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The first steel is the most prevalent material used in building. Steel’s intrinsic hardness and durability make it appropriate for different uses, but its greater adaptability makes it ideal for seismic design. The brittle fracture occurred in welded moment connections of steel structures, which were originally thought to be ductile for resistance to earthquakes. The research aims to optimize structural parameters in steel structure seismic design. This paper presents an effective technique for the best seismic design of steel structures, which consists of two computational methodologies. First, particle swarm optimization (PSO) was presented to accurately define the structural characteristics in the seismic design of steel constructions, then a feed-forward neural network (FFNN) to determine unconventional seismic design methodologies for steel frameworks, precisely forecast the structural responses, and improve seismic resistance and dependability under dynamic conditions by using high-tech components and technological advancements. This study presents designing a realistic storey steel moment-resisting frame (MRF) structure and maximum weight under full seismic loading. The outcome demonstrates the reduction in generations that was accomplished during the optimization procedure. Although the PSO method in the paper converges in lower generations, the process indeed requires a significant amount of computing power. The FFNN approach involves the suggestion of a neural network model that works well to predict the necessary structural reactions during optimization. The proposed model considerably minimizes the total computation time. Study aims to improve the seismic analysis of steel using PSO along with forecasting structural responses using a network of feed-forward neural networks (FFNN) to enhance accuracy and reduce the computation time (2.4 min). The proposed FFNN model is more accurate than earlier methods, with the lowest MAPE values in S_IO (3.0661), S_LS (3.562), and S_CP (3.9252). Moreover, it reveals the highest predictive precision with the lowest RRMSE values of 0.0231 (S_IO), 0.0281 (S_LS), and 0.0314 (S_CP). Moreover, the FFNN model has a competitive run time of 2.4 minutes while possessing good goodness-of-fit, with 1.0096, 1.0995, and 0.9925 of R2 for S_IO, S_LS, and S_CP, respectively. As compared to WCFBP-RB, the proposed PSO+FFNN model has better prediction for S_IO, where the predicted value of 0.7879 is almost identical to the actual value of 0.8000. As compared to WCFBP-RB, the model predicts 1.4085 for S_LS, while the actual value is 1.4388. For S_CP, PSO+FFNN predicts 1.8621, which is more precise than WCFBP-RB and almost equals the actual figure of 1.9000.

This article investigates the thermodynamic properties of the SU(2) Nambu–Jona–Lasinio (NJL) model under the chiral chemical potential μ 5 , employing Tsallis non-extensive statistics. The introduction of the parameter q , which characterizes the non-extensivity of the system through Tsallis statistics, offers a novel perspective for studying the behavior of strongly interacting matter under extreme conditions. By calculating thermodynamic quantities such as quark mass, critical temperature, chiral density, pressure, entropy, and speed of sound, we systematically analyze the effects of μ 5 and q on these quantities. It is observed that both μ 5 and q exhibit an inverse relationship with the critical temperature T pc , while showing a positive correlation with the chiral density n 5 .

By using the method of weight function, the technique of real analysis, and the theory of special functions, a multi-parameter Hilbert-type integral inequality and its equivalent form are established, and their constant factors are proved to be the best possible. The expressions of operator with norm are given. As an application, relevant results in the references and some new inequalities are obtained by assigning some parameter values.

Based on the two-flavor NJL model with Tsallis non-extensive statistics, this work explores the QCD phase structure and thermodynamic properties under strong magnetic fields and chiral imbalance. The Tsallis parameter q captures non-equilibrium effects relevant to heavy-ion collisions. Key findings reveal that the critical temperature T c decreases with increasing q , indicating that non-equilibrium conditions promote chiral symmetry restoration at lower temperatures. The chiral chemical potential μ 5 significantly alters the magnetic response, with a transition from magnetic catalysis to inverse magnetic catalysis under certain conditions. For q > 1 , non-monotonic behavior of T c with magnetic field eB emerges. Pressure becomes anisotropic under strong eB , and the speed of sound exhibits a dip near T c , shifting to lower temperatures with larger q . These results highlight how non-extensive statistics, chiral imbalance, and magnetic fields collectively influence the QCD phase diagram and thermodynamic observables, offering insights for interpreting heavy-ion collision data.

The driving force for active physical and biological systems is determined by both the underlying landscape and nonequilibrium curl flux. While landscape can be experimentally quantified from the histograms of the collected real-time trajectories of the observables, quantifying the experimental flux remains challenging. In this work, we studied the single-molecule enzyme dynamics of horseradish peroxidase with dihydrorhodamine 123 and hydrogen peroxide (H₂O₂) as substrates. Surprisingly, significant deviations in the kinetics from the conventional Michaelis–Menten reaction rate were observed. Instead of a linear relationship between the inverse of the enzyme kinetic rate and the inverse of substrate concentration, a nonlinear relationship between the two emerged. We identified nonequilibrium flux as the origin of such non-Michaelis–Menten enzyme rate behavior. Furthermore, we quantified the nonequilibrium flux from experimentally obtained fluorescence correlation spectroscopy data and showed this flux to led to the deviations from the Michaelis–Menten kinetics. We also identified and quantified the nonequilibrium thermodynamic driving forces as the chemical potential and entropy production for such non-Michaelis–Menten kinetics. Moreover, through isothermal titration calorimetry measurements, we identified and quantified the origin of both nonequilibrium dynamic and thermodynamic driving forces as the heat absorbed (energy input) into the enzyme reaction system. Furthermore, we showed that the nonequilibrium driving forces led to time irreversibility through the difference between the forward and backward directions in time and high-order correlations were associated with the deviations from Michaelis–Menten kinetics. This study provided a general framework for experimentally quantifying the dynamic and thermodynamic driving forces for nonequilibrium systems.

Alzheimer’s disease is a progressive neurodegenerative disorder with no cure, making preventive strategies crucial. Dietary interventions, particularly the Mediterranean (MeDi) and MIND diets, have been associated with reduced cognitive decline, but their long-term comparative effects remain underexplored. To compare the long-term neuroprotective effects of the Mediterranean and MIND diets in healthy individuals and AD patients, assess dietary adherence and cognitive function relationships, and investigate the impact of micronutrients on cognitive biomarkers. A 5-year prospective cohort study was conducted with 1500 participants (750 healthy controls, 750 AD patients). Dietary adherence was assessed using validated dietary screening tools. Cognitive function was evaluated via MMSE and MoCA scores, while biomarkers (amyloid-beta, tau, NfL, CRP, IL-6, TNF-α, polyphenols, omega-3, and B vitamins) were measured through blood and CSF samples. Machine learning techniques were utilized to analyze dietary patterns and predict cognitive trajectories. Higher adherence to both diets was associated with significantly better cognitive scores ( p  < 0.0001), lower amyloid-beta, tau, and NfL levels, and reduced inflammatory markers (CRP, IL-6, TNF-α). The MIND diet showed a slightly stronger association with cognitive protection than MeDi. Micronutrients such as polyphenols, omega-3, and B vitamins correlated with improved cognitive performance. Genetic analysis suggested that APOE-ε4 carriers may experience variable responses to dietary interventions. The Mediterranean and MIND diets provide significant neuroprotection against cognitive decline and AD progression. While both diets confer benefits, the MIND diet demonstrated a marginally greater impact on cognitive preservation. These findings underscore the importance of dietary interventions as non-pharmacological strategies for AD prevention and management. Further research is needed to optimize dietary recommendations based on genetic predisposition and metabolic factors.

Rhodiola rosea is a valuable functional medicinal plant widely utilized in China and other Asian countries for its anti-fatigue, anti-aging, and altitude sickness prevention properties. Salidroside, a most active constituent derived from Rhodiola rosea , exhibits potent antioxidative, hypoxia-resistant, anti-inflammatory, anticancer, and anti-aging effects that have garnered significant attention. The appreciation of the pharmacological role of salidroside has burgeoned over the last decade, making it a beneficial option for the prevention and treatment of multiple diseases, including atherosclerosis, Alzheimer’s disease, Parkinson’s disease, cardiovascular disease, and more. With its anti-aging and renoprotective effects, in parallel with the inhibition of oxidative stress and inflammation, salidroside holds promise as a potential therapeutic agent for kidney damage. This article provides an overview of the microinflammatory state in kidney disease and discuss the current therapeutic strategies, with a particular focus on highlighting the recent advancements in utilizing salidroside for renal disease. The potential mechanisms of action of salidroside are primarily associated with the regulation of gene and protein expression in glomerular endothelial cells, podocytes, renal tubule cells, renal mesangial cells and renal cell carcinoma cell, including TNF-α, TGF-β, IL-1β, IL-17A, IL-6, MCP-1, Bcl-2, VEGF, ECM protein, caspase-3, HIF-1α, BIM, as well as the modulation of AMPK/SIRT1, Nrf2/HO-1, Sirt1/PGC-1α, ROS/Src/Cav-1, Akt/GSK-3β, TXNIP-NLRP3, ERK1/2, TGF-β1/Smad2/3, PI3K/Akt, Wnt1/Wnt3a β-catenin, TLR4/NF-κB, MAPK, JAK2/STAT3, SIRT1/Nrf2 pathways. To the best of our knowledge, this review is the first to comprehensively cover the protective effects of salidroside on diverse renal diseases, and suggests that salidroside has great potential to be developed as a drug for the prevention and treatment of metabolic syndrome, cardiovascular and cerebrovascular diseases and renal complications.

Elevated CO 2 concentrations have been observed to accelerate flowering time in Arabidopsis through the action of a highly conserved regulatory network controlled by miR156 and miR172. However, the network’s robustness to the impact of increasing CO 2 concentrations on flowering time remains poorly understood. In this study, we investigate this question by conducting a comprehensive analysis of the global landscape of network dynamics, including quantifying the probabilities associated with juvenile and flowering states and assessing the speed of the transition between them. Our findings reveal that a CO 2 concentration range of 400–800ppm only mildly advances flowering time, contrasting with the dramatic changes from 200 to 300ppm. Notably, the feedback regulation of miR156 by squamosal promoter binding protein-like proteins (SPLs) plays a substantial role in mitigating the effects of increasing CO 2 on flowering time. Intriguingly, we consistently observe a correlation between delayed flowering time and increased variance in flowering time, and vice versa, suggesting that this might be an intrinsic adaptation mechanism embedded within the network. To gain a deeper understanding of this network’s dynamics, we identified the sensitive features within the feedback loops of miR156 SPLs and miR172—APETALA2 family proteins (AP2s), with the latter proving to be the most sensitive. Strikingly, our study underscores the indispensability of all feedback regulations in maintaining both juvenile and adult states as well as the transition time between them. Together, our research provides the first physical basis in plant species, aiding in the elucidation of novel regulatory mechanisms and the robustness of the miRNAs-regulated network in response to increasing CO 2 , therefore influencing the control of flowering time. Moreover, this study provides a promising strategy for engineering plant flowering time to enhance their adaptation and resilience.

Acute myocardial infarction (AMI) is one of the most common cardiovascular diseases that leads to high mortality and morbidity globally. Various therapeutic targets for AMI have been investigated in recent years, including the non‐coding RNAs (ncRNAs). NcRNAs, a class of RNA molecules that typically do not code proteins, are divided into several subgroups. Among them, microRNAs (miRNAs) are widely studied for their modulation of several pathological aspects of AMI, including cardiomyocyte apoptosis, inflammation, angiogenesis and fibrosis. It has emerged that long ncRNAs (lncRNAs) and circular RNAs (circRNAs) also regulate these processes via interesting mechanisms. However, the regulatory functions of ncRNAs in AMI and their underlying functional mechanisms have not been systematically described. In this review, we summarize the recent findings involving ncRNA actions in AMI and briefly describe the novel mechanisms of these ncRNAs, highlighting their potential application as therapeutic targets in AMI.

Intermetallic compounds (IMCs) with fixed chemical composition and ordered crystallographic arrangement are highly desirable platforms for elucidating the precise correlation between structures and performances in catalysis. However, diffusing a metal atom into a lattice of another metal to form a controllably regular metal occupancy remains a huge challenge. Herein, we develop a general and tractable solvothermal method to synthesize the Bi-Pd IMCs family, including Bi 2 Pd, BiPd, Bi 3 Pd 5 , Bi 2 Pd 5 , Bi 3 Pd 8 and BiPd 3 . By employing electrocatalytic CO 2 reduction as a model reaction, we deeply elucidated the interplay between Bi-Pd IMCs and key intermediates. Specific surface atomic arrangements endow Bi-Pd IMCs different relative surface binding affinities and adsorption configuration for *OCHO, *COOH and *H intermediate, thus exhibiting substantially selective generation of formate (Bi 2 Pd), CO (BiPd 3 ) and H 2 (Bi 2 Pd 5 ). This work provides a comprehensive understanding of the specific structure-performance correlation of IMCs, which serves as a valuable paradigm for precisely modulating catalyst material structures. Precise synthesis of Intermetallic compounds and understanding of the structure-performance correlation are highly desirable in catalysis. Here, the authors develop a general method to synthesize up to six BiPd intermetallic compounds and study the mechanism toward the electrocatalytic carbon dioxide reduction reaction.