Search Results (445)

A novel adaptive intelligent control system (AICS) with learning-while-controlling capability is developed for a highly nonlinear single-input single-output plant by redesigning the conventional model reference adaptive control (MRAC) framework, originally based on first-order Lyapunov stability, and employing customized neural networks. The AICS is designed with a simple structure, consisting of two main subsystems: a meta-learning-triggered mechanism-based physics-informed neural network (MLTM-PINN) for plant identification and a self-tuning neural network controller (STNNC). This structure, featuring the triggered mechanism, facilitates a balance between high controllability and control efficiency. The MLTM-PINN incorporates the following: (I) a single self-supervised physics-informed neural network (PINN) without the need for labelled data, enabling online learning in control; (II) a meta-learning-triggered mechanism to ensure consistent control performance; (III) transfer learning combined with meta-learning for finely tailored initialization and quick adaptation to input changes. To resolve the conflict between streamlining the AICS’s structure and enhancing its controllability, the STNNC functionally integrates the nonlinear controller and adaptation laws from the MRAC system. Three STNNC design scenarios are tested with transfer learning and/or hyperparameter optimization (HPO) using a Gaussian process tailored for Bayesian optimization (GP-BO): (scenario 1) applying transfer learning in the absence of the HPO; (scenario 2) optimizing a learning rate in combination with transfer learning; and (scenario 3) optimizing both a learning rate and the number of neurons in hidden layers without applying transfer learning. Unlike scenario 1, no quick adaptation effect in the MLTM-PINN is observed in the other scenarios, as these struggle with the issue of dynamic input evolution due to the HPO-based STNNC design. Scenario 2 demonstrates the best synergy in controllability (best control response) and efficiency (minimal activation frequency of meta-learning and fewer trials for the HPO) in control. Full article

The optimal design of truss structures is one of the most complex problems, as it requires achieving high stiffness and stability while pursuing lightweight structures. With the recent advancements in AI technologies, machine learning-based approaches for predicting the optimal cross-sectional areas of truss structures have garnered significant attention from researchers. However, the design problem of truss structures poses substantial challenges for machine learning models due to the highly diverse and nonlinear characteristics of the optimal cross-sectional distributions, which may hinder effective learning. To address these limitations, the importance of hyperparameter optimization (HPO) has been increasingly recognized. This paper employs metaheuristic algorithms, which are efficient in searching for global optima, to perform HPO on 10-bar and 17-bar truss structure datasets. By balancing exploitation and exploration capabilities, metaheuristic algorithms demonstrate superior performance and time efficiency compared to conventional HPO methods. The results underscore the critical role of hyperparameters in machine learning-based truss structure design and suggest that leveraging metaheuristic algorithm-based HPO holds significant potential for addressing complex structural design problems in future applications. Full article

The activation mechanism of the reproductive axis in Kazakh ewes during the non-breeding season was explored by supplementation with glycerol complex (7% glycerol + tyrosine + vitamin B9). The experiment divided 50 ewes into five groups (n = 10). After 90 days of intervention, it was found that significant changes in serum DL-carnitine, N-methyl-lysine and other differential metabolites were observed in the GLY-Tyr-B9 group (p < 0.05, “p < 0.05” means significant difference, “p < 0.01” means “highly significant difference”). The bile acid metabolic pathway was specifically activated (p < 0.01). The group had a 50% estrus rate, ovaries contained 3–5 immature follicles, and HE staining showed intact granulosa cell structure. Serum E2/P4 fluctuated cyclically (p < 0.01), FSH/LH pulse frequency increased (p < 0.01), peak Glu/INS appeared on day 60 (p < 0.05), and LEP was negatively correlated with body fat percentage (p < 0.01). Molecular mechanisms revealed: upregulation of hypothalamic kiss-1/GPR54 expression (p < 0.01) drove GnRH pulses; ovarian CYP11A1/LHR/VEGF synergistically promoted follicular development (p < 0.05); the HSL of subcutaneous fat was significantly increased (p < 0.05), suggesting involvement of lipolytic supply. Glycerol activates the reproductive axis through a dual pathway—L-carnitine-mediated elevation of mitochondrial β-oxidation efficacy synergizes with kisspeptin/GPR54 signalling enhancement to re-establish HPO axis rhythms. This study reveals the central role of metabolic reprogramming in regulating seasonal reproduction in ruminants. Full article

The hypothalamus–pituitary–ovarian (HPO) axis orchestrates reproductive functions through intricate neuroendocrine crosstalk. Here, we integrated single-nucleus RNA sequencing (snRNA-seq) and spatial transcriptomics (ST) to decode the cellular heterogeneity and intercellular communication networks in the reproductive systems of pregnant Mongolian cattle. We retained a total of 6161 high-quality nuclei from the hypothalamus, 14,715 nuclei from the pituitary, and 26,072 nuclei from the ovary, providing a comprehensive cellular atlas across the HPO axis. In the hypothalamus, neurons exhibited synaptic and neuroendocrine specialization, with glutamatergic subtype Glut4 serving as a TGFβ signaling hub to regulate pituitary feedback, while GABAergic GABA1 dominated PRL signaling, likely adapting maternal behavior. Pituitary stem cells dynamically replenished endocrine populations via TGFβ, and lactotrophs formed a PRL–PRLR paracrine network with stem cells, synergizing mammary development. Ovarian luteal cells exhibited steroidogenic specialization and microenvironmental synergy: endothelial cells coregulated TGFβ-driven angiogenesis and immune tolerance, while luteal–stromal PRL–PRLR interactions amplified progesterone synthesis and nutrient support. Granulosa cells (GCs) displayed spatial-functional stratification, with steroidogenic GCs persisting across pseudotime as luteinization precursors, while atretic GCs underwent apoptosis. Spatial mapping revealed GCs’ annular follicular distribution, mediating oocyte–somatic crosstalk, and luteal–endothelial colocalization supporting vascularization. This study unveils pregnancy-specific HPO axis regulation, emphasizing multi-organ crosstalk through TGFβ/PRL pathways and stem cell-driven plasticity, offering insights into reproductive homeostasis and pathologies. Full article

This study investigates the behavior of phosphate ion transport through two structurally distinct anion-exchange membranes—AMV (homogeneous) and HC-A (heterogeneous)—in an electrodialysis system under both static and stirred conditions at varying pH levels. Chronopotentiometric and current–voltage analyses were used to investigate the influence of pH and hydrodynamics on ion transport. Under underlimiting (ohmic) conditions, the AMV membrane exhibited simultaneous transport of H₂PO₄⁻ and HPO₄²⁻ ions at neutral and mildly alkaline pH, while such behavior was not verified at acidic pH and in all cases for the HC-A membrane. Under overlimiting current conditions, AMV favored electroconvection at low pH and exhibited significant water dissociation at high pH, leading to local pH shifts and chemical equilibrium displacement at the membrane–solution interface. In contrast, the HC-A membrane operated predominantly under strong electroconvective regimes, regardless of the pH value, without evidence of water dissociation or equilibrium change phenomena. Stirring significantly impacted the electrochemical responses: it altered the chronopotentiogram profiles through the emergence of intense oscillations in membrane potential drop at overlimiting currents and modified the current–voltage behavior by increasing the limiting current density, reducing electrical resistance, and compressing the plateau region that separates ohmic and overlimiting regimes. Additionally, both membranes showed signs of NH₃ formation at the anodic-side interface under pH 7–8, associated with increased electrical resistance. These findings reveal distinct ionic transport characteristics and hydrodynamic sensitivities of the membranes, thus providing valuable insights for optimizing phosphate recovery via electrodialysis. Full article

A simple and rapid precipitation process was successfully employed to prepare silver phosphate (SP, Ag₃PO₄). Two different phosphate sources: diammonium hydrogen phosphate ((NH₄)₂HPO₄) and dipotassium hydrogen phosphate (K₂HPO₄) were applied separately as the precursor, obtaining ((NH₄)₂HPO₄)⁻ and K₂HPO₄⁻ derived SP powders, named SP-A or SP-P, respectively. Fourier transform infrared (FTIR) spectra pointed out the vibrational characteristics of P–O and O–P–O interactions, confirming the presence of the PO43– functional group for SP. X-ray diffraction (XRD) patterns revealed that the SP crystallized in a cubic crystal structure. Whereas the field emission scanning electron microscope (FESEM) exposed spherical SP particles. The potentially antibacterial activity of SP-A and SP-P against bacterial Bacillus stratosphericus, yeast Meyerozyma guilliermondii, and fungal Phanerodontia chrysosporium was subsequently investigated. All studied microorganisms were recovered and isolated from the aquatic plant during the tissue culture process. The preliminary result of the antimicrobial test revealed that SP-A has higher antimicrobial activity than SP-P. The superior antimicrobial efficiency of SP-A compared to SP-P may be attributed to its purity and crystallite size, which provide a higher surface area and more active sites. In addition, the presence of potassium-related impurities in SP-P could have negatively affected its antimicrobial performance. These findings suggest that SP holds potential as an antimicrobial agent for maintaining sterility in tissue cultures, particularly in aquatic plant systems. The growth of both B. stratosphericus and M. guilliermondii was suppressed effectively at 30 ppm SP-A, whereas 10 ppm of SP-A can suppress P. chrysosporium development. This present work also highlights the potential of SP at very low concentrations (10–30 ppm) for utilization as an effective antimicrobial agent in tissue culture, compared to a commercial antimicrobial agent, viz., acetic acid, at the same concentration. Full article

In this study, high-energy milled (HEM) samples of natural phosphorites from Estonian deposits were investigated. The activation was performed via planetary mill with Cr-Ni grinders with a diameter of 20 mm. This method is an ecological alternative, since it eliminates the disadvantages of conventional acid methods, namely the release of gaseous and solid technogenic products. The aim of the study is to determine the changes in the structure to follow the solid-state transitions and the isomorphic substitutions in the anionic sub-lattice in the structure of the main mineral apatite in the samples from Estonia, under the influence of HEM activation. It is also interesting to investigate the influence of HEM on structural-phase transformations on the structure of impurity minerals-free calcite/dolomite, pyrite, quartz, as well as to assess their influence on the thermal behavior of the main mineral apatite. The effect of HEM is monitored by using a complex of analytical methods, such as chemical analysis, powder X-ray diffraction (PXRD), wavelength-dispersive X-ray fluorescence (WD-XRF) analysis, and Fourier-transformed infrared (FTIR) analysis. The obtained results prove the correlation in the behavior of the studied samples with regard to their quartz content and bonded or non-bonded carbonate ions. After HEM activation of the raw samples, the following is established: (i) anionic isomorphism with formation of A and A-B type carbonate-apatites and hydroxyl-fluorapatite; (ii) solid-phase synthesis of calcium orthophosphate-CaHPO₄ (monetite) and dicalcium diphosphate-β-Ca₂P₂O₇; (iii) enhanced chemical reactivity by approximately three times by increasing the solubility via HEM activation. The dry milling method used is a suitable approach for solving technological projects to improve the composition and structure of soils, increasing soil fertility by introducing soluble forms of calcium phosphates. It provides a variety of application purposes depending on the composition, impurities, and processing as a soil improver, natural mineral fertilizer, or activator. Full article

Heat stress (HS) is a major environmental factor negatively impacting the reproductive performance of livestock. This study investigates the molecular mechanisms of heat stress on the hypothalamic–pituitary–ovarian (HPO) axis in Hu sheep. A heat-stressed animal model was established, and high-throughput RNA sequencing (RNA-seq) was employed to analyze gene expression in the hypothalamus, pituitary, and ovarian tissues of both control and heat-stressed groups. The results revealed significant changes in estrus behavior, hormone secretion, and reproductive health in heat-stressed sheep, with a shortened estrus duration, prolonged estrous cycles, and decreased levels of FSH, LH, E₂, and P4. A total of 520, 649, and 482 differentially expressed genes (DEGs) were identified in the hypothalamus, pituitary, and ovary, respectively. The DEGs were enriched in pathways related to hormone secretion, neurotransmission, cell proliferation, and immune response, with significant involvement of the p53 and cAMP signaling pathways. Tissue-specific responses to heat stress were observed, with distinct regulatory roles in each organ, including GPCR activity and cytokine signaling in the hypothalamus, calcium-regulated exocytosis in the pituitary, and cilium assembly and ATP binding in the ovary. Key genes such as SYN3, RPH3A, and IGFBP2 were identified as central to the coordinated regulation of the HPO axis. These findings provide new insights into the molecular basis of heat stress-induced impairments in reproductive function—manifested by altered estrous behavior, reduced hormone secretion (FSH, LH, E₂, and P4), and disrupted gene expression in the hypothalamic–pituitary–ovarian (HPO) axis—and offer potential targets for improving heat tolerance and reproductive regulation in sheep. Full article

The sustainable utilization of solid waste is crucial for environmental protection. This work investigates the fabrication of foamed ceramics from Cr slag and municipal solid waste incineration (MSWI) fly ash, focusing on the effects of three inhibitors—NH₂SO₃H, ZnO·TiO₂, and (NH₄)₂HPO₄—on material properties and Cr leaching behavior. Experimental analysis, chemical thermodynamic calculations, and material characterization were all employed. Results show that the prepared foamed ceramics meet the JG/T 511-2017 standard for building materials, exhibiting excellent physical properties but significant Cr leaching. Among the inhibitors, (NH₄)₂HPO₄ with a molar ratio of n(P)/n(Cr) = 1 shows the best performance, achieving a bulk density of 205 kg/m³, compressive strength of 0.850 MPa, Cr leaching concentration of 188 μg/L, and a 70.0% of Cr leaching inhibition rate. The improvement is attributed to the AlPO₄ formation that enhancing the strength, and Ca₂P₂O₇ that stabilizing Cr during sintering. This work provides a feasible method for the safe resource utilization of Cr-containing waste. Full article

This paper investigates the nonlinear bending analysis of nano-beams using the physics-informed neural network (PINN) method. The nonlinear governing equations for the bending of size-dependent nano-beams are derived from Hamilton’s principle, incorporating nonlocal strain gradient theory, and based on Euler–Bernoulli beam theory. In the PINN method, the solution is approximated by a deep neural network, with network parameters determined by minimizing a loss function that consists of the governing equation and boundary conditions. Despite numerous reports demonstrating the applicability of the PINN method for solving various engineering problems, tuning the network hyperparameters remains challenging. In this study, a systematic approach is employed to fine-tune the hyperparameters using hyperparameter optimization (HPO) via Gaussian process-based Bayesian optimization. Comparison of the PINN results with available reference solutions shows that the PINN, with the optimized parameters, produces results with high accuracy. Finally, the impacts of boundary conditions, different loads, and the influence of nonlocal strain gradient parameters on the bending behavior of nano-beams are investigated. Full article

Background/Objectives: Wolf–Hirschhorn syndrome (WHS; OMIM #194190) is a rare neurodevelopmental disorder, caused by deletions in the distal short arm of chromosome 4. It is characterized by developmental delay, epilepsy, intellectual disability, and distinctive facial dysmorphism. Clinical presentation varies widely, complicating prognosis and individualized care. Methods: We assembled a cohort of 140 individuals with genetically confirmed WHS from Spain and Latin-America, and developed and validated a multidimensional, Clinician-Reported Outcome Assessment (ClinRO) based on the Global Functional Assessment of the Patient (GFAP), derived from standardized clinical questionnaires and weighted by HPO (Human Phenotype Ontology) term frequencies. The GFAP score quantitatively captures key functional domains in WHS, including neurodevelopment, epilepsy, comorbidities, and age-corrected developmental milestones (selected based on clinical experience and disease burden). Results: Higher GFAP scores are associated with worse clinical outcomes. GFAP showed strong correlations with deletion size, presence of additional genomic rearrangements, sex, and epilepsy severity. Ward’s clustering and discriminant analyses confirmed GFAP’s discriminative power, classifying over 90% of patients into clinically meaningful groups with different prognoses. Conclusions: Our findings support GFAP as a robust, WHS-specific ClinRO that may aid in stratification, prognosis, and clinical management. This tool may also serve future interventional studies as a standardized outcome measure. Beyond its clinical utility, GFAP also revealed substantial social implications. This underscores the broader socioeconomic burden of WHS and the potential value of GFAP in identifying high-support families that may benefit from targeted resources and services. Full article

Per- and polyfluoroalkyl substances (PFASs) comprise a diverse array of synthetic chemicals that resist environmental degradation. They are increasingly recognised as endocrine-disrupting compounds (EDCs). These chemicals, found in non-stick cookware, food packaging, and industrial waste, accumulate in human tissues and fluids, raising substantial concerns regarding their impact on female reproductive health. Epidemiological studies have demonstrated associations between PFAS exposure and reduced fertility; nevertheless, the underlying molecular pathways remain inadequately understood. This narrative review investigates the multifaceted effects of PFASs on ovarian physiology, including its disruption of the hypothalamic–pituitary–ovarian (HPO) axis, alteration of anti-Müllerian hormone (AMH) levels, folliculogenesis, and gonadotropin receptor signalling. Significant attention is directed towards the emerging association between PFASs and polycystic ovarian syndrome (PCOS), wherein PFAS-induced hormonal disruption may exacerbate metabolic issues and elevated androgen levels. Furthermore, we analyse the current data regarding PFAS exposure in women undergoing treatment based on assisted reproductive technologies (ARTs), specifically in vitro fertilisation (IVF), highlighting possible associations with diminished oocyte quality, suboptimal embryo development, and implantation failure. We examine potential epigenetic and transgenerational alterations that may influence women’s reproductive capabilities over time. This study underscores the urgent need for further research and regulatory actions to tackle PFAS-related reproductive toxicity, particularly in vulnerable populations, such as women of reproductive age and those receiving fertility treatments. Full article

Acid phosphatase (ACPase) is an essential industrial enzyme, but its production via recombinant bacterial fermentation is often limited by insufficient dissolved oxygen control. This study optimized the aerobic fermentation of the ACPase-producing recombinant bacterium Bacillus subtilis 168/pMA5-Acp by refining the bioreactor’s aerodynamic structure using computational fluid dynamics (CFD) simulations. This was combined with fermentation kinetics modeling to achieve precise process control. First, the gas distributor structure of the 5 L bioreactor was optimized using CFD simulation results. Optimal mass transfer conditions were identified through comprehensive analysis of K_La in different reactor regions (aeration ratio: 1.142 VVm, K_La = 264.2 h⁻¹). The simulation results showed that the optimized oxygen transfer efficiency increased 2.49 fold compared to the prototype. Second, the process control issue was addressed by developing a BP (backpropagation) neural network model to predict K_La under alternative media conditions. The prediction error was less than 5%, and the model was combined with the logistic equation to construct the bacterial growth kinetic model (R² > 0.99). The experiments demonstrated that using the optimized reactor with a molasses–urea medium (molasses 7.5 g/L; urea 15 g/L; K₂HPO₄ 1.2 g/L; MgSO₄·7H₂O 0.25 g/L) reduced production costs while maintaining enzyme activity (215.99 U/mL) and biomass (OD₆₀₀ = 101.67) by 90.03%. This study provides an efficient and cost-effective process solution for the industrial production of ACPase and a theoretical foundation for bioreactor design and scale-up. Full article

The drilling and blasting method is commonly employed for the rapid demolition of outdated buildings by destroying key structural components and inducing progressive collapse. The residual bearing capacity of these components is governed by the deformation morphology of the longitudinal reinforcement, characterized by bending deflection and exposed height. This study develops and validates a finite element (FE) model of a reinforced concrete (RC) column subjected to demolition blasting. By varying concrete compressive strength, the yield strength of longitudinal reinforcement, the longitudinal reinforcement ratio, and the shear reinforcement ratio, 45 FE models are established to simulate the post-blast morphology of longitudinal reinforcement. Two databases are created: one containing 45 original simulation cases, and an augmented version with 225 cases generated through data augmentation. To predict bending deflection and the exposed height of longitudinal reinforcement, artificial neural network (ANN) and random forest (RF) models are optimized using the hunter–prey optimization (HPO) algorithm. Results show that the HPO-optimized RF model trained on the augmented database achieves the best performance, with MSE, MAE, and R² values of 0.004, 0.041, and 0.931 on the training set, and 0.007, 0.057, and 0.865 on the testing set, respectively. Sensitivity analysis reveals that the yield strength of longitudinal reinforcement has the most significant impact, while the shear reinforcement ratio has the least influence on both output variables. The partial dependence plot (PDP) analysis indicates that the ratio of shear reinforcement has the most significant impact on the deformation of longitudinal reinforcement. Full article