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Microbes in nature often live in dense and diverse communities exhibiting a variety of spatial structures. Microbial range expansion is a universal ecological process that enables populations to form spatial patterns. It can be driven by both passive and active processes, for example, mechanical forces from cell growth and bacterial motility. In this review, we provide a taste of recent creative and sophisticated efforts being made to address basic questions in spatial ecology and pattern formation during range expansion. We especially highlight the role of motility to shape community structures, and discuss the research challenges and future directions. [ABSTRACT FROM AUTHOR]

Active braking control systems in high-speed trains are vital to ensure safety and are intended to reduce brake distances and prevent the wheels from locking. The slip ratio, which represents the relative difference between the wheel speed and vehicle velocity, is crucial to the design and successful implementation of active braking control systems. Slip ratio estimation and active braking control are challenging owing to the uncertainties of wheel–rail adhesion and system nonlinearities. Therefore, this paper proposes a novel adaptive slip ratio estimation approach for the active braking control based on an improved extended state observer. The extended state observer is developed through the augmentation of the system state-space to estimate the unmeasured train states as well as the model uncertainty. The accurate slip ratio is estimated using the observed extended states. Furthermore, the adaptability of the observer is improved by introducing the beetle antennae search algorithm to determine the optimal observer parameters. Finally, a feedback linearization braking control law is established to stabilize the closed-loop system due to its potential in coping with nonlinearities, which benefits the proven theoretical bounded stability. Experimental results validate the effectiveness of the proposed method. • An active braking control method based on an improved extended state observer is proposed for high-speed trains. • The designed observer is utilized to estimate both the slip ratio and train adhesion. • The adaptability of the extended state observer is improved by introducing the beetle antennae search algorithm to optimize its parameters. • A feedback linearization braking control law is established to counteract the system nonlinearity and uncertainty. [ABSTRACT FROM AUTHOR]

Dyes pose significant risks for aquatic environments and biological health in general owing to their non-biodegradable nature, carcinogenicity, and toxicity. The effective treatment of dye wastewater has become an important research topic. In this study, acrylic polymers (AP) loaded with magnetic iron manganese oxides (MIMO) (AP/MIMO) were prepared and used for the first time for the adsorption of methylene blue (MB). Carbon in AP/MIMO exists predominantly in the C–H and C–C forms, with its content reaching 50.7%. Oxygen and nitrogen in AP/MIMO exist mainly in the –C O- and -N-C forms, with contents of up to 41.5% and 73.3%, respectively. MB removal by AP/MIMO was consistent with the pseudo-second-order kinetic model (R2 = 0.99), equilibrium was achieved within 20 min, and the highest MB capacity of 2611.23 mg g−1 was predicted by the Langmuir isotherm model (R2 = 0.91–0.94). AP/MIMO exhibited excellent MB adsorption performance in the pH range of 4–10, with a removal efficiency higher than 99.0% (MB = 100 mL 1000 mg L−1; AP/MIMO = 50 mg). Thermodynamic indicators, such as positive entropy (Δ S 0 ; 98.30 J⋅mol−1⋅K−1), negative Gibbs free energy (Δ G 0 ; −29.40, −28.50, and −27.50 KJ⋅mol−1), and positive enthalpy (Δ H 0 ; 2.30 KJ⋅mol−1), demonstrated that MB removal by AP/MIMO was autonomous, favorable, and endothermic. In addition, the integration of experimental results and theoretical calculations verified that electrostatic interactions were the primary mechanism for MB adsorption at carboxyl sites on AP/MIMO. The total interaction energy between AP and MB was −310.43 kJ⋅mol−1, and the electrostatic effect had a decisive contribution to the MB adsorption, with a value of up to −341.06 kJ⋅mol−1. AP and MB were most likely bound by –COO and S atoms. Overall, AP/MIMO exhibits high adsorption capacity and shows potential as a high-performance magnetic polymer for MB removal. [Display omitted] • AP/MIMO were prepared by bulk polymerization combined with chemical precipitation method. • MB removal by AP/MIMO was autonomous, favorable, and endothermic. • The highest MB capacity of 2611.23 mg g−1 was predicted by the Langmuir model. • The electrostatic interaction energy was −341.06 kJ mol−1. • AP and MB were most likely bound by –COO and S atoms. [ABSTRACT FROM AUTHOR]

Battery energy management systems have been studied in control communities for many years. This paper proposes a new perspective by integrating control and scheduling for battery-powered autonomous systems. This is motivated by the observations that battery closed-loop control can significantly improve the DC-bus stability but reduce the battery durability, while load scheduling can considerably improve the battery durability by smoothing the load power. In view of the above findings, we propose a proactive energy management strategy for the battery energy management system to improve both the DC-bus stability and battery durability. We first analyze the schedulability of load tasks to check if they are schedulable. Then, the power of schedulable loads is scheduled with an active load scheduling algorithm to smooth the fluctuation of battery current and extend the battery lifetime. Thereafter, the scheduled load power is integrated with a feedforward control to restrain DC-bus voltage fluctuation. In addition to the classical sporadic/periodic load tasks model, we propose a new aperiodic load task model to characterize the load power triggered by events in practical applications. An experimental platform is built to verify the effectiveness of the proposed proactive energy management method. Experimental results show that the proposed proactive energy management method can suppress the 15.71% DC-bus voltage fluctuation and reduce the 8.93% battery current fluctuation, extending the battery lifetime by 7.57% compared to existing energy management strategies. • A proactive energy management strategy integrated scheduling and control is proposed. • An aperiodic load model is proposed for characterizing events-triggered loads. • An active scheduling method based fixed-priority is proposed to guarantee real-time. • Li-ion battery lifetime and DC-bus voltage regulation are improved. • An experiment platform is built to verify the performance of the proposed method. [ABSTRACT FROM AUTHOR]

Zinc oxide nanoparticles (Nano-ZnO) are widely used in sunscreens, clothes, medicine and electronic devices. However, the potential risks of human exposure and the potential for adverse health impacts are not well understood. Previous studies have demonstrated that exposure to Nano-ZnO caused liver damage and hepatocyte apoptosis through oxidative stress, but the molecular mechanisms that are involved in Nano-ZnO-induced hepatotoxicity are still unclear. Endoplasmic reticulum (ER) is sensitive to oxidative stress, and also plays a crucial role in oxidative stress-induced damage. Previous studies showed that ER stress was involved in many chemical-induced liver injuries. We hypothesized that exposure to Nano-ZnO caused oxidative stress and ER stress that were involved in Nano-ZnO-induced liver injury. To test our hypothesis, mice were gavaged with 200 mg/kg or 400 mg/kg of Nano-ZnO once a day for a period of 90 days, and blood and liver tissues were obtained for study. Our results showed that exposure to Nano-ZnO caused liver injury that was reflected by focal hepatocellular necrosis, congestive dilation of central veins, and significantly increased alanine transaminase (ALT) and aspartate transaminase (AST) levels. Exposure to Nano-ZnO also caused depletion of glutathione (GSH) in the liver tissues. In addition, our electron microscope results showed that ER swelling and ribosomal degranulation were observed in the liver tissues from mice treated with Nano-ZnO. The mRNA expression levels of ER stress-associated genes (grp78, grp94, pdi-3, xbp-1) were also up-regulated in Nano-ZnO-treated mice. Nano-ZnO caused increased phosphorylation of RNA-dependent protein kinase-like ER kinase (PERK) and eukaryotic initiation factor 2α (eIF2α). Finally, we found that exposure to Nano-ZnO caused increased ER stress-associated apoptotic protein levels, such as caspase-3, caspase-9, caspase-12, phosphorylation of JNK, and CHOP/GADD153, and up-regulation of pro-apoptotic genes (chop and bax). These results suggest that oxidative stress and ER stress-induced apoptosis are involved in Nano-ZnO-induced hepatotoxicity in mice. [ABSTRACT FROM AUTHOR]

Gadolinium is a soluble neutron poison for ensuring criticality safety of nuclear facility. A neutron induced gamma activation device was developed for the on-line measurement of gadolinium. The experimental device consisted of an 241Am–Be neutron source, six 3He detectors and a liquid scintillation detector. The size of sample container was optimized by using Monte Carlo simulations. Aqueous sample containing gadolinium nitrate were conducted with the device to obtain the calibration curve, and neutron self-shielding effect was also studied to correct the non-linear response. The results showed the minimum detectable concentration (MDC) of gadolinium was 0.426 mg/L. Two test samples were conducted to evaluate the performance of the device. The results demonstrated that the discrepancies were within 10%, which indicate the developed system can be successfully used for on-line monitoring of gadolinium. • Neutron induced gamma activation technique was applied for the on-line measurement of gadolinium. • An 241Am–Be neutron source, a liquid scintillation detector and six 3He detectors were used to develop the device. • The neutron self-shielding effect was corrected by using Monte Carlo simulations and experimental data. [ABSTRACT FROM AUTHOR]

Encouraged by our previous findings and in continuation of our ongoing study project in designing and synthesis of novel Nur77-targeting anti-cancer agents, a series of 5-((4-(pyridin-3-yl)pyrimidin-2-yl)amino)-1H-indole-2-carboxamide derivatives were designed, synthesized and biologically evaluated as potent Nur77 modulators. Among synthesized compounds, 8b maintained good potency against different liver cancer cell lines and other types of cancer cell lines while exhibiting lower toxicity than the positive compound celastrol. Moreover, 8b displayed excellent Nur77-binding activity, superior to the lead compound 10g and comparable to the reference compound celastrol. The cytotoxic action of 8b towards cancer cells was associated with its induction of Nur77-mitochondrial targeting and Nur77-dependent apoptosis. Notably, 8b has good in vivo safety and anti-hepatocellular carcinoma (HCC) activity. Altogether, this study reveals that 8b is a novel Nur77 modulator with great promise for further research. [Display omitted] • New 5-((4-(pyridin-3-yl)pyrimidin-2-yl)amino)-1H-indole-2-carboxamide derivatives are synthesized. • 8b is a good binder of Nur77 (K D = 354 nM) with broad-spectrum antitumor activity. • 8b induces Nur77-targeting mitochondria and Nur77-dependent apoptosis. • 8b displays a better safety than reference compound celastrol in vitro and in vivo. • 8b effectively inhibits tumor growth in a mice hepatoma HepG2 xenograft model. [ABSTRACT FROM AUTHOR]

Acute lung injury (ALI) is characterized by tissue damage that leads to pulmonary epithelial membrane dysfunction and macrophage activation. Currently however, the exact mechanism by which the initial mediators of mouse lung epithelial (MLE-12) cells induce inflammation remines unclear. We constructed co-culture systems of MLE-12 cells with mouse macrophage cells RAW246.7 which were realized by the supernatant and Transwell chamber. In previous study, we successfully constructed an influenza A virus-induced MLE-12 cells model. Extracellular Vesicles (EVs) from cells supernatant were isolated by differential ultracentrifugation and confirmed by transmission electron microscopy. High-throughput sequencing results showed that MLE-12 cells stimulated by influenza A virus had higher level of miR-1249–5p. The results were validated by RT-qPCR analysis. The research aimed to investigate the roles and mechanisms of miR-1249–5p in ALI. RAW246.7 cells were transfected with miR-1249–5p mimic/inhibitor. The concentrations of TNF-α, IL-6 were determined by ELISA and the uptake of EVs was monitored by confocal laser scanning microscope. Western blotting detected changes in the SLC4A1 and NF-κB signaling pathway. The results indicated that miR-1249–5p played an important role in ALI, and further investigation of its target gene SLC4A1 and NF-κB signaling pathway provides ideas for new therapeutic targets and strategies for ALI. [ABSTRACT FROM AUTHOR]

Lithium-ion batteries have been employed extensively in many important applications in the electronics industry. For safety and reliability, it is extremely critical to get an accurate and early-stage remaining useful life prognostic of lithium-ion batteries. However, battery lifetime predictions are challenging due to the nonlinear battery degradation and the operational diversity among batteries. To increase the prediction accuracy, this paper proposes a hybrid framework combining the model-based method and data-driven method. In this framework, after estimating the battery capacity using online operating data, battery lifetime is predicted by the model-based empirical model as well as the data-driven support vector regression model. For the empirical model, its adaptability is improved by updating the parameters dynamically with particle filters. For the support vector regression model, its performance is optimized by an artificial bee colony algorithm. Finally, a fusion method with cascaded structure is proposed to integrate predictions from these two models, which boosts the prediction accuracy by iteratively exerting two concatenated Kalman filters. The generality and effectiveness of the proposed method are verified on battery data sets provided by NASA and our testing bench, respectively. The experimental results illustrate that the proposed method can improve the prediction accuracy of battery remaining lifetime, especially at the early stage. RMSE and MAE of the proposed hybrid framework are within 4 and 3.5. Compared with two existed hybrid methods, RMSE of prediction can be reduced by at least 7.6%. A reduction of not less than 5.9% in MAE of prediction is achieved. • A hybrid prediction method is proposed to predict RUL at the early stage of batteries. • The proposed method integrates the empirical model and data-driven model through cascaded Kalman filters. • Empirical model is updated by particle filters online to adapt to battery dynamically. • Data-driven model is optimized by artificial bee colony algorithm. [ABSTRACT FROM AUTHOR]

Abstract: The heavy-haul trains consist of a large number of locomotives and wagons which usually cover a very long range of train tracks with different slopes and curvatures. As a consequence, the control design for the heavy-haul trains has posed a significant challenge due to the modeling complexity and the complicated traveling conditions, under which the problems of communication delays and input constraints naturally arise. In this paper, a novel decentralized control design is proposed for the heavy-haul trains by explicitly addressing the issues of input constraints and time-varying communication delays. Specifically, the complicated longitudinal dynamical model of the heavy-haul trains is first converted into a double integrator form by introducing a set of state and input transformations. Then, a decentralized cooperative control is proposed to regulate the speeds of individual train units (locomotives and wagons) to the desired profile with the objective of maintaining the minimum in-train force for safety consideration. It is rigorously proved that the closed-loop system is uniformly asymptotically cooperative stable under the least communication conditions among individual train units. Extensive simulations are conducted to validate the performance of the proposed new design. [Copyright &y& Elsevier]