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This review provides a comprehensive analysis of the critical role played by macrophages and their underlying mechanisms in the progression of diabetic cardiomyopathy (DCM). It begins by discussing the origins and diverse subtypes of macrophages, elucidating their spatial distribution and modes of intercellular communication, thereby emphasizing their significance in the pathogenesis of DCM. The review then delves into the intricate relationship between macrophages and the onset of DCM, particularly focusing on the epigenetic regulatory mechanisms employed by macrophages in the context of DCM condition. Additionally, the review discusses various therapeutic strategies aimed at targeting macrophages to manage DCM. It specifically highlights the potential of natural food components in alleviating diabetic microvascular complications and examines the modulatory effects of existing hypoglycemic drugs on macrophage activity. These findings, summarized in this review, not only provide fresh insights into the role of macrophages in diabetic microvascular complications but also offer valuable guidance for future therapeutic research and interventions in this field.

Spatial truss structures (STSs), serving as the bottom support structure of a cooling tower, effectively harness the superior load-bearing capacity offered by lattice-type truss structures. STSs are composed of main bars, diagonal bars, and horizontal bars, with horizontal bars serving as vital components of the truss structure. They play a pivotal role in maintaining the overall integrity and stability of the structure. The proportional relationship between the stiffness of each bar in STSs has a profound impact on the mechanical characteristics of the overall structure. This relationship directly influences the ultimate load-bearing capacity of the structure. Therefore, conducting research on the influence patterns of this relationship is of utmost importance. This paper explores the study of triangular truss structures (TTSs) and quadrilateral truss structures (QTSs). Firstly, through theoretical analysis, considering structural elements such as the stiffness of the horizontal bars, the number of layers in the truss, and the angle between the diagonal bars and the horizontal bars, theoretical expressions for the calculation of the ultimate load capacity of TTSs and QTSs are derived. Furthermore, a parametric finite element (FE) model was established for the TTSs and QTSs. Through numerical simulations, the validity of the theoretical calculation expressions was verified. Finally, this paper discusses the influence of factors such as the stiffness of the horizontal bars, the number of layers in the truss, and the angle between the diagonal and horizontal bars on the TTSs and QTSs. It analyzes the patterns and trends of these influences. The research results indicate that the theoretical and numerical simulation results for the TTSs have an error ranging from 0.40% to 4.93%, while the relative error for the QTSs ranges from 1.59% to 4.88%. These errors are within an acceptable range for engineering calculations. As the stiffness of the horizontal bars increases, the proportionality coefficient of the truss’s ultimate load capacity shows an initial increase followed by a stable trend. It reaches an equilibrium state when the stiffness of the horizontal bars reaches a certain threshold. As the number of layers in the truss and the angle between the diagonal and horizontal bars increase, the proportionality coefficient of the load capacity gradually decreases. The research findings provide a theoretical basis for the application of TTSs and QTSs in cooling towers.

In this paper, the effect of Alcaligenes sp. on the corrosion process of X65 steel was investigated by using non-targeted metabolomics techniques for comprehensive characterization of metabolites, combined with surface analysis techniques and electrochemical testing. The results showed that the organic acids produced by Alcaligenes sp. accelerated the corrosion process of X65 steel in the early stage, and the presence of Alcaligenes sp. promoted the deposition of stable corrosion products and minerals in the middle and late stages. In addition, proteoglycans and corrosion inhibiting substances were enriched on the metal surface, which enhanced the stability of the film. The combined effect of multiple factors makes the mixed film of biofilm and corrosion products more dense and complete, which effectively inhibits the corrosion of X65 steel.

A large amount of wet-discharged fly ash has caused serious harm to the ecological environment, so the utilization of fly ash has received attention. This paper analyzes the formation of products of fly ash–lime system under the autoclave process by X-ray diffraction (XRD) analysis and thermogravimetric–differential thermal (TG-DSC) analysis. The hydrothermal reaction product generation was quantitatively analyzed using the hydrochloric acid selective dissolution method to quantify the degree of reaction of fly ash in the pressure evaporation specimens in combination with the reaction degree of lime in the autoclave specimens. The hydrothermal reaction products were calcined and hydrated, and the mineral composition of the calcined products and the mechanical and microstructure of the hydrated products were analyzed. The results show that hydrothermal reactions occur in the fly ash–lime pressure evaporation system to produce C2SH, C3AH6, C3ASH4, and other products. The optimum ratio of lime is 22%, and the appropriate autoclave parameter is 140 °C for 8 h. Under this condition, the reaction degree of fly ash is 15.39%, the reaction degree of CaO is 78.63%, and its f-CaO value is 4.93%. The formation of C2SH in the hydrothermal reaction ranged from 14.33% to 18.53%, and the formation of C3ASH4 ranged from 14.06% to 15.26%. The hydrothermal reaction products were calcined at 850 °C for 1.5 h to produce new gelling materials with gelling phases, such as C12A7, α’L-C2S, β-C2S, and C2AS. The compressive and flexural strengths of the new gelling materials reached 34.4 MPa and 6.4 MPa, respectively, at the age of 180 days.

Advanced Persistent Threat (APT) is now the most common network assault. However, the existing threat analysis models cannot simultaneously predict the macro-development trend and micro-propagation path of APT attacks. They cannot provide rapid and accurate early warning and decision responses to the present system state because they are inadequate at deducing the risk evolution rules of network threats. To address the above problems, firstly, this paper constructs the multi-source threat element analysis ontology (MTEAO) by integrating multi-source network security knowledge bases. Subsequently, based on MTEAO, we propose a two-layer threat prediction model (TL-TPM) that combines the knowledge graph and the event graph. The macro-layer of TL-TPM is based on the knowledge graph to derive the propagation path of threats among devices and to correlate threat elements for threat warning and decision-making; The micro-layer ingeniously maps the attack graph onto the event graph and derives the evolution path of attack techniques based on the event graph to improve the explainability of the evolution of threat events. The experiment’s results demonstrate that TL-TPM can completely depict the threat development trend, and the early warning results aremore precise and scientific, offering knowledge and guidance for active defense. [ABSTRACT FROM AUTHOR]

Cyber Threat Intelligence (CTI) is a valuable resource for cybersecurity defense, but it also poses challenges due to its multi-source and heterogeneous nature. Security personnel may be unable to use CTI effectively to understand the condition and trend of a cyberattack and respond promptly. To address these challenges, we propose a novel approach that consists of three steps. First, we construct the attack and defense analysis of the cybersecurity ontology (ADACO) model by integrating multiple cybersecurity databases. Second, we develop the threat evolution prediction algorithm (TEPA), which can automatically detect threats at device nodes, correlate and map multisource threat information, and dynamically infer the threat evolution process. TEPA leverages knowledge graphs to represent comprehensive threat scenarios and achieves better performance in simulated experiments by combining structural and textual features of entities. Third, we design the intelligent defense decision algorithm (IDDA), which can provide intelligent recommendations for security personnel regarding the most suitable defense techniques. IDDA outperforms the baseline methods in the comparative experiment. [ABSTRACT FROM AUTHOR]

Ten novel molecular tweezer anion receptors based on diphenic acid carbonyl thiosemicarbazide have been designed and synthesised in high yield and their binding properties were examined by UV-Vis spectra titration. Their structures were characterised by 1H NMR, IR, MS spectra and elemental analysis. [ABSTRACT FROM AUTHOR]

A rapid, efficient and environmentally friendly methodology has been developed for the synthesis of indole-3-carboxaldehyde thiosemicarbazones by using aluminum oxide as the solid support under microwave assisted solvent-free conditions. Compared with the conventional heating method, this method gave the target products in good yield. [ABSTRACT FROM AUTHOR]