Abstract: In this paper, we construct a probabilistic model of a sliding mode. This model is based on the moment a random walk with positive jumps crosses a certain critical level. It is assumed that the jump magnitude has a geometric distribution. If the initial state is negative and the critical level is zero, then after crossing this level, a random walk begins in the opposite direction until it crosses zero again. As a result, motion orthogonal to the slip line is defined as a regenerative process, in which the moments of regeneration are the moments of zero crossings from right to left. An estimate of the Qi Fan metric of the maximum deviation of this random walk over a certain time interval is constructed under the assumption that the time and magnitude of the jumps are reduced by a factor of m. This estimate is found to be of the order of lnm/m as m→∞ and characterizes the deviation of a random trajectory orthogonal to the slip line. In the model of motion along a slip line, its velocity is assumed to assume fixed values when the trajectory of motion orthogonal to the slip line is above or below zero. Using the central limit theorem for the integral of a regenerative process, an estimate of the non-uniformity of motion of a random trajectory along the slip line is constructed. It is found that the characteristic magnitude of this non-uniformity is of the order of 1/m as m→∞. This indicates that the accumulation of random errors during motion along the slip line is significantly faster than during motion orthogonal to the slip line.

Abstract: Reactive oxygen species are essential signalling molecules that regulate numerous aspects of skeletal muscle physiology. These effects are mediated through redox post-translational modifications on protein cysteine thiols, which influence the structure and function of redox-sensitive proteins. Mass spectrometry–based redox proteomic approaches have greatly advanced our ability to detect and characterise cysteine redox modifications, revealing a broad network of redox-sensitive proteins and pathways in skeletal muscle. Recent methodological developments enable quantification of the stoichiometry of reversible oxidative modifications at specific cysteine residues, providing critical insight into the extent and functional relevance of site-specific redox regulation. Redox proteomic approaches are being employed to improve our understanding of the specific redox protein modifications underlying physiological and pathophysiological processes in skeletal muscle. This review summarises current proteomic strategies for quantifying redox post-translational modifications and their application to study redox signalling in skeletal muscle. Emerging experimental approaches that offer the potential to study the specific roles of site-specific redox modifications in muscle physiology are also discussed. Collectively, these technologies present exciting opportunities to define the mechanistic roles of individual cysteine residues in muscle biology and help uncover new therapeutic avenues for conditions characterised by impaired redox homeostasis.

Abstract: This review explores the catalytic conversion of carbon dioxide (CO2) into glycerol carbonate (GC), positioning this pathway as a sustainable strategy that couples environmental mitigation with the valorization of surplus glycerol from biodiesel production. Glycerol carbonate maintains extensive industrial utility as a green solvent, chemical intermediate, and functional component in polymers, cosmetics, and packaging. Distinct from prior literature, this study systematically integrates the evaluation of catalysts derived from agro-industrial waste and hybrid catalytic systems, correlating their structural architectures with catalytic efficiency. The review evaluates diverse catalytic frameworks, with a primary focus on heterogeneous systems. Silica-based materials are highlighted, particularly those synthesized from rice husk ash, an abundant amorphous silica source. The sol–gel method is identified as a robust route for engineering porous matrices with high surface areas and tunable structural properties. Furthermore, the doping of silica with metal oxides, such as niobium oxide (Nb2O5) and nickel oxide (NiO), is discussed as a strategic approach to introduce synergistic acid–base sites and redox properties that facilitate CO2 activation. The integration of ionic liquids into hybrid systems is also examined as a promising frontier to enhance reaction kinetics and selectivity. Finally, this review delineates the nexus between agro-industrial waste management and the reduction of greenhouse gas emissions, proposing a circular economy framework for the biodiesel value chain.

Abstract: Yellow fever remains a major public health threat in endemic and re-emerging regions of Africa and South America, with recent outbreaks highlighting persistent gaps in prevention and surveillance. Pregnant women represent a particularly vulnerable population, yet the epidemiology, clinical impact, and preventive strategies for yellow fever in pregnancy are insufficiently characterized. Physiological and immunological changes during gestation may increase susceptibility to severe disease and contribute to adverse maternal and fetal outcomes, including miscarriage, stillbirth, preterm birth, and, in rare cases, perinatal transmission. Diagnostic challenges, overlapping clinical presentations with other arboviral and hepatic diseases, and limited access to specialized care further complicate clinical management in many endemic settings. This perspective provides a comprehensive overview of yellow fever in pregnancy during the 2024–2026 outbreak in the Americas, including a risk-stratification framework for prevention. We summarize current evidence on epidemiology, pathophysiology, diagnosis, and supportive care, and examine prevention strategies with particular emphasis on vaccination. Accumulated observational evidence and substantial real-world experience have not demonstrated an increased risk of serious adverse events and generally support the effectiveness of yellow fever vaccination during pregnancy when administered with appropriate clinical judgment. In high-risk settings, the benefits of maternal immunization clearly outweigh theoretical concerns, supporting a flexible, risk-based approach, despite relatively limited evidence. We also discuss national and international policies, post-pregnancy booster recommendations, and the importance of integrating vaccination assessment into antenatal care. Finally, we highlight critical knowledge gaps and research priorities, including the need for prospective registries and strengthened pharmacovigilance. Coordinated clinical and public health strategies are essential to protect maternal and neonatal health and to reduce the burden of yellow fever in endemic and re-emerging settings.

Abstract: Background/Objective: Nurses play a central role in operationalizing integration through coordination, screening, nursing care processes, community empowerment, and reporting. This study to examine the empirical distribution of an Implementation Fidelity Index (IFI) for nurse-led integrated primary care in Indonesia, grounded in five core domains: planning and coordination, early detection, nursing care processes, community education and empowerment, and reporting. Methods: We conducted a cross-sectional, facility-based online survey in 2025 among registered nurses working in Indonesian primary health care facilities (Puskesmas) and involved in integrated primary care activities. Implementation was measured using a structured 28-item questionnaire across five domains: planning/coordination, early detection, nursing care processes, community education/empowerment, and reporting (Likert 1–5). Domain scores were calculated as the mean of items within each domain; the overall Implementation IFI was calculated as the mean across all items and as the summed total score (range 28–140). We summarized domain and overall distributions (mean, SD, range) and examined inter-domain associations using Spearman correlations. Results: A total of 252 nurses completed the survey with no missing item responses. Overall IFI (item-mean) was 3.99 (SD 0.92; range 1.04–5.00), corresponding to a total score mean of 111.84 (SD 25.90; range 29–140). Domain means were highest for nursing care processes (4.28, SD 0.91) and early detection (4.09, SD 0.94), and lowest for community education/empowerment (3.75, SD 1.10). Using mean ±1 SD thresholds, 12.3% of nurses were categorized as low implementers, 71.8% moderate, and 15.9% high, indicating substantial heterogeneity. Inter-domain correlations were consistently positive and moderate-to-strong (ρ≈0.54–0.80; p<0.001). Conclusions: Nurse-led integrated primary care implementation in Indonesia was moderate-to-high overall but uneven across nurses and domains, with comparatively weaker performance in community empowerment and reporting.

Abstract: The peroxisome proliferator-activated receptor alpha (PPARα) is a ligand-activated nuclear transcription factor belonging to the nuclear receptor superfamily. Although classically characterised as the master regulator of hepatic fatty acid oxidation (FAO) and lipid catabolism, accumulating evidence positions PPARα as an indispensable molecular conductor at the feto-maternal interface. Within the human placenta, PPARα is expressed in both cytotrophoblast and syncytiotrophoblast layers throughout gestation, where it governs mitochondrial and peroxisomal β-oxidation, orchestrates pro-resolution inflammatory signalling, modulates trophoblast differentiation and invasion, and participates in epigenetic programming of the developing fetus. Derangements of placental PPARα activity are increasingly identified in major obstetric complications, including preeclampsia, gestational diabetes mellitus, and intrauterine growth restriction, where aberrant lipid accumulation, heightened oxidative stress, and amplified pro-inflammatory cytokine signalling converge. This review synthesises current knowledge on the molecular biology and genomic targets of PPARα in the placenta, its integration with maternal metabolic adaptations of pregnancy, its role in nutrient sensing and fetal programming, and the consequences of its dysregulation in pregnancy pathology. We further discuss emerging therapeutic implications of PPARα modulation and outstanding questions in this rapidly evolving field.

Abstract: Accurate and robust brain tumor segmentation remains a critical challenge in medical image analysis due to high inter-patient variability, complex tumor morphology, and modality-specific noise in MRI scans. This study proposes PSO-GA-U-Net, a novel hybrid deep learning framework that integrates Particle Swarm Optimization (PSO) and Genetic Algorithms (GA) to optimize the U-Net architecture for enhanced segmentation performance and generalization. PSO dynamically tunes the learning rate to accommodate modality-specific variations, while GA adaptively regulates dropout to improve feature diversity and reduce overfitting. The model is evaluated on three benchmark datasets---FBTS, BraTS 2021, and BraTS 2018---using five-fold cross-validation. PSO-GA-U-Net achieves Dice Similarity Coefficients (DSC) of 0.9587, 0.9406, and 0.9480, and Jaccard Index (JI) scores of 0.9209, 0.8881, and 0.9024, respectively, consistently outperforming state-of-the-art models in both overlap accuracy and boundary delineation. Statistical tests confirm that these improvements are significant across folds ($p< 0.05$). Visual heatmaps further illustrate the model's ability to preserve structural integrity across tumor types and modalities. These results indicate that metaheuristic-guided deep learning offers a promising and clinically applicable solution for automatic tumor segmentation in radiological workflows.

Abstract: Automobiles have been the pivotal instrument shaping the cities' structures and urban lives. While promising numerous benefits, the successful introduction of self-driving cars depends not only on their technical completeness, but mostly on the market acceptance for these disruptive transformations. To gauge the market response, we first summarize the most recent 15 research applying technical acceptance model (TAM) to compare their objectives, findings, and applied constructs around the countries. Then we examine to identify some influential factors whether or not the public use these self-driving machines, using 519 Korean samples. We use three groups as the system characteristics, social influence, and individual differences to do the quantitative survey and the structure equation model (SEM). The findings show that technical completeness, law and regulations, media support, perceived cost, trial and experience influence significantly on perceived usefulness and again on the usage intention while perceived safety do not significantly influence perceived usefulness. The results of this study help to strengthen existing knowledge about the self-driving cars by emphasizing the key elements that drive the intention to use the self-driving cars in the future.

Abstract: Temporal effects associated with surface plasmon polaritons (SPP) in a quantum slab of a plasma material, such as a thin film of metal, semiconductor or a graphene plate, where the quantum dispersion effects, and in particular exchanges effects, are retained.

Abstract: This study evaluates the antimicrobial properties of nanocomposite materials based on polyvinyl alcohol (PVA) reinforced with cellulose nanofibrils (CNFs) and/or supplement-ed with biobased additives derived from blueberry pruning wastes, with the objective of developing biodegradable food packaging systems with antimicrobial properties. The nanocomposites were prepared using a solvent-casting processing approach, and their thermal, physicochemical, and antimicrobial properties were assessed. All the nanocomposites exhibited thermal stability up to 200 °C, confirming their suitabil-ity for conventional food packaging processing conditions. Antimicrobial activity tests re-vealed inhibitory effects against both Gram-positive and Gram-negative bacteria. Bleached PVA/CNFs films showed complete growth inhibition (100%) against E. coli and S. aureus. In contrast, unbleached PVA/CNFs and PVA/CNFsB supplemented with blueber-ry-derived additives exhibited selective inhibition against E. coli, highlighting the influ-ence of nanofibril composition and additive incorporation on antimicrobial performance. Zeta potential measurements revealed values of –35.3 mV for the CNFs, confirming their negatively charged surface, which may contribute to interactions with bacterial mem-branes. Additionally, scanning electron microscopy (SEM) showed that the incorporation of CNFs generates nanostructured surfaces with exposed fibrillar domains, where bacteri-al cells become adhered and immobilized. These topographical features suggest that the antimicrobial behavior of the nanocomposites is associated with direct bacteria–surface interactions, supporting a contact-active antimicrobial behavior associated with the CNFs.

Abstract: In architecture and construction, it is common to use acrylic products with a high flammable content, from lacquers to improve the curing of concrete and mortar to resins that offer protection, sealing, flexibility and elasticity properties. The drying process of the treated surface involves the formation of volatile organic compound (VOC) vapours. To prevent these from degenerating into a potentially dangerous flammable atmosphere, a procedure is presented that establishes the maximum application yield for solvent-based products, providing equations that relate the maximum application surface area and minimum drying time to the air velocity available in the work area. The results are provided for both indoor and outdoor applications. A maximum application speed is established to prevent the generation of areas classified as fire or explosion hazards: 1.5 m²/h indoors and 1 m²/h outdoors. When this is carried out at an ambient temperature of 20°C, and above 40°C, it is not possible to apply varnishes without generating a flammable atmosphere.

Abstract: Introduction: Climate change is increasingly affecting the health of older people. This study aimed to determine the knowledge, skills, and attitudes of nurses and undergraduate nursing students regarding the effects of climate change on older people’s health. Material and Methods: A descriptive cross-sectional study was conducted between January and April 2024 with 708 participants (210 nurses and 498 undergraduate nursing students). The Nursing Competencies Questionnaire on Environmental Health of Older People (NCQ-OPEH) was used to assess environmental competencies. Descriptive values were calculated and interrelationships between knowledge, attitudes, and skills were analysed. Results: A total of 115 nurses (54.75%) and 185 students (37.15%) demonstrated good-excellent knowledge. Similarly, a higher percentage of nurses (50.77%) reported better perceived skills than students (42.52%). However, the majority of both samples (98.97% and 87.85%, respectively) had good to excellent attitudes. These differences were significant for knowledge (p< .001) and attitudes (p= .013), but not for skills (p= .054). Furthermore, a significant relationship was found between prior education on climate change and health and greater knowledge (p= .019) and skills (p= .027) among nurses and better skills and attitudes (p< .001 in both) among nursing students. Conclusion: Nurses have better environmental competencies than undergraduate nursing students. Therefore, it is important to include education on climate change and older people's health to be included in the academic curriculum of university nursing degrees. Nurses also need to reinforce these competencies through specific educational programmes. This new tool will evaluate educational and formation sessions on climate change and the health of older adults.

Abstract: Diffuse pollution from agricultural runoff, characterized by intermittent discharges of complex contaminant mixtures—including nutrients, pesticides, and heavy metals (HMs)—poses a persistent threat to global water quality. Conventional "end-of-pipe" strategies often fail to address these decentralized, nonpoint sources. This review examines the evolution of Permeable Reactive Barriers (PRBs) from static, abiotic filters into modern Permeable Reactive Bio-Barriers (PRBBs), engineered as dynamic, fixed-bed biofilm reactors. A key advancement in PRBB efficacy is the exploitation of biofilm plasticity, particularly in response to coexistence with organic and inorganic pollutants. While heavy metals are traditionally viewed as inhibitors, this review synthesizes evidence showing that sub-inhibitory HM levels can act as structural and functional drivers. These metals induce the upregulation of Extracellular Polymeric Substances (EPS), creating a "protective shield" that sequesters metals and confers functional resilience on the microbial consortia responsible for nutrient removal and pesticide biodegradation. The review analyzes contaminant removal mechanisms, highlighting the bio-chemo synergy between reactive media and biofilms, and proposes a classification framework based on target contaminants, media, and technological integration. Significant focus is placed on emerging hybrid multi-media systems designed to protect the "biological engine" from toxic metal shocks, alongside the integration of artificial intelligence for predictive control. While challenges in hydraulic sustainability and field validation remain, PRBBs represent a compact, low-energy, and scalable eco-technology. They offer a strategically targeted solution within the Nature-Based Solutions toolkit for building resilient protection of aquatic ecosystems at the critical land-water interface.

Abstract: This paper proposes a formal method and associated techniques for completing the ISO/IEC/IEEE Standard 15288 technical process 6.4.2 – stakeholder needs and requirements definition within the 15288-SysML grid framework. The paper is a companion work to Engineering systems with standards and digital models: Development of a 15288-SysML Grid, which describes an engineering design method that supports the tenets of the Industry 4.0 paradigm. The formal method presented here is grounded using established constructs from systems science; specifically, the systems principles of hierarchy, emergence, requisite parsimony, minimum critical specification, and requisite saliency. The application of accepted principles ensures that stakeholders are able to objectively specify measurable criterion that can satisfy stakeholder needs and capabilities. The method uses: (1) international standards for systems (e.g., ISO/IEC/IEEE 15288); (2) adopts the four fundamental aspects of system design supported by model-based systems engineering (MBSE); (3) invokes the international standard for the systems modeling language (SysML); and (4) adopts a hierarchical requirements tree that specifies Mission, Goals, Objectives, and Sub-objectives (MGOS) to provide the stakeholder-analysis process for the articulation of system-level engineering requirements. Utilization of the MGOS is intended to have a positive impact on the system design process by ensuring reproducibility, replicability, transparency, and generalization.

Abstract: Biological coherence arises from coordinated integration of redox chemistry, hydration dynamics, electromagnetic interactions, and bioenergetic flux. Although substantial progress has been made in characterizing these processes individually, current frameworks do not fully explain how distributed biochemical events achieve stable temporal coordination across scales. In thermally noisy, dissipative environments, energy alone cannot account for sustained biological organization. A missing element is the establishment and renewal of phase reference - the temporal alignment that enables spatially distributed processes to act in synchrony. Here we propose a physical mechanism for phase reference access and anchoring based on cyclic nanodomain dynamics at a nanoscale redox-photonic interface previously termed the Redox Photonic Coupling System (RPCS). This interface supports an additional functional modality - phase breathing - a process mediated by molecular nitrogen (N₂) through which cyclic nanodomain nucleation and collapse anchors and sustains phase reference in living systems. Nitrogen-mediated oscillatory boundary dynamics create transient coherence windows that permit local access to phase reference, enabling phase-aligned oxidative-reductive resolution and anchoring of phase onto redox-generated Photonic Activation Quanta (PAQs). Absorption of phase-conditioned PAQs by adjacent hydration shells enables generation and accumulation of centropy, defined as stored organizational capacity that supports coordinated biological work.This framework identifies phase breathing as a previously unrecognized mechanism sustaining biological coherence and assigns molecular nitrogen a structural organizational role beyond respiratory dilution. By integrating nanodomain mechanics, photonic phase conditioning, and redox dynamics within a single interface, it provides a mechanistic basis for how coherent biological function is generated and maintained.

Abstract: Maternal vaccination against respiratory syncytial virus (RSV) represents a major advance in early-life infection prevention. Although clinical efficacy and early real-world effectiveness are well established, sustained population-level impact depends on equitable uptake. This review synthesizes determinants influencing maternal RSV vaccination within the evolving dual-strategy landscape that includes both maternal vaccination and infant monoclonal antibody prophylaxis. A structured narrative review was conducted following PRISMA principles. PubMed/MEDLINE and Google Scholar were searched for studies published between January 2022 and February 2026. Eligible studies examined behavioral, interpersonal, structural, economic, and policy determinants of maternal RSV vaccination uptake, as well as early implementation and modelling evidence. Findings were integrated within a multilevel analytical framework. Maternal uptake is shaped by interacting determinants across individual, healthcare provider, and health system domains. Key drivers include perceived infant disease severity, vaccine safety confidence, perceived effectiveness, and prior antenatal vaccination behavior. Healthcare provider recommendation consistently emerges as the strongest facilitator. Coverage variability reflects differences in reimbursement, antenatal care integration, and national policy endorsement. The coexistence of maternal vaccination and infant monoclonal antibody strategies introduces additional comparative decision-making complexity. Early implementation data indicate heterogeneous uptake and socioeconomic gradients, while modelling demonstrates sensitivity to coverage, timing, epidemiology, and cost. Translating biological efficacy into sustained public health benefit requires coordinated behavioral, structural, and policy strategies, strong provider engagement, and context-sensitive implementation frameworks to ensure equitable coverage.

Abstract: The Central Dogma has provided a foundational framework for biological information flow, yet it does not fully explain how living systems preserve stable identity, functional robustness, and recoverability under continuous molecular noise and environmental perturbation. Here, I propose the Central Homeostatic Principle (CHP) as a complementary first-principle framework that shifts the explanatory center from information execution alone to the physical constraint architecture that makes biological execution possible. The CHP posits that, in living cells, a central homeostatic state functions as a system-level coordinating layer that defines the feasible state space within which genetic and biochemical programs can operate.This framework is motivated by convergent evidence across mechanical confinement, electrophysiological coupling, membrane contact-site transduction, phase-state regulation, and non-genetic phenotypic heterogeneity, all of which indicate that global physical states can gate, reshape, or buffer molecular outcomes. Building from systemic prerequisites and material constraints, I further argue through an exclusionary first-principle analysis that lipid-organized boundary systems occupy a near-irreplaceable physical position in implementing this central homeostatic constraint in aqueous cellular life-not as exclusive causal authors, but as the dominant substrate of feasibility control.To render the theory scientifically actionable, this manuscript provides a formal articulation of CHP, a three-tier realization model, operational corollaries, and a rule typology that distinguishes stronger and weaker forms. It then derives a set of falsifiable hypotheses spanning temporal commitment dynamics, non-genetic resistance, aging-related resilience loss, state-engineering-based reprogramming, and evolutionary primacy in prebiotic systems. By reframing life as a problem of constrained state maintainability rather than information flow alone, the CHP offers a testable theoretical scaffold for integrating molecular biology, biophysics, systems biology, and translational state engineering.

Abstract: This data descriptor provides a standardized and reproducible subsystem-level represen-tation of the NREL wind turbine gearbox condition monitoring benchmarking dataset. The released records are derived from Healthy (H1–H10) and Damaged (D1–D10) meas-urement files and include subsystem-level standardized indices (KHI_HS, KHI_IMS, KHI_PL) together with a calibrated 0–1 Gearbox Health Index (GHI). The indices are gen-erated using a fully specified and deterministic feature extraction and aggregation work-flow based on established vibration indicators and healthy-referenced normalization. The Zenodo deposit contains machine-readable CSV tables intended to support transparent benchmarking across supervised classification and anomaly detection studies. The pro-posed GHI is introduced as an interpretable and reproducible reference baseline rather than an optimized diagnostic model. Technical validation demonstrates condition-level separability within the analyzed dataset while emphasizing the descriptive nature of the index. By releasing structured derived records and a documented regeneration procedure, this work enables implementation-independent comparison of gearbox condition moni-toring approaches and supports reproducible evaluation of alternative health index formulations.

Abstract: If the invariance of light speed is absolutely universal in covariant space rather than contra variant space, the following researches and conclusions on general covariance would be so far as to catch up with very high probabilities and reliabilities. As has been verified, it is. General covariance is tested controversial after the investigations on gravitational redshift and acceleration. Further inspections on differential geometry indicate the opportunities of inequality of mixed derivatives of bases for the transformations between Riemannian spaces that will then lead to the inequality of Christoffel symbols of alternative sub-index and then the failure of the classical equations of Christoffel symbols. That is one of the reasons that causes controversies on general covariance. Even the negative form of time metric could be proved to be a false setting in that space transformations do nothing with the negative sign inherited from that of Minkowski space. Nevertheless, after discussions on transformations between original spherical space, distance expressed spherical space and Cartesian space, it has been seen that the distance factors for angular coordinates of a spherical space are improper to be employed the metrics in general relativity, instead of that, the concept of gravitational metrics were suggested. In fact, Christoffel symbols and base derivatives both are valid methodologies for analysis in a non-Euclidean space. The concept of trajectory derivatives was carried out to define the derivations on trajectory of matter motions that could help to revise those equations and calculations. Measurable experiments on gravitational redshifts and accelerations have been carried out to support the theoretical results. Conclusions have been drawn that light speed keeps general covariance in gravitational fields but light energy momentum would not, may as well, the motions of massive matters in gravitational fields do not perform general covariance thoroughly. It is impossible to geometrize the gravity effects of massive matters with position depending metrics in that the variable velocities cannot be eliminated thoroughly. Consequently, inferences on kinematics and relativistic release were carried out, which might have been forcefully verified in applications. With the concept of gravitational metrics, the so-called geodesic equations have been falsified to be kinematic equations anymore. Velocities, mass energy and momentum all should have their conservative forms. To seek for these conservative forms is the critical route to create kinematic or dynamic equations of motions of light rays and massive matters. The conservativeness of light angular momentum has been discovered in most surprising form. Renovated solutions for light rays as well as massive matters have been carried out that forcefully impact the traditional methodologies on kinematics of trajectory and time delay because they are the correct interpretations of the realities. It should be highlighted that the renovated mass equation, the general mass equation for free motions, could completely demonstrate energy variations, especially the variations in gravitational fields, that help to create more general dynamic equations, so as to cause an irrelativistic solution of planet perihelion precession. As a proof by contradictions, the traditional solution of that must be involved with errors. Newtonian ballistic method was put forward to make numerical analyses on close-to-light-speed motions, and the invalidity of that method on light propagation could be seen as another support to the conclusions and inferences. Another forceful falsification on energy momentum conservativeness carried out in the discussions on the traditional treatment of time delay of close-to-light-speed particles, has thoroughly exposed the essential mistakes in the way of methodologies. Dynamic models of fluid planet rings were founded to interpret the evolutions of accretions of quasars and active galactic nuclei and the mechanism of relativistic release. It is predicted that the peak release of an inflow is at 1.5 of gravitational radius and the peak luminosity of an accretion may locate at the position of about 1.33 of gravitational radius. Relativistic frequency shift interprets the mechanism of giant redshifts that predict the probability of observational redshifts might be up to a particularly higher level with respect to that have been observed in the past years. The width equations of emission and absorption lines indicate the mechanism and the positions of broad line regions and narrow line regions. It could be imagined that the relativistic emissions and relativistic absorptions with relativistic redshifts would have been involved with fantastic mystery of intrinsic structures of matters that we know less.

Abstract: Since the beginning of modern computer history, the Turing machine has been a dominant architecture for most computational devices, which consists of three essential components: an infinite tape for input, a read/write head, and finite control. In this structure, what the head can read (i.e., bits) is the same as what it has written/outputted. This is actually different from the ways in which humans think or do thought/tool experiments. More precisely, what humans imagine/write on paper are images or texts, and they are not the abstract concepts that they represent in the human brain. This difference is neglected by the Turing machine, but it actually plays an important role in abstraction, analogy, and generalization, which are crucial in artificial intelligence. Compared with this architecture, the proposed architecture uses two different types of heads and tapes, one for traditional abstract bit inputs/outputs and the other for specific visual ones. The mapping rules among the abstract bits and the specific images/texts can be realized by neural networks with a high accuracy rate. Logical reasoning is thus performed through the transfer of mapping rules. The statistical decidability of the Halting Problem with an imperceptibly small error rate in reasoning steps is established for this type of machines. As an example, this paper presents how the new computer architecture (what we call ``Ren machine" for simplicity here) autonomously learns a distributive property/rule of multiplication in the specific domain and further uses the rule to generate a general method (mixed in both the abstract domain and the specific domain) to compute the multiplication of any positive integers based on images/texts. The machine's strong reasoning ability is also corroborated in proving a theorem in Plane Geometry. Moreover, a robotic architecture based on Ren machine is proposed to address the challenges faced by the Vision-Language-Action (VLA) models in unsound reasoning ability and high computational cost.