Abstract: The rapid expansion of Generative Artificial Intelligence (GAI) is transforming higher education systems, particularly public institutions seeking to advance toward smart governance models and digital transformation. In this context, digital teaching competence emerges as a strategic factor for the effective, ethical, and pedagogically sound adoption of these technologies. This study assesses the level of digital competence among public higher education faculty in Paraguay and examines its predictive capacity regarding the adoption of GAI tools using machine learning models. A nationwide quantitative study was conducted with a sample of 800 faculty members from public universities across Paraguay. Data were collected through a structured questionnaire based on international digital competence frameworks, incorporating additional variables such as attitudes toward GAI, technological experience, institutional infrastructure, and perceived organizational support. Data analysis involved the application of machine learning techniques, including Logistic Regression, Random Forest, and Gradient Boosting, to identify the variables with the strongest predictive power regarding faculty readiness and willingness to integrate GAI into teaching practices. Model performance was evaluated using metrics such as accuracy, F1-score, and AUC-ROC. The findings identify key predictors of technological readiness and structural gaps within Paraguay’s public higher education system. This research provides empirical evidence from Latin America on the factors influencing GAI adoption in public sector educational contexts and contributes to the design of educational policies aimed at fostering smart universities and digitally sustainable academic ecosystems.

Abstract: Multi-modal remote sensing image registration is a challenging task due to differences in resolution, viewpoint, and intensity, which often leads to inaccurate and time-consuming results with existing algorithms. To address these issues, we propose an algorithm based on Curvature Scale Space Contour Point Features (CSSCPF). Our approach combines multi-scale Sobel edge detection, dominant direction determination, an improved curvature scale space corner detector, a new gradient definition, and enhanced SIFT descriptors. Test results on publicly available datasets show that our algorithm outperforms existing methods in overall performance. Our code will be released at https://github.com/JianhuaZhu-IR.

Abstract: This article addresses the “Hard Problem” of consciousness not as an immutable ontological barrier of nature, but as an iatrogenic separation—a methodological artifact induced by the reductive third-person perspective (3P). By systematically and intentionally removing the subject from the world-description to achieve a veneer of objectivity, modern physicalism creates a restrictive “substance grammar” that subsequently struggles to locate the qualitative dimension of experience within its own datasets. Using Hans Holbein the Younger’s painting The Ambassadors (1533) as a primary epistemic model, we analyze the anamorphic “blot” as a representation of the Real that eludes frontal, mathematical domestication. We argue that the resolution of this parallax requires more than a simple shift in focus; it demands a “step to the side”—a transition from static representation to the processual performance of enactive inference. Integrating Karl Friston’s Free Energy Principle (FEP) and the Neurophenomenological Enactive System Schema (NESS), we define meaning not as an intrinsic property of objects, but as a temporal alignment and an energetic achievement of a system striving for coherence under the constant pressure of existential concern (Sorge). The paper concludes by proposing a “processual perspectivism” and the figure of the Sovereign Witness, suggesting that the Hard Problem is dissolved when subjectivity is understood as the active, embodied performance of the world-relation.

Abstract: Sustainability has become a crucial strategic priority for firms operating in re-source-intensive industries such as food processing, where long-term competitiveness depends on responsible governance, strategic orientation, resource management and or-ganizational resilience. While prior research has established a general link between sus-tainability and organizational performance, less is known about how specific internal sustainability governance and management components contribute to firm financial per-formance. Drawing on the Resource-Based View and institutional theory, this study ex-amines the direct effects of a sustainability-oriented vision, business policy, organization-al culture, and strategies on firm financial performance. The study is based on survey data collected from 247 food processing firms operating in Slovenia, an EU member state. Ex-ploratory factor analysis and multiple regression analysis were used to test the proposed relationships. The results show that sustainability strategies have the strongest direct, sta-tistically significant positive effect on firm financial performance, followed by sustainabil-ity-oriented organizational culture. In contrast, sustainability vision and business policy exhibit a statistically significant, but negative, direct association, suggesting that formal sustainability commitments alone may not yield financial benefits without effective cul-tural support and strategic integration. These findings indicate that firm financial perfor-mance is directly driven primarily by sustainability strategies that are via practices opera-tionally embedded and supported by organizational capabilities such as organizational culture, rather than by normative symbolic commitments alone. This opens up possibili-ties for further research, based on the probability that the sustainable development vision and business policy serve as a catalyst for defining sustainable development strategies and implementing sustainable development practices, and that the normative commit-ments, in particular, indirectly influence financial performance. The study contributes to the sustainability governance and management literature by distinguishing the norma-tive, cultural, and strategic dimensions of sustainability and demonstrating their distinct direct implications for financial performance. The findings also provide practical insights for owners/governors and managers by highlighting the importance of integrating sus-tainability into organizational culture and core strategic processes to achieve long-term financial value.

Abstract: Servo motors typically utilize Field-Oriented Control (FOC). However, the conventional cascaded PI control framework is inherently constrained by its fixed-parameter design, making it highly susceptible to parameter variations and unmodeled disturbances. While intelligent control strategies—such as model predictive control (MPC)—provide a robust, multi-objective alternative, their intensive stepwise computational demand often degrades transient response. Motivated by the stochastic dynamics of motor operation, we propose a novel physics-informed control paradigm. Specifically, we formulate the FOC-based motor control as an online stochastic optimization problem, wherein the objective function is updated iteratively using stochastic gradient estimates, and the resulting time-varying subproblems are solved efficiently by the MSALM algorithm. Our approach significantly outperforms conventional PI controllers in environmental adaptability and disturbance rejection. Experimental results demonstrate that the proposed method achieves comparable high-precision tracking performance while significantly reducing computational time per iteration, ensuring rapid dynamic response and strict enforcement of physical constraints.

Abstract: Robotic assistance in minimally invasive surgery has significantly improved precision and dexterity; however, many supportive tasks, such as blood aspiration, still rely on manual operation. This work presents the design and implementation of an autonomous robotic aspirator capable of detecting and removing intraoperative bleeding without continuous human intervention. The proposed system integrates a perception module based on a convolutional neural network for real-time blood segmentation, a task planner for high-level actions execution, and a control strategy based on artificial potential fields for autonomous navigation. Additionally, a mixed-reality human–robot interaction interface is incorporated to enable system supervision and seamless transition to teleoperation when required. The system was experimentally validated with a set of in-vitro experiments under three representative bleeding scenarios, evaluating four suction strategies based on the computation method for the target selection. Results demonstrate fast reaction times (below 0.04 s) and high blood removal rates (above 80% in all cases). The comparative analysis reveals that the performance of the suction strategies is scenario-dependent and highlights a trade-off between suction efficiency and removed area. These findings support the feasibility of autonomous robotic aspiration and provide insights into the design of adaptive strategies for surgical assistance, contributing toward increased autonomy and improved workflow efficiency in minimally invasive procedures.

Abstract: Percutaneous cable infection of left ventricular assist device (LVAD) patients is a significant source of morbidity, often caused by biofilm producing or multidrug resistant bacteria. We hypothesized that bacteriophage viruses can be identified from biological samples of patients with active driveline infection. Six patients with local percutaneous lead infections were enrolled. Microbiological samples were collected from the infected wound and other skin regions. The isolated viral strains and phages from wastewater samples were then tested against the pathogen bacterial cultures in vitro. Biofilm disruption assay and genetic analysis of the strains were also performed. Bacteriophages with lytic activity could be identified from samples of two patients. One patient contained four strains showing strong efficacy against his own Staphylococcus epidermidis. Furthermore, this bacterium was susceptible to phages identified from another patient and strains from wastewater samples. Genomic analysis suggested lysogenic lifestyle of the phages. However, none of them have shown any microbiological signs of lysogeny. In conclusion, we have been able to prove in vitro lytic activity of bacteriophages originating from the same LVAD patient. We also found effective phages in biological samples of other patients and wastewater samples, suggesting that patients implanted in the same center may share bacteriophage flora.

Abstract: Vascular endothelial cells (ECs) coordinate with osteogenic processes to establish the specialized vasculature of bone tissue, where endothelial cells and bone cells interact, and bone cells regulate EC proliferation and differentiation. However, it remains unclear how ECs and bone cells are coordinated during early bone formation and whether these interactions differ between endochondral ossification (e.g., femur) and intramembranous ossification (e.g., skull). To address this question, we analyzed endothelial and osteogenic marker expression in the femur and skull between postnatal days 3 and 39. We identified distinct expression patterns of endothelial markers (Endomucin, VE-cadherin and CD31) and osteogenic markers (Osterix, Cbfa1 and BGLP) during osteogenesis in these tissues. In the femurs, endothelial marker expression alternated with the expression of osteogenic markers, suggesting potential reciprocal regulation. In contrast, in the skull, endothelial and osteogenic markers exhibited similar temporal expression patterns without alternation. We also analyzed the expression of VEGF and its receptor FLK1. In the femur, VEGF expression paralleled osteogenic marker expression, whereas in the skull VEGF expression differed from both osteogenic and endothelial marker patterns. Together, these results demonstrate that the coordination of endothelial and osteogenic marker expression, as well as VEGF signaling, differs between endochondral and intramembranous ossification, suggesting distinct modes of interaction between endothelial and bone cells during the formation of long and flat bones.

Abstract: Alzheimer’s disease (AD) disproportionately affects women, with risk increasing sharply during and after the menopausal transition. While declines in estrogen have traditionally been emphasized, emerging evidence suggests that elevations in follicle-stimulating hormone (FSH) may represent a critical and underappreciated driver of neurodegenerative vulnerability. This review synthesizes current evidence linking reproductive aging to AD pathobiology, with a focus on endocrine, metabolic, and inflammatory mechanisms. We examine how sustained FSH elevation interacts with key molecular pathways implicated in AD, including C/EBPβ–δ-secretase signaling, mitochondrial dysfunction, impaired glucose metabolism, and disruptions in autophagic and lysosomal clearance. These processes converge to promote amyloid-β accumulation, tau pathology, and chronic neuroinflammation. In parallel, FSH influences apolipoprotein biology - particularly ApoE - through effects on lipid metabolism, protein lipidation, and clearance dynamics, thereby modulating both amyloid kinetics and inflammatory responses in an isoform-dependent manner. Reproductive aging is further characterized by systemic shifts in vascular integrity, blood–brain barrier function, and immunometabolic regulation, all of which may amplify susceptibility to neurodegenerative processes. Importantly, these upstream disturbances precede classical pathological hallmarks, reframing amyloid and tau accumulation as downstream manifestations of broader regulatory failure. Collectively, this work positions FSH not merely as a biomarker of ovarian decline, but as an active endocrine mediator of neurodegeneration. Targeting FSH signaling and its downstream pathways may therefore represent a promising and mechanistically grounded approach for mitigating AD risk, particularly in women.

Abstract: This research aims to investigate the concept of Industrial Symbiosis as a change agent in the Circular Economy, with its consequent effects on the economy, the environment, and society in terms of sustainable development. This study employs qualitative research with quantitative support from a structured survey of 152 IS project experts, researchers, and practitioners, utilizing a questionnaire comprising Likert-type and multiple-choice questions. Data were aggregated into composite indicators and analyzed by using a log-log regression model. Empirical results reveal that economic benefits are the most significant positive drivers. The actors’ involvement also contributes positively, highlighting the importance of multi-stakeholder collaboration. Conversely, barriers have the strongest negative impact on perceived obstacles and reduce IS synergies on the largest scale. Broader economic and social conditions moderately enhance, while awareness and training show a weaker but positive effect. IS is both economically viable and environmentally necessary, but its expansion depends on reducing financial, regulatory, and infrastructural barriers. Certain economic policy-driven interventions, such as fiscal incentives, regulatory clarity, and investment, enable infrastructure to scale up the adoption of IS.

Abstract: Background: Age-related hearing loss (HL) is a significant independent risk factor for Alzheimer's disease (AD), yet the molecular mechanisms underlying this comorbidity and the comparative efficacy of hearing interventions on cognitive outcomes remain unclear. This study aims to integrate clinical evidence and molecular data to address these gaps. Objective:To conduct a systematic review and network meta-analysis (NMA) to: 1) compare the effects of hearing interventions on cognitive function in AD patients; 2) identify and rank key microRNAs (miRNAs) associated with AD-HL comorbidity; 3) explore heterogeneity sources; and 4) cross-validate findings with independent clinical sequencing data. Methods: We systematically searched PubMed, Web of Science, Embase, and Cochrane Library up to May 2025. Included studies involved AD patients with/without HL, re-porting cognitive scores (MoCA, MMSE, AVLT) or miRNA expression data. A NMA was performed to rank interventions (cochlear implants-CI, hearing aids-HA, no in-tervention-NI) and miRNAs using surface under the cumulative ranking (SUCRA) curves. Heterogeneity was assessed via subgroup analysis and meta-regression. Pooled miRNA expression results were cross-validated against an independent clinical se-quencing dataset (LC-P20240110033, n=16) using intraclass correlation coefficient (ICC) and Bland-Altman plots. Results: Twelve studies (2,137 patients) were included. HL was significantly associated with worse cognitive function (MoCA: SMD = -0.82, 95% CI: -1.15 to -0.49; AVLT delayed recall: SMD = -1.12, 95% CI: -1.56 to -0.68). NMA revealed CI (SUCRA=0.89) was superior to HA (SUCRA=0.62) and NI (SUCRA=0.09) for preserving MoCA scores. Among nine differentially expressed miRNAs, hsa-miR-6875-5p was the most consistent biomarker (pooled FC = 1.52, 95% CI: 1.04–2.23), showing excellent agreement with sequencing data (FC = 3.29; ICC = 0.82, 95% CI: 0.67–0.91). Heterogeneity was significantly influenced by miRNA detection platform (p=0.04) and HL severity (p=0.03).Conclusion: This study demonstrates that HL exacerbates cognitive decline in AD in a dose-dependent manner. Cochlear implants may offer superior cognitive protection compared to hearing aids. The consistently dysregulated hsa-miR-6875-5p emerges as a promising cross-modal biomarker, bridging clinical observation and molecular pathology in AD-HL comor-bidity.

Abstract: This introduction to Pharmutopia: How Drug Regulation Fails Patients and What We Can Do About It explores the complex interplay between pharmaceutical knowledge, government regulation, and individual autonomy in the United States. The text argues that Americans’ unprecedented consumption of pharmaceuticals is the product of a century-long alliance between medical professionals seeking to eliminate competition and a federal government expanding its regulatory domain. This alliance forged the concepts of “pharmaceutical fact”—the regulatory structures defining drug legitimacy—and “pharmaceuticalization,” the process by which increasing aspects of human life are framed as pharmaceutical problems. These frameworks, the author contends, are not neutral but constitute a sociopolitical system that determines who has authority over medical decisions and the limits of personal autonomy. Drawing on the work of Thomas Szasz, the critique highlights the evolution of the “Therapeutic State,” where state power and medical authority become inseparably linked, resulting in surveillance, behavioral control, and exclusion from necessary medicines for those outside the system. The book traces how professional organizations, in partnership with federal agencies, used regulation to enforce their definitions of scientific fact, transforming both the nature of medicines and the roles of those who dispense them. Through the lens of Nico Stehr’s “knowledge capitalism,” the text demonstrates that pharmaceutical knowledge has been turned into monopoly property, enforced through legal and regulatory mechanisms like the FDA and international agreements such as TRIPS. This transformation, the author asserts, underlies the economic and social power of the pharmaceutical industry, shaping access to medicines and the governance of individual bodies. The introduction frames the book’s central inquiry: whether the current system serves patients or entrenches a regime of knowledge monopolism and state authority.

Abstract: Behavioral Authentication (BA) systems verify user identity claims based on unique behavioral characteristics using machine learning (ML)-based classifiers trained on user behavioral profiles. Although effective, ML-based BA systems face serious privacy threats, including profile inference and reconstruction attacks. This paper presents RUIP-BA (Renewable, Unlinkable, and Irreversible Privacy-Preserving Behavioral Authentication), a non-cryptographic framework tailored to low-computation devices such as IoT and mobile platforms. Random Projection (RP) maps behavioral profiles into lower-dimensional protected templates while approximately preserving utility-relevant geometry, and local Differential Privacy (DP) injects calibrated stochastic perturbations to provide formal privacy protection. The proposed design jointly targets the ISO/IEC 24745 requirements of renewability, unlinkability, and irreversibility. We provide complete algorithmic realizations for enrollment, verification, template renewal, unlinkability testing, and GAN-based adversarial privacy evaluation. We also introduce rigorous formal privacy derivations and proofs under explicit assumptions, including formal security games, theorem-level guarantees at information-theoretic and statistical levels, Cram'er-Rao lower bounds for irreversibility, full Jensen-Shannon divergence derivations for unlinkability, and GAN Nash-equilibrium attack bounds. Experiments on voice, swipe, and drawing datasets show authentication accuracy above 96% while sharply limiting feature recoverability under strong GAN-based attacks. RUIP-BA provides a scalable, mathematically grounded, and deployment-ready privacy-preserving BA solution.

Abstract: Atmospheric nitrogen dioxide (NO₂) is an important component of reactive nitrogen and plays a key role in the atmospheric nitrogen cycle outside major emission regions. However, its variability under remote background conditions remains poorly characterized, as most observational studies focus on urban or continental environments. This study investigates the background variability of in situ NO₂ measurements at a remote North Atlantic island (Azores) over the period 2015–2024 and examines its association with large-scale atmospheric transport regimes. Monthly NO₂ concentrations were classified into background Atlantic conditions and months influenced by continental air masses using an objective PM₁₀ percentile-based criterion. Differences between regimes were assessed using non-parametric statistics. Although NO₂ concentrations were systematically higher during months associated with continental transport, the differences did not reach statistical significance. Wind speed analysis for the overlapping period 2018–2024 showed consistently higher values during continental transport months, supporting enhanced large-scale advection during these periods. Overall, the results indicate that background NO₂ levels in this remote insular environment exhibit modest but coherent modulation associated with atmospheric transport regimes. These findings contribute to improving the interpretation of reactive nitrogen variability in remote marine settings and highlight the value of island observatories for studying the atmospheric nitrogen cycle.

Abstract: UV−curable L(-)−borneol−functionalized antibacterial hydrogels for packaging of fresh−cut banana and cherry tomato (UV−LBs) were designed from L(-)−Borneol−Functionalized polyurethane acrylate prepolymers (LB−PUAs) and thiol–functionalized PVA (PVA–SH) by UV initiated thiol−ene click reaction. UV−LBs exhibit good thermal stability with Td5 in the range of 225−240 oC, high mechanical performance with the tensile strength and the elongation at break in the range of 1.38−2.05 MPa and 44.4−68.6%, respectively. The antibacterial efficiency of UV−LBs against S. aureus, E. coli, and M. albican can reach 67.4%, 75.6% and 83.7%, respectively. The storage time of fresh−cut banana and cherry tomato packaged can be extended from 12 h to 30 h, 4 d to 5 d, respectively.

Abstract: The concepts of anthromes and human appropriation of net primary production (HANPP) are both valuable in understanding our human-dominated planet, yet they have never been integrated theoretically or empirically. Here we utilize an extensive county-level dataset on HANPP and its product-level components to derive, through cluster analysis, ten contemporary US anthromes. From highest to lowest density of harvested HANPP, the anthromes are: Rainfed Corn-Soy, Dairy Fodder, Spring Wheat-Small Grain, Winter Wheat-Sorghum and Corn-Soy Dry Margin, Subtropical Soy-Cotton, Commercial Timber, Mixed Hardwood and Pasture, Recovered Eastern Forest, Prairie-Sagebrush Rangeland, and Arid and Alpine Sparse Grazing. Expanding to thirteen anthromes maintains these, while bifurcating the commercial timber (softwood, hardwood), rainfed corn-soy (core, fringe) and mixed hardwood and pasture anthromes. Cluster analysis was more successful than hierarchical modeling at producing empirically meaningful anthromes.

Abstract: Background: The growing demand for versatile laboratory automation is exemplified in the context of liquid biopsy, where multi-analyte approaches are increasingly recognised for their potential to enhance diagnostic sensitivity in oncology. However, current practice often necessitates the use of dedicated instruments and workflows for the extraction of each analyte, posing financial and logistical barriers for automated multi-analyte liquid biopsy. Methods: Here, we present Robotic Centrifugal Microfluidics (RoCM), an all-in-one platform that combines the versatility of centrifugal microfluidics and operational flexibility of robotic liquid handling. This combination enables the automation of complex micro- and macrofluidic protocols, realised through the use of (1.) exchangeable microfluidic cartridges and (2.) programmable robotic operations such as in-rotation liquid supply, magnetic bead manipulation, or microfluidic valving. In-rotation robotic liquid manipulation maintains fluid control under centrifugal forces and reduces the cartridge footprint associated with pre-loaded liquid reservoirs. Platform applicability was demonstrated using two exemplary liquid biopsy workflows: the extraction of cell-free DNA (cfDNA) from blood plasma using RoCM-cfDNA slices and the extraction of extracellular vesicles (EVs) from blood plasma using RoCM-EV slices. Results: In a pilot study with patient samples from different cancer entities, the RoCM-cfDNA slices yielded comparable variant allele frequencies to a commercial bead-based instrument, while the RoCM-EV slices achieved a recovery of a greater diversity of EV subpopulations and up to one magnitude higher recovery than semi-automated size exclusion chromatography. Conclusion: By simply exchanging cartridges, RoCM enables the extraction of diverse analytes within a single automated system. Its application can be extended to further analytes, such as circulating tumor cells (CTCs), or to applications beyond liquid biopsies, where versatile micro- and macrofluidic protocols benefit from implementation in a single automation instrument.

Abstract: Introduction and Purpose. Aquatic organisms, including invertebrates such as sponges, mollusks, and jellyfish, are sources of environmentally friendly marine collagen and low-molecular-weight bioactive oligopeptides, purified using advanced technologies. Since the early 2010s, numerous high-quality experimental and human studies have explored the properties of hydrolyzed marine collagen fragments as systemic functional ingredients in regenerative medicine. The purpose of this review is to discuss these properties and the rationale behind them, with a focus on wound healing. Mechanisms underlying chronic wound healing may offer a strong foundation for the still-missing, high-level clinical studies, particularly in patients with diabetic and pressure ulcers. Methods. This review examines only academically significant studies published in PubMed-indexed journals with significant impact factors, supplemented by a few contributions from Google Scholar for methodologically sound in vitro and animal studies. Results. Activation of skin fibroblasts and other mesenchymal cells underpins the systemic regenerative properties of highly purified hydrolyzed marine collagens. For example, 50 µg/mL of hydrolyzed marine collagen peptides nearly replicated in vitro the accelerated cell migration induced by 10 µg/mL of recombinant human epidermal growth factor. Faster wound healing, associated with increased collagen neosynthesis, is accompanied by increased immunohistochemical expression of platelet-endothelial cell adhesion molecule-1, basic fibroblast growth factor, and transforming growth factor β-1. The potential supportive role of collagen hydrolysates in managing insulin resistance could benefit the treatment of chronic diabetic and pressure ulcers. Conclusions. An increasing number of preclinical and human studies highlight the systemic regenerative properties of hydrolyzed marine collagens and their excellent safety profile. The evidence for their regenerative properties in aesthetic skin rejuvenation appears solid. Preclinical evidence is also growing for wound-healing support. Unfortunately, sound clinical studies confirming the experimental evidence in everyday wound care practice are still lacking, with long-term safety as a primary concern.

Abstract: Reliable assessment of small-strain soil stiffness is essential for geotechnical site characterization and for analysing the behaviour of embankments and other earth structures. Surface-wave methods provide an efficient non-destructive means of estimating shear-wave velocity profiles; however, their application is limited by the non-uniqueness of the inversion process. This paper presents a multimodal inversion procedure for Rayleigh-wave dispersion curves based on the particle swarm optimization algorithm. The procedure involves the calculation of theoretical dispersion curves for a horizontally layered medium and their matching with experimental data through a global search scheme. The proposed procedure was first verified using two synthetic soil profiles, and its robustness was further assessed by considering perturbations of the theoretical dispersion curve of up to 10%. Particular attention was given to the influence of higher modes on the inversion results. The results show that including higher modes leads to a more accurate and reliable determination of shear-wave velocity profiles than an inversion based solely on the fundamental mode. The procedure was subsequently validated on a transverse embankment profile using an experimental MASW dispersion curve and comparison with SCPT results. Good agreement was obtained, and the eight-layer model proved to be a good compromise between accuracy and model complexity. The proposed multimodal approach therefore represents a reliable tool for the geotechnical characterization of layered soil profiles.

Abstract: This paper introduces the Monte Carlo Stochastic Optimization Technique (MOST), a global optimization framework based on region-wise integral comparison. Unlike classical pointwise methods, MOST evaluates candidate regions through aggregated objective values, enabling a structured and global exploration of the search space. We establish a unified theoretical foundation. Deterministic geometric shrinking of regions ensures that their diameters converge to zero, while a non-circular integral separation principle guarantees global convergence. Incorporating Monte Carlo estimation, we derive exponential concentration bounds and prove almost sure convergence under suitable sampling schedules. For constrained problems, we introduce an extended functional whose minimizers are equivalent to Karush–Kuhn–Tucker (KKT) points, allowing constraint handling without projection or penalty tuning. The framework is further extended to multi-objective optimization, where convergence to Pareto–KKT stationary points is established. Numerical experiments on multimodal benchmark functions confirm the theoretical results. Overall, MOST provides a derivative-free, deterministic–probabilistic framework for global optimization that extends naturally to constrained and multi-objective settings.