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Experimental test campaigns have begun to demonstrate the potential of methanol as an alternative fuel for heavy-duty spark-ignited engines. However, there is no consensus yet on the scope of this solution in terms of maximum power and engine size. A zero-dimensional combustion model is therefore being developed outside the scope of this work. Its main objective will be to predict key performance parameters such as power and efficiency as function of engine size. Due to the high loads typically encountered in heavy-duty engines, knock will be the main constraint to maximize the engine's potential. This work therefore aims to find an accurate knock model that can be implemented in the modelling framework. The Livengood–Wu knock integral model is being considered as a good candidate, as it is computationally inexpensive and thus allows for a large number of engine configurations to be modelled within a reasonable time. Due to a lack of autoignition delay times of methanol at conditions relevant to heavy-duty engines, a large database was created using chemical kinetics calculations. A neural network model was trained with the tabulated data for fast data retrieval. To validate whether the knock integral approach is robust enough to be applied to a wide range of engine sizes, a calibration constant was added to match the knock predictions to experimental data. Its value was calculated for three different engines, a light and heavy-duty SI engine and a large-bore dual-fuel engine. They highlight a remarkable difference in calibration constant across the different engines investigated.

In this study, carbon nanotube (CNT)/carbon nanofiber (CNF) composite electrothermal films were prepared by electrospinning, and the effects of the CNT content and carbonization temperature on the electrothermal properties of the CNT/CNF composite films were investigated. The experimental results demonstrated that the conductivity of the CNT/CNF composite electrothermal film (0.006–6.89 S/cm) was directly affected by the CNT content and carbonization temperature. The electrothermal properties of the CNT/CNF positively correlated with the CNT content, carbonization temperature, and applied voltage. The surface temperature of CNT/CNF can be controlled within 30–260 °C, and continuously heated and cooled 100 times without any loss. The convective heat transfer with air is controllable between 0.008 and 31.75. The radiation heat transfer is controllable between 0.29 and 1.92. The prepared CNT/CNF exhibited a heat transfer efficiency of up to 94.5%, and melted a 1 cm thick ice layer within 3 min by thermal convection and radiation alone.

To meet climate targets, a global shift away from fossil fuels is essential. For sectors where electrification is impractical, it is crucial to find sustainable energy carriers. Renewable methanol is widely considered a promising fuel for powering heavy-duty applications like shipping, freight transport, agriculture, and industrial machines due to its various sustainable production methods. While current technological efforts focus mainly on dual-fuel engines in shipping, future progress hinges on single-fuel solutions using renewable methanol to achieve net-zero goals in the heavy-duty sector. This review examines the research status of technologies enabling methanol as the sole fuel for heavy-duty applications. Three main categories emerged from the literature: spark-ignition, compression-ignition, and pre-chamber systems. Each concept’s operational principles and characteristics regarding efficiency, stability, and emissions were analyzed. Spark-ignition concepts are a proven and cost-effective solution with high maturity. However, they face limitations due to knock issues, restricting power output with larger bore sizes. Compression-ignition concepts inherently do not suffer from end-gas autoignition, but encounter challenges related to ignitability due to the low cetane number of methanol. Nonetheless, various methods for achieving autoignition of methanol exist. To obtain stable combustion at all load points, a combination of techniques will be required. Pre-chamber technology, despite its lower maturity, holds promise for extending the knock limit and enhancing efficiency by acting as a distributed ignition source. Furthermore, mixing-controlled pre-chamber concepts show potential for eliminating knock and the associated size and power limitations. The review concludes by comparing each technology and identifying research gaps for future work.

A stereolithography process with thermal assistance is proposed in this work to address the tradeoff between the flowability and the high concentration of solute loadings at room temperature, through which the improved performance of polymers prepared using stereolithography 3D printing can be achieved. For the experiment, polyethylene glycol diacrylate (PEGDA) with a high molecular weight of 4000 is adopted to improve the mechanical properties of 2-Hydroxyethyl methacrylate (HEMA). For the polymer of HEMA, the highest soluble concentration of PEGDA is about 20 wt% at 25 °C (room temperature) while the concentration could be raised up to 40 wt% as the temperature increases to 60 °C. The 3D printing tests showed that the objects could be easily fabricated with the HEMA polymer loaded with 40 wt% of PEGDA through the thermally assisted projection stereolithography technology. By adding the 40 wt% of PEGDA, the Young’s modulus has been enhanced by nearly 390% compared to the HEMA resin without solute, of which the Young’s modulus is 63.31 ± 2.72 MPa. The results of the cell proliferation test proved that the HEMA resin loaded with PEGDA led to a better biocompatibility compared to the HEMA resin without the loading of the PEGDA solute. All of the results demonstrate that the polymer loaded with high solute is feasible to be precisely 3D-printed using the projection stereolithography process with thermal assistance, and the improved mechanical properties are beneficial for biomedical applications.

IntroductionAnaerobic ammonium oxidation (anammox) plays a vital role in the global nitrogen cycle by oxidizing ammonium to nitrogen under anaerobic environments. However, the existence, abundance, and diversity of anammox bacteria between different temperatures are less studied, particularly in purple paddy soils.Methods13C-DNA stable-isotope probe combined with Illumina MiSeq high-throughput sequencing was employed to explore soil abundance and diversity of anammox bacteria. In doing so, 40–60 cm depth soils from typical purple paddy soils in Chongqing, southwest China, were cultured under 12CO2-labeled and 13CO2-labeled at 35°C, 25°C, 15°C, and 5°C for 56 days.Results and DiscussionAnammox bacteria were not labeled at all by 13CO2 at 5°C. The highest abundance of anammox bacteria was found at 25°C (3.52 × 106~3.66 × 106 copies·g−1 dry soil), followed by 35°C and 15°C (2.01 × 106~2.37 × 106 copies·g−1 dry soil) and almost no increase at 5°C. The relative abundance of Candidatus Jettenia sp. was higher at 25°C and 15°C, while Candidatus Brocadia sp. was higher at 35°C and 5°C. Our results revealed differences in anammox bacteria at different temperatures in purple paddy soils, which could provide a better understanding of soil N cycling regulated by anammox bacteria.

The design of railway alignment and station locations involves two intertwined problems, which makes it a complex and time-consuming task. Especially in mountainous regions, the large 3-dimensional (3D) search spaces, complex terrain conditions, coupling constraints and infinite numbers of potential alternatives of this problem pose many challenges. However, most current optimization methods emphasize either alignment optimization or station locations optimization independently. Only a few methods consider coordinated optimization of alignment and stations, but optimize them sequentially. This paper proposes a concurrent optimization method based on a 3-dimensional distance transform algorithm (3D-DT) to solve this problem. It includes the following components: (1) To optimize the location of stations within specified spacing intervals, a novel perceptual search strategy is proposed and incorporated into the basic 3D-DT optimization process. (2) A combined-alignment-station 3D search neighboring mask is developed and employed to search for both the alignment and stations. In order to implement the perceptual process, two additional kinds of 3D reverse perceptual neighboring masks are also developed and employed in the algorithm. (3) Multiple coupling constraints between alignment and stations are also formulated and addressed during the search process. In this study, the effectiveness of the method is verified through a real-world case study in a complex mountainous region. The optimization results show that the proposed method can find high-quality alternatives satisfying multiple coupling constraints.

A railway track gradually deviates from the originally designed vertical alignment in the operation. To ensure the safety and comfort, railway maintenance department must periodically recreate vertical alignment and calibrate existing track to it. The recreated alignment should be as close as possible to the measured points along the existing railway track, while satisfying multiple constraints. A vertical alignment consists of tangents and curves. Identifying the geometric element attribution of the measured points accurately and recreating the vertical alignment efficiently and accurately with all the constraints satisfied are the key problems. Existing methods need manual assistance and few constraints are considered. This paper proposes an automatic global iterations method considering multiple constraints. Firstly, geometric elements are identified based on the change rate of gradient and are set as initial values for the iterations. Then, the geometric elements are fitted iteratively. In each iteration, all the tangents are fitted simultaneously followed by the fitting of all vertical curves and the constraints are handled while the geometric elements are fitted. The attributions of all points are adjusted after each iteration. If the attributions of all the points are consistent with the ranges of fitted geometric elements, the iteration terminates. A software is developed based on this method, and applications demonstrate this method can identify all geometric elements automatically and recreate an optimized vertical alignment while satisfying all the constraints.

In this paper, the fixed-time synchronization problem for a class of memristive neural networks with discontinuous neuron activation functions and mixed time-varying delays is investigated. With the help of the fixed-time stability theory, under the framework of Filippov solution and differential inclusion theory, several new and useful sufficient criteria for fixed-time synchronization are obtained by designing two types of energy-saving and simple controllers for the considered systems. Compared with the traditional fixed-time synchronization controller, the controllers used in this paper only have one power exponent term, which is a function of the system state error rather than a constant. Moreover, some previous relevant works are especially improved. Finally, two numerical examples are given to show the correctness and the effectiveness of the obtained theoretical results.

Aiming at analyzing the influence of multi-step attack,as well as reflecting the system’s security situation accurately and comprehensively,a network security situation evaluation method for multi-step attack was proposed.This method firstly clustered security events into several attack scenes,which was used to identify the attacker.Then the attack path and the attack phase were identified by causal correlation of every scene.Finally,combined with the attack phase as well as the threat index,the quantitative standard was established to evaluate the network security situation.The proposed method is assessed by two network attack-defense experiments,and the results illustrate accuracy and effectiveness of the method.

Antimicrobial peptides and their analogues have become substitutes for antibiotics in recent years. The antimicrobial peptide analogue SAMP‐A4‐C8 (n‐octanoic‐VRLLRRRI) with high antimicrobial activity was found in our lab. We speculate that it may kill pathogens by some lethal mechanism of action. In the present investigation, the microbicidal activities of SAMP‐A4‐C8 and its mechanism of action were investigated. The results demonstrated that SAMP‐A4‐C8 had lethal activities against Staphylococcus aureus and Candida albicans by cell disruption. Based on its microbicidal activities, we believe that it is worth further research for its potential as drug candidate. The results showed that SAMP‐A4‐C8, with low propensity to induce the resistance of S. aureus and C. albicans, could kill the persister cells of S. aureus and C. albicans, exhibited biofilm forming inhibition activity and preformed biofilm eradication ability against S. aureus and C. albicans, and displayed therapeutic potential on pneumonia in S. aureus‐infected mice by reducing lung inflammation. The present study provided a promising drug candidate in the war against multidrug resistance. [ABSTRACT FROM AUTHOR]