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Intelligent control algorithms have been extensively utilized for adaptive controller parameter adjustment. While the Particle Swarm Optimization (PSO) algorithm has several issues: slow convergence speed requiring a large number of iterations, a tendency to get trapped in local optima, and difficulty escaping from them. It is also sensitive to the distribution of the solution space, where uneven distribution can lead to inefficient contraction. On the other hand, the Beetle Antennae Search (BAS) algorithm is robust, precise, and has strong global search capabilities. However, its limitation lies in focusing on a single individual. As the number of iterations increases, the step size decays, causing it to get stuck in local extrema and preventing escape. Although setting a fixed or larger initial step size can avoid this, it results in poor stability. The PSO algorithm, which targets a population, can help the BAS algorithm increase diversity and address its deficiencies. Conversely, the characteristics of the BAS algorithm can aid the PSO algorithm in finding the optimal solution early in the optimization process, accelerating convergence. Therefore, considering the combination of BAS and PSO algorithms can leverage their respective advantages and enhance overall algorithm performance. This paper proposes an improved algorithm, W-K-BSO, which integrates the Beetle Antennae Search strategy into the local search phase of PSO. By leveraging chaotic mapping, the algorithm enhances population diversity and accelerates convergence speed. Additionally, the adoption of linearly decreasing inertia weight enhances algorithm performance, while the coordinated control of the contraction factor and inertia weight regulates global and local optimization performance. Furthermore, the influence of beetle antennae position increments on particles is incorporated, along with the establishment of new velocity update rules. Simulation experiments conducted on nine benchmark functions demonstrate that the W-K-BSO algorithm consistently exhibits strong optimization capabilities. It significantly improves the ability to escape local optima, convergence precision, and algorithm stability across various dimensions, with enhancements ranging from 7 to 9 orders of magnitude compared to the BAS algorithm. Application of the W-K-BSO algorithm to PID optimization for the Pointing and Tracking System (PTS) reduced system stabilization time by 28.5%, confirming the algorithm's superiority and competitiveness. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel convex combination algorithm based on the distributed diffusion strategy, utilizing the least mean square (LMS) approach to enhance the performance of sensor networks. By enabling communication among nodes, the algorithm achieves decentralization and improves the robustness of the network. To address the limitations of slow convergence speed and large static error associated with fixed step size errors, we introduce a convex combination strategy that integrates two filters with variable step sizes. The LMS algorithm with the convex combination variable step size assigns a higher weight to the filter with a larger step size when the error is significant, ensuring rapid convergence. Conversely, the convex combination small step size filter is assigned a higher weight when the error is small, reducing the error in the stable state. The convergence behavior of the proposed algorithm is analyzed through theoretical analysis, and its complexity is compared with that of the distributed diffusion LMS algorithm through extensive experimental simulations. The results demonstrate that the combination of the LMS algorithm with the distributed diffusion strategy offers advantages in challenging external environments, including improved convergence speed and reduced stability error. This study makes significant contributions to the existing research field by introducing a novel convex combination algorithm that addresses the shortcomings of fixed step size errors and expands the range of available algorithms. By leveraging the distributed diffusion strategy, our approach enhances the robustness of sensor networks and achieves improved performance. The findings of this study provide valuable insights for researchers working on decentralized algorithms and highlight the potential of combining the LMS algorithm with the distributed diffusion strategy in challenging environmental conditions. [ABSTRACT FROM AUTHOR]

Pneumocystis pneumonia (PCP) is a fungal pulmonary disease with high mortality in immunocompromised patients. Neutrophils are essential in defending against fungal infections; however, their role in PCP is controversial. Here we aim to investigate the effects of neutrophil extracellular traps (NETs) on Pneumocystis clearance and lung injury using a mouse model of PCP. Intriguingly, although neutrophils play a fundamental role in defending against fungal infections, NETs failed to eliminate Pneumocystis, but instead impaired the killing of Pneumocystis. Mechanically, Pneumocystis triggered Leukotriene B4 (LTB4)‐dependent neutrophil swarming, leading to agglutinative NET formation. Blocking Leukotriene B4 with its receptor antagonist Etalocib significantly reduced the accumulation and NET release of neutrophils in vitro and in vivo, enhanced the killing ability of neutrophils against Pneumocystis, and alleviated lung injury in PCP mice. This study identifies the deleterious role of agglutinative NETs in Pneumocystis infection and reveals a new way to prevent NET formation, which provides new insights into the pathogenesis of PCP. [ABSTRACT FROM AUTHOR]

Two-dimensional metal–organic frameworks (2D MOFs) as an ideal prototype material for the electrocatalytic oxygen evolution reaction (OER) can expose more metal active sites due to their ultrathin 2D structure. Herein, a two-dimensional Co3BDC6Py3DMF1 (termed Co MOF-Py3, BDC = 1,4-benzene dicarboxylic acid, Py = pyridine, and DMF = N,N-dimethylformamide) catalyst was prepared by a solvothermal bottom-up method by introducing pyridine to replace the triethylenediamine organic coordination in three-dimensional (3D) Co2(BDC)2(DABCO)·4DMF·H2O (termed Co MOF, DABCO = 1,4-diazabicyclo[2.2.2]octane). Compared to the 3D columnar Co MOF, the overpotential of ultrathin 2D nanosheet Co MOF-Py3 at 10 mA cm−2 decreased by 55 mV to 307 mV, and the Tafel slope was 52.14 mV dec−1. To further improve the catalytic capability of Co MOF-Py3, the Fe element was introduced into Co MOF-Py3 by impregnation to obtain a Co3Fe1 MOF-Py3 catalyst, which exhibited excellent OER performance with a low overpotential of 269 mV at 10 mA cm−2 and a small Tafel slope of 45.29 mV dec−1. Structural characterization reveals that the addition of a specific quantity of pyridine could completely replace the triethylenediamine ligands, thus leading to structural reconfiguration of the entire MOF, resulting in a structural alteration from 3D to 2D and enhancing the number of metal active sites to catalyze the OER. [ABSTRACT FROM AUTHOR]

Due to the simplicity of vacancy creation, Eu2+-doped melilite is an outstanding persistent luminescence (PersL) material with a continuing glow lifetime of more than several hours. In this paper, we propose a novel technique for activating a long-lasting phosphor (LLP) via oxygen-vacancy-rich Ca2MgSi2O7:Eu2+ (VO-CMSE), which shows that more VO defects activate the persistent luminescence of Eu2+. VO-CMSE has a long duration and high charge storage capacity, allowing it to perform efficiently in a variety of applications. Consequently, the intensity of VO-CMSE is enhanced, which has been demonstrated to be useful in compensating for the flicker effect of AC-LEDs (alternating current light-emitting diodes). A new approach for generating white light emission during dimming time was presented, and an AC-LED lamp with a flicker percentage drop of 29.9% was manufactured. Dynamic anti-counterfeiting applications were also presented. These discoveries are likely to hasten the development of new LLP materials. [ABSTRACT FROM AUTHOR]

This paper proposes a new optimized parameter model that enhances the pointing accuracy of moving-platform electro-optical telescopes (MPEOTs). The study begins by comprehensively analyzing the error sources, including the telescope and the platform navigation system. Next, a linear pointing correction model is established based on the target positioning process. To eliminate multicollinearity, stepwise regression is applied to obtain the optimized parameter model. The experimental results show that the MPEOT corrected by this model outperforms the mount model, with pointing errors of less than 50 arcsec for approximately 23 h. In the three tests conducted, the modified azimuth error(s) (RMS) were 14.07″, 12.71″, and 28.93″, and the elevation error(s) (RMS) were 12.94″, 12.73″, and 28.30″, respectively. [ABSTRACT FROM AUTHOR]

Objective: Cytokine storm syndrome is a fatal condition related to infectious and autoimmune diseases. Here, we aim to investigate the regulatory mechanisms of Blimp-1 on multiple cytokine production. Methods: The Blimp1 shRNA was transfected into RAW264.7 macrophages, followed by Toll-like receptor (TLR) ligand stimulation. The mRNA and protein levels of cytokines were detected by real-time PCR and flow cytometric bead array. The nuclear translocation of AP-1 and NF-κB p65 was measured by immunofluorescence staining. The transcriptional activity was detected by luciferase reporter assay with 5 × NF-κB reporter or with IL6 promoter reporter. Results: Blimp-1 significantly inhibited the expression and secretion of IL-1β, IL-6, and IL-18 in macrophages during stimulation with a variety of TLR ligands. The immunofluorescence staining results showed that Blimp-1 strictly controlled the nuclear translocation of NF-κB p65 in LPS-challenged macrophages. Furthermore, Blimp-1 directly inhibited the transcriptional activity of NF-κB and the transcription of IL6 gene. Conclusion: Blimp-1 represses the production of multiple pro-inflammatory cytokines by directly binding the genomic region and restricting the nuclear translocation and transcriptional activity of NF-κB. This finding may provide potential therapeutic strategies for the cytokine storm-related diseases. [ABSTRACT FROM AUTHOR]

Broadband near-infrared (NIR) phosphors have received increasing attention for fabricating NIR light sources. In this article, based on our predictions of heavy Mn-doped models obtained using DFT calculations, we successfully synthesize and characterize manganese-based magnetoplumbite-type La(Zn,Mn)Al11O19 phosphors, which crystallize into a hexagonal structure with space-group P63/mmc. Under excitation at 450 nm, it was found that LaZn0.7Mn0.3Al11O19 and LaZn0.2Mn0.8Al11O19 had the optimal emission intensity and the maximum quantum efficiencies were 99% and 55%, respectively. An anomalous near-infrared (NIR) emission band at ∼730 nm is observed for the LaZnAl11O19 host with heavy Mn2+ doping. The density functional theory calculations and transient and steady-state luminescence investigation suggest that this unusual NIR emission band comes from the Mn2+–Mn2+ dimers. Moreover, the as-prepared phosphor, being integrated into high-powered photonic devices, could operate at high temperature without degeneration, due to the great advantage of the phosphor-in-glass (PiG) approach. Consequently, our study not only develops a viable strategy for synthesising innovative NIR phosphors, but also sheds light on the development of high-power photonic devices and procedures. [ABSTRACT FROM AUTHOR]

Developing chemically and thermally stable, highly efficient green-emitting inorganic phosphors is a significant research field in solid-state lighting. In this work, we successfully tailor the properties of an yttrium silicate based Na3(Y,Sc)Si3O9:Eu2+ phosphor as a highly efficient green phosphor via crystal field engineering. The quantum efficiency (QE) and thermal stability of Na3(Y,Sc)Si3O9:Eu2+ were increased by 33% and 35%, respectively, via the combination of structure and bandgap engineering. Meanwhile, persistent luminescence (PersL) was observed, followed by a more thorough investigation of the relationship between the intensity of afterglow and Sc3+ concentration. Accordingly, the excitation temperature-dependent and fading thermoluminescence experiments are conducted, and the trap properties are deeply studied by the initial rising method. The results reveal the PersL mechanism and the significant role of Sc3+ as substitute ions. These results clearly indicate that our proposed designing concept of PersL materials are indeed effective and feasible, and the as-prepared Na3Y0.5Sc0.5Si3O9:Eu2+ phosphors are certainly promising for multifunctional applications. [ABSTRACT FROM AUTHOR]

Developing durable and highly active non‐noble electrocatalysts for oxygen evolution reaction (OER) is highly desirable for water splitting. Herein, we report a NiFe carbonate hydroxides embedded in a carbon nanotubes and graphite composite material (NiFe CHs‐CNT/G) by a facile and green precipitation method. The NiFe CHs are in‐situ grown on CNT/G using NH3⋅H2O as precipitant and CO2 in air as the source of CO32− under room temperature and pressure. The introduction of CNT/G not only improves the conductivity of material, but also enhances the combination of CNT/G and NiFe CHs nanosheets, thereby accelerating the transfer of electrons and reactants. Meanwhile, the catalyst with a special sandwich morphology provides larger active area to expose more active sites. Moreover, the effective interaction within the Ni and Fe in NiFe CHs‐CNT/G is benefiting for improving OER performance. All these lead to the optimized NiFe CHs‐CNT/G catalyst delivers an outstanding OER performance with a low overpotential of 300 mV at 10 mA cm−2 and a small Tafel slope of 60.13 mV dec−1. [ABSTRACT FROM AUTHOR]

The pathogenesis of liver fibrosis in nonalcoholic fatty liver disease (NAFLD) remains unclear and the effective treatments have not been explored yet. The activation of hepatic stellate cells (HSCs) is considered as the most critical factor in the progression of liver fibrosis and cirrhosis. Autophagy has recently been identified as a new mechanism to regulate HSC activation. Here, we found that liver macrophages were polarized toward type 2 (M2) during the progression of nonalcoholic steatohepatitis (NASH) and liver fibrosis in both patients and NAFLD mice. Using the methionine–choline-deficient (MCD) diet NAFLD murine model and the in vitro cell culture system, we identified that the M2 macrophages promoted HSC autophagy by secreting prostaglandin E2 (PGE2) and binding its receptor EP4 on the surface of HSCs, which consequently enhanced HSC activation, extracellular matrix deposition, and liver fibrosis. Mechanistically, PGE2/EP4 signals enhanced HSC autophagy through the Erk pathway. A specific PGE2/EP4 antagonist E7046 significantly inhibited M2 macrophage-mediated HSC autophagy and improved liver fibrosis and histopathology in NAFLD mice. Our study provides novel mechanistic insights into the regulation of HSC activation and liver fibrosis. Our findings suggest that the PGE2/EP4 pathway is a promising therapeutic target to prevent NASH progression into cirrhosis. [ABSTRACT FROM AUTHOR]

Transparent glass-ceramics are a highly attractive class of materials for photonic applications. Transition metal ions are promising candidates for luminescence centers thanks to the sensitivity of the ligand ions to d–d electron transition. Here, broadband second near-infrared (NIR-II) photoluminescence was achieved via precipitation of ZnGa2O4:Ni2+ nanocrystals within a zinc gallium–silicate glass matrix by a crystallization process. Excited by 260 nm UV photons, ZnGa2O4:Ni2+ GC displays NIR-II emission peaking at 1240 nm and has a full width at half maximum wider than 288 nm, attributed to 3T2g(3F) → 3A2g(3F) electronic transition of octahedrally coordinated Ni2+ ions. Moreover, broad persistent luminescence of Ni2+ ions can be effectively obtained after irradiation in UV light. Based on the electron paramagnetic resonance spectra and a thermoluminescence method, a physical model was constructed to demonstrate the mechanism of persistent luminescence. This developed afterglow luminescent glass-ceramic exhibits potential applications in biological imaging. [ABSTRACT FROM AUTHOR]

In wireless sensor networks, dynamic environmental changes may lead to the distribution of some sensors becoming very dense, which leads to the waste of communication resources in distributed estimation. In this paper, it is proposed that Event‐triggered distributed dynamic adaptive‐neighbour selection LMS (ET‐dyANDLMS) algorithm can effectively solve the problems mentioned above. On the one hand, the network communication resources are reduced by the adaptive‐neighbour selection. On the other hand, the network data redundancy is reduced by the event‐trigger mechanism. From a theoretical point of view, the algorithm converges stably in mean meaning and mean square meaning, and the communication cost is reduced compared with other distributed algorithms. The theoretical analysis results verified by experimental simulation demonstrate the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

With the development of distributed algorithms, many researchers are committed to the goal of maintaining the long-term stability of the network by reducing the communication cost. However, many algorithms that lessen communication costs often result in a significant decrease in estimation accuracy. In order to reduce the communication cost with less performance degradation, the distributed neighbor-partial diffusion least-mean-square algorithm (NPDLMS) is proposed in this paper. Besides, considering the data redundancy in the network, we offer the distributed data selection NPDLMS algorithm, which further improves the estimation accuracy and reduces the communication cost. In the performance analysis, the stability and the communication cost of the algorithms are given. [ABSTRACT FROM AUTHOR]

In wireless sensor networks, the dynamic network topology and the limitation of communication resources may lead to degradation of the estimation performance of distributed algorithms. To solve this problem, we propose an event-triggered adaptive partial diffusion least mean-square algorithm (ET-APDLMS). On the one hand, the adaptive partial diffusion strategy adapts to the dynamic topology of the network while ensuring the estimation performance. On the other hand, the event-triggered mechanism can effectively reduce the data redundancy and save the communication resources of the network. The communication cost analysis of the ET-APDLMS algorithm is given in the performance analysis. The theoretical results prove that the algorithm is asymptotically unbiased, and it converges in the mean sense and the mean-square sense. In the simulation, we compare the mean-square deviation performance of the ET-APDLMS algorithm and other different diffusion algorithms. The simulation results are consistent with the performance analysis, which verifies the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]