Search Results (11,729)

This work proposes an Adaptive Neural Control for the asymptotic stabilization of a chain of integrators at the origin. The proposed approach addresses the stabilization of the integrator chain by means of a control law whose applied signal is structurally bounded to $(-1,1)$ by the hyperbolic tangent architecture, i.e., $u\left(t\right)=tanh\left(z\right)$, where z represents a weighted linear combination of the system states and a bias term. Furthermore, an adaptation law for the weights is proposed, based on the classical backpropagation algorithm for neural networks. The stability analysis is conducted using singular perturbation theory, demonstrating that, under a sufficiently high learning rate, the closed-loop system exhibits a Standard Singular Perturbation Form. This formulation allows for the analysis of the system across two distinct time scales: the adaptation dynamics (fast subsystem) and the state dynamics (slow subsystem). Based on this formulation, explicit conditions on the learning rate and the initial conditions are derived to guarantee local asymptotic stability using Tikhonov’s theorem. These conditions characterize the region of attraction and ensure that the adaptive neural controller stabilizes the system. Numerical simulations were carried out to evaluate the controller’s performance under three different scenarios: ideal conditions, initialization outside the region of attraction, and a low learning rate. These scenarios illustrate the closed-loop system behavior and validate the theoretical conditions required for asymptotic stability. Furthermore, comparative numerical simulations were conducted on an Inverted Pendulum on a Cart system to benchmark the proposed Adaptive Neural Control against Linear Quadratic Regulator, Sliding Mode Control, and Nested Saturation Function controllers. Based on the Integral of Time-weighted Squared Error performance index, the Adaptive Neural Control demonstrated a significant reduction in control effort, achieving performance improvements of up to 95.02% compared to the aforementioned strategies. Full article

Microplastics (MPs) are an emerging environmental pollutant, and their contamination has emerged as a pressing global environmental concern. Developmental processes exhibit heightened sensitivity to environmental perturbations, and MP exposure can induce long-term adverse effects on organismal health by disrupting fundamental cellular processes. This review focuses on the toxicity and developmental toxicity risks of microplastics investigated using stem cell models. The core section comprehensively summarizes the primary mechanisms through which MP exposure interferes with the biological functions of stem cells, including the impairment of self-renewal capacity and lineage specification, as well as the inhibition of tissue-specific differentiation and organogenesis. Finally, the integration and application of modern toxicological methods in deepening research and improving risk assessment capabilities are synthesized. This review aims to provide a systematic perspective to understand the developmental hazards of MPs and look forward to future risk studies based on stem cell modeling, providing theoretical basis and fundamental support. Full article

Prefabricated mechanical, electrical, and plumbing (MEP) systems have been increasingly adopted in energy station projects; however, systematic evaluation frameworks capable of integrating construction performance, cost constraints, and uncertain multi-indicator assessments remain limited. To address this gap, this study constructs an Analytic Hierarchy Process (AHP)–Entropy–Fuzzy evaluation framework to assess the comprehensive benefits of BIM-enabled prefabricated MEP construction in energy stations. A hierarchical evaluation system was established based on five dimensions: schedule, quality, cost, safety, and environmental performance, and ten secondary indicators were defined. The Analytic Hierarchy Process was used to determine expert-based subjective weights, the entropy method was applied to capture objective data variability, and multiplicative normalization was employed to obtain combined weights. A fuzzy comprehensive evaluation model was then introduced to transform heterogeneous construction records into comparable benefit levels and scores. The prefabricated method scored 87.80 and was classified as “high”, whereas the conventional method scored 60.85 and was classified as “low”. A Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)-based sensitivity analysis further showed that, under 10%, 20%, and 50% criterion-weight perturbations, the prefabricated group consistently achieved higher closeness coefficients than the conventional group. The smallest margin occurred when the schedule weight was reduced by 50%, but the prefabricated group retained a positive advantage. The results demonstrate that Building Information Modeling (BIM)-enabled prefabricated MEP construction can achieve superior overall project performance through the coordinated optimization of schedule, cost, safety, quality, and environmental objectives, offering a practical evaluation framework and decision-support tool for the industrialized delivery of future energy infrastructure projects. Full article

Three-dimensional UAV operations require path planning methods that can jointly maintain route efficiency, threat avoidance, and trajectory smoothness under spatially distributed and time-varying constraints. To address this problem, this paper develops an integrated Dual-Layer Adaptive T-perturbation and Opposition-based Multi-Objective Particle Swarm Optimization framework, termed DATO-MOPSO, for 3D UAV path planning in complex threat environments. The method integrates a dual-layer adaptive inertia-weight and velocity-regulation mechanism with symmetric T-perturbation, an elite quasi-opposition-based learning strategy for diversity recovery and feasible local exploitation, and an archive-driven simulated annealing rule for stagnation-aware personal-best updating. A three-objective model minimizing path length, threat exposure, and path smoothness is established, and comparative experiments against MOPSO, ZAMOPSO, NSGA-II, and SPEA2 are conducted in both static and dynamic environments, together with statistical and ablation analyses. In the static scenario, DATO-MOPSO achieved the highest mean HV and stable repeated-run performance, but its IGD was comparable to ZAMOPSO with higher computational cost. In the dynamic scenario, DATO-MOPSO showed its main advantage, achieving the highest mean HV and the lowest mean IGD with statistically significant HV and IGD improvements over all baselines. Overall, DATO-MOPSO is most advantageous in time-varying complex threat environments, whereas its static-scenario advantages are accompanied by higher computational cost. Full article

Complex optimization problems are widely encountered in engineering design, intelligent manufacturing, communication systems, and wireless sensor network deployment. However, the original Enterprise Development Optimization Algorithm (EDOA) still suffers from insufficient population diversity, weak search guidance, and limited adaptability in balancing exploration and exploitation when solving high-dimensional and multimodal optimization problems. To address these issues, this paper proposes a Multi-Strategy Improved Enterprise Development Optimization Algorithm (MIEDOA). First, a Strategic Diversification Initialization (SDI) strategy is developed by integrating Sobol sequence sampling, random initialization, and Gaussian perturbation to improve the diversity and distribution quality of the initial population. Second, an Organizational Synergy Learning (OSL) mechanism is introduced to enhance search guidance through the collaborative utilization of elite information, population mean information, and peer interaction. Third, an Adaptive Governance with Feedback Regulation (AGFR) strategy is designed to dynamically regulate the exploration–exploitation behavior according to the current population fitness state. The proposed MIEDOA is evaluated on the CEC2017 and CEC2020 benchmark suites and compared with representative EDOA variants, CEC winner algorithms, and other advanced optimization methods. The experimental results indicate that MIEDOA generally achieves competitive performance in terms of solution quality, convergence behavior, and robustness across different benchmark scenarios. In addition, strategy effectiveness analysis, parameter sensitivity analysis, and statistical tests further provide evidence supporting the effectiveness of the proposed strategies. Finally, MIEDOA is applied to a three-dimensional wireless sensor network deployment problem. The results suggest that the proposed algorithm can obtain competitive deployment solutions and satisfactory coverage performance under different node scales, demonstrating its potential applicability to practical engineering optimization problems. Full article

GNSS array receivers suffer tracking degradation under array nonidealities such as element-position perturbations, channel amplitude/phase errors, and slowly varying manifold mismatch. Conventional blind anti-jamming suppresses interference, but adaptive weight fluctuations can propagate into the correlator domain, increasing cross-branch correlation, causing Early/Late metric imbalance, and reducing Prompt phase consistency. Existing noncoherent combining methods mainly convert multi-branch correlator outputs into scalar energy metrics for code tracking, leaving the carrier loop’s complex Prompt input insufficiently constrained. To address this problem, we propose a blind adaptive joint code–carrier channel-combining method for nonideal arrays. After first-stage anti-jamming, the method estimates an Early/Late correlator-domain covariance matrix and reuses it as a shared statistical constraint. In the code loop, this matrix drives whitened noncoherent energy combining with closed-loop gain normalization to stabilize the DLL discriminator scale. In the carrier loop, it is combined with a Prompt-derived coherent direction to form a covariance-constrained PLL complex input. Simulations under wideband interference, static array errors, and dynamic mismatch show that the proposed J-WNCC reduces both code-phase error and carrier-phase jitter, improving joint tracking robustness in nonideal array environments. Ablation results further reveal a dominant-effect separation: DLL gain normalization mainly calibrates the whitened code-discriminator scale, whereas coherent Prompt combining mainly reconstructs the complex PLL input. Full article

Background/Objectives: Ultra-processed foods (UPFs) are increasingly recognized as dietary exposures associated with cardiometabolic, hepatic, and neurocognitive outcomes. However, UPFs are often treated mainly as nutrient-poor foods, whereas their processing-related features may perturb gut–liver–brain communication. This review examines whether metabolic dysfunction-associated steatotic liver disease (MASLD) can be conceptualized as a hepatic metabolic amplifier linking UPF exposure to cognitive aging. Methods: We conducted a structured narrative search of PubMed/MEDLINE, Web of Science Core Collection, and Scopus from January 2010 to 11 May 2026 across four evidence modules: UPFs and MASLD/NAFLD; UPFs and cognitive aging or dementia; UPFs and gut–liver–brain mechanisms; and MASLD/NAFLD and cognitive aging. Representative studies were prioritized according to direct relevance to the proposed axis, study design, exposure and outcome validity, mechanistic specificity, and contribution to major evidence gaps. Results: Observational and mechanistic evidence links higher UPF consumption with liver steatosis, MASLD/NAFLD-related outcomes, cognitive decline, cognitive impairment, stroke, and dementia-related outcomes, although causality remains incompletely established and residual confounding is important. Candidate pathways include food-matrix disruption, rapid eating, displacement of microbial substrates, selected additives and processing-derived compounds, intestinal barrier dysfunction, metabolic endotoxemia, bile acid signaling, hepatic lipotoxicity, systemic inflammation, vascular dysfunction, and neuroimmune activation. Many pathways overlap with general cardiometabolic dysfunction; the processing-centered contribution lies in positioning industrial formulation as an upstream exposure and MASLD as a hepatic node that may amplify gut-derived and metabolic signals relevant to brain aging. Conclusions: A processing-centered gut–liver–brain framework integrates UPFs, MASLD, and cognitive aging as linked metabolic-aging phenomena. Future studies should test UPF substitution using liver imaging, microbiome profiling, metabolomics, bile acid and inflammatory biomarkers, neuroimaging, and cognitive assessment. Full article

Lipophilic marine toxins (LMTs) are important toxic risk factors in marine ecosystems and seafood safety, yet the comparative cytotoxicity-associated molecular responses of different LMT classes remain unclear. Here, Neuro-2a cells were exposed to four representative LMTs—dinophysistoxin-1 (DTX1), azaspiracid-3 (AZA3), yessotoxin (YTX), and pectenotoxin-2 (PTX2)—and acute cytotoxicity was evaluated together with integrated transcriptomic, proteomic, and metabolomic analyses. Cell viability assays showed a cytotoxic potency order of DTX1 > AZA3 > YTX > PTX2. Integrated multi-omics analysis revealed that DTX1, the most cytotoxic toxin, caused the broadest molecular perturbations, mainly involving mitochondrial energy metabolism, p53-mediated stress responses, and multilayered metabolic networks. AZA3 and YTX induced intermediate cytotoxicity and showed partially similar perturbation patterns, particularly affecting cytoskeleton-related, immune-related, and metabolism-related processes. In contrast, PTX2, the least cytotoxic toxin, produced more limited responses mainly involving tyrosine metabolism and the cGMP–PKG signaling network. Overall, molecular perturbation patterns generally corresponded to acute cytotoxic potencies, while each toxin exhibited distinct key pathways and functional modules. These findings provide a multi-omics basis for cytotoxic responses of representative LMT classes and guide subsequent functional validation. Full article

Autophagy-associated readouts in localized prostate cancer cannot be interpreted based on LC3, p62/SQSTM1, or LC3 puncta alone. In line with the concept of autophagy as a stress-response system, this review proposes a flux-aware, organelle-centered framework for assigning biological meaning to autophagy-related changes under disease-relevant stress. The framework integrates oxidative burden, lysosomal competence, selective autophagy, mitophagy, ferritinophagy, p62/SQSTM1-NRF2 signaling, ferroptosis-aware controls, and disease-stage context to distinguish four interpretive states: homeostatic quality control, adaptive tumor survival, blocked clearance, and stress-overload vulnerability. Flavonoid-associated responses are used as stress-test examples because they expose recurrent limitations in the field, including supraphysiologic exposures, limited metabolite realism, static-marker inflation, and insufficient assessment of lysosomal function. However, the framework is not restricted to dietary compounds; it applies to metabolic, pharmacological, inflammatory, androgen-related, radiation-associated, or therapy-induced perturbations in which autophagy-associated markers are altered without resolution of flux or organelle function. By linking autophagosome formation, cargo turnover, lysosomal acidification, redox buffering, and phenotype-level endpoints, this review defines a practical evidence hierarchy for interpreting autophagy in localized prostate cancer and for prioritizing translational vulnerabilities arising from organelle crosstalk. This contribution is primarily conceptual and is operationalized methodologically through flux-based evaluation criteria and translationally through disease-window-specific study-design recommendations. Full article

Prostate club-like cells have emerged as a recurrent but conceptually unsettled epithelial population across normal prostate, benign remodeling, inflammatory lesions, and prostate cancer. Although the term derives from airway biology, current evidence suggests that, in the prostate, these cells are better viewed as context-dependent noncanonical epithelial states than as a definitive lineage. Single-cell, spatial transcriptomic, and integrative studies place club-like cells most consistently in the prostatic urethra and proximal ducts under near-homeostatic conditions, whereas related programs reappear in benign prostatic hyperplasia, proliferative inflammatory atrophy, and tumor-associated niches. Across these contexts, club-like states intersect with androgen perturbation, inflammatory remodeling, epithelial plasticity, and treatment adaptation. Molecularly, they are defined less by a single marker than by a partially overlapping secretory, stress-associated, and remodeling-related gene program, with variable relationships to urethral luminal, intermediate, and progenitor-like epithelial states. This review synthesizes current evidence on the definition, distribution, molecular identity, functional implications, and disease relevance of prostate club-like cells. We argue that their main significance lies in clarifying prostate epithelial heterogeneity and state transitions, while key priorities include harmonized nomenclature, longitudinal sampling, spatial validation, and functional perturbation. Full article

Chronic coronary syndromes (CCSs) are increasingly recognized as complex immunometabolic vascular disorders in which coronary microvascular dysfunction (CMD), persistent low-grade inflammation, oxidative stress, and maladaptive cellular remodeling contribute to ischemic symptoms and adverse outcomes beyond epicardial stenosis. CMD represents a heterogeneous condition comprising both functional and structural endotypes and constitutes a major determinant of myocardial ischemia, heart failure progression, and adverse cardiovascular outcomes, even in the absence of obstructive coronary artery disease. Emerging evidence indicates that immunometabolic reprogramming of endothelial cells, vascular smooth muscle cells, and immune cells sustains microvascular dysfunction in CCSs. Metabolic shifts toward glycolysis, mitochondrial dysfunction, redox imbalance, and dysregulated lipid metabolism promote chronic inflammatory activation within the coronary microenvironment. Convergent mitochondrial stress (including NAD⁺ decline) and redox injury promote endothelial senescence and increase susceptibility to regulated cell death, progressively limiting vasodilatory reserve and predisposing to microvascular rarefaction. Pyroptosis and ferroptosis-like lipid peroxidation further exacerbate endothelial barrier disruption and inflammatory amplification. In parallel, inflammasome activation, iron-dependent lipid peroxidation, impaired autophagy, and endoplasmic reticulum stress form interconnected molecular networks that amplify vascular injury through self-reinforcing mechanisms. This narrative review integrates mechanistic and translational evidence linking immunometabolic dysregulation, mitochondrial stress, thromboinflammatory signaling, endothelial senescence, and regulated cell death to distinct CMD endotypes. We propose a systems-level framework in which coronary microvascular dysfunction is conceptualized as an immunometabolic vascular network disorder, with reduced coronary flow reserve (CFR)—often termed myocardial flow reserve (MFR) in PET studies—emerging as the integrative functional endpoint of these interacting molecular perturbations and a robust predictor of major cardiovascular events. Full article

Copper ions (Cu²⁺) and intracellular biothiols are tightly coupled in cellular redox regulation, where copper–thiol coordination governs oxidative stress and metal homeostasis. However, analytical platforms capable of sequentially monitoring Cu²⁺ and biothiols within a single molecular system remain scarce. Herein, we report a coumarin-based fluorescent probe XDP that enables sequential ON–OFF–ON sensing of Cu²⁺ and biothiols through a coordination–competition mechanism. The imine (C=N) site of XDP selectively coordinates Cu²⁺, leading to fluorescence quenching arising from coordination-induced electronic perturbation and enhanced nonradiative decay. The probe exhibits a linear response toward Cu²⁺ over 1–80 μM with a detection limit of 0.108 μM. Subsequent competitive binding of biothiols (GSH, Cys, and Hcy) releases Cu²⁺ from the complex, thereby restoring fluorescence and enabling detection within 1–30 μM with submicromolar sensitivity. XDP also displays a large Stokes shift (135 nm), which minimizes spectral overlap and improves signal reliability. Notably, Cu²⁺ binding triggers a distinct color change that supports naked-eye detection and smartphone-based RGB quantification. The probe further enables visualization of Cu²⁺ and thiol-triggered signal recovery in living cells and zebrafish. This work establishes a versatile analytical platform for probing copper–thiol interactions in environmental and biological systems. Full article

Autoimmune and immune-mediated inflammatory diseases (IMIDs) develop when genetically and environmentally susceptible hosts lose stable immune tolerance. The gut ecosystem is increasingly recognized as a biologically active interface in this process. Its bacterial, fungal, and viral components may shape mucosal and systemic immunity through antigenic stimulation, barrier regulation, and metabolite-dependent signaling, although the strength of evidence is uneven: bacteriome data are currently the most mature, whereas mycobiome, virome, and phageome findings remain more disease-specific and emerging. Dysbiosis may influence autoimmunity through overlapping routes, including epithelial barrier failure, altered short-chain fatty acid, bile acid, and tryptophan metabolism, molecular mimicry, and cross-kingdom microbial interactions. Nutrition is central to this network because dietary substrates determine microbial growth, metabolic output, epithelial integrity, and immune-cell differentiation. In this narrative review, we integrate evidence on disease-associated bacteriome, mycobiome, and virome patterns in systemic autoimmune diseases, with emphasis on rheumatoid arthritis, systemic lupus erythematosus, Sjögren’s syndrome, systemic sclerosis, spondyloarthritis, vasculitides, and idiopathic inflammatory myopathies. COVID-19 is considered not as a proven causal driver of autoimmunity, but as an example of an environmental and infectious insult capable of perturbing microbiome–barrier–immune communication. Finally, we discuss diet-based and microbiome-targeted approaches, including probiotics, prebiotics, synbiotics, and postbiotics, as adjunctive strategies that may help restore microbial resilience and immune balance. A better understanding of the diet–microbiome–host immunity axis may support more personalized preventive and therapeutic concepts in autoimmune disease. Full article

Neuroinflammation is a key hallmark of both neurodegenerative and neurospecific autoimmune diseases, including multiple sclerosis (MS), where immune dysregulation contributes to cellular stress, autophagy, and disease progression in Alzheimer’s disease (AD), Parkinson’s disease (PD), and MS. Emerging evidence suggests a shared mechanism behind MS, AD, and PD, driven by chronic interaction between the peripheral immune system and the central nervous system (CNS). While MS was traditionally viewed as a primary autoimmune condition, recent research indicated that all three disorders involve a breakdown of the blood–brain barrier (BBB). This structural failure enables peripheral immune cells and cytokines to enter the brain, causing sustained neuroinflammation and accelerating disease progression. Here, we propose an end-to-end framework for identification of the diagnostic and therapeutic cell-specific protein markers commonly regulated in mild–moderate AD (MMAD), early-stage PD (ESPD), and MS within peripheral blood mononuclear cells (PBMCs). PBMC markers were first identified based on shared differential protein expression, followed by filtering for BBB permeability. Subsequently, sorted cell markers were mapped to disease-specific neural cell types. Our analysis suggests that PBMC-derived cells, including astrocyte- and monocyte-like populations, share overlapping transcriptional signatures and functional similarity with macrophages and neuroglial cells, indicating potential transcriptional similarity or functional convergence. Furthermore, intra- and inter-cellular pathway analysis suggested both shared and disease-specific signaling mechanisms, with kinase–integrin interactions emerging as key regulatory factors. Selected potential seed markers, primarily kinases and immunoglobulins, were further analyzed through evolutionary sequence–structure space to identify druggable structural features. Next, protein moonlighting possibilities were tested to enhance the temporal functional trajectory of the markers for precise therapeutic impact. Hence, the framework provides a robust strategy to identify immune-based disease-specificcandidate diagnostic andpotential therapeutic targets. Full article

This paper studies the continuation problem for the three-dimensional compressible Navier–Stokes–Fourier system inside an admissible thermo-acoustic regime under periodic boundary conditions. The analysis considers strong solutions in the Sobolev class $H^s\left(\mathrm{\Omega }\right)$, $s>$ 5/2, with positive density and temperature and strict subsonic evolution. Using dyadic Fourier–triadic decomposition together with localized Littlewood–Paley analysis, the nonlinear transfer structure is decomposed into perturbative interaction classes and coherent same-scale High–High interactions. Within the present framework, coherent same-scale High–High persistence is identified as the only currently identified potentially nonperturbative concentration mechanism. A transport–acoustic alternative structure is then derived connecting persistent transport concentration with nonvanishing pressure response. The resulting pressure response is decomposed into thermodynamic and acoustic branches. The transonic acoustic branch is shown to be incompatible with the strict subsonic admissible class. The remaining interaction structure is controlled through entropy-driven thermodynamic dissipation and localized thermo-acoustic regularization. The exclusion of dynamically sustained critical thermo-acoustic concentration yields a localized ε-regularity framework combining thermodynamic dissipation, Campanato decay, and interior parabolic regularization. The resulting estimates provide localized Lipschitz control sufficient for the continuation of admissible strong solutions within the same thermo-acoustic class. The framework further remains compatible with weak–strong stability and irreversible long-time thermodynamic relaxation through the relative entropy structure and free-energy dissipation. Full article