Abstract: Recent work on the evaluation of large language models emphasizes that the relevant unit of intelligence is not the artificial system alone but the human–AI hybrid. In parallel, topological and dynamical models of cognition based on Painlev\'e equations and non-semisimple topology propose that consciousness, intelligence, and creativity emerge from constrained long-horizon dynamics near criticality. This perspective article argues that these two research directions are deeply compatible. We show that the empirical framework for human--AI collaboration can be interpreted as a fusion process between complementary cognitive sectors: exploration (AI) and selection (human cognition). The dynamical mechanism underlying this fusion is identified with noisy phase locking between cognitive oscillators. Two independent routes to a universal 1/f spectral signature are developed: a geometric route through the WKB/Stokes analysis of Painlev\'e~V confluence, and an arithmetic route through the Mangoldt function and harmonic interactions in phase-locked loops. We connect these results to the Bost--Connes quantum statistical model, whose phase transition at the pole of the Riemann zeta function provides an exact mathematical framework for the lock-in phase hypothesis of identity consolidation in AI systems. This synthesis suggests a unified research program for hybrid intelligence grounded in topology, dynamical systems, number theory, and real-world AI evaluation.

Abstract: Background: Exosomes are nanosized extracellular vesicles that range from 30 to 150 nm and have a bilayer lipid membrane which encapsulates proteins, lipids, and nucleic acids, first identified in the 1960s and expanded in application from disease diagnostics to targeted therapeutics. They are intercellular communicators with roles in physiological regulation and pathological progression. Results: Exosomes applications in gene therapy, drug delivery, tissue regeneration, and disease diagnostics activate signaling pathways such as Wnt/β-catenin, PI3K/Akt, etc., deliver anti-aging molecules, and promote angiogenesis refers to their properties such as biocompatibility, cross the blood-brain barrier, serving as vectors and selective cargo delivery. Altogether, these effects promote tissue regeneration, as well as its therapeutic potential in dermatology, orthopedics, cardiology, neurology, and wound healing. However the same mechanisms that promote regeneration can also drive tumor progression, induce drug resistance, suppress immune responses, and mediate the pathogenic factors spread. It means that exosome's dual nature presents challenges. On the therapeutic side, exosomes can promote tumor growth, drug resistance, and immune suppression. In contrast, the transmission of viral or pathogenic proteins, tumor progression, and so on, underscores their “Trojan horse” potential. Conclusion: Exosomes embody a biological paradox as mentioned. It is essential for developing safe and effective exosome based therapies to understanding of this duality deeper for harnessing their therapeutic potential while mitigating associated risks.

Abstract: Dark Energy entered the arena of the speculative physics since 30 years after the observation of the slight acceleration of material bodies established by supernovae used as standard candles in the Gigaparsec distance range. Recent advances in the study of cosmic rays redundantly indicate that galaxy clusters have permanent, steady electrostatic fields of maximum strength of 5 V/m, general centripetal direction and electrostatic potentials 10²¹-10²³ Volt. This work determines for the first time how the slight acceleration of material bodies, in the interval 10^-10- 10^-13 m/s², is caused by electrostatic fields in galaxy clusters and that Dark Energy is electrostatic energy. Unlike matter that is concentrated in galaxies and galaxy clusters, electrostatic energy at cosmic scale is quite diffuse. Empirical evidence of the electrostatic fields is based on the rich and variegated synchrotron emission in galaxy clusters and, notably, on the absence of diffuse gamma rays in galaxy clusters which amounts to three orders of magnitude relative to current, reiterated predictions and on other data.

Abstract: Hiatal hernia is a complex pathology, associated with gastroesophageal reflux disease, and whose management involves complex surgical treatment. Knowing the role of gastropexy in reducing postoperative recurrences, the current study aimed to highlight the intraoperative advantages and results of this surgical technique. Our study includes 29 patients, aged between 34 to 84 years. Regarding the mechanism of occurrence, two thirds of the patients presented with mixed hiatal hernias, 31.03% with sliding hiatal hernias and 3.45% with paraesophageal hiatal hernias. The hernia size played a decisive role in the choice of surgical procedure, for large hernias (with a diameter of over 7 cm) the Nissen procedure associated with gastropexy was preferred.For hernias with a diameter of less than 7 cm, the Nissen procedure associated with hernia orifice repair was performed. For hernias between 5 and 6 cm, gastropexy was also performed. The association of gastropexy does not increase hospitalization costs, but in the long term it has the advantage of reducing relapse.

Abstract: Quantum computing exploits the principles of quantum mechanics to perform computation. Information is stored in qubits and processed with a sequence of quantum gates arranged as circuits. Verifying the correctness of quantum circuits is becoming essential as hardware scales in qubit count and architectural complexity. Traditional testing and naive simulation do not scale and quickly become computationally infeasible because the state space grows exponentially. This creates a strong need for more powerful and scalable verification techniques. Formal methods offer a viable solution by providing mathematically rigorous and scalable verification techniques that address these scalability challenges through abstraction, symbolic reasoning, and probabilistic guarantees. This study examines how formal methods are applied to quantum circuit verification. Specifically, four families of formal techniques: barrier certificates, abstract interpretation, model checking, and theorem proving are examined, along with the theoretical foundations and practical applications of these techniques. Finally, the study highlights open challenges and identifies promising directions for future research. An extensive set of references is included to support further study and exploration.

Abstract: With the evolution of the new power system, the importance of substation grounding network performance is increasingly prominent, the optimization of the old substation renovation work is also gradually into the right track and attention. In this paper, the impact of resistive coupling between the grounding network system and its surrounding underground metal pipe network system in the substation renovation project is explored and analyzed in depth, and the electromagnetic field model of the grounding network and the pipe network is established respectively by using the research method of field-circuit coupling and the two simulation software CDEGS and ETAP are integrated to focus on the changes in key performance parameters during the renovation of substation grounding network, and it is found that its resistive coupling effect leads to some fluctuations in the key performance parameters. Based on the above research content, a series of optimized protection measures suitable for the actual reconstruction project are further proposed, aiming at guaranteeing the safe and stable operation of the grounding system as well as the surrounding metal pipe network under fault conditions. This study provides a theoretical basis and practical technical support for the optimization of substation grounding network and similar projects.

Abstract: This study evaluated the potential of Gliricidia sepium foliage as a protein source to replace cottonseed cake (CSC) in the diets of young Bunaji bulls, with emphasis on nutrient digestibility, rumen fermentation characteristics and serum metabolites. Animals were allocated to four dietary treatments in which G. sepium replaced CSC at 0, 25, 50 and 75% levels. The basal diet was Brachiaria decumbens hay, while concentrates were offered at 2% of body weight. Blood samples were collected at the start, mid-point and end of the 44 day feeding trial to determine packed cell volume (PCV), total protein (TP) and blood urea nitrogen (BUN). Rumen pH, ammonia nitrogen and total volatile fatty acids were measured before and after feeding. Metabolic study was conducted at the end of the feeding period. Results showed that PCV, TP and BUN were within normal physiological ranges. Rumen fermentation characteristics were comparable across treatments. Nutrient digestibility was generally unaffected, except for crude fibre, while all diets resulted in positive nitrogen balance, with higher nitrogen retention at 50% inclusion levels. In conclusion, Gliricidia sepium foliage can effectively replace cottonseed cake up to 50 % in diets of Bunaji bulls without compromising health status, rumen function or nutrient utilization.

Abstract: This paper translates a GIS-based multi-criteria evaluation (GIS–MCE) developed for the Food and Agriculture Organization (FAO) Hand-in-Hand Initiative (HiH), into a scien-tific manuscript on aquaculture zoning and site suitability in the Republic of Benin. We integrate sub-models on market accessibility, demand (population and asset wealth in-dex), biophysical conditions (water balance, soils, slope), and input availability (crop and livestock systems) to produce suitability indices for three fish farming systems: (i) ex-tensive to semi-intensive small-scale and integrated ponds; (ii) peri-urban intensive closed systems (tanks, ponds, RAS); and (iii) intensive open tilapia cages in waterbodies. A marked south–north gradient emerges, with southern and central communes showing highest suitability for non intensive systems. Priority communes include Bassila, Bantè, Ouessè, Savè, Kétou, Djidja, Agbangnizoun, Zangnanado, Ouinhi, Lalo, Bonou, and Ad-johoun. Intensive closed systems concentrate around Abomey-Calavi, Cotonou, and Porto-Novo due to superior market access. For open cage farming, southern permanent waterbodies—particularly Lakes Ahémé and Nokoué and selected reservoirs such as Zagnanando, Azili, and Ilauko—appear promising, though environmental risks (eu-trophication, pollution) warrant caution. We discuss methodological assumptions, data constraints, and limitations (e.g., absence of formal MCDA methods), and conclude with policy recommendations emphasizing environmental safeguards, support to traditional systems (e.g., whédo), improved feed and seed access, and strengthened biosecurity and monitoring frameworks for sustainable aquaculture expansion.

Abstract: Objectives: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and has increasingly been associated with cognitive impairment and dementia. Structural remodelling of the left atrium may contribute to early cognitive decline in patients with AF.This study aimed to evaluateearly cognitive impairment in middle-aged patients withAFusing comprehensive neuropsychological testing and to explore its association with conventional echocardiographic parameters of left atrial structure and function. Methods: Between 2023-2024, fifty-six consecutive outpatients with AF aged 45–65 years underwent clinical evaluation, transthoracic echocardiography, and comprehensive neuropsychological assessment using the Montreal Cognitive Assessment (MoCA) and the Consortium to Establish a Registry for Alzheimer’s Disease battery (CERAD). A con-trol group of 58 age group-matched individuals without known cardiovascular disease was included in comparative cognitiveanalyses.Results: Patients with AF demonstrat-edearly cognitive deficits, particularly in episodic memory and visuospatial functions, detectable even in individuals with normal MoCA scores. Patients with abnormal MoCA results exhibited more pronounced and widespread cognitive impairment. No statistically robust associations were observed between cognitive performance and conventional echocardiographic parameters of left atrial structure and function. These findings may reflect limited statistical power or the need for more sensitive markers of atrial remodeling. Conclusions: Early cognitive impairment in AF may be present before abnormalities are detectableby brief cognitive screening tools. The combined use of comprehensive neuropsychological assessment and echocardiographic evaluation may enhance early identification of cognitive vulnerability in this population. Further prospective studies are warranted to clarify the clinical relevance of atrial structural remodeling in this context.

Abstract: Morphostructural characterization of Creole cattle is essential for assessing the diversity and productive potential of this resource in the highland livestock systems. The study was conducted in Chuschi and Chipao districts, at 3,800 m above sea level, with the objective of morphostructurally characterizing and determining the zoometric indices of 154 Creole cows. Seventeen phaneroptic variables and twenty-one morphometric variables were rec-orded. The multivariate analysis identified three cattle biotypes. Based on proportionality, compactness, and cannon bone load indices, Biotype 1 (16.9%) comprised more compact, robust, and heavier animals with a greater tendency toward meat production aptitude, followed by Biotype 2 (48.1%) and Biotype 3 (35.1%), more slender but with a stronger bone structure. No association was found between biotypes and phaneroptic characteris-tics, except for teat type (p< 0.05). The proportions of red, black, dull black, qosca, and roan coat colors were common across all biotypes; however, Biotype 1 predominated in callejón (15.38%), Biotype 2 in qosne (8.11%) and in other less frequent coat colors (10.81%), while Biotype 3 predominated in dark roan (16.67%) and jet black (11.11%). In the high-Andean region of Ayacucho, three subpopulations of Creole cattle were identified with potential for beef production, dual-purpose use, and adaptation to rugged terrain.

Abstract: This study investigates ionospheric total electron content (TEC) and differential code bias (DCB) based on GPS and Galileo data collected aboard the training ship (HANS) from DOY 249 to 300 in 2024. The estimated TEC was compared with the Center for Orbit Determination in Europe (CODE) global ionospheric map (GIM), resulting in a mean difference of –2.41 TEC units (TECU) and a root mean square (RMS) error of 6.53 TECU. Furthermore, although inland GNSS stations in South Korea were incorporated to stabilize receiver DCB estimation, the results still exhibited significant temporal fluctuations. The Pearson correlation revealed a moderate negative relationship between the receiver DCB change and the Dst index, with a correlation coefficient (R) of –0.35. It suggests that geomagnetic disturbances influence receiver DCB changes. The R between receiver DCB and the Kp index was approximately 0.18, while that with the F10.7a index was about –0.26, both indicating a relatively weak correlation. In addition, receiver DCB changes exhibited a positive correlation (R ~ 0.33) with vertical TEC (VTEC). Multipath errors showed negligible correlation with receiver DCB changes. Therefore, we suggest that the significant variability in the receiver DCB on the HANS has a strong correlation with the Dst and VTEC. It can also be attributed to the complex interaction of several factors.

Abstract: To study follicular growth pattern and luteal dynamics during natural and induced estrous cycle in Arunachali Yak maintained at the Nyukmadung farm of ICAR-NRC on Yak of Arunachal Pradesh. A total of 36 animals of apparently healthy cyclic female yaks of first to fourth parity and free from any post parturient complications, maintained under intensive system of rearing were selected for the study and equally divided into two groups. Female yak with natural oestrus was placed in Group-I and the female yak subjected to Double Ovsynch protocol were placed in Group-II. Transrectal-ultrasonography was performed daily for one oestrous cycle to monitor the follicular growth pattern and Luteal dynamics. Three wave patterns were observed in natural oestrus and four wave patterns were observed in induced oestrous female yak. The common follicular wave pattern in Arunachali Yak was two wave pattern (66.67%) in natural oestrus and three wave pattern (77.78%) in induced oestrus. The overall mean oestrous cycle length in natural oestrous (Group I) and induced oestrous (Group II) female yak was found to be 20.00±0.86 and 22.50±0.57 daysrespectively.Two follicular wave patterns in natural oestrus and three follicular wave patterns in induced oestrus was the most common in Arunachali Yak. The length of first follicular wave was found to be maximum in both natural and induced oestrous. The length of follicular wave decreases successively as the number of follicular waves increases in Arunachali Yak. The size of Corpus Luteum was found significant difference in between the group.

Abstract: With the deep integration of artificial intelligence (AI) into education, AI literacy has emerged as a core competency indispensable for pre-service teachers. However, the formation mechanisms and sustainable cultivation pathways remain underexplored. This study integrates the Technology Acceptance Model (TAM) and the Innovation Diffusion Theory (IDT) to construct a theoretical model where Individual Innovations (II) and Self-Efficacy (SE) serve as antecedents, Perceived Usefulness (PU) and Perceived Ease of Use (PEOU) as mediators, Behavior Intention (BI) as a proximal variable, and AI literacy (AIL) as the outcome variable. Through a questionnaire survey of 778 pre-service teachers, mixed empirical tests were conducted using Structural Equation Modeling (SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA). SEM results indicate that II and SE significantly and positively influence AIL through a chain mediation involving PE, PEOU, and BI. fsQCA further identifies four convergent high-AIL configurational pathways: "High-efficacy-practice-oriented" "High-adoption-intention-oriented" "High-innovative-qualities-oriented" and "Balanced-development-oriented". The study reveals that enhancing pre-service teachers' AIL involves diverse yet equivalent mechanisms, necessitating a shift beyond singular training paradigms. Based on these findings, the research proposes differentiated cultivation pathways, providing both theoretical foundations and practical references for teacher-training institutions to implement precise and sustainable AIL development.

Abstract: The immunoglobulins (IG) or antibodies and the T cell receptors (TR) are the antigen receptors of the adaptive immune responses (AIR) of the jawed vertebrates (Gnathostomata). IMGT®, the international ImMunoGeneTics information system®, was created in 1989 by Marie-Paule Lefranc (Laboratoire d’ImmunoGénétique Moléculaire (LIGM), Université de Montpellier and CNRS) to deal with and to manage the huge diversity of the IG or antibodies and TR. The founding of IMGT® marked the advent of immunoinformatics, a new science which emerged at the interface between immunogenetics and bioinformatics. For the first time, the IG and TR variable (V), diversity (D), joining (J) and constant (C) genes were officially recognized as ‘genes’ as well as were the conventional genes. The IMGT-ONTOLOGY CLASSIFICA-TION axiom and the concepts of classification have generated the IMGT nomenclature and the IMGT Scientific chart rules for assigning IMGT names to IG and TR genes and alleles of Homo sapiens and of an

Abstract: The optimization of herbicide application is one of the most important topics in Precision Agriculture, driven by both economic efficiency and ecological sustainability. Excessive herbicide use can lead to soil degradation, water contamination, and negative impacts on biodiversity, while also contributing to human health risks and climate-related concerns. Developing accurate, automated approaches for distinguishing crops from weeds is therefore essential to support sustainable agricultural practices. In this paper, a novel architecture for crops and weed segmentation in tobacco plantations is proposed: a U-Net variant which incorporates several specific design elements, including deep supervision, a Vegetation Global Context block, and a dual-headed output that separately predicts vegetation and crop masks. Weed regions are derived as the difference between vegetation and crop predictions, allowing the model to enforce logical consistency directly within a single framework, in contrast to other two-step approaches. The proposed architecture was evaluated using multiple modern encoder backbones. Experimental results demonstrate that this architecture not only improves segmentation accuracy compared to prior approaches, with best scores of 94.24% Dice for crop segmentation and 93.72% for weeds, but also significantly reduces inference time by avoiding multi-stage pipelines, making it much better suited for real-time deployment in field conditions.

Abstract: The approval of the selective NaV1.8 inhibitor Suzetrigine for acute pain has renewed optimism for developing novel analgesics, yet the clinical failure of its successor VX993 highlights the persistent difficulty of translating promising pain targets into effective therapies. This review examines why progress has been limited and how modern human centered approaches can reshape pain drug discovery. Human genetic studies from large biobanks demonstrate that genetically supported targets have a higher likelihood of clinical success. However, for pain, the relationship between genetic association and therapeutic efficacy is complex. Rare mutations in NaV1.7 and NaV1.8 strongly validate these channels as valid pain targets, yet common variant studies reveal little association with chronic pain risk, underscoring a polygenic and pathway level architecture rather than single gene causation. Human transcriptomic atlases of dorsal root ganglia (DRG) reveal extensive redundancy across NaV channel isoforms, helping explain the modest efficacy of selective NaV1.8 inhibition and pointing toward the need for multi target or pathway wide approaches. Multiomic analyses in osteoarthritis highlight additional pain generating mechanisms, including synovial inflammation, neuroimmune interactions, metabolic dysregulation, and osteoclast activity, along with the involvement of specific nociceptor subtypes. Human DRG electrophysiology and PK/PD modeling show that Suzetrigine achieves high NaV1.8 target engagement yet cannot fully silence nociceptors, and that central not solely peripheral NaV1.8 channel blockade may be required for robust analgesia. This helps explain the failures of peripherally restricted NaV1.7, NaV1.8 and TRPA1 channel blockers. Despite limitations, animal models remain essential for capturing integrated physiological responses and active drug metabolites not evident in vitro. Together, these findings support a more rigorous framework for target validation, integrating human genetics, multiomics, electrophysiology, and translational pharmacology to guide the development of next generation of pain therapeutics.

Abstract: Introduction: Heart failure (HF) is a commonly encountered fatal clinical condition. Catestatin is a peptide produced by the breakdown of chromogranin A and inhibits catecholamine secretion. The main goal of this study is to identify the difference between catestatin levels in patients at without and with different stages of HF. It is important to determine catestatin’s relationship with pro-B-type natriuretic peptide (proBNP) and left ventricular ejection fraction (LVEF), that are used to identify HF and as well as other laboratory findings in order to better understand the contribution of catestatin. Materials-Methods: Sixty HF patients with LVEF< %45 and 53 matching control patients of factors that can impact catestatin level were included in the study. Plasma samples of these patients and controls were simultaneously collected in tube containing a drop of aprotinin (proteinase inhibitor). Plasma catestatin levels were measured by using enzyme-linked immunosorbent assay method. Results: The study findings showed that catestatin levels of HF patients (45.46±16.69 ng/ml) were significantly higher than that of patients without (37.15±16.36 ng/ml) (t=2.69, p< 0.05) and that the catestatin level increases as the HF stage progresses (J-T=2.19; p< 0.05). Catestatin level is found to be correlated positively with proBNP (r=0.241; p< 0.05), and inversely with LVEF (r=-0.19; p< 0.05). The area under the ROC curve calculated in order to demonstrate catestatin’s diagnostic adequacy in heart failure was 0.635. Discussion: Catestatin is considered an indicator of HF and it seems reasonable to use it for diagnosis and follow-up as it increases with disease severity.

Abstract: Previous studies suggest that elevated competitive anxiety may increase the likeli-hood of injury. The present research aims to examine the role of competitive anxiety as a predictor of injury occurrence, frequency, and severity. A cross-sectional, correlational de-sign was conducted with 131 athletes, (mean age = 16.49 years), predominantly male. In-juries data were obtained through medical record review, and competitive anxiety was assessed using the Competitive Anxiety Inventory-2. Empirical frequency distributions, descriptive statistics, non-parametric tests, and logistic and ordinal regression models were employed. A high incidence of injuries was observed, although most were minor. Competitive anxiety was characterized by elevated levels of cognitive anxiety and self-confidence. Injured athletes exhibited greater overall competitive anxiety (r = .31, p < .001), with higher levels observed among those who sustained more injuries (ε² = .12, p = .001), and a very large effect was found in relation to injury severity (ε² = .17, p < .001). The occurrence of injury can only be predicted in 10.9–14.7% of cases through increased cogni-tive and somatic anxiety, whereas an increase across all dimensions of competitive anxi-ety predicts a greater number (13–14%) and severity (20.3–21.8%) of injuries. These find-ings underscore the importance of developing skills to manage competitive anxiety, par-ticularly its cognitive dimension and maintaining optimal levels of self-confidence in young athletes.

Abstract: This study aimed to investigate sex-specific behavioral differences in adult Wistar rats using a 3-minute Open Field Test (OFT), aligning with ethical guidelines emphasizing inclusive animal research for translational validity. While previous literature suggests female Wistar rats often display greater locomotor activity and central exploration, indicative of lower anxiety, these findings are not universal due to protocol variations. Fourteen Wistar rats (7 males, 7 females), aged 12 weeks, underwent the OFT in a controlled environment, adhering strictly to ethical protocols. Behavioral parameters assessed included locomotor activity, time in central zone, rearing frequency, grooming, and defecation. Data were analyzed using Student's t-test or Mann-Whitney test, with a significance level of p < 0.05. Results revealed no statistically significant differences between sexes for any analyzed variable (p > 0.05). Females exhibited numerically higher locomotor activity (50.43 ± 10.0 vs. 45.29 ± 12.3) and rearing frequency (17.43 ± 5.56 vs. 14.29 ± 4.15), whereas males showed numerically higher grooming (2.43 ± 2.51 vs. 0.14 ± 0.38) and defecation (1.71 ± 1.5 vs. 0.43 ± 1.13). These numerical trends, however, did not reach statistical significance. The findings align with the mixed results reported in the literature concerning sex differences in anxiety and exploratory behaviors within the OFT paradigm, particularly when using small sample sizes. Methodological limitations include the sample size and the absence of estrous cycle control, though the latter was reinterpreted for its ecological validity. Despite the lack of robust differences in spatial or general activity metrics, the observed trends in grooming and defecation hint at subtle sex-specific stress reactivity. This study contributes to methodological optimization by demonstrating the applicability of a brief 3-minute OFT protocol, which reduces animal exposure to experimental stress. Furthermore, it reinforces the critical importance of systematically including both sexes in behavioral research to ensure translational validity, even when statistically robust differences are not immediately apparent. Future research incorporating larger sample sizes and comprehensive hormonal monitoring is necessary for a more nuanced characterization of sex-specific behavioral responses in stress-related paradigms.

Abstract: Financial fraud is one of the biggest operational risks for financial institutions, generating significant financial losses and destabilizing the market. While machine learning models are good at predicting, their evaluation often relies on statistical performance metrics that don't directly translate into financial impact. This research develops an evaluation framework that integrates the costs of early fraud detection with predictive effectiveness and economic criteria for decision-making. Several supervised learning models (XGBoost, neural network, random forest, decision tree, and logistic regression) were trained and tested on an unbalanced dataset of credit card transactions. To measure the potential benefit of the models for financial institutions, the savings rate and expected loss were used, along with classic metrics such as F1 score, AUC-PR, AUC-ROC, recall, and accuracy. The economic results are highly sensitive to models with similar predictive capabilities. The ensemble methods, in particular, achieved the optimal balance between fraud detection capabilities and loss reduction, while models optimized solely for accuracy resulted in higher operating costs due to false positives or undetected fraud. The results indicate that the choice of fraud detection models should not be based solely on predictive accuracy, but also on cost asymmetry and risk tolerance. The proposed framework offers practical guidance to financial institutions seeking to align operational risk management and regulatory requirements with the implementation of machine learning, enabling risk-informed decision-making.