Abstract: The object of research in the scientific article is the process of converting wind flow energy into mechanical energy. The process of converting wind energy into mechanical energy is carried out by two counter-rotating wind wheels. And into electrical energy in the generator, with the armature and inductor rotating in opposite directions. The purpose of the scientific article is to study and develop an efficient power supply system for autonomous consumers based on a wind power plant of a special design with an increased wind energy utilization coefficient. In the course of the work, the main parameters of a special-designed wind turbine with counter-rotating wind wheels were determined and the process of electric generation was modeled on the principle of counter-rotation of the armature and generator inductor; a physical model of a special-designed wind turbine based on a two-wheeled system located in the same wind flow and providing rotation of the armature and generator inductor individually from each wind wheel in the opposite direction was developed; a design documentation on the basis of which the experimental design sample was made; experimental studies of the experimental design sample of a wind turbine were conducted to determine its main parameters for the purpose of efficient power supply to autonomous consumers. Main design and technical and economic indicators: optimization of wind power plant parameters, dimensions of wind wheels, their relative location, as well as generator power depending on the expected wind speed. The degree of implementation lies in the fact that a wind generator with variable torque of a wind wheel is patented (patent for invention of the Republicof Kazakhstan No. 36903; Eurasian patent for invention No. 047230). The effectiveness of the research lies in the application of technical solutions patented by the authors in practice, which makes it possible to increase the energy efficiency of wind turbines. Scope of application of the developed wind turbine of special design in the field of alternative energy and decentralized agricultural consumers.

Abstract: Galaxy evolution models usually treat environment as a driver of quenching and morphological transformation, but less often as a regulator of how systems retain or erase long-term memory of past conditions. This paper uses the homeostatic potential framework $\hat{\phi}$ to ask a focused question: once a galaxy has crossed the structural ``stability gate'', how much additional leverage does environment still have on its chemical memory?Using SDSS DR8 and GAMA DR4 as low-redshift benchmarks, and the EAGLE RefL0100N1504 simulation as a controlled comparison, galaxies are split into structurally ``infant'' and ``adult'' regimes by the stability proxy $\hat{S}$. For each regime, the dispersion of the metallicity-based memory proxy $\hat{M}$ is measured as a function of local density and group-scale environment (k-nearest-neighbour density, projected surface density, and host-group halo mass). The same diagnostics are then applied to the TNG suite to test whether the infant/adult environmental contrast is a robust feature of hydrodynamical models with different feedback prescriptions. A MaNGA pilot sample provides an independent sanity check that $\hat{S}$ behaves as a structural maturity indicator rather than a data-quality or environment artefact. In SDSS, metallicity scatter rises with local density for structurally infant galaxies, but remains lower and only weakly environment-dependent for adults at fixed mass and stability. In GAMA, the scatter is nearly flat across four decades in projected density once $\hat{S}$ is fixed, with only a mild broadening in the highest-density adult bin. In EAGLE, the dependence of scatter on host halo mass is similarly weak at fixed structural state. TNG runs show very weak correlations between the homeostatic components and local density once mass selection is imposed, indicating that the stability gate is not simply a field--cluster split in disguise. The MaNGA pilot confirms that the entropy-like component $\hat{S}$ correlates strongly with galaxy size but only weakly with S/N, behaving as a structural maturity coordinate. Together, these results support a simple picture: environment acts as a strong modulator of homeostatic potential before the stability gate is crossed, but mainly tunes residual variance once galaxies have internalised their history into a stable configuration. Environment is a modulator of memory, not its primary container.

Abstract: Post-transcriptional regulation of gene expression is influenced by RNA-binding proteins (RBPs) and small non-coding RNAs which bind to conserved mRNA sequences to modulate mRNA processing. These regulatory molecules effect the structural conformation of mRNAs, creating formations like G-quadruplexes (G4s) which alter translation initiation and regulatory factor site accessibility. Recent studies have highlighted Nuclear factor erythroid 2-related factor 2 (NRF2) as a key regulator of cellular redox homeostasis and cellular response to oxidative stress. An intriguing feature of NRF2 is the structural formation of its 5’ untranslated region (UTR) which may promote or inhibit translation initiation depending on the cellular context. In this study with mini genes, we provide evidence of RNA G4s in NRF2 mRNA’s 5’ UTR regions under basal (no stress) conditions in vitro through EMSA and fluorescence spectra in the presence of pyridostatin. Understanding how structural motifs within NRF2’s 5’UTR regions influence mRNA function provides insights into a common molecular mechanism underlying diseases where NRF2 is dysregulated, like cancers, cardiovascular disease, and neurodegeneration, and highlights potential therapeutic avenues through regulation of NRF2.

Abstract: Remote sensing semantic segmentation encounters several challenges, including scale variation, the coexistence of class similarity and intra-class diversity, difficulties in modeling long-range dependencies, and shadow occlusions. Slender structures and complex boundaries present particular segmentation difficulties, especially in high-resolution imagery acquired by satellite and aerial cameras, UAV-borne optical sensors, and other imaging payloads. These sensing systems deliver large-area coverage with fine ground sampling distance, which magnifies domain shifts between different sensors and acquisition conditions. This work builds upon DeepLabV3+ and proposes complementary improvements at three stages: input, context, and decoder fusion. First, to mitigate the interference of complex and heterogeneous data distributions on network optimization, a feature-mapping network is introduced to project raw images into a simpler distribution before they are fed into the segmentation backbone. This approach facilitates training and enhances feature separability. Second, although the Atrous Spatial Pyramid Pooling (ASPP) aggregates multi-scale context, it remains insufficient for modeling long-range dependencies. Therefore, a routing-style global modeling module is incorporated after ASPP to strengthen global relation modeling and ensure cross-region semantic consistency. Third, considering that the fusion between shallow details and deep semantics in the decoder is limited and prone to boundary blurring, a fusion module is designed to facilitate deep interaction and joint learning through cross-layer feature alignment and coupling. The proposed model improves the mean Intersection over Union (mIoU) by 8.83% on the LoveDA dataset and by 6.72% on the ISPRS Potsdam dataset compared to the baseline. Qualitative results further demonstrate clearer boundaries and more stable region annotations, while the modifications to the baseline are minimal and easy to integrate into camera-based remote sensing pipelines and other imaging-sensor systems.

Abstract: In the transition towards digitalization and automation of mining processes, high vol-umes of data are generated, including data from distributed sensor and actuator networks, voice communications, videos and vehicle telemetry data. This generated data is prepro-cessed on-site and subsequently transferred not only to headquarters for detailed analysis but also between mining machines and vehicles in case of automation or autonomous mining. Stable and efficient communication in the mining industry and particularly in underground environments is essential for increasing safety and productivity, support fast and secure transportation and facilitate logistical processes, ensuring continuous and smooth operations. Several different communication technologies and protocols exist related to the mining field, each with its unique characteristics, advantages, or limitations. This article focuses on two essential technologies that, despite their shared goal of enhancing communication networks, exhibit notable contrasts in some of their characteristics: Long Range (LoRa) as an existing technology in the industry since years and the technology of the fifth genera-tion (5G) of cellular network will be presented and discussed in this article, highlighting the significant differences in their properties and applications. This provides an important basis for understanding the limits and possible trade-offs of the wireless communication technologies required in the mining industry for large scale sensor networks.

Abstract: High pressure processing (HPP) and ultrasound assisted extraction (UAE) can effectively shorten extraction time and increase extraction efficiency of cold brew (CB). however, their application in CB citri reticulatae pericarpium (CRP) and the underlying mechanisms of flavor modulation remain poorly understood. In this study, CB-CRP beverage was prepared with HPP-assisted, UAE-assisted and HPP-UAE-assisted extraction from 1, 3, 5, and 10 years CRP. Results revealed that the total soluble solids (TSS), total sugars, flavonoids, polyphenols, and volatile organic compounds (VOCs) and antioxidant activity of CB-CRP increased after assisted extraction. The combined application of HPP and HPP-UAE assisted extraction exhibited the most pronounced effects. The kinds and total content of VOCs of CB beverage prepared from 10-year-aged CRP increased from 45 to 81, and from 2.44 to 5.98 μg/mL resectively. Moreover, the combined HPP-UAE extraction promoted the enrichment of fatty and woody aroma-related compounds, which drove a shift in the flavor profile from fresh to a richer woody type. And this endowed the CB-CRP water with a more complex and multidimensional aroma profile.

Abstract: The Qinghai–Tibet Plateau and surrounding montane valleys comprise one of the world’s most pronounced freshwater environmental gradients, where cold, intense UV radiation, variable dissolved oxygen, and heterogeneous hydrodynamics interact with drainage reorganization and connectivity constraints. Schizothoracinae are among the most representative endemic lineages in these systems, combining exceptional lineage diversity with pervasive polyploid genomic backgrounds. Here we synthesize schizothoracine research through an “environment–evolution–conservation” framework, linking (i) taxonomic and phylogenetic foundations under pervasive convergence, cryptic diversity, and hybridization; (ii) geologic history and drainage evolution as drivers of radiation and gene exchange; (iii) polyploidy, post-WGD structural remodeling, and early rediploidization as a testable process rather than a static ploidy fact; and (iv) omics resources and analytical pipelines that enable verifiable evidence chains across comparative genomics, population genomics, and tissue-level stress responses. Across major stressors, recurrent molecular themes emerge for cold-associated metabolic remodeling and UV-associated DNA repair and genome maintenance, whereas hypoxia-related signals are often inconsistent, plausibly reflecting strong spatiotemporal heterogeneity and multi-route physiological accommodation. We further connect molecular candidates to functional outcomes using reusable phenotypic evidence streams, including geometric morphometrics, high-throughput phenotyping, otolith microchemistry, and age–growth life-history syndromes of slow growth and longevity. Finally, we translate population structure into operational MU/ESU delineation and propose an auditable, iterative management checklist centered on MU-aligned stocking, connectivity performance metrics during critical seasonal windows, and quantified habitat restoration targets. We conclude by outlining priorities to raise evidentiary strength across basins: chromosome-level genomes across lineages, systematic SV/TE comparisons, standardized stressor–phenotype–transcriptome designs, and intensified sampling in geomorphic transition zones and putative hybrid regions to enable cumulative, decision-ready synthesis.

Abstract: Postoperative aneurysm sac enlargement is a significant clinical issue in endovascular aortic aneurysm repair that is potentially associated with impaired microcirculation in the aneurysmal wall. We developed centimeter-long, fiber-shaped aggregates of human bone marrow-derived mesenchymal stromal cells (HMSC fiber) to function as a scaffold-free cellular construct applicable to endovascular treatment. HMSC fibers were fabricated using a cell self-aggregation technique and optimized by controlling the cell number per unit length to preserve cellular viability and mechanical stability. The resulting fibers retained mesenchymal stromal cell characteristics and endogenous extracellular matrix, facilitating smooth handling and intraluminal delivery without structural collapse. After transcatheter administration into a swine aortic aneurysm model, HMSC fiber-induced fibroconnective tissue formation stimulated neovascularization within the aneurysm cavity. These findings demonstrate the feasibility of HMSC fiber as a controllable and stable platform for localized endovascular cell delivery. Furthermore, this study established their potential utility as a regenerative adjunct to current endovascular treatment for aortic disease.

Abstract: Introduction: Despite improved health service accessibility, neonatal mortality in Ethiopia remains high at 33 per 1,000 live births. Thus, improving health facilities’ readiness across infrastructure, basic amenities, equipment, medications, laboratory services, Kangaroo Mother Care, infection prevention and control, staffing, and guidelines availability is critical for improving the quality of neonatal care and improving survival. Objective: To evaluate the readiness of Ethiopian hospitals to provide services to small and sick newborns. Methods: A cross-sectional study including 208 hospitals across four regions in Ethiopia in 2021–2024, prior to the phased implementation of the Saving Little Lives program. Data were collected using an adapted World Health Organization’s Service Availability and Readiness Assessment tool and are presented using composite scores. Results: The mean composite readiness score for the 208 hospitals for providing services to small and sick newborns in labour and delivery wards was 59%, with domain-specific scores of 47% for basic amenities, 56% for essential neonatal care, and 74% for newborn resuscitation. Significant variation was seen across hospital levels, and basic amenities were available in 68%, 49%, and 43%, essential neonatal care in 68%, 81%, and 71%, and newborn resuscitation in 68%, 66%, and 50% of referral, general, and primary hospitals, respectively. The mean composite readiness score to provide newborn care in the neonatal care units was 57%. Scores varied by hospital levels, with scores of 73%, 64%, and 50% for referral, general, and primary hospitals, respectively. Domain-specific scores were 63% for basic amenities, 65% for equipment, 67% for medications, 63% for laboratory services, 25% for Kangaroo Mother Care, 68% for infection prevention and control, 55% for staffing, and 51% for guidelines. Functional bCPAP machines were available in 14% of labour and delivery wards and in 35% of neonatal care units. Conclusion: There is a substantial gap in readiness to provide care for small and sick newborns, and significant variations across hospital levels. Immediate actions must be taken to address the observed gaps to reach the sustainable development goal of reducing neonatal mortality to at least 12 per 1,000 live births by 2030.

Abstract: Charles Bonnet syndrome (CBS) is characterized by complex visual hallucinations in visually impaired individuals who maintain intact cognitive function. Despite significant progress in understanding this condition, the precise neural mechanisms underlying CBS remain incompletely understood. This review synthesizes current evidence regarding the pathophysiology of CBS, with particular emphasis on emerging neurobiological models that extend beyond simple cortical hyperexcitability. Recent neuroimaging, neurophysiological and computational modeling studies suggest that CBS hallucinations may arise from complex interactions between deafferentation-induced neural plasticity, neurotransmitter imbalances and altered functional connectivity within visual processing hierarchies. The evidence increasingly points toward a model involving desynchronization between bottom-up and top-down visual processing pathways, rather than mere hyperexcitability of deafferented visual cortex. This integrated perspective has important implications for both theoretical understanding of visual perception and the development of targeted therapeutic interventions.

Abstract: Asymmetry Theory (AT) is a unified mathematical framework that derives both classical and relativistic phenomena from a single empirically validated principle: light propagates at constant speed c from its emission origin. By retaining classical time and space, while introducing observer-dependent light velocity, AT bridges the conceptual divide between classical mechanics and relativistic physics, providing a common mathematical foundation that encompasses both regimes within a coherent structure.From this single principle, AT derives: (1) a light observed velocity formula explaining the Sagnac effect, GPS one-way light speed measurements, stellar aberration, and optical clock variation; (2) a unified formula encompassing both classical and relativistic Doppler effects, cosmological redshift, and Cherenkov radiation; (3) electrodynamics equations addressing particle acceleration, mass-energy equivalence, and matter waves; (4) an observer-frame formulation of Maxwell's equations that directly yields Doppler and Sagnac effects as solutions.AT reproduces all validated predictions of Special Relativity (STR) when the observer’s motion is perpendicular to the “source-observer” line, while preserving classical time synchronization and causality and naturally handling non-inertial frames.AT maintains consistency with all established empirical evidence: Michelson-Morley, optical cavity resonators, Hafele-Keating, optical clock, Ives-Stilwell spectroscopy, particle accelerators, muon decay, nuclear reactions and GPS Sagnac corrections. It also reconciles with the contested Gezari lunar ranging and Thim microwave. We demonstrate that the extensive empirical evidence traditionally cited as validating STR equally supports AT - a unified framework based on classical spacetime.To distinguish from STR, AT is empirically testable with novel predictions: (1) Sagnac phase shift Δt = 2vL/c² in inertial frame; (2) momentum asymmetry for parallel acceleration versus deceleration. A motion-controlled interferometer with first order sensitivity detecting two-way light speed deviation is proposed for the confirmative test of AT.

Abstract: Theoretical background: Occupational burnout remains a key organizational challenge, while the phenomenon of quiet quitting (QQ - conscious limitation of effort to formal requirements) gains significance in contemporary workplaces. However, existing literature lacks frameworks for distinguishing deliberate disengagement from unintentional, apathetic withdrawal. To address this gap, the concept of passive quitting (PQ - apathetic withdrawal from exhaustion and loss of meaning) is introduced and both mechanisms' unique contributions to explaining burnout are examined.Purpose of the article: To determine the impact of quiet quitting and passive quitting phenomena on occupational burnout and empirically assess their unique contributions within a single coherent latent model.Research methods: Cross-sectional CAWI study on a nationwide sample of Polish employees (N = 1040). QQ and PQ were measured using validated scales, burnout was assessed with the OLBI questionnaire. Covariance-based structural equation modeling (CB-SEM) was employed to test hypotheses assuming both phenomena as significant predictors of occupational burnout.Main findings: Passive quitting is a strong and significant predictor of occupational burnout (β = 0.475, p < 0.001), while quiet quitting shows virtually no relationship (β = 0.0012, p > 0.001). The most influential factors were items related to loss of job satisfaction and meaning (PQS6, PQS7), distinguishing apathetic withdrawal from conscious boundary-setting. PQ may serve as a practical early warning indicator, while QQ behaviors alone do not increase burnout risk when PQ is controlled for.

Abstract: Hierarchical triple systems (HTSs), composed of an inner compact binary and a distant tertiary companion, can undergo secular interactions that induce Kozai–Lidov (KL) oscillations. These oscillations can drive the inner binary to high eccentricities, substantially enhancing its gravitational wave (GW) emission. In this work, we simulate the evolution of such systems using the N-body integrator REBOUND, selecting astrophysical models from constrained parameter spaces that are likely to exhibit KL dynamics. To assess detectability, we employ tools such as EccentricFD to model GW signals from these eccentric binaries, varying mass ratios and eccentricities across detectors, including LIGO, LISA, and LGWA. Our results highlight the influence of general relativistic corrections at 1PN order on the suppression or modulation of KL cycles and suggest the existence of an additional dynamical constraint governing HTS stability. We find that GW signals from such systems are within the sensitivity range of both current and future detectors. This study underscores the role of three-body dynamics in shaping GW observables and provides a foundation for the development of waveform templates for eccentric sources.

Abstract: The effect of a pre-nitriding treatment, applied prior to vacuum carburizing, on the carburizing efficiency of 20CrMnTi steel is investigated. The results demonstrate that pre-nitriding significantly enhances the vacuum carburizing efficiency of 20CrMnTi steel, refines the martensitic microstructure of the carburized layer, and promotes carbide precipitation. At the same carburized layer depth, the hardness and carbon content of the pre-nitriding samples are markedly higher than those of the without pre-nitriding samples. Specifically, the effective hardened depth and the surface hardness increase by approximately 0.15 mm and 75 HV500gf, respectively. These improvements are attributed to the formation of loose, porous nano-sized nitride particles on the surface during the pre-nitriding process, which substantially increases the surface roughness and pore volume. This surface morphology facilitates the adsorption and inward diffusion of carbon atoms during carburizing, and the presence of nitrogen in solid solution further enhances carbon diffusion.

Abstract: Based on the core premise that "ether = energy", this paper proposes the central hypothesis that consciousness is a high-level form of etheric motion, systematically explaining the essential connection between consciousness and physical reality. The study argues that consciousness is not an inherent cosmic property but a product of the universe expanding to a specific stage. High-level etheric motion (consciousness) follows exclusive laws such as logic, and there is an intersection of laws with the low-level etheric motion studied in physics. This intersection constitutes the intrinsic connection between mathematics and physics. On this basis, the paper demonstrates the negative correlation between mathematical complexity and the validity of physical theories, pointing out that simple mathematical forms are more compatible with objective physical reality, while physical theories relying on advanced mathematics (such as string theory) have an extremely high probability of being incorrect. Finally, it discusses the issue of the independent existence of consciousness separate from living organisms, providing a new theoretical perspective for the study of the nature of consciousness and cosmic laws.

Abstract: Large Language Models (LLMs) in Intelligent Computer-Assisted Language Learning (iCALL) offer personalization potential but introduce critical challenges in pedagogical grounding, data privacy, and pedagogical validity. While Knowledge Graphs (KGs) and Federated Learning (FL) address these concerns individually, systematic integra-tion of all three technologies remains absent or insufficiently addressed in current re-search. This scoping review maps the FL–KG–LLM convergence landscape in educa-tional contexts. Following PRISMA-ScR guidelines, we searched six databases and screened 51 papers published between 2019 and 2025 using automated extraction. Our findings reveal a pronounced convergence deficit: no papers integrate all three domains, while 58.8% of approaches operate within isolated technological silos. Criti-cal reporting gaps emerge across the corpus, with an average “Not Reported” (NR) rate of 84.5%, particularly in privacy mechanisms (92.2%), validation metrics (90.2%), and Common European Framework of Reference for Languages (CEFR) alignment (88.2%). Domain-specific analysis reveals two distinct patterns: inter-domain gaps (disciplinary silos resulting in expected CEFR absence in single-domain papers) and intra-domain gaps (failure to report domain-critical variables, including 100% parameter NR in FL studies, 86.7% validation NR in KG studies, and 100% CEFR NR in convergence pa-pers). We identify two pillars of pedagogical grounding: a Grounding Pillar, which con-strains LLM outputs via Knowledge Graph rules, and a Validation Pillar, which con-cerns how authoritative source frameworks are mapped onto Knowledge Graph schemas. The latter remains completely unaddressed in the reviewed literature, re-vealing what we term the Integrity Gap—a systematic disconnection between techno-logical innovation and pedagogical grounding in iCALL. By framing pedagogical alignment as an upstream control and validation problem, this review offers insights relevant to the design of user-facing automated systems where trust, transparency, and human oversight are critical.

Abstract: Global outdoor furniture consumes large amounts of virgin wood and polyolefins, while multilayer beverage cartons and rice husks are usually landfilled or burnt despite their polymer and lignocellulosic value. However, no study has yet provided experimentally validated formulations that convert both waste streams into extruded wood-like boards for low-load urban elements. This work therefore characterised hybrid composites containing 50–80 wt.% recycled Tetra Pak PolyAl and 20–50 wt.% ground rice husk, produced at pilot scale by single-screw extrusion plus compression moulding. Boards were tested for density, tensile and flexural properties, Shore D hardness, water absorption (ISO 62-inspired) and 254 nm UV ageing. Increasing rice-husk content from 20 to 50 wt.% raised Shore D hardness from 54 to 63 but almost doubled water uptake (≈45 vs 25 g m⁻² at 7 d), while UV exposure increased surface hardness by 3–5 points without visible cracking. The 70 Tetra Pak/30 rice-husk formulation gave the best balance, with a flexural modulus of 2.1 GPa and MOR of 18 MPa, exceeding the ASTM D7032 requirement for outdoor decking (MOR ≥ 11 MPa). By valorising two locally available wastes into a market-ready material, the proposed symbiosis supports circular-economy strategies for urban furniture.

Abstract: Traffic forecasting in cellular networks is a challenging spatiotemporal prediction problem due to strong temporal dependencies, spatial heterogeneity across cells, and the need for scalability to large network deployments. Traditional cell-specific models incur prohibitive training and maintenance costs, while global models often fail to capture heterogeneous spatial dynamics. Recent spatiotemporal architectures based on attention or graph neural networks improve accuracy but introduce high computational overhead, limiting their applicability in large-scale or real-time settings. We propose HiSTM (Hierarchical SpatioTemporal Mamba), a spatiotemporal forecasting architecture built on state-space modeling. HiSTM combines spatial convolutional encoding for local neighborhood interactions with Mamba-based temporal modeling to capture long-range dependencies, followed by attention-based temporal aggregation for prediction. The hierarchical design enables representation learning with linear computational complexity in sequence length and supports both grid-based and correlation-defined spatial structures. Cluster-aware extensions incorporate spatial regime information to handle heterogeneous traffic patterns. Experimental evaluation on large-scale real-world cellular datasets shows that HiSTM achieves state-of-the-art accuracy, with up to 29.4% MAE reduction over strong spatiotemporal baselines and 47.3% improvement on unseen datasets. HiSTM shows improved robustness to missing data and better stability in long-horizon autoregressive forecasting, showcasing its effectiveness for scalable 5/6G traffic prediction.

Abstract: The goal of this paper is to combine algebraic quantum field theory with methods from modal logic and the causal set program. We introduce a factorially damped past-influence operator on causal sets, formulate locally covariant nets over Alexandrov intervals, and give discrete analogues of the Haag–Kastler axioms. We close by sketching a route toward dynamics via sequential growth and incidence-algebra localization.

Abstract: Background/Objectives Steroid-induced glaucoma (SIG) or ocular hypertension is a well-known complication after corticosteroid exposure to the eye, particularly intravitreal dexamethasone im-plantation. The main mechanism of elevated intraocular pressure (IOP) is trabecular meshwork dysfunction, leading to increased aqueous outflow resistance. Although most SIG cases respond to medical treatment, some patients develop persistent IOP elevation requiring surgical intervention. Minimally invasive glaucoma surgery (MIGS) has recently emerged as a safer surgical option, but there are a limited number of reports using MIGS for SIG. Methods: A 73-year-old man, who had branch retinal vein occlusion with refractory macular edema despite multiple anti-VEGF injections, received an intravitreal Ozurdex® (Allergan, Irvine, CA, USA) implant. He developed marked IOP elevation from 17 to 34 mmHg despite maximal topical therapy. Visual field progression and progressive retinal nerve fiber layer thinning were also observed. Given the need for continued ocular steroid use and only having one arm due to trauma making drops difficult, three trabecular micro-bypass stent devices (iStent infinite®, Glaukos Corp., Aliso Viejo, CA, USA) were implanted for IOP control. Postoperatively, IOP decreased to 13 mmHg and remained stable at 15 mmHg for 12 months. Additionally, macular edema was well-controlled with ongoing Ozurdex treatment and no observed IOP spikes. Conclusions: This is the first reported case of SIG-associated Ozurdex successfully managed with triple trabecular micro-bypass stents. The iStent infinite implantation provided safe and sustained IOP control for SIG, highlighting its potential role in patients requiring continuous intravitreal steroids.