To resolve the conflict between equipment degradation and quality control in production-storage systems under random demand, this paper proposes a joint optimization model that treats production cycles and economic specification limits as decision variables. It innovatively establishes a linkage mechanism between the internal state of equipment and product quality. Specifically, the Gamma process characterizes continuous degradation, while a linear mapping model transforms unobservable degradation states into observable quality attributes. A quadratic loss function quantifies the quality loss, and a genetic algorithm (GA) optimizes the joint model. The effectiveness of this model was validated through numerical experiments based on a hybrid power generation system. Results demonstrate that this joint optimization strategy significantly reduces total system costs and exhibits robust performance under diverse demand distributions. By transforming fixed economic specification limits into decision variables, this study provides a theoretical foundation for enterprises to achieve reliability management and cost control under the dual uncertainties of random demand and equipment degradation.
Organic electrode materials (OEMs) have shown great potential for various electrochemical energy storage applications (EESs) due to their high theoretical capacity, structure designability, environmental friendliness, and low cost. However, OEMs face several inherent challenges, such as low electronic conductivity and detrimental structural evolution. Here, 2D MXenes have shown enormous potential to solve the issues of OEMs owing to their metallic conductivity, abundant surface chemistry, and exceptional mechanical strength. Serving as a multifunctional conductive scaffold, MXene not only enhances the electronic conductivity of the MXene/OEMs composites to facilitate the electron/ion transport but also addresses electrochemical instability issues via physical/chemical interaction, thereby endowing the MXene/OEMs composites with improved electrochemical performance. This review offers a comprehensive examination of the advancements in MXene/OEMs composites for EESs. It introduces various strategies for combining MXene with different OEMs, including small-molecules/polymers, conducting polymers, metal–organic frameworks, and covalent organic frameworks, along with their structural characteristics. The discussion extends to the application of MXene/OEMs composites in various EESs, emphasizing the corresponding structure-performance relationships. Lastly, the review outlines the challenges and future perspectives for research on MXene/OEMs composites, aiming to provide a foundational reference for the development of advanced MXene/OEMs composites designed for high-performance EESs.
In practical engineering applications, curved structures rarely conform to idealized rectangular or circular planforms and often involve far more intricate geometries. Among these, L-shaped spherical panels have emerged as a structurally significant form, found in subsystem interfaces, aerospace fuselage junctions, complex biomedical shells, and multifunctional architectural surfaces. This study explores the free damped-vibration behavior of such panels constructed from a graphene platelet (GPL)-reinforced magnetorheological elastomer (MRE) nanocomposite. Unlike conventional elastic matrices, the MRE base material exhibits time- and fielddependent viscoelastic behavior, influenced by both magnetic field intensity and ferromagnetic content. This behavior is mathematically formulated through an experimentally validated generalized Kelvin-Voigt-type model, tailored to represent the storage and dissipation characteristics of the matrix under dynamic excitation. The reinforcing particles are graded through the panel thickness. The effective elastic properties of the composite are homogenized using the Halpin-Tsai micromechanical model, accounting for the influence of GPL content and sizes. To address the geometric complexity, a hybrid element-based GDQ (generalized differential quadrature) approach is developed. The L-shaped spherical panel is subdivided into rectangular elements, each governed by equations derived using Hamilton's principle, first-order shear deformation theory, and Sander's straindisplacement relations. Discretization via quadrature nodes enables the GDQ method to transform the governing PDEs into an efficient algebraic system. The global system is constructed by enforcing both displacement and force continuity at shared nodes and applying appropriate boundary conditions. The proposed framework achieves excellent accuracy in capturing frequencies and loss factors, demonstrating its capability for efficient dynamic analysis of non-standard. In addition to validating the accuracy of the proposed approach against benchmark problems, the study reveals distinct mode-switching and mode-jumping phenomena triggered by changes in geometric parameters-highlighting the sensitivity of vibrational behavior to panel shape and reinforcing the need for precise modeling in advanced smart structures.
The anodic small-molecule electrooxidation reaction, which is both thermodynamically and kinetically more favorable than the oxygen evolution reaction, when coupled with the hydrogen evolution reaction, has garnered increasing attention and achieved significant progress. This method presents a promising avenue for hydrogen production at industrial current densities (≥ 200 mA/cm2) via water electrolysis while enabling the synthesis of value-added products or the removal of pollutants. However, the correlations among anode small-molecule types, catalyst design, reaction mechanisms, and electrolytic cell configuration remain unclear at industrial current densities. In this review, the characteristics and challenges of hydrogen production via coupling with various small-molecule oxidation reactions at industrial current densities are discussed for the first time, emphasizing key advances in catalyst design–substrate correlations, reaction mechanisms, and electrolytic cell configuration. Additionally, the challenges and future prospects of this field are explored.
Increasing evidence indicates that long non-coding RNAs (lncRNAs) antisense non-coding RNA in the INK4 locus (ANRIL) has been involved in various diseases and promotes tumorigenesis and cancer progression as an oncogenic gene. However, the effect of ANRIL on chemoresistance remains still unknown in colorectal cancer (CRC). Here, we investigated ANRIL expression in 63 cases of colorectal cancer specimens and matched normal tissues. Results revealed that ANRIL was up-regulated in tumor tissues samples from patients with CRC and CRC cell lines. Increased ANRIL expression in CRC was associated with poor clinical prognosis. Kaplan-Meier analysis showed that ANRIL was associated with overall survival of patients with colorectal cancer, and patients with high ANRIL expression tended to have unfavorable outcome. In vitro experiments revealed that ANRIL knockdown significantly inhibited CRC cell proliferation, improved the sensitivity of chemotherapy and promoted apoptosis. Further functional assays indicated that ANRIL overexpression significantly promoted cell chemoresistance by regulating ATP-binding cassette subfamily C member 1 through binding Let-7a. Taken together, our study demonstrates that ANRIL could act as a functional oncogene in CRC, as well as a potential therapeutic target to inhibit CRC chemoresistance.
