Drawing inspiration from the self-regulating carbon–nitrogen cycling of saline ecosystems, this study investigates how substrate flux and biomass density co-regulate the structure and function of marine sediment-derived halophilic heterotrophic ammonia assimilation (HAA) microbiome cultivated in saline ammonia-containing wastewater with a COD/N radio of 20 under volumetric exchange ratios (VER) of 75 %, 50 %, and 25 % and mixed liquor suspended solids (MLSS) increasing from 5 to 15 g/L. The combined variation in VER and MLSS generated a gradient in food-to-microorganism radio (F/M). With increasing in biomass, COD removal efficiencies peaked at 94.4–99.3 % at 15 g MLSS/L, whereas ammonia removal efficiencies reached at 90.3–96.8 % at 12.5 g MLSS/L before declining. A VER of 25 % reduced sludge activity, while a VER of 75 % impaired floc settleability. The directed HAA community shifted in substrate flux and biomass density, centering on dominant genera such as Halomonas and Marinobacter, ultimately forming a stable microbiome.

Microbially induced carbonate precipitation (MICP) presents a promising strategy for the softening and purification of produced water. However, produced water from heavy oil reservoirs exhibits high salinity, refractory organics, particularly with hardness ions such as Ca²⁺ and Mg²⁺, all of which substantially inhibit microbial mineralization activity. Industrially viable continuous-flow operational strategies remain underdeveloped, and the underlying biomineralization mechanisms are not yet fully elucidated. Here, we report the successful construction of an engineering microbiome through substrate gradient acclimation, achieving continuous and stable precipitation of Ca²⁺ (87.28 %) and Mg²⁺ (84.16 %). The process also revealed the sequential transformation of organic functional groups under high salinity perturbation. Hydroxyl groups (−OH) in extracellular polymeric substances preferentially bound divalent cations under neutral conditions, whereas carboxyl groups (−COO⁻) served as nucleation sites for carbonate formation under alkaline conditions. Extracellular carbonate precipitation predominated, while a minor fraction of amorphous magnesium carbonate was accumulated intracellularly. The engineering microbiome, dominated by urease-positive and hydrocarbon-degrading taxa, tolerated extreme salinity and hardness through metabolic complementarity and coordinated gene regulation. These findings demonstrate a robust, continuous-flow MICP process for HPW treatment, offering a foundation for industrial-scale integration with improved stability, efficiency, and microbiome resilience in complex environments.

Collision avoidance is a priority task for ensuring the safety of a maritime transportation system. However, for a ship towing system, which is characterized by multiple vessels and physical connections, the research works about collision avoidance is limited. Thus, this paper proposes a speed and heading control-based conflict resolution of a ship towing system for collision avoidance. Two systems compose the core of the proposed conflict resolution: the risk assessment system and the coordination control system. The risk assessment is to identify the conflict and determine the time of avoiding action by calculating the index of conflict and the available maneuvering margin. The coordination control is based on the model predictive control (MPC) strategy to cooperatively control two tugboats for regulating the position, heading, and speed of the manipulated ship. Simulation experiments show that according to the index of conflict, the time cost, and the fuel consumption, a selected operation of combined heading and speed can be recommended for a ship towing system to provide a safer and more efficient towage manipulation.

This article proposes a fixed-time adaptive fault-tolerant control methodology for a larger class of high-order (powers are positive odd integers) nonlinear systems subject to asymmetric time-varying state constraints and actuator faults. In contrast with the state-of-the-art control methodologies, the distinguishing features of this study lie in that: (a) high-order asymmetric time-varying tan-type barrier Lyapunov function (BLF) is devised such that the state variables can be convergent to the preassigned compact sets all the time provided their initial values remain therein, which not only preserves the constraints satisfaction, but warrants the validity of the adopted neural network approximator; (b) the proposed control design ensures the tracking errors converge to specified residual sets within fixed time and makes the size of the convergence regions of tracking errors adjustable a priori by means of a new BLF-based tuning function and a projection operator; (c) a variable-separable lemma is delicately embedded into the control design to extract the control terms in a “linear-like” fashion which not only overcomes the difficulty that virtual control signals appear in a non-affine manner, but also solves the problem of actuator faults. Comparative simulations results finally validate the effectiveness of the proposed scheme.

High-tech giants and start-ups are investing in drone technologies to provide urban air delivery service, which is expected to solve the last-mile problem and mitigate road traffic congestion. However, air delivery service will not scale up without proper traffic management for drones in dense urban environment. Currently, a range of Concepts of Operations (ConOps) for unmanned aircraft system traffic management (UTM) are being proposed and evaluated by researchers, operators, and regulators. Among these, the tube-based (or corridor-based) ConOps has emerged in operations in some regions of the world for drone deliveries and is expected to continue serving certain scenarios that with dense and complex airspace and requires centralized control in the future. Towards the tube-based ConOps, we develop a route network planning method to design routes (tubes) in a complex urban environment in this paper. In this method, we propose a priority structure to decouple the network planning problem, which is NP-hard, into single-path planning problems. We also introduce a novel space cost function to enable the design of dense and aligned routes in a network. The proposed method is tested on various scenarios and compared with other state-of-the-art methods. Results show that our method can generate near-optimal route networks with significant computational time-savings.

In human activity recognition (HAR) based on radar, significant research exists on statistical features extracted from the spectrogram (μD), whereas the research which considers other domains is less developed. This paper is aimed to investigate three domains of radar data: μD, Cadence Velocity Diagram (CVD), and range-time (RT) information, evaluating which ones are best suited to classify specific activities. In addition, information fusion is applied to enhance classification accuracy and compare it with the results of single domain approach. Based on the previous results, a hierarchical structure is proposed to improve the performance of classification further. The preliminary results show that different domains have distinctive sensitivity to specific activities. RT information is sensitive to the moving target crossing range bins, while CVD is more sensitive to body movement. The μD is more balanced, which means it can observe both moving targets and body movements. Furthermore, improvement in accuracy is approximately 6-23 % using feature-level fusion. A hierarchical classification approach is also investigated, which has accuracy in the order of approximately 92 %.

The functional efficiency of the pervious pavement is evaluated in terms of skid resistance and tire/road noise, which determines the highway safety and comfort benefits to the travellers. The primary objective of this paper is to incorporate the functional performances such as frictional and acoustic characteristics into the pervious pavement design procedures. The existing pervious pavement design procedures assume that the functional requirement is satisfied arbitrarily with the volumetric and composition requirement. This paper formulates the functional design of porous mixture as the bi-objective optimization model, which maximizes the skid number and minimizes the tire/road noise level, both were obtained from the numerical simulation models. A fast nondominated sorting genetic algorithm (NSGA II) was adopted as the solution algorithm to solve the optimization model. Pareto solutions from this model indicate that the performance of skid resistance could not be improved without increasing the tire/road noise. The optimum solutions for this model were selected as the appropriate trade-off between both the parameters. This model allows a highway agency for the incorporation of frictional and acoustic parameters into the existing pervious pavement mixture and thickness design procedures.