Abstract: Background: Maternal overweight, obesity, and inappropriate gestational weight gain (GWG) are increasingly recognized as major contributors to adverse pregnancy outcomes worldwide. Elevated pre-pregnancy body mass index (BMI) is associated with gestational diabetes mellitus (GDM), hypertensive disorders, cesarean delivery, fetal overgrowth, and long-term cardiometabolic risks for both mother and child. Regional contemporary data from Bulgaria remain limited. Objective: To evaluate trends in maternal obesity and gestational weight gain among pregnant women in Southeastern Bulgaria between 2021 and 2025, using a regional cohort from Burgas, and to assess associations with maternal and neonatal outcomes. Methods: This retrospective cohort study included 1,176 singleton pregnancies registered for antenatal follow-up at MC Prime Clinic – Dr. Kirovakov Ltd., Burgas, Bulgaria, between January 2021 and December 2025. Women were classified according to World Health Organization BMI categories as underweight, normal weight, overweight, and obese. Gestational weight gain was categorized as below, within, or above Institute of Medicine recommendations. Maternal and neonatal outcomes were analyzed using comparative statistics and multivariable logistic regression. Results: The mean maternal age was 30.8 ± 5.4 years, and the mean pre-pregnancy BMI was 25.1 ± 4.8 kg/m². BMI distribution was: underweight 7.6%, normal weight 49.8%, overweight 27.9%, and obesity 14.7%. Overall, 42.6% of women entered pregnancy overweight or obese. Mean total GWG was 13.2 ± 5.6 kg. Excessive GWG occurred in 39.0% of women, while only 39.6% remained within recommended ranges. Excessive GWG was significantly more common among obese women (52.8%) than among women with normal BMI (34.7%, p<0.001). Compared with women of normal BMI, obese women had significantly higher rates of gestational diabetes mellitus (16.7% vs 5.8%), hypertensive disorders (12.9% vs 4.2%), preeclampsia (8.4% vs 2.1%), cesarean delivery (47.4% vs 28.6%), macrosomia (14.5% vs 6.1%), and preterm birth (10.7% vs 6.9%) (all p<0.05). In multivariable analysis, maternal obesity independently predicted GDM (aOR 2.94, 95% CI 1.82-4.73), preeclampsia (aOR 3.18, 95% CI 1.87-5.39), cesarean delivery (aOR 2.11, 95% CI 1.42-3.14), macrosomia (aOR 2.46, 95% CI 1.51-4.01), and preterm birth (aOR 1.67, 95% CI 1.02-2.74). Conclusions: Maternal obesity and excessive gestational weight gain were highly prevalent among pregnant women in Southeastern Bulgaria during 2021-2025 and were strongly associated with adverse maternal and neonatal outcomes. These findings support the need for preconception counseling, individualized antenatal weight management, and targeted regional public health strategies.

Abstract: Speculative decoding accelerates autoregressive generation by allowing a lightweight drafter to propose future tokens while a target model verifies them in parallel. Its lossless guarantee has motivated a line of work that pushes the drafter itself into parallel generation—the most recent enorous method is block-parallel generative approaches, including diffusion-based drafting methods such as DFlash and DSpark, achieving a 3.6x speedup on common daily chatting tasks. While this transition is well studied in text-only LLMs, its applicability to multimodal models remains an open question. Existing multimodal speculative decoding efforts focus on input compression, adapter alignment, candidate coverage, or modality-specific verification; however, block-parallel generative drafting remains largely unexplored. To bridge this gap, this paper combines a modality-centered survey with a cross-architecture empirical study to ask: Is multimodal speculative decoding ready for diffusion-based parallel drafting? In this survey, we systematically analyze a wide spectrum of multimodal models—spanning Vision-Language, Video-Language, Audio, and Vision-Language-Action (VLA) architectures—from the dual perspectives of drafting parallelism and cross-modal information interaction. We introduce a unified taxonomy that isolates drafter-side parallelism from orthogonal design choices such as tree construction and verification strategies. Furthermore, we provide a comprehensive empirical comparison of existing methods under varying degrees of parallelism across standardized multimodal benchmarks, including OCR, VQA, visual reasoning, and image captioning. Finally, we summarize the limitations of current approaches, discuss open challenges, and outline promising future directions for this rapidly evolving field.

Abstract: In this paper, recurrent MAP flows are constructed using a Markov?modulated Poisson process. Given the deterministic dead time for these flows, recurrent observation flows are determined. Dead times are estimated as the minimum distances between adjacent observation times. The validity of these estimates is proved using an upper bound for the jump size of the random walk defined by the recurrent MAP flow. This upper bound is investigated using the continuity theorem for uniformly convergent series of continuous functions and the Weierstrass theorem on the maximum of a continuous function on a segment.

Abstract: Let pk denote the k-th prime and let θ(x) = Σ_p≤x log p be Chebyshev’s function. For S(k) :=^k−1Σ_i=1(log θ(p_i+1)/θ(p_i)−log p_i/p_i, we show that S(k) telescopes exactly to log θ(p_k)−log log 2− M(p_k−1), where M(x) := Σ_p≤x log p/p, and that consequently lim _k→∞S(k) = −log log 2 − E = 1.699095 . . . , where E ≈ −1.332582 is the constant of Mertens’ first theorem – a consequence of the Prime Number Theorem alone. Using the Vinogradov–Korobov zero-free region, we upgrade this to the rate statement S(k) < 1.699095 . . . + C exp(−c₄(log p_k)^3/5(log log p_k)^−1/5) for absolute, effectively computable but not explicitly evaluated constants C, c₄ > 0, the best known unconditional shape for the convergence of S(k) to its limit. We also show that a natural candidate combination of S(k) with Σ_p<pk log p/p and e^−γ Π_p≤pk p/(p−1) provides strong structural evidence that Nicolas’ 1983 inequality is never violated, thus unconditionally supporting the truth of the Riemann Hypothesis. We also record an explicit bound of Axler for the product Π_p≤x(1 − 1/p), an explicit Dusart-type estimate for the Mertens sum, and Nicolas’ criterion itself, which recasts RH as the statement that X_k := Π_p≤pk p/(p − 1) − e^γ log θ(p_k) is positive for every k; if RH is false, X_k is known to change sign infinitely often.

Abstract: Enterprise adoption of artificial intelligence has accelerated from analytical systems and predictive models toward generative AI, knowledge-based systems, and autonomous agentic workflows. However, many organizations continue to experience fragmented AI initiatives, disconnected governance mechanisms, isolated knowledge repositories, and limited integration between intelligence generation and accountable decision execution. This paper proposes a Reference Architecture for Governed Cognitive Enterprises (GCEA), a conceptual architecture model that integrates enterprise intelligence, knowledge memory, decision intelligence, agentic AI, and AI assurance into a unified enterprise-scale intelligence operating architecture. The proposed architecture addresses a fundamental limitation of current enterprise AI approaches: the separation between strategic intent, organizational capability, knowledge retention, decision processes, autonomous execution, and governance controls. The architecture introduces six integrated capability domains: 1. Strategic Intelligence Foundation; 2. Knowledge Memory Fabric; 3. Decision Intelligence Layer; 4. Governed Agentic Intelligence Layer; 5. AI Assurance and Governance Layer; 6. AI Operations and Continuous Evolution Layer. Unlike domain-specific AI frameworks, GCEA focuses on architectural integration, defining how intelligence capabilities, governance mechanisms, human accountability boundaries, and operational feedback loops interact as a unified enterprise system. The proposed model provides a reference architecture for organizations seeking to move from fragmented AI experimentation toward governed cognitive enterprises capable of producing trusted, explainable, measurable, and continuously improving intelligence. The paper contributes: 1. A unified architecture model for governed cognitive enterprises; 2. An integration model connecting multiple enterprise AI capabilities; 3. A governance-aware approach for human–AI collaboration; and 4. A maturity perspective for cognitive enterprise evolution.

Abstract: The rational design of inorganic phosphors with targeted emission wavelengths is challenging because luminescence depends on strongly coupled structural, electronic, and excitation-dependent factors. Machine-learning studies in this area often prioritize predictive accuracy without systematically evaluating descriptor reproducibility and physical interpretability. Here, we develop a physics-guided explainable machine-learning framework that combines multi-method feature selection, descriptor stability analysis, and physicochemical interpretation for emission-wavelength prediction. A curated dataset of 2327 single-dopant phosphor compositions, initially represented by 125 physicochemical descriptors, was refined to 49 physically meaningful descriptors. Twelve complementary feature-selection methods were evaluated using eight stability metrics and 10-fold cross-validation. Pearson correlation and ANOVA-F independently converged on the same seven-descriptor subset with complete 10/10 fold-level reproducibility. The resulting Random Forest model achieved a mean cross-validated R² = 0.9308, MAE = 7.78 nm, and RMSE = 22.55 nm. The seven-descriptor model retained essentially the same predictive performance as the best fully reproducible 24-descriptor model while reducing descriptor dimensionality by about 71% relative to that model and by about 86% relative to the full physically meaningful candidate space. On the independent test set, RF and GB achieved R² values of 0.9192 and 0.9023, respectively. SHAP analysis, descriptor ablation, interaction analysis, and complementary feature-importance methods consistently identified the same descriptor hierarchy. The ionic radius of the emission-center site was the dominant predictor, followed by excitation source and dopant valency. These results suggest four practical considerations for phosphor screening, namely activator-site compatibility, dopant oxidation state, host chemical environment, and excitation conditions. The results show that descriptor selection should consider not only predictive accuracy but also reproducibility, compactness, generalizability, and physical interpretability, as confirmed by learning-curve analysis.

Abstract: Credit card fraud detection remains a challenging classification problem due to the severe imbalance between legitimate and fraudulent transactions, where conventional accuracy can provide a misleading assessment of model effectiveness. This study proposes an explainable machine learning model for credit card fraud detection by comparatively evaluating Logistic Regression, Random Forest, XGBoost, LightGBM, and CatBoost against a Dummy Classifier baseline. Model performance was assessed using balanced accuracy, precision, recall, F1-score, ROC-AUC, PR-AUC, confusion matrices, prediction errors, and computational training time. McNemar’s test was further employed to statistically assess differences in paired model predictions, while SHapley Additive exPlanations (SHAP) provided global and local interpretability of the best-performing model. Experimental results identified XGBoost as the strongest overall classifier, achieving a PR-AUC of 0.8231, ROC-AUC of 0.9752, fraud precision of 0.9259, recall of 0.7895, and F1-score of 0.8523. XGBoost additionally produced the fewest prediction errors and the shortest training time among the evaluated gradient-boosting models. McNemar’s test indicated a statistically significant difference in paired model predictions (p = 1.29 × 10⁻¹¹). SHAP analysis identified V14, V4, V12, V10, and V11 as the most influential features, while transaction-level explanations revealed how individual feature values contributed toward or against fraud predictions. The findings demonstrate that combining gradient boosting, imbalance-sensitive evaluation, statistical validation, and explainable AI can provide an accurate, computationally efficient, and interpretable approach to credit card fraud detection.

Abstract: To address the limited channel robustness of invertible neural networks against Gaussian noise, JPEG compression, and scaling/resampling in image information hiding, while maintaining their embedding capacity, we propose an invertible steganography algorithm that integrates a dual-branch attention mechanism in the frequency domain. First, a dual-branch attention module is designed to adaptively generate embedding weights from both global subband energy and local texture pixel dimensions after wavelet multi-frequency decomposition, thereby constructing a four-channel extended secret payload. Second, a four-channel extension strategy is developed to enhance embedding capacity without introducing random noise distortion. Additionally, dual enhancement mechanisms are employed to preprocess the original carrier before embedding, optimize frequency-domain feature distribution, and restore images contaminated by noise, compression, or scaling attacks during reconstruction. Experimental results demonstrate that under a 1:1.34 embedding ratio, the proposed algorithm achieves a clean-channel C-PSNR of 36.27 dB; under Gaussian noise (σ=10) and JPEG(QF=50) attacks, PSNR values for all channels reach 27.96 dB and 29.43 dB respectively. Compared to comparable models without attention mechanisms, this approach improves carrier quality and secret recovery metrics by over 2 dB on average, combining high transmission capacity with excellent channel robustness and visual imperceptibility.

Abstract: This work presents a comprehensive analysis of the Zero Pairs Interaction Functional (ZPIF) within the Unified Spectral Alignment and Coherence (USAC) framework, integrated with the Zigzag Zero–Fractional Zero (ZZFZ) formulation, to investigate the full spectrum of Zero Behavior Motions (ZBM) and their direct connection to Prime Distribution (PD).Unlike classical approaches that treat zeta zeros as static and independent, this framework redefines zeros as active spectral entities that interact with themselves before interacting with others. These self-interactions include quadratic, higher-order polynomial, and fractional interactions (division, root extraction, and logarithmic mappings), followed by cross-mode interactions with other zeros.The theory introduces a unified spectrum of interconnected phenomena: zigzag motion, aberration, energy stability, cavitation, spectral reflection, spectral constriction, unstable spectral oscillation, spectral fissure, temporal succession, spectral pulsing, spectral bursting, axial orientation, spectral cleavage, boundary reflection, slicing and reformation, layered spectral stratification, and spectral unfolding.The entire system operates under a closed, energy-conserving regime that guarantees spectral stability and coherence across all scales. The framework offers a natural, mathematically rigorous explanation for the distribution of prime gaps, the nature of dark energy, the emergence of consciousness, and the geometric structure of spacetime. Numerical simulations using the first 100 non-trivial zeta zeros confirm convergence and stability.This work establishes ZPIF-USAC-ZZFZ as a new foundational paradigm that unifies spectral theory, number theory, and mathematical physics, opening new directions in quantum gravity, information theory, and consciousness studies.

Abstract: Background and Objectives: Older women with stress urinary incontinence (SUI) or stress-predominant mixed urinary incontinence (MUI) may remain dependent on pads or diapers despite clinically important symptoms. We described age-related care patterns and examined whether age remained associated with a predefined treatment gap after accounting for frailty and symptom burden. Materials and Methods: This single-center observational study combined record review (December 2023-April 2026) with a one-time questionnaire assessment (19 June-3 August 2026). The analysis included 480 women aged ≥65 years in three equal age groups (65-74, 75-84, and ≥85 years; n = 160 each). The treatment gap required an International Consultation on Incontinence Questionnaire-Urinary Incontinence Short Form score ≥8, at least one pad or diaper per day, containment-only current management, and no active treatment during the preceding 12 months. Frailty and anxiety were assessed with the FRAIL scale and Geriatric Anxiety Inventory. Multivariable logistic regression examined factors associated with the treatment gap and a positive anxiety screen. Results: Treatment-gap prevalence was 33.8%, 44.4%, and 55.0% across increasing age groups. Supervised pelvic floor muscle training declined from 55.0% to 40.0% and 25.0%; active treatment in the preceding year from 50.0% to 35.0% and 20.0%; and previous continence surgery from 30.0% to 18.1% and 8.1%. After adjustment, age was not independently associated with the treatment gap. Higher symptom scores (adjusted odds ratio [aOR] 1.10 per point, 95% confidence interval [CI] 1.02-1.19) and stress-predominant MUI (aOR 1.53, 95% CI 1.03-2.25) remained associated. A positive anxiety screen was associated with symptom severity, MUI, nighttime containment, and social-activity limitation. Conclusions: Containment dependence increased and active-treatment exposure decreased with age; however, symptom burden and incontinence phenotype explained more of the adjusted treatment-gap risk than chronological age. Regular reassessment may help distinguish appropriate containment from potentially remediable under-treatment.

Abstract: Background: Body composition may be a relevant determinant of metabolic and fun-ctional vulnerability in patients with colorectal cancer. This study aimed to investigate the association between different therapeutic strategies and body composition parameters. Methods: An observational, analytical, cross-sectional study was conducted in adult pa-tients with colorectal adenocarcinoma receiving active antineoplastic treatment at Hospital Universitario de Badajoz, Spain, consecutively recruited between November 2023 and June 2024. Nutritional status was assessed using the Patient-Generated Subjective Global Assessment (PG-SGA), and body composition was evaluated by multifrequency bio-electrical impedance analysis (BIA). Fat mass, fat-free mass, skeletal muscle mass, bone mass, protein mass, total body water, visceral fat, and basal metabolic rate were assessed. Patients were stratified according to treatment modality: surgery alone, FOREST protocol, neoadjuvant chemotherapy, adjuvant chemotherapy, and combined neoadju-vant-adjuvant chemotherapy. Between-group differences were assessed using ANOVA and association tests, complemented by regression models. Statistical significance was set at p< 0.05. Results: A total of 91 patients were included, with a mean age of 64.97±9.92 years; 56 (61.5%) were men. Significant differences between treatment modalities were observed in bone mass (p=0.023), protein mass (p=0.002), skeletal muscle mass (p=0.022), fat-free mass (p=0.022), and basal metabolic rate (p=0.039). Patients receiving adjuvant chemotherapy alone exhibited the lowest values for protein mass, skeletal muscle mass, fat-free mass, and basal metabolic rate, whereas those receiving combined neoadju-vant-adjuvant chemotherapy showed the highest values. No significant differences were observed in the remaining body composition parameters. Conclusions: Body composition differs significantly according to therapeutic modality, particularly in parameters related to skeletal muscle mass and physiological reserve. These findings support incorporating body composition assessment into comprehensive clinical and nutritional evaluation to identify patients with reduced physiological reserve and potentially greater treatment vulnerability. However, the cross-sectional design precludes causal inference. Prospective longitudinal studies are warranted to determine changes in body composition and their impact on treatment-related toxicity and clinical outcomes.

Abstract: This paper presents photographic records of orchids observed along the trail of Mt. Opao, Igbaras, Panay Island, Philippines. At least seven species were documented, including four terrestrial taxa and three epiphytes. Moreover, photographic evidence of Appendicula laxifolia represents a new island record for Panay, extending the species’ known distribution. The documentation was conducted during a hiking event in August 2026 and highlights the value of mobile photography and community‑accessible digital platforms for rapid biodiversity documentation and for detecting range extensions that inform conservation and biogeographic research.

Abstract: The Industrial Revolution is commonly periodized through successive technological discontinuities associated with mechanization, steam, electricity, mass production, computing, digital networks, and artificial intelligence. This paper proposes an alternative variable of historical observation: the functional-delegability frontier, defined as the historically demonstrated set of functions whose execution by technical systems is technically feasible under identifiable operating conditions. A function is specified independently of its mechanism as a transformation from an admissible input domain to a required output condition under specified operating conditions, F = (I, O, C). The framework distinguishes extensive expansion, in which a previously non-demonstrated function enters technical executability, from intensive expansion, in which the domain or conditions of an already delegable function broaden. It further separates functional flexibility—the range of distinct functions executable through a common architecture—from recursive expansion, in which delegated functions materially participate in developing additional technical capabilities. Historical cases ranging from pre-industrial automatic regulation and textile machinery to machine tools, punched-card systems, automatic telephone switching, general-purpose computing, industrial robotics, and machine learning are used to test the distinctions. The paper advances, as a falsifiable historical hypothesis rather than a definition, that mechanization, electrification, computing, digital technologies, and artificial intelligence can be interpreted as major technological discontinuities within a single, still-unfolding Industrial Revolution. The claim rests not on simple technological continuity but primarily on two proposed continuities: repeated reallocation of executable functions between humans and technical systems, and cumulative dependence of later technological systems on capabilities generated in earlier industrial development. A further, separately testable proposition is that delegated functions increasingly participate in producing subsequent technical capabilities, particularly after programmable computing. The framework does not explain the causes of industrialization or predict the economic consequences of automation; it offers a complementary historical variable through which continuity can be examined across technological discontinuities.

Abstract: This paper is a second in a three-part series providing an auxiliary parameter method for factorizing maximally entangled states. A major vulnerability of entangled states is they cannot be factored, leaving the whole composite system highly susceptible to decoherence. Factorizing these states creates a protective barrier that prevents local noise or measurements in one subsystem corrupting the rest of the system. This paper introduces an auxiliary parameter method that uses semi-structured complex numbers to create (1) an unphysical auxiliary parameter k_n and (2) a unique j-conjugate framework to embed maximally entangled systems in semi-structured state space and factorize them into independent single-qubit product states. To demonstrate this method the maximally entangled GHZ_n and W States were completely factorized. These factorizations strictly satisfy classical local realism, passing the Mermin Inequality Test (for GHZ-type states) and the MARS inequality test (for W states) whilst in semi-structured state space. Finally, an inverse transformation maps these auxiliary terms back to zero, recovering the original standard Euclidean quantum states. This framework provides a novel algebraic tool for manipulating maximally entangled states as formal tensor product states.

Abstract: Despite the significant role of hormonal health in adolescent well-being, substantial cycle education gaps remain in how menstrual cycle education is standardized and delivered. This literature review evaluates the current landscape of comprehensive, evidence-based menstrual cycle curriculums for adolescents to determine what instructional frameworks are available and have been effective. Findings highlight a shortage of comprehensive, evidence-based curriculums that address overall cycle health and well-being for adolescents and stigma around discussing menstruation. Comprehensive cycle education integrates biology with cycle-tracking and the psychosocial impacts of the menstrual cycle. This review attempts to map out the strengths and deficiencies identified in current programming and resources in K-12 public schools in the United States and community-based educational curriculums and discusses digital interventions that have emerged independently to provide foundational resources for educators and curriculum developers aiming to implement holistic cycle health education programs for adolescent populations.

Abstract: Extracellular vesicles (EVs) have emerged as promising cell-free therapeutic agents for bone regeneration due to their ability to modulate osteogenesis, angiogenesis, and immune responses. This review summarizes current knowledge on EV biology, including their classification, biogenesis, and molecular cargo, with a particular focus on their role in bone healing. EVs derived from mesenchymal stromal cells and other cell sources promote osteoblast differentiation, inhibit osteoclast activity, enhance vascularization, and modulate inflammation through the transfer of bioactive proteins and non-coding RNAs. Recent advances in EV engineering, biomaterial-assisted delivery, and isolation techniques are discussed, together with their translational potential for the treatment of critical bone defects and avascular osteonecrosis. Although preclinical evidence is highly encouraging, clinical translation remains limited by challenges in standardization, scalable manufacturing, and regulatory approval. Overall, EV-based therapies represent a promising future strategy for regenerative orthopedics and bone tissue engineering.

Abstract:

Organizations have long been understood as information-processing systems, and technological change has commonly been analyzed in terms of its capacity to increase the speed, scale, and complexity of information processing. This paper develops a complementary perspective by focusing on how information-processing functions are distributed between the human and technological components of organizations and how that distribution changes over time. We define information-processing allocation (IPA) as the distribution of information-processing functions across human and technological components at a given point in time, and information-processing reallocation (IPR) as a change in that distribution. Drawing on organizational information-processing theory, human–automation research, distributed cognition, and coordination theory, we argue that technological change modifies the range of allocations that are technically feasible without determining which of them organizations will adopt. Organizational, economic, and institutional conditions shape the transition from technological possibility to observed allocation. We further propose that reallocation becomes organizationally consequential when it restructures dependencies among actors, technological components, information flows, and decision processes, thereby creating opportunities or pressures for organizational redesign. The framework distinguishes information-processing allocation from information-processing capacity and from the automation of complete tasks, allowing hybrid human–technology configurations to be analyzed without assuming technological substitution or a predetermined direction of change. Mechanical tabulation, enterprise computing, and contemporary artificial intelligence illustrate how different technological capabilities can alter the allocation of organizational information processing. The paper contributes an organizational and explicitly temporal account of human–technology information processing and develops propositions for studying when technological possibilities become organizational reallocations and when those reallocations lead to changes in coordination and organizational design.

Abstract: This paper studies dynamic off-premise pricing for a capacity-constrained dine-in service system. We consider a food retailer with limited seating capacity, stochastic customer arrivals, and random dine-in service durations. Customers choose among dine-in consumption, off-premise ordering, and no purchase. The dine-in price is fixed, while the store dynamically controls the off-premise price. Unlike classical queue-pricing models, in which price regulates congestion by discouraging customers from entering the system, our model uses off-premise pricing to redirect customers from a capacity-consuming channel to a capacity-free channel. We develop a continuous-time Markov decision process in which the state is the number of occupied seats. The model captures the tradeoff between reducing off-premise margins and relieving future seat congestion. Numerical analysis compares optimal state-dependent pricing with the best constant-price policy and identifies the conditions under which dynamic diversion pricing improves long-run profit. The results provide managerial insights into when off-premise discounts can be used not merely as demand stimulation tools, but as congestion-management instruments in dine-in service operations.

Abstract: Background: Judo performance is multifactorial; judo-specific anaerobic fitness and shuttle agility speed have already been investigated separately in adolescent judoka. What remains unexplored is whether a technology-assisted neuromuscular training program can concurrently influence these established performance measures alongside plantar-support biomechanics during throwing techniques such as ippon-seoi-nage. Pilot data integrating these domains are lacking in adolescent judoka. Methods: Twenty-four male judoka (aged 15–17 years; ≥3 years of experience) were allocated to an experimental group (EG, n = 12) or control group (CG, n = 12). The EG performed a 12-week technology-assisted neuromuscular training program (BlazePod light-sensor system) before each session; the CG continued standard uchi-komi. Three outcome domains were assessed at baseline and post-intervention: (i) judo-specific anaerobic fitness (SJFT); (ii) specific shuttle agility (BlazePod protocol); and (iii) static plantar pressure (BTS P-WALK baropodometer). Results: Retention was 100% with no adverse events. A 2×2 mixed-design ANOVA (group × time) showed a significant interaction for BlazePod shuttle agility perfor-mance (Total Hits: p = .026; Total Average Reaction Time: p = .009), an effect that re-mained significant after a sensitivity analysis controlling for baseline anthropometric imbalance between groups. A significant interaction was also observed for the SJFT in-dex (p = .028), but this effect did not survive the same sensitivity analysis (p = .10). No significant group × time interaction was detected for any of the six static plantar pres-sure regions assessed (all p > .09). Conclusions: This pilot study demonstrated full feasibility and provided preliminary evidence of a group × time effect on judo-specific shuttle agility performance that re-mained significant after adjustment for baseline anthropometric imbalance, a less cer-tain effect on anaerobic fitness, and no detectable effect on static plantar pressure dis-tribution. These preliminary, hypothesis-generating findings support conducting a de-finitive, randomized, weight-stratified controlled trial.

Abstract: Interest-free banking and finance (IFB) has evolved from a marginal regulatory accommodation into an increasingly significant segment of Ethiopia’s financial sector within little more than a decade. This paper presents a market landscape and gap analysis of Ethiopia’s IFB industry, examining its institutional evolution, market structure, regulatory architecture, growth trajectory, opportunities, and persistent structural challenges. Drawing on the National Bank of Ethiopia’s Financial Stability Reports, recent regulatory directives, institutional reports, and industry evidence, the analysis indicates that deposits under IFB services reached ETB 379.1 billion by June 2025, supported by nine fully fledged institutions and 48 window-based providers across the banking, microfinance, and insurance sectors. Despite this substantial expansion, significant gaps remain in capital-market depth, Sharia-compliant liquidity-management instruments, financing-to-deposit conversion, technological capacity, specialized human capital, product diversification, and Shariah governance. The evolving regulatory and financial-market environment, including Banking Business Proclamation No. 1360/2025 and the establishment of the Ethiopian Securities Exchange, presents opportunities for developing Sukuk, Takaful, and other innovative IFB products. The reviews suggest that IFB represents an underexploited pathway for enhancing financial inclusion, particularly among Ethiopia’s Muslim population. However, sustainable growth requires stronger regulatory parity, improved liquidity infrastructure, enhanced Shariah-compliant capital-market instruments, greater technological and human-resource capacity, and increased consumer awareness. Coordinated action among regulators, financial institutions, researchers, and industry stakeholders is therefore essential for developing a resilient, inclusive, and competitive IFB ecosystem in Ethiopia.