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The echelon utilization of electric vehicle batteries is regarded as an effective method for treating waste batteries, enabling the recycling and reuse of retired electric vehicle batteries. However, the efficiency of battery disassembly is a crucial factor that impacts the potential for battery recycling. When manufacturers take disassembly efficiency into account during the design phase of new electric vehicle batteries, they can significantly reduce disassembly costs at the time of decommissioning. This, in turn, incentivizes recycling and echelon utilization of waste batteries. Our research aims to promote the echelon use of waste batteries and analyze how market competition intensity and profits from battery echelon utilization influence decision-making within the battery recycling supply chain. This paper explores the effect of market competition on battery recycling and echelon utilization, while developing a supply chain model that includes a battery manufacturer responsible for determining the level of battery disassembly design and recycling waste batteries from the market, as well as a new energy vehicle manufacturer that focuses solely on recycling waste batteries. The findings indicate that as market competition increases, the battery manufacturer tends to lower both the level of battery disassembly design and the recycling price for waste batteries. Additionally, the recycling price for waste batteries offered by new energy vehicle manufacturers is also influenced by the intensity of market competition. In scenarios with low competition intensity, the recycling price tends to rise as competition intensifies. Conversely, in highly competitive markets, the recycling price decreases with increased competition. Furthermore, the overall volume of battery recycling is impacted by the intensity of market competition; in highly competitive markets, waste battery recycling is hindered. To enhance the echelon utilization of battery recycling, relevant government agencies should strive to maintain market competition at lower levels while also encouraging the recycling of batteries that do not meet usage standards. This dual approach will improve the benefits associated with the echelon utilization of waste batteries, thereby fostering greater enthusiasm for recycling among the involved enterprises.

A surface plasmon resonance (SPR) sensor based on a D-shaped photonic crystal fiber (PCF) with an uncomplicated structure is proposed to detect the change of refractive index of liquid analytes, and numerical simulation is carried out by the finite element method (FEM). Using silver as the plasmonic metal, the performances of the SPR-PCF sensor coated with a graphene layer and zinc oxide (ZnO) layer were assessed. The sensor designed is only coated with material on the polished surface, which makes the sensor production uncomplicated and solves the problems of filling material in the hole and coating on the hole wall. The effects of structural parameters such as graphene layer thickness, silver layer thickness, ZnO thickness, lattice spacing and manufacturing tolerance of blowhole diameter on the sensor performance were numerically simulated. The numerical results show that the sensitivity of the SPR-PCF sensor coated with 25 nm ZnO is highest in the ZnO thickness range from 10 to 25 nm. In the refractive index range of 1.37–1.41 for liquid analyte, the maximum sensitivity and corresponding resolution reach 6000 nm/RIU and 1.667 × 10−5, respectively. In addition, the sensor has good stability and high structural tolerance under the tolerance of ±5% of blowhole diameter. This work has wide application value in the detection of biochemical analytes, water pollution monitoring, food quality, and medical diagnosis.

Background 1-Hydroxyphenazine (1-OH-PHZ) is a phenazine microbial metabolite with broad-spectrum antibacterial activities against a lot of plant pathogens. However, its use is hampered by the low yield all along. Metabolic engineering of microorganisms is an increasingly powerful method for the production of valuable organisms at high levels. Pseudomonas chlororaphis is recognized as a safe and effective plant rhizosphere growth-promoting bacterium, and faster growth rate using glycerol or glucose as a renewable carbon source. Therefore, Pseudomonas chlororaphis is particularly suitable as the chassis cell for the modification and engineering of phenazines. Results In this study, enzyme PhzS (monooxygenase) was heterologously expressed in a phenazine-1-carboxylic acid (PCA) generating strain Pseudomonas chlororaphis H18, and 1-hydroxyphenazine was isolated, characterized in the genetically modified strain. Next, the yield of 1-hydroxyphenazine was systematically engineered by the strategies including (1) semi-rational design remodeling of crucial protein PhzS, (2) blocking intermediate PCA consumption branch pathway, (3) enhancing the precursor pool, (4) engineering regulatory genes, etc. Finally, the titer of 1-hydroxyphenazine reached 3.6 g/L in 5 L fermenter in 54 h. Conclusions The 1-OH-PHZ production of Pseudomonas chlororaphis H18 was greatly improved through systematically engineering strategies, which is the highest, reported to date. This work provides a promising platform for 1-hydroxyphenazine engineering and production. Graphical Abstract

The randomness, volatility, and intermittency of renewable energy sources such as wind and solar energy present significant challenges to energy management in microgrids, resulting in low management efficiency and poor accuracy. This paper proposes an energy optimization method for microgrids based on an uncertainty-aware deep deterministic policy gradient (DDPG) algorithm. First, considering the uncertainty of renewable energy output, an uncertainty awareness model is constructed based on information gap decision theory (IGDT). Second, the DDPG algorithm is employed to optimize the energy scheduling strategy, incorporating a bidirectional feedback collaborative optimization framework. The uncertainty radius is used for forward feedback adjustment of the optimization step size of the DDPG model, while the risk-aversion coefficient of the IGDT model is adjusted via backward feedback based on the DDPG optimization results. This approach enables adaptive regulation in dynamic and complex environments. The research demonstrates that the proposed algorithm significantly enhances the robustness, convergence, and adaptability of the microgrid in uncertain environments, improving peak shaving and valley filling performance as well as the adaptability to fluctuations in renewable energy sources. The proposed method demonstrates significant improvements in robustness, convergence speed, and adaptability when applied to microgrid energy management. Numerical results show a 5.44% and 70.26% improvement in total microgrid revenue compared to baseline algorithms, highlighting the effectiveness of the uncertainty-aware DDPG algorithm in dynamic and uncertain environments.

This article proposes a multi-resonant three-port DC-DC converter (MRTPC) that can achieve power decoupling in the presence of deviations in the parameters of the resonant elements. The MRTPC consists of a four-element resonant tank (FERT), a three-element resonant tank (TERT), and an LC resonant tank (LCRT). Due to the fact that the FERT can be configured with first and third resonant frequencies (RF), it can transmit the energy of the fundamental and third harmonic components. By reasonably setting the RFs of the FERT, TERT, and LCRT, decoupling control of primary and tertiary energy transmission can be achieved. Due to the characteristics of the FERT, TERT and LCRT at different frequencies, decoupling the transmission of the power of the primary and tertiary frequency components can be achieved even when there is a certain deviation in the parameters of the resonant elements of the FERT. This feature can effectively reduce the cost of selecting resonant elements. To improve the efficiency of the MRTPC, an optimized triple-phase-shift modulation strategy (OTPSMS) is proposed to minimize the root mean square value of the resonant current (RMSRC). For the nonlinear problem of minimizing the RMSRC, the KKT condition is used for the optimization solution. Finally, an experimental prototype with a power level of 1 kW is built to verify the theoretical correctness of the MRTPC and its OTPSMS.

AbstractThe potential risk associated with ACP nanoparticles (ACP NPs) cultured with immune cells and their indirect effects on osteogenesis have not been studied deeply. This project aims to evaluate the safety of ACP NPs in macrophages, the responses of macrophages (macrophage polarization, the cytokine secretion pattern of macrophages and intracellular homeostasis) to ACP NPs and the effect of ACP NPs/macrophage-modulated environments on the osteogenic ability of BMSCs. The cell proliferation rate and apoptosis were detected by CCK-8 and Annexin V Apoptosis Detection kits. ROS and autophagy expression were evaluated by ROS test kits and Western blot (WB). Macrophage polarization and cytokine expression were determined by SEM, cytoskeletal staining, RT-PCR and ELISA. TMT™ quantitative protein analysis was used to evaluate protein expression. BMSC osteogenic differentiation was detected by ALP staining, Alizarin Red solution staining and RT-PCR. ACP NPs were safe to macrophages but promoted autophagy and induced ROS production at high concentrations. ACP NPs changed morphology of macrophages and induced polarization into M1 type, thus promoting the expression of inflammatory cytokines. ACP NPs/macrophage-modulated environments weakened the osteogenic ability of BMSCs. ACP NPs polarize macrophages into the M1 phenotype and change the cytokine secretion pattern. ACP NPs/macrophage-modulated environments weaken the osteogenic ability of BMSCs. ACP NPs may cause aseptic inflammation and attenuate osteogenesis.

Power electronics technology plays an increasingly important role in modern energy utilization systems [...]

Objective We report a rare case of spontaneous bilateral perineal hematoma during pregnancy. We analyze its etiology, clinical features, treatment, and prognosis to provide a reference for clinical practice. Methods Detailed clinical information was collected, including the patient’s pregnancy course, delivery process, imaging findings, and subsequent pregnancy outcomes. We discuss the potential mechanisms, management principles, and prognosis of spontaneous perineal hematoma during pregnancy in light of relevant literature. Results The patient began self-administered perineal massage at 36 weeks of gestation. At 39^+5 weeks, before delivery, bilateral spontaneous perineal hematomas developed. A left mediolateral episiotomy was performed during delivery. After conservative postpartum treatment, the hematomas gradually resolved, and the wound healed well. Eighteen months later, the patient had another vaginal delivery without reoccurrence of perineal hematoma or laceration. Conclusions Spontaneous perineal hematoma during pregnancy is rare. Its occurrence may be related to increased vascular fragility, venous congestion, and external forces. Although perineal massage in pregnancy may affect perineal tissues, there is no definitive evidence of a direct causal relationship with spontaneous hematoma. Proper guidance on correct technique and force is advised.

In order to further explore the properties of graphene-reinforced matrix composites, the adsorption behaviors of intrinsic graphene, vacant defect graphene (VG), and Nd-doped graphene (Nd-doped) adsorbed with Ti were studied. The calculation results show that, compared with intrinsic graphene, the p-type doping and n-type doping are formed in the VG and Nd-doped, respectively. After the Ti adsorption of the above three adsorption systems, the stability of the VG and Nd-doped systems has been significantly improved. What’s more, in optical performance, the absorption peaks and reflection peaks have different degrees of red-shift compared with the intrinsic graphene, indicating both adsorption and doping will change the spectral characteristics of graphene. Meanwhile, Ti adsorption can enhance absorption and reflection of graphene in the low-energy region. This study provides a novel method with the exploration of the new function of graphene for the better application of graphene-reinforced matrix composites in optoelectronic equipment in the future.

Multiple myeloma (MM) is a distinguished hematologic malignancy, with existing studies elucidating its interaction with neutrophil extracellular traps (NETs), which may potentially facilitate tumor growth. However, systematic investigations into the role of NETs in MM remain limited. Utilizing the single-cell dataset GSE223060, we discerned active NET cell subgroups, namely neutrophils, monocytes, and macrophages. A transcriptional trajectory was subsequently constructed to comprehend the progression of MM. Following this, an analysis of cellular communication in MM was conducted with a particular emphasis on neutrophils, revealing an augmentation in interactions albeit with diminished strength, alongside abnormal communication links between neutrophils and NK cells within MM samples. Through the intersection of differentially expressed genes (DEGs) between NET active/inactive cells and MM versus healthy samples, a total of 316 genes were identified. This led to the development of a 13-gene risk model for prognostic prediction based on overall survival, utilizing transcriptomics dataset GSE136337. The high-risk group manifested altered immune infiltration and heightened sensitivity to chemotherapy. A constructed nomogram for predicting survival probabilities demonstrated encouraging AUCs for 1, 3, and 5-year survival predictions. Collectively, our findings unveil a novel NET-related prognostic signature for MM, thereby providing a potential avenue for therapeutic exploration.