Abstract: This case report describes longitudinal gait mechanics in a 62-year-old man who underwent left total knee arthroplasty (TKA) and subsequently laparoscopic sleeve gastrectomy with massive weight loss. Gait was evaluated using a wearable inertial sensor system at 6 months (T1) and 12 months (T2) after arthroplasty, alongside functional mobility and endurance tests (Timed Up and Go and 2-minute walk). Body mass decreased from 120 kg (BMI approximately 43 kg/m²) to 69 kg (BMI approximately 25 kg/m²) between T1 and T2. Despite the substantial reduction in mechanical loading, spatiotemporal gait parameters and pelvic kinematics remained largely stable, with persistent asymmetry and a compensatory gait strategy. Acceleration-derived estimates suggested approximately 42.5% mechanical offloading after weight loss. These findings indicate that, in this patient, massive postoperative weight loss did not translate into marked improvements in gait mechanics within the first year after TKA, underscoring the need for targeted rehabilitation even after successful weight reduction.

Abstract:

The escalating prevalence of occupational burnout constitutes a global public health crisis, exacerbating the existing supply-demand disparity in mental healthcare provision. This paper investigates the transformative potential of Artificial Intelligence (AI) as an adjunctive and autonomous modality in the treatment of burnout, employing a dialectical framework to assess the tension between algorithmic scalability and clinical nuance. We analyze the utility of Natural Language Processing (NLP) for sentiment analysis and the emergence of Digital Phenotyping as a mechanism for objective behavioral quantification. Furthermore, we critically evaluate the efficacy of CBT-based conversational agents versus the indispensable nature of the human therapeutic alliance. The analysis reveals that while AI significantly lowers barriers to entry and reduces stigma, it introduces profound ethical paradoxes regarding surveillance, algorithmic bias, and the ”Black Box” of machine cognition. We conclude that the future of psychiatric care lies not in replacement but in Augmented Intelligence—a ”Human-in-the-Loop” (HITL) hybrid model that synthesizes computational precision with intersubjective empathy.

Abstract: Video Question Answering (VideoQA) presents significant challenges, demanding comprehensive understanding of dynamic visual content, object interactions, and complex temporal-causal logic. While Multimodal Large Language Models (MLLMs) offer powerful reasoning capabilities, existing approaches often provide singular, potentially flawed reasoning paths, limiting the robustness and depth of VideoQA models. To address these limitations, we propose Contextualized Diverse Reasoning (CDR), a novel framework designed to furnish VideoQA models with richer, multi-perspective auxiliary supervision. CDR comprises three key innovations: a Diverse Reasoning Generator that leverages MLLMs with distinct viewpoint prompts to generate multiple, complementary reasoning pathways; a Reasoning Pathway Refiner and Annotator that purifies these paths by removing explicit answers and enriching them with semantic type annotations; and a Context-Aware Reasoning Fusion module that dynamically integrates these refined, multi-dimensional reasoning cues with video and question features using an attention-based mechanism. Extensive experiments on several benchmark datasets demonstrate that CDR consistently achieves state-of-the-art performance, outperforming leading VideoQA models and MLLM-based methods. Our ablation studies confirm the crucial role of each CDR component, while qualitative analysis and human evaluations further validate the superior correctness of answers and the coherence, completeness, and helpfulness of the generated reasoning pathways.

Abstract:

Background/Objectives: The clinical superiority of rotating-bearing (RB) versus fixed-bearing (FB) total knee arthroplasty (TKA) remains controversial despite the proposed biomechanical advantages of mobile-bearing designs. Objective gait assessment with inertial measurement units (IMUs) provides a measurable view of functional recovery that may complement patient-reported outcome measures (PROMs). This study compared spatiotemporal gait parameters between FB and RB TKA over 24 months. Methods: This prospective longitudinal comparative study enrolled 47 patients undergoing primary unilateral TKA for end-stage knee osteoarthritis. Spatiotemporal gait parameters (gait velocity, cadence, and stance-phase duration) were measured using wireless IMUs (G-WALK system) at 6, 12, and 24 months post-surgery. WOMAC and the 10-point Geriatric Locomotive Function Scale (GLFS-1) were assessed at 12 and 24 months. Group, time, and Group × Time effects were analyzed using linear mixed-effects models. Results: Both groups improved during follow-up, with performance largely plateauing between 12 and 24 months. At 24 months, there were no significant differences between groups in gait velocity (FB 1.17 vs. RB 1.16 m/s; p = 0.65), cadence (99.8 vs. 97.4 steps/min; p = 0.72), or stance-phase duration (59.3% vs. 59.0%; p = 0.82). Group × Time interactions were not significant across gait outcomes. WOMAC and GLFS-1 improved similarly in both groups (p > 0.05). Cadence was inversely correlated with the WOMAC function subscale at 24 months (rho = −0.563; p = 0.036). Conclusions: FB and RB bearing designs showed similar objective gait recovery trajectories and PROM improvements through 24 months after primary TKA, suggesting no intermediate-term functional advantage from bearing design.

Abstract: The scaling of large-scale AI systems increasingly encounters operational instabilities that cannot be attributed to interconnect limitations alone. Even in infrastructures with sufficient network capacity, cost escalation, non-deterministic behavior, and soft degradation persist, indicating coordination and control as distinct failure domains. Building on prior structural analyses of interconnect-induced instability, this article introduces runtime control coherence as a structural property describing the degree to which distributed control decisions across schedulers, orchestrators, runtime engines, and policy layers remain mutually consistent. The loss of control coherence gives rise to economically significant inefficiencies without manifesting as discrete faults or performance violations. Classical metrics fail to capture coherence loss because conflicts between control layers are distributed, emergent, and temporally decoupled. This work provides a structural problem analysis that positions control incoherence as a first-order economic and operational variable, complementing existing analyses of interconnect-driven instability. The methodology is deliberately conceptual, avoiding implementation details or prescriptive solutions.

Abstract: This study examines how banks navigate the dual strategic imperatives of securing market power and optimizing multidimensional operational efficiency—technical, scale, and allocative efficiency—within emerging and transitional banking systems. Focusing on business model diversification and financial stability, the study also accounts for the conditioning roles of governance quality, institutional complexity, credit risk, and digitalization. Using bank-level data from ASEAN and MENA countries, the analysis applies Partial Least Squares Structural Equation Modeling (PLS-SEM) and multi-group analysis to assess direct, mediating, and moderating relationships. The results indicate that diversification and financial stability significantly strengthen market power, while their effects on efficiency are largely negative across efficiency dimensions. Governance quality partially mediates the stability–market power relationship, whereas institutional complexity weakens this linkage. Digital transformation maturity and market digitalization condition the diversification–efficiency nexus, with effects varying across efficiency types and regions. Overall, the findings reveal a strategic trade-off between competitive positioning and operational efficiency, emphasizing the importance of governance structures and digital capabilities in shaping bank performance across heterogeneous institutional contexts.

Abstract: As sedentary lifestyles are becoming more common, related health conditions including obesity, diabetes, heart disease, etc. are also becoming more prevalent. Physical exercise and activity are proven to be important for improving health, however, less common yet just as important for overall health is using performance enhancing techniques. While there are a wide variety of performance enhancing techniques, this paper focuses on 4 of the most common: Cold-Water-Immersion (CWI), Heat Stress, Blood-Flow-Restriction (BFR), and sleep. Research has shown CWI decreases hypertrophy in response to resistance exercise and has been shown to increase some markers of endurance adaptations but has not shown long-term physiological benefits. Heat Stress has shown to improve both hypertrophy in response to resistance exercise and mitochondrial biogenesis in response to endurance exercise. BFR training has not been shown to contribute to significant improvements in exercise adaptations compared to traditional higher intensity resistance and endurance exercise. Finally, sleep deprivation has shown to significantly decrease hypertrophy and mitochondrial health, indicating sufficient sleep is very important to obtaining exercise adaptations and health benefits. All together, these results suggest the importance of performance enhancing techniques for overall skeletal muscle health.

Abstract: Snowpack plays a vital role in Earth’s water cycle, especially in mountain regions where it serves as a major source of freshwater. Accurate estimation of snowpack microwave backscatter is critical for retrieving key physical properties of snow, such as snow depth (SD) and snow water equivalent (SWE), typically modeled using radiative transfer models (RTMs). Among the various sources of uncertainty in RTM simulations, snow-ground reflectivity—used as a boundary condition—plays a critical role in influencing the ac-curacy of simulated backscatter. This study leverages high-resolution X- and Ku-band SAR backscatter aircraft measurements using SWESARR and SnowSAR from NASA’s SnowEx campaigns, co-located with in-situ snow pit observations in Grand Mesa, Colorado, to estimate the parameters governing the estimation of the snow-ground reflectivity and quantify the uncertainties associated with them. Focusing on the snow-ground interface, we compare multiple soil reflectivity models to assess the sensitivity of backscatter to key ground parameters such as surface roughness, moisture content, and specular to total reflectivity ratio (STRR). At X-band, increasing ground surface roughness reduced the simulated backscatter by ~1.5 dB across the tested range, and increasing the specular to total reflectivity ratio (STRR) produced an additional ~1.0 dB decrease. A Bayesian MCMC parameter optimization was used to estimate each parameter, and the posterior distributions were then analyzed to quantify the uncertainties. The retrieval sensitivity to the specular to total reflectivity ratio (STRR) is minimized in the 0.6-0.7 range and it can be fixed at 0.65 without having discernible impact. The Bayesian inversion reveals that extreme parameter values act as diagnostic indicators of unmodeled complexity rather than retrieval failures, with representativeness error often dominating over instrument noise. The study highlights the importance of the snow-ground backscatter boundary condition in forward modeling of snowpack backscatter and provides robust guidance on parameter ranges to reduce uncertainty in RTMs, ultimately aiding SWE and SD retrieval from active microwave observations. While this study relied on Grand Mesa, the framework developed here, along with the model uncertainty, is broadly applicable to other snow-dominated mountain regions where active microwave observations can be used for snowpack monitoring.

Abstract:

In this research study, effect of laser surface texturing on the tribological performance of composite of polytetrafluoroethylene with 25 wt.% glass fibre against grey cast iron. Dimples (50 µm diameter) were ablated on GCI with dimple pitches of 100 µm and 150 µm. Friction and wear tests were conducted on a pin-on-disc tribometer under ambient conditions. Specific wear rate of both PTFE and its composite generally decreased with increasing sliding distance for all GCI surfaces, whether textured or untextured. The coefficient of friction (COF) followed a similar trend for PTFE but increased for 25 wt.% glass fibre/PTFE on textured GCI surfaces. Compared to untextured GCI, PTFE exhibited a 14.2-16.7% reduction in COF and specific wear rate when sliding against GCI with a 150 µm dimple pitch. For 25 wt.% glass fibre/PTFE, LST increased friction but significantly reduced specific wear rate by 66.6-73.2%.Increasing the dimple pitch from 100 µm to 150 µm further decreased COF and wear. FESEM micrographs of textured GCI surfaces post-sliding against PTFE revealed polymer debris deposition, forming transfer films that contributed to friction and wear reduction. These findings highlight the potential of LST in enhancing the tribological performance of PTFE-based materials, particularly in optimizing wear resistance and friction control through surface texturing.

Abstract: Connecting rod bushings are core friction-pair components in diesel engine crank-connecting rod mechanisms, and their loosening failure—causing lubrication failure, accelerated wear, and even catastrophic damage. To address this critical issue, this study systematically investigates the influence of key structural parameters (inner diameter, wall thickness, width) on the retention force of the bushing’s interference fit. Through a combination of theoretical analysis, finite element analysis (FEA), and experiments, the safe interference range for typical bushing geometries is determined to be 0.08–0.11 mm (corresponding to a retention force range of 33.61–46.25 kN). Further parametric studies reveal that the retention force decreases with increasing inner diameter while increasing significantly with greater wall thickness and width, with wall thickness identified as the most influential parameter. For bushings featuring a large inner diameter, thin wall, and narrow width, stricter interference tolerance is required to ensure connection reliability. These findings establish a reliable parametric design framework, providing actionable engineering guidance for optimizing bushing structural design, controlling assembly processes, and mitigating loosening risks in similar heavy-duty equipment components.

Abstract: In this paper we first give a new formula of the Liouville function and then by using the method for proving the Bateman-Horn conjecture, we give a parallel proof of the Chowla conjecture.

Abstract: Background/Objectives: 40-Hz sensory stimulation is being explored as an everyday, non-pharmacological approach for cognitive-health applications, but sustained use depends on acceptability and implementable delivery/UX. We examined user-perceived acceptability and implementation considerations for a 40-Hz sine-wave–integrated soundscape intervention. Methods: Eleven adults aged ≥40 years in Seoul, Republic of Korea were assigned to waves or forest soundscapes (between-participants) and completed a within-participant comparison of 40-Hz–OFF (soundscape-only) versus 40-Hz–ON (soundscape plus an additively layered 40-Hz sine wave). Each condition comprised seven cycles of 50 s playback and 10 s silence (~7 min) with a 10 min washout. Participants completed a session-end 7-point Likert appraisal of the 40-Hz–ON stimulus and a semi-structured interview. Interview transcripts were analyzed using thematic analysis and interpreted using the Theoretical Framework of Acceptability and Proctor et al.’s implementation outcomes as sensitizing frameworks. Results: Likert appraisals indicated mid-to-high comfort and immersion (medians = 5) and moderate calmness (median = 4), with relatively low unpleasantness (median = 2). Perceived artificiality varied widely (range 1–7) and overall preference was moderate (median = 4). Interviews showed heterogeneous detectability of 40-Hz inclusion; acceptability depended on whether the layered component blended naturally or was perceived as mechanical/rumbling. Participants highlighted context fit (e.g., bedtime versus morning routines), “backgroundability,” and low-friction automation (timers/scheduling) as key sustainability factors, while emphasizing acoustic safeguards such as gentle onset and conservative default levels. Conclusions: A 40-Hz sine-wave–integrated soundscape can be acceptable, but responses are heterogeneous and sensitive to timbral salience and usage context. Scalable delivery should incorporate space-oriented playback options, simplified automation, acoustic safeguards, and coherence-focused guidance with appropriate disclaimers.

Abstract: This article advances EcoTechnoPolitics as a transformational conceptual and policy rec-ommendation framework for hybridizing digital–green twin transitions under conditions of planetary polycrises. It responds to growing concerns that dominant policy approaches by supranational institutions—including the EU, UN, OECD, World Bank Group, WEF, and G20—remain institutionally siloed, technologically reductionist, and insufficiently attentive to ecological constraints. Moving beyond the prevailing digital–green twin transitions paradigm, the article coins EcoTechnoPolitics around three hypotheses: the need for planetary thinking grounded in (i) anticipatory governance, (ii) hybridization, and (iii) a transformational agenda beyond cosmetic digital–green alignment. The research question asks how EcoTechnoPolitics can enable planetary thinking beyond digital–green twin transitions under ecological and technological constraints. Methodologically, the study triangulates (i) an interdisciplinary literature review with (ii) a place-based analysis of two socially cohesive city-regions—the Basque Country and Portland (Oregon)—and (iii) a macro-level policy analysis of supranational digital and green governance frameworks. The results show that, despite planetary rhetoric around sustainability and digitalization, prevailing policy architectures largely externalize ecological costs and consolidate technological power. Building on this analysis, the discussion formulates transformational policy recommendations. The conclusion argues that governing plan-etary-scale ecotechnopolitical systems requires embedding ecological responsibility within technological governance.

Abstract: For years, PTSD has been viewed mainly as something people "catch" after a bad experience, the result of an adult-onset failure in the brain's fear circuit. The standard story focuses on shaky extinction learning, a mis-tuned HPA axis, and glitches in glutamate-driven plasticity. Yet the newest, large-scale genetic studies paint a different picture. They show that the strongest polygenic signals sit not in classic glutamatergic genes but in the neuro-immune machinery that prunes synapses while the brain is still wiring itself. These signals hold up even after we account for every bit of shared variation with the glutamate system.Using MAGMA gene-set tests, partitioned heritability, and transcriptome-wide association built around the latest multi-ancestry GWAS of PTSD, we found repeatable, Bonferroni-safe enrichments in pruning regulators such as complement C4A, MHC-I gene HLA-B, the guidance cues SEMA3F and EFNA5, and the schizophrenia-linked transcription factors TCF4 and ERBB4. Together, the data point to what we call a "pruning-vulnerability cascade." First, genetically driven mis-pruning during sensitive windows leaves key circuits immature and easily rattled. Later trauma then overwhelms this shaky scaffold, setting off secondary failures in glutamate signalling and HPA feedback and locking them in through lasting epigenetic marks.Seeing PTSD as a problem that starts in development pulls together its early-life risk factors, the small hippocampi and other structural oddities on imaging, and its genetic overlap with disorders like schizophrenia. It also spotlights fresh prevention angles: for instance, dampening complement activity in young people who carry high pruning-risk profiles. To move from idea to intervention, we will need broad, multi-omic work in more diverse cohorts—but the roadmap is now clearer than ever.

Abstract: Early-life exposure to toxic metals remains a major global public health concern, particularly for children, whose developing neuroendocrine and metabolic systems are highly vulnerable. Within the exposome and Developmental Origins of Health and Disease (DOHaD) frameworks, this narrative review synthesizes human evidence on pediatric exposure to lead (Pb), mercury (Hg), cadmium (Cd), and arsenic (As) and its associations with neurodevelopmental, metabolic, and endocrine outcomes. We primarily examined epidemiological studies, systematic reviews, and meta-analyses published between 2010 and 2025 that relied on biomonitoring-based exposure assessment and appropriate adjustment for socioeconomic status and passive smoking, while seminal earlier studies were considered to contextualize biological mechanisms and conceptual frameworks. The evidence for neurodevelopmental toxicity is the most consistent, with prenatal and early childhood exposure to Pb and Hg robustly associated with adverse cognitive, behavioral, and motor outcomes and no identified safe exposure threshold for lead. In contrast, associations with obesity and pubertal timing are more heterogeneous and metal-specific, reflecting nonlinear dose–response relationships, sex-specific susceptibility, and critical exposure windows. Emerging data indicate that metals may act as metabolism- and endocrine-disrupting chemicals, with effects amplified by mixture exposures and adverse social conditions, and partially modified by nutritional status. Overall, the findings support life-course–oriented, biomonitoring-based research and prevention strategies that address cumulative exposures and developmental vulnerability to reduce long-term disease risk.

Abstract: Oleaginous yeasts are promising microbial platforms for lipid production from non-conventional carbon sources; however, acetate utilization is frequently constrained by physiological limitations associated with culture pH. In this study, acetate utilization, biomass formation, and lipid production by Lipomyces starkeyi were investigated under flask and fed-batch cultivation to evaluate the influence of culture pH and pH control strategy. Statistically supported flask-scale experiments demonstrated that acetate concentration and cultivation time significantly affected acetate consumption, biomass formation, lipid yield, and culture pH, with excessive acetate loading resulting in culture alkalization, incomplete substrate utilization, and reduced process performance. Although lipid yield increased with increasing acetate concentration, lipid content and fatty acid composition remained unchanged, indicating that enhanced lipid production was primarily attributable to increased biomass formation rather than to changes in lipid biosynthesis. Fed-batch cultivation under different pH-control strategies provided qualitative insights into the relationships among pH regulation, acetate availability, and lipid accumulation under controlled fermentation conditions. While lipid accumulation was observed under both HCl-based and acetic acid–based pH control, differences in pH stability and cumulative acetate availability were associated with distinct patterns of lipid production. Collectively, these results identify culture pH as a critical physiological parameter influencing acetate utilization and lipid accumulation in L. starkeyi and suggest that coordinated pH control and carbon feeding strategies may improve the robustness of acetate-based lipid production processes. Further replicated fed-batch studies will be required to quantitatively validate these trends and support industrial applications.

Abstract: Spinal cord regeneration requires a transformative strategy capable of rewriting inhibitory genetic programs while orchestrating real-time electrical communication with regenerating neural tissues. Recent advancements in precision CRISPR genome editing effectively silence or activate crucial molecular gatekeepers such as PTEN, SOCS3, and various epigenetic repressors, thereby reactivating dormant intrinsic regenerative pathways and enabling robust axonal growth. Concurrently, cutting-edge bioelectronic technologies utilizing piezoelectric, triboelectric, and magnetoelectric scaffolds have emerged, adeptly harnessing the body's inherent biomechanical energy. These innovative materials convert subtle physiological micromotions into finely tuned electrical stimuli, precisely guiding neuronal regeneration without external power sources, addressing limitations associated with traditional implants such as infection risks and mechanical incompatibility.Integrating these genetic modifications with bioelectric innovations creates a potent synergy. Genome-level reprogramming amplifies neuronal responsiveness to bioelectrical signals, markedly enhancing axonal regeneration. Simultaneously, autonomous electrical stimulation sustains and stabilizes cellular, metabolic, and synaptic improvements induced by genomic interventions, forming a closed-loop, self-sustaining therapeutic platform. This advanced system significantly transcends conventional transient recovery approaches, moving toward durable, personalized outcomes. Such convergence of advanced genetic engineering and intelligent biomaterial design represents a groundbreaking shift in regenerative neurology.Despite promising preclinical outcomes, significant translational challenges remain. Critical hurdles include ensuring precise delivery of CRISPR tools, mitigating off-target genomic effects, enhancing biocompatibility and scaffold stability, and navigating rigorous regulatory pathways. Addressing these challenges necessitates integrating next-generation gene-editing technologies, comprehensive genomic surveillance, advanced biomaterial sciences, and meticulous preclinical evaluations. Future directions in spinal cord injury research encompass multiplex genome editing, AI-driven scaffold optimization via digital twins, and tailored immune-evasive biomaterials. Collectively, this innovative approach has the potential to redefine regenerative medicine's boundaries, offering unprecedented hope for sustained, personalized recovery and dramatically improving quality of life for individuals affected by spinal cord injuries.

Abstract: Background and Objectives: Formal education in Africa is becoming increasingly influ-enced by the traditional media consumption, ranging from television and radio to in-ternet usage. This study aims to determine the effects of traditional media consump-tion on health literacy in provinces with high illiteracy. Materials and Method: The study adopted a retrospective cross-sectional study design using the 2016 South Afri-can Demographic Survey Data to analyse the factors affecting health literacy. Partici-pants were selected using a stratified two-stage sampling method to ensure national and provincial representativeness. A total of 1 982 participants aged 15 – 29 years who met the inclusion criteria were included for further analysis. Pearson’s Chi-square test was used to test for association between health literacy and media consumption. Mul-tivariate logistic regression was used to determine the effects of traditional media consumption on health literacy, p ≤ 0.05 was considered statistically significant. STATA version 16.1 (StataCorp, LLC, College Station TX, USA) was used for analysis. Results: The results showed that media consumption emerged as a strong predictor, in-dividuals who reported watching television had increased odds of health literacy (OR = 2.67; 95% CI: 1.55 - 4.61; p < 0.001). Similarly, internet use was positive predictor of health literacy (OR = 3.11; 95% CI: 1.76 - 5.52; p < 0.001. Other variables such as educa-tional level also emerged as a significant predictor, individuals with secondary school education had significantly higher odds of health literacy compared to those with lower educational levels (OR = 17.10; 95% CI: 4.20 - 69.63; p < 0.001). Conclusion: This study highlights the critical role media consumption plays in shaping health literacy outcomes among the youth, particularly in provinces with high illiteracy rates. By us-ing media platforms strategically and ensuring equitable access, educators, health practitioners and policymakers can unlock new pathways to health literacy, fostering a more informed, empowered, and connected society.

Abstract: As artificial intelligence (AI) technologies, particularly generative and collaborative learning models— are increasingly integrated into healthcare and other sensitive domains, data privacy, security, and fairness concerns have grown significantly. This paper focuses on a thorough examination of current privacy-preserving AI models, including federated learning (FL), differential privacy (DP), homomorphic encryption, and generative adversarial networks (GANs). Key contributions are reviewed across recent works that explore privacy-preserving mechanisms within domains such as clinical diagnostics, drug discovery, Internet of Medical Things (IoMT), and virtual health systems. Dynamic federated models (e.g., DynamicFL) that adjust model architecture based on computational heterogeneity and encryption-augmented FL architectures are presented to maintain data locality while ensuring equitable performance. GAN-based synthetic data generators (e.g., medGAN, CorGAN) offer alternative solutions to share healthcare data without compromising patient identity and introducing new threats if misused. Across these models, a multi-phase life cycle of threats is identified—spanning data collection, model training, inference, and system integration—highlighting the importance of proactive governance. Information compliance frameworks such as the EU AI Act and the U.S. AI Bill of Rights are counting for standardizing technological implementation in healthcare data management. This research work will cover explaining existing AI models and trying to identify the best one worked for ensuring data privacy and shareability with ethical responsibility for proposing a layered privacy-preservation paradigm essential for safely deploying AI in sensitive environments.

Abstract: The Wallonia region of Belgium aims to transition to a modern hydrogen infrastructure. Since hydrogen is much lighter than natural gas, so it is important to understand its nature and behavior while transporting through pipelines. This research aims to observe the pressure loss in pipelines due to surface roughness with H2 and other singular losses to find a solution to minimize the amount of pressure loss that occurs during transportation. This study involves numerical methods and gas equation models to determine thse pres-sure loss. This analysis includes the properties of hydrogen gas, pipeline material used, friction factor, pipeline efficiency, and other relevant properties of hydrogen and the pipe-lines. To address this challenge, this study integrates numerical fluid dynamics methods with structural modelling of pipeline walls. It accounts for long-term friction effects, erosion over several years, radial pressure gradients (mixing pressure drop), acceleration effects, and gravity influences, considering the non-ideal behavior of gaseous hydrogen (GH2).