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With the development of the social informatization, the demand for optical fiber communication system capacity continues to grow. Channel impairment has always been the key factor limiting the capacity in optical fiber communication system. As the basic function and key technology in optical fiber communication system, channel impairment compensation is constantly improved. Applying deep learning technology in channel impairment compensation of optical fiber communication has attracted the attention of many researchers. This paper introduces the common deep learning models used and the development of deep learning technology for impairments compensation of optical fiber communication systems in recent years.

The accumulation of ice and snow will have a great impact on industry and people's lives. People usually adopted active deicing method for deicing in the past, which is characterized by high energy consumption, low efficiency, and high cost. Passive anti‐icing materials are the most widely used due to their low icing adhesion strength and energy saving, but passive anti‐icing materials tend to lose anti‐icing performance after mechanical damage or following exposure to harsh environments resembling low temperatures, high humidity. Recently, new anti‐icing materials have been rationally designed through the combination of passive and active anti‐icing, exhibiting high‐efficiency and energy‐saving anti‐icing properties. The design idea is that low surface energy polymers combine photothermal and electrothermal particles to achieve photothermal and electrothermal superhydrophobic anti‐icing. Anti‐icing materials are easily damaged after long‐term outdoor use, so the self‐healing capabilities of the materials are important. This review briefly introduces the ice formation mechanism and anti‐icing methods, focusing on the recent progress in the structural design of superhydrophobic, photothermal, electrothermal, and self‐healing anti‐icing materials. The design of the new generation of anti‐icing materials will be a combination of active and passive anti‐icing, which can achieve ideal all‐weather anti‐icing and deicing and repair the damage during long‐term use. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the underlying molecular mechanisms of Withaferin A (WA) in hepatocellular carcinoma (HCC). The gene and protein expression were analyzed using RT-qPCR and western blot, respectively. The proliferation of HCC cells was evaluated by CCK-8 assays. The migrative ability of HCC cells was measured by transwell assays. We revealed that WA suppressed the proliferation and migration of HCC cells and inhibited IGF2BP3 (insulin like growth factor 2 mRNA binding protein 3) expression. IGF2BP3 abundance reversed the reactive oxygen species (ROS) accumulation and suppression of HCC cell proliferation and migration induced by WA. Besides, IGF2BP3 suppressed ROS production to promote the growth and migration of HCC cells. Furthermore, we found that IGF2BP3 exerted its tumor-promotive and ROS-suppressive effect on HCC cells by regulating the expression of FOXO1 (forkhead box O1). In addition, IGF2BP3-stimulated activation of JAK2 (Janus kinase 2)/STAT3 (signal transducer and activator of transcription 3) phosphorylation effectively decreased the transcription of FOXO1. FOXO1 abundance decreased the phosphorylation of JAK2 and STAT3 by increasing ROS level, forming a feedback loop for the inhibition of JAK2/STAT3 signaling activated by IGF2BP3. WA-induced ROS inhibited HCC cell growth and migration through the inhibition of IGF2BP3 to deactivate JAK2/STAT3 signaling, resulting in increased FOXO1 expression to further stimulate ROS production and inhibit JAK2/STAT3 signaling. [ABSTRACT FROM AUTHOR]

Purpose: To investigate the correlation between tumor volume reduction rate (TVRR) and prognosis in patients with diverse clinical types of nasopharyngeal carcinoma (NPC) undergoing chemoradiotherapy, thereby aptly categorizing risks and directing the personalized treatment of NPC. Materials and Methods: A total of 605 NPC patients with varying clinical types were enrolled in this study and subsequently segregated into six subgroups based on their clinical types and TVRR. To accentuate the efficacy of grouping, Groups 1–6 underwent clustered analysis of hazard atio (HR) values pertaining to progression‐free survival (PFS), forming three risk clusters denoted as low, intermediate, and high. The log‐rank test was employed to discern differences, and R 4.1.1 was utilized for cluster analysis. Results: According to survival rates, we classified the first (G2 and G4), second (G1 and G6), and third (G3 and G5) risk clusters as low‐, intermediate‐, and high‐risk, respectively. When comparing risk stratification with the 8th edition of the TNM staging system, our classification exhibited superior predictive prognostic performance. Subgroup analysis of treatments for each risk cluster revealed that the PFS in the neoadjuvant chemotherapy (NACT) + concurrent chemoradiotherapy (CCRT) group surpassed that of the CCRT group significantly (p < 0.05). Conclusion: The reliance on clinical types and TVRR facilitates risk stratification of NPC during chemoradiotherapy, providing a foundation for physicians to tailor therapeutic strategies. Moreover, the risk cluster delineated for NPC patients during the mid‐term of chemoradiotherapy stands as an independent prognostic factor for progression‐free survival (PFS), overall survival (OS), distantmetastasis‐free survival (DMFS), and local recurrence‐free (LRRFS) posttreatment. Additionally, individuals in the high‐risk cluster are recommended to undergo adjuvant chemotherapy after CCRT. [ABSTRACT FROM AUTHOR]

Fundamental understanding of the synergistic effect of bimetallic catalysts is of extreme significance in heterogeneous catalysis, but a great challenge lies in the precise construction of uniform dual‐metal sites. Here, we develop a novel method for constructing Pt1−Fe1/ND dual‐single‐atom catalyst, by anchoring Pt single atoms on Fe1−N4 sites decorating a nanodiamond (ND) surface. Using this catalyst, the synergy of nitroarenes selective hydrogenation is revealed. In detail, hydrogen is activated on the Pt1−Fe1 dual site and the nitro group is strongly adsorbed on the Fe1 site via a vertical configuration for subsequent hydrogenation. Such synergistic effect decreases the activation energy and results in an unprecedented catalytic performance (3.1 s−1 turnover frequency, ca. 100 % selectivity, 24 types of substrates). Our findings advance the applications of dual‐single‐atom catalysts in selective hydrogenations and open up a new way to explore the nature of synergistic catalysis at the atomic level. [ABSTRACT FROM AUTHOR]

This paper deals with the cyclic-periodic structure with piezoelectric shunt circuits or a parallel piezoelectric network. The objective is to obtain the vibration suppression effect of them on the cylic-periodic structure. The background of the research is about vibration reduction of bladed disks in aero-engines, and the system is simulated by a lumped parameter model. The tuned and mistuned dynamic equations of the system are derived. The method of equivalent blisk model (EBM) is used to identify the lumped parameters of a finite element model, which is related to the experimental model. Then the Modified Modal Assurance Criterion (MMAC) is used to evaluate the vibration suppression ability of shunt circuits and the network. The numerical results show that both of these two systems can control vibration well, even the mechanical and electrical mistuning level are up to 10 %, and there is an optimal resistance which can be used to design the system to get a good performance of vibration suppression. An experiment is performed to validate the analytical results. The experimental results demonstrate that the ability of vibration suppression for both two systems are almost the same, but the piezo-network has an advantage in vibration delocalization of the mistuned system. [ABSTRACT FROM AUTHOR]