionizing radiation exposure precipitates acute and chronic radiation injuries. The traditional paradigm of mitigating radiotherapy‐associated adverse side effects has ignored the gender‐specific dimorphism of patients' divergent responses. Here, the effects of sexual dimorphism on curative efficiencies of therapeutic agents is examined in murine models of irradiation injury. Oral gavage of simvastatin ameliorates radiation‐induced hematopoietic injury and gastrointestinal tract dysfunction in male mice, but adversely deteriorates these radiation syndromes in female animals. In a sharp contrast, feeding animals with high‐fat diet (HFD) elicites explicitly contrary results. High‐throughput sequencing of microbial 16S rRNA, host miRNA, and mRNA shows that simvastatin or HFD administration preventes radiation‐altered enteric bacterial taxonomic structure, preserves miRNA expression profile, and reprogrammes the spectrum of mRNA expression in small intestines of male or female mice, respectively. Notably, faecal microbiota transplantation of gut microbes from opposite sexual donors abrogates the curative effects of simvastatin or HFD in respective genders of animals. Together, these findings demonstrate that curative efficiencies of therapeutic strategies mitigating radiation toxicity might be dependent on the gender of patients, thus simvastatin or HFD might be specifically useful for fighting against radiation toxicity in a sex‐dependent fashion partly based on sex‐distinct gut microbiota composition in preclinical settings. Traditional remedies for radiotherapy‐intertwined adverse side effects ignore the sex‐specific dimorphism of patients' divergent responses. Individuals of different sexes represent variant performances following a same therapeutic regimen. In the present study, simvastatin or high fat diet is developed to specifically protect against radiation toxicity of males or females partly based on sex‐distinct gut microbiota structure.

In this article, the improvements on vibration isolation performance of hydraulic excavators are achieved via the optimization of powertrain mounting system. The powertrain is viewed as a rigid body and described by a 6-degree-of-freedom model. The rigid-flexible coupling model of hydraulic excavators is carried out based on software ADAMS, in which the influences from the mass and elastic deformation of base are considered. In the process of optimization for the powertrain mounting system, energy decoupling rate and vibration transmissibility are set to be the objective functions, while the stiffness coefficients in three directions of the mounting coordinate systems are chosen as the designed variables. With the given constrained conditions of these variables, nondominated sorting genetic algorithm II is employed to optimize the stiffness coefficients of suspension elements. The simulations for the rigid-flexible coupling model with the optimized mounting system show that the vibration isolation performances of hydraulic excavators are improved comparing with that with non-optimized powertrain mounting system.