Optimization of PID control parameters for marine dual-fuel engine using improved particle swarm algorithm.

This study presents a comprehensive investigation into the optimization of PID control parameters for marine dual-fuel engines using an improved particle swarm algorithm. Through the development of a Matlab/Simulink simulation model, the thermodynamic behavior of the engine and the functionality of its control system are analyzed. The PID control parameters for air-fuel ratio control and mode switching control systems are fine-tuned utilizing the improved particle swarm algorithm (PSO). Simulation results demonstrate that the proposed improved PID-PSO approach outperforms traditional PID and traditional PSO-PID control methods in terms of reduced overshoot, minimized steady-state error, faster response times, and improved stability across various operating conditions and response modes. In comparison to traditional PID and PSO-PID controllers, the improved PSO-PID controller reduces the response time by 0.47 s and 0.21 s, the maximum overshoot by 98.43% and 96.05%, and decreases the absolute errors by 87.42% and 90.55%, respectively, in air-fuel ratio control using the step response method. The study's findings offer valuable insights into enhancing the performance and efficiency of marine dual-fuel engines through advanced control strategies.

A rapid staged protocol for efficient recovery of microplastics from soil and sediment matrices based on hydrophobic separation.

Microplastics (MPs) in soil and sediment (SS) matrices are emerging pollution hazards to ecosystems and humans. To mitigate MP pollution, suitable extractors and associated extracting solutions are required to efficiently separate MPs from SS matrices. In this study, we introduced a four-stage microplastic extractor (ME) device and investigated the fractional separation efficiencies of three extracting solutions (ultrapure water, saturated NaCl, and corn oil-in-NaCl) plus aeration, magnetic stirring, and electric stirring for three kinds of SS matrices (loam soil, sandy sediment, and muddy sediment) with four types of virgin MP pellets (acrylonitrile butadiene styrene (ABS), polycarbonate (PC), polypropylene, and polystyrene). In addition, fragments of these four types of post-consumer MPs were also tested by the ME device. The mean recovery efficiencies of these MPs in the three SS matrices were 88.3 %-100 %. Oil-in-NaCl further improved the recovery efficiencies for the denser ABS and PC up to 40 % based on NaCl extraction.

Improvement and analysis of mechanistic modeling of root canal preparation by a computer-based method.

BACKGROUND AND OBJECTIVE: Root canal preparation is a cutting process between nickel-titanium (Ni-Ti) file and root canal, which aims to remove the bacteria and to keep teeth from infection. A mechanistic model in root canal preparation is proposed to investigate the mechanical mechanism of Ni-Ti file, which is essential to prevent physical and thermal damage on root canal. METHODS: First, the mathematic modeling is introduced based on oblique cutting theory, which the loading condition of Ni-Ti file is derived from each cutting element by expressing a function of geometric parameters. For the modeling improvement, a cutting simulation algorithm (CSA) based on Boolean operation is proposed to achieve the complicated cutting situation between root canal and Ni-Ti file instantaneously. After establishment of model, the predictive precision is verified by conducting in vitro experiments. Eighteen artificial root canals were prepared in 6 mm straight and 2 mm C-shaped curved specification with 0.3 mm diameter, which was a single canal for each position, all the canals do not have connections with each other. During experiments, root canals were prepared using Wave One Gold (GWO) instruments with reciprocating rotational motion. Different influential factors (curvatures of root canal and movements of Ni-Ti file) and cutting parameters (feed rate and spindle speed) were analyzed by conducting a series of simulations under the mechanistic model. RESULTS: Experiment results show that the predictive error of thrust force based on the proposal model is around 15%. The thrust force will increase dramatically after Ni-Ti file gets into craved canal. It can be indicated that the curvatures of root canal, movements of Ni-Ti file have a strong influence on root canal preparation. 20° increasement of curved degrees can lead to the 0.73 N increase of thrust force, while pecking movement can decrease 19.88% of thrust force compared with continues one. Furthermore, investigation on pecking distance represent that 2-1 mm movement can effectively reduce the thrust force of 15.82% compared to 4-2 mm movement. CONCLUSION: Based on simulation results, 2-1 mm pecking movement is recommended for dentists compared with 4-2 mm pecking movement or continues movement. In addition, this paper provides a novel insight of interactive mechanism between Ni-Ti file and root canal, so as to contribute to both the theoretical and practical research by elucidating mechanisms and providing quantitative predictions that can be validated. Compared with conventional analytical model, both calculated precision and efficiency are improved in the proposed model.

Ensembled deep learning model outperforms human experts in diagnosing biliary atresia from sonographic gallbladder images.

It is still challenging to make accurate diagnosis of biliary atresia (BA) with sonographic gallbladder images particularly in rural area without relevant expertise. To help diagnose BA based on sonographic gallbladder images, an ensembled deep learning model is developed. The model yields a patient-level sensitivity 93.1% and specificity 93.9% [with areas under the receiver operating characteristic curve of 0.956 (95% confidence interval: 0.928-0.977)] on the multi-center external validation dataset, superior to that of human experts. With the help of the model, the performances of human experts with various levels are improved. Moreover, the diagnosis based on smartphone photos of sonographic gallbladder images through a smartphone app and based on video sequences by the model still yields expert-level performances. The ensembled deep learning model in this study provides a solution to help radiologists improve the diagnosis of BA in various clinical application scenarios, particularly in rural and undeveloped regions with limited expertise.

Visible Light-Induced Decarboxylative Alkylation of Heterocyclic Aromatics with Carboxylic Acids via Anthocyanin as a Photocatalyst.

A visible light-induced decarboxylative alkylation of heterocyclic aromatics with aliphatic carboxylic acids was developed by using anthocyanins as a photocatalyst under mild conditions. A series of alkylated heterocyclic compounds were obtained in moderate to good yields by using the metal-free decarboxylative coupling reaction under blue light. This strategy uses cheap and readily available carboxylic acids as alkylation reagents with good functional group tolerance and environmental friendliness. It is worth noting that this is the first time that anthocyanin has been used to catalyze the Minisci-type C-H alkylation. The mechanism of decarboxylation alkylation was studied by capturing the adduct of alkyl radical and hydroquinone, thus confirming a radical mechanism. This protocol provides an alternative visible light-induced decarboxylative alkylation for the functionalization of heterocyclic aromatics.

Spore Carbon from Aspergillus Oryzae for Advanced Electrochemical Energy Storage.

Development of novel advanced carbon materials is playing a critical role in the innovation of electrochemical energy storage technology. Hierarchical porous spore carbon produced by Aspergillus oryzae is reported, which acts as a biofactory. Interestingly, the spore carbon not only shows a porous maze structure consisting of crosslinked nanofolds, but also is intrinsically N and P dual doped. Impressively, the spore carbon can be further embedded with Ni2 P nanoparticles, which serve as porogen to form a highly porous spore carbon/Ni2 P composite with increased surface area and enhanced electrical conductivity. To explore the potential application in lithium-sulfur batteries (LSBs), the spore carbon/Ni2 P composite is combined with sulfur, forming a composite cathode, which exhibits a high initial capacity of 1347.5 mAh g-1 at 0.1 C, enhanced cycling stability (73.5% after 500 cycles), and better rate performance than the spore carbon/S and artificial hollow carbon sphere/S counterparts. The synergistic effect on suppressing the shuttle effect of intermediate polysulfides is responsible for the excellent LSBs performance with the aid of a physical blocking effect arising from the electrical maze porous structure and the chemical adsorption effect originating from N, P dual doping and polarized compound Ni2 P.