Battery management system (BMS) refers to a critical electronic control unit in the power battery system of electric vehicles. It is capable of detecting and estimating battery status online, ...especially estimating state of charge (SOC) and state of health (SOH) accurately. Safe driving and battery life optimization are of high significance. As indicated from recent literature reports, most relevant studies on battery health estimation are offline estimation, and several problems emerged (e.g., long time-consuming, considerable calculation and unable to estimate online). Given this, the present study proposes an online estimation method of lithium-ion health based on particle swarm support vector machine algorithm. By exploiting the data of National Aeronautics and Space Administration (NASA) battery samples, this study explores the changing law of battery state of charge under different battery health. In addition, particle swarm algorithm is adopted to optimize the kernel function of the support vector machine for the joint estimation of battery SOC and SOH. As indicated from the tests (e.g., Dynamic Stress Test), it exhibits good adaptability and feasibility. This study also provides a certain reference for the application of BMS system in electric vehicle battery online detection and state estimation.
To solve the problems of the decreased reliability and safety of battery pack due to the inconsistency between batteries after single batteries are grouped is of great significance to find an ...appropriate sorting method of single batteries. This study systematically reviews the available literature on battery sorting applications for battery researchers and users. These methods can be roughly divided into three types: direct measurement, sorting based on the model, and sorting based on the material chemistry of batteries. Among them, direct measurement is about the direct measurement of the state parameters of batteries using some professional instruments or testing tools to sort and group batteries with similar or close parameters. Sorting based on the model classifies batteries into groups by establishing a battery equivalent model and carrying out model identification and parameter estimation with machine learning or artificial intelligence algorithm. Sorting based on the material chemistry of batteries is to explore some characteristics related to the chemical mechanism inside the battery. On the basis of reading extensive literature, the methods for classification of battery are provided with an in-depth explanation, and each corresponding strengths and weaknesses of these methods are analyzed. Finally, the future developments of advanced sorting algorithms and batteries prospect.
The state of charge (SOC) and state of health (SOH) of a power battery system are the research hotspots of researchers in recent years. An accurate state estimation is conducive to research on ...battery life optimization and guarantees the safe driving of electric vehicles. The use of artificial intelligence, machine learning and other methods has always been the mainstream of research on SOC and SOH prediction, but there are defects such as a strong data dependence, a large calculation volume and a long-time consumption. in view of this, a battery SOC-SOH online estimation method is proposed in the previous work of this paper based on PSO-SVM algorithm to solve the above problems. However, due to the PSO-SVM algorithm, there is a problem that the stability of the estimated battery SOH is not high. Therefore, an integrated learning AdaBoost algorithm is introduced in this paper to improve the PSO-SVM regression model, meanwhile through integrated processing, multiple weak learners are combined to construct a strong regression. Simulation and experimental analysis show that this method has a good data adaptability and accuracy, whose average estimation error does not exceed 2.316.
Low-cost, high-quality, and large-area superhydrophobic surfaces are in high demand. This study demonstrates laser-engineered polydimethylsiloxane (PDMS) as a platform for versatile and highly ...efficient water manipulation. The fabrication process consists of two steps: patterning PDMS with arrayed microlenses and laser pulse scanning. The obtained PDMS is superhydrophobic and exhibits excellent chemical resistance, UV stability, pressure robustness, and substantial mechanical durability. Notably, there is no significant change in the water contact angles after storage in air for 14 months. Microstructural analysis revealed that the sample contained stable nanostructured inorganics such as crystalline silicon, silicon carbide, and sp3-like carbon. The superhydrophobic surface was demonstrated to have versatile and wide applications in oil/water separation and water collection.
Generative Adversarial Networks (GAN) has become more and more popular these years. However, it is difficult to train and suffers from the training instability problem. To tackle this difficulty, ...this paper proposes a novel approach. Our idea is intuitive but proven to be very useful. In essence, it combines saturating loss and non-saturating loss into the loss function. Thus it will exploit the complementary statistical properties from two kinds of loss functions to effectively improve the training stability. We term our method twin discriminator Generative Adversarial Networks (TWGAN), which, unlike GAN, has a generator and a twin discriminator. The twin discriminator consists of two discriminators with identical architecture and both of them aim to distinguish whether the samples are from real data or fake data. We develop theoretical analysis to show that, given the optimal discriminators, optimizing the generator of TWGAN reduces to minimizing the Kullback-Leibler (KL) divergence between the distribution of generated data (<inline-formula><tex-math notation="LaTeX">P_g</tex-math></inline-formula>) and the distribution of real data (<inline-formula><tex-math notation="LaTeX">P_data</tex-math></inline-formula>), hence effectively addressing the training instability problem. Extensive experiments on MNIST, Fashion MNIST, CIFAR-10/100 and STL-10 datasets demonstrate that the competitive performance of our TWGAN in generating good quality and diverse samples over baselines. The obtained highest inception score (IS) and lowest Fr <inline-formula><tex-math notation="LaTeX">\acute{e}</tex-math></inline-formula> chet Inception Distance (FID), compared with other state-of-the-art GANs, show the superiority of our TWGAN.
•Amorphous iron oxide packaged with oxaliplatin as an apoptosis-ferroptosis combination for pancreatic cancer therapy.•In pancreatic cancer, AIOoxp has significant anti-tumor effect compared with ...free oxaliplatin in vitro and in vivo.•AIOoxp can reduce CA19-9 level by the excellent antitumor effect.
Pancreatic cancer is a highly malignant tumor with early metastasis, poor prognosis, and resistant to existing chemotherapy drugs such as oxaliplatin (Oxp). Therefore, a nanodrug of amorphous iron oxide packaged Oxp (AIOoxp) was proposed to achieve a more efficient treatment of orthotopic pancreatic cancer than that of free Oxp. The obtained AIOoxp increased the accumulation of Pt at tumor sites and effectively reduced Oxp-induced systemic toxicity. In addition, the Fe2+/Fe3+ ions released by AIOoxp react with H2O2 through Fenton’s reaction and produce a large amount of reactive oxygen species (ROS), which further induce ferroptosis, thus promoting Oxp-induced apoptosis and achieve synergistic tumor therapy. Furthermore, AIOoxp nanoplatforms can significantly reduce the levels of carbohydrate antigen 19–9 (CA19-9), which is the most important biomarker and promoter of pancreatic cancer, suggesting favorable therapeutic effects and prognosis. Overall, this study provides new insights and solutions for the clinical treatment of pancreatic cancer.
Neuromorphic computing is an emerging area with prospects to break the energy efficiency bottleneck of artificial intelligence (AI). A crucial challenge for neuromorphic computing is understanding ...the working principles of artificial synaptic devices. As an emerging class of synaptic devices, organic electrochemical transistors (OECTs) have attracted significant interest due to ultralow voltage operation, analog conductance tuning, mechanical flexibility, and biocompatibility. However, little work has been focused on the first-principal modeling of the synaptic behaviors of OECTs. The simulation of OECT synaptic behaviors is of great importance to understanding the OECT working principles as neuromorphic devices and optimizing ultralow power consumption neuromorphic computing devices. Here, we develop a two-dimensional transient drift–diffusion model based on modified Shockley equations for poly(3,4-ethylenedioxythiophene) (PEDOT)-based OECTs. We reproduced the typical transistor characteristics of these OECTs including the unique non-monotonic transconductance–gate bias curve and frequency dependency of transconductance. Furthermore, typical synaptic phenomena, such as excitatory/inhibitory postsynaptic current (EPSC/IPSC), paired-pulse facilitation/depression (PPF/PPD), and short-term plasticity (STP), are also demonstrated. This work is crucial in guiding the experimental exploration of neuromorphic computing devices and has the potential to serve as a platform for future OECT device simulation based on a wide range of semiconducting materials.
The pancreatic reconstruction technique decides the incidence of postoperative pancreatic fistulas (POPF) in pancreaticoduodenectomy (PD). This study aims to evaluate the safety of modified ...single-needle continuous suture (SNCS) of duct-to-mucosa and compare the efficacy with double-layer continuous suture (DLCS) of duct-mucosa pancreaticojejunostomy (PJ) in open PD (OPD).
A total of 266 patients that received PD between January 2019 and May 2023 were retrospectively analyzed. Among them, 130 patients underwent DLCS, and 136 patients underwent SNCS 73 OPD and 63 laparoscopic PD (LPD). The primary outcome was clinically relevant POPF (CR-POPF) according to the definition of the revised 2016 International Study Group of Pancreatic Fistula (ISGPF). Propensity score matching (PSM) was conducted to reduce confounding bias.
A total of 66 pairs were successfully matched using PSM in OPD. No significant difference was observed in the occurrence of CR-POPF between the two groups (9.1%
21.2%, P=0.052). However, the median duration of operation and PJ was shorter in the SNCS group. The incidence of CR-POPF in LPD was 9.5%. Furthermore, regarding the alternative fistula risk score (a-FRS), the CR-POPF rate were 2.1%, 10.5%, and 15.6% in low-, intermediate-, and high-risk groups (P=0.067).
The SNCS is a facile, safe, and effective PJ technique and does not increase the incidence of POPF, regardless of a-FRS stratification, pancreatic texture, and main pancreatic duct (MPD) size.
The spout at the connection of the pipe and the chamber is easily clogged when a large amount of molten metal is conveyed to the chamber in squeeze casting for large parts. In order to reduce the ...chances of clogging and clean up quickly when clogged, a quickly removable pipe is designed. The pipe is heated through thermal conduction by resistance wire, and thermal equilibrium is used to derive the power of heating element. Solid-state regulator is applied to control the heating power. Molten aluminum is conveyed from furnace to chamber using electromagnetic pump. The experiment shows that the molten metal flowing through the pipe is smooth, and the temperature of molten metal can be maintained stability.
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