Abstract: Background: Early and accurate assessment of traumatic injuries in pediatric patients is critical for timely diagnosis and prevention of missed associated injuries. The Pediatric Trauma Support System (PTSS) is a digital clinical decision support tool designed to integrate physiological parameters, trauma mechanism, and demographic characteristics to provide automated trauma risk assessment in children. Aim: To evaluate the clinical applicability of the Pediatric Trauma Support System (PTSS) in the primary assessment of pediatric patients with blunt trauma and to analyze the sensitivity of the Pediatric Trauma Score (PTS), particularly in children under one year of age. Materials and Methods: A prospective observational study was conducted in the Emergency Department and the Department of Pediatric Surgery at the University Hospital “St. George”, Plovdiv, Bulgaria. The study included 100 pediatric patients aged 0-18 years presenting with blunt traumatic injuries. Standard clinical evaluation was performed for all patients, including assessment of vital signs and neurological status using the Glasgow Coma Scale (GCS). PTSS was used to automatically calculate the Pediatric Trauma Score (PTS) and generate recommendations for imaging diagnostics. Twenty-five patients were under two years of age, including nine infants younger than one year (6 boys and 3 girls). Demographic and clinical variables were analyzed descriptively. Results: Among the nine patients under one year of age, all had PTS values below the normal age-adjusted threshold. In cases of mild trauma the PTS was 9/12, while in moderate trauma it was 8/12. The PTSS algorithm generated recommendations for head computed tomography (CT) and abdominal ultrasound in all infants. Head imaging was performed in all nine patients, revealing a parietal bone fracture in one 27-day-old infant. Abdominal ultrasound was not performed in clinical practice despite the algorithmic recommendation. In patients older than one year with similar trauma severity, PTS values were higher (11/12), and PTSS recommended only head CT without additional abdominal imaging. Conclusion: PTSS provides a structured and automated approach to pediatric trauma assessment by integrating PTS with clinical and demographic parameters. The system demonstrates increased sensitivity in infants under one year of age, where physiological characteristics may mask significant associated injuries. Automated recommendations for additional imaging may contribute to earlier detection of occult injuries and improved patient safety in pediatric trauma care.

Abstract: Background/Objectives: Nuclear receptor corepressors NCOR1 and NCOR2 are key regulators of transcriptional repression, chromatin remodelling, and immunometabolic signalling. While NCOR1 has already been linked to vascular biology, its relevance in abdominal aortic aneurysm (AAA) remains unclear, particularly for NCOR2. This study aimed to investigate the expression, cellular localisation, and molecular interactions of NCOR1/2 in human AAA tissue. Methods: Human AAA samples (elective and ruptured) (n=45) and non-aneurysmal control aortas (n=18) were obtained from our Swiss Vascular Biobank. Transcriptomic profiling was performed using ribosomal RNA-depleted RNA sequencing. Differential expression and correlation analyses were performed using DESeq2/EdgeR and Spearman rank correlation with Benjamini–Hochberg correction. Cellular localisation was assessed through immunohistochemistry (IHC). Results: Bulk transcriptomic analyses showed no significant differences in NCOR1 or NCOR2 expression between AAA and controls. IHC revealed that NCOR1 was found in endothelial cells (ECs), smooth muscle cells (SMCs), and inflammatory infiltrates, while NCOR2 was primarily associated with macrophages. Correlation analyses suggest NCOR1 linking with various cellular markers, proteolytic enzymes, inflammatory mediators, and epigenetic regulators, including lncRNA MALAT1. NCOR2 showed distinct associations with remodelling enzymes, TGFB1 signalling, selective epigenetic modifiers, and lncRNA H19. Conclusions: The lack of transcriptional differences in NCOR1 and NCOR2 between AAA and controls does not exclude cell-type-specific regulation or functional relevance. The specific cellular distributions and molecular associations in human AAA imply that NCOR1 and NCOR2 play non-redundant roles in vascular remodelling, inflammation, and epigenetic regulation. Our findings highlight NCOR pathways as potential modulators of AAA pathophysiology and promising targets for future therapies.

Abstract:

Unregulated Housing (UrH) is a widespread urban phenomenon in Morocco, largely driven by rapid population growth and accelerated urbanization. It has expanded mainly on the outskirts of cities and within housing developments that already benefit from basic infrastructure and superstructure services. In response to this challenge, public authorities have adopted several urban planning instruments, particularly the Land Management Plan (LMP). According to Law No. 12-90 on urban planning, the LMP seeks to regulate urban expansion, improve the architectural and aesthetic quality of the built environment, and preserve the overall coherence of developed areas. As a legally binding planning document, the LMP establishes strict land-use regulations, and any breach of these rules constitutes an offence. Traditionally, detecting such violations requires on-site inspections by control officers, followed by the preparation of official reports submitted to the competent legal authorities. However, recent advances in aerial image acquisition and processing technologies provide powerful tools to improve and facilitate the monitoring of urban planning compliance. This paper proposes a conceptual framework that integrates artificial intelligence with urban planning regulations to enable the automatic detection of urban planning offences using RGB orthophotos covering areas subject to a Land Management Plan, relying on deep learning techniques.

Abstract: Haploid embryos constitute a valuable model for genetic and epigenetic studies; however, their developmental competence is reduced compared with diploid counterparts. This study evaluated whether supplementation of the culture medium with specific small molecules could improve developmental competence and outgrowth establishment of parthenogenetic haploid embryos. The effects of TGF-β inhibition (A83-01), WNT pathway modulation (CHIR99021 and IWR-1), and activin A (AA) supplementation were assessed from the morula stage onward under serum-free conditions. A83-01 treatment did not improve blastocyst formation or morphology and was associated with reduced total cell numbers relative to IVF controls. CHIR99021 supplementation increased the number of SOX2-positive cells compared with IWR-1 and vehicle-treated embryos, suggesting partial support of pluripotency; however, overall developmental progression remained inferior to diploid controls. In contrast, activin A significantly increased the proportion of haploid morulae developing into blastocyst and improved hatching rates. Nevertheless, AA supplementation did not restore CDX2-positive cell numbers or total cell counts to diploid levels. Furthermore, neither CHIR99021 nor AA affect DNA fragmentation levels, although a tendency toward increased TUNEL-positive cells was observed. Activin A treatment also failed to improve embryonic outgrowth formation. Collectively, these findings demonstrate that although activin A enhances blastocyst yield and hatching in bovine haploid embryos, modulation of TGF-β or WNT signaling alone is insufficient to restore diploid-like proliferative developmental competence.

Abstract: Office workers are exposed to a range of occupational health risks, including prolonged sedentary behaviour, postural load, elevated heart rate, and noise, yet objective and continuous monitoring of these risk factors in workplace settings remains uncommon. This study aimed to co-design occupational health visualizations based on smartphone and smartwatch data, through a multi-stakeholder group of office workers and occupational health professionals. A generative co-design framework was applied, comprising a pre-design phase with a field study and questionnaire, a structured multi-stakeholder workshop, and a follow-up evaluation session. Thematic analysis of the workshop transcript yielded 17 occupational health themes, which were subsequently assessed for technical feasibility relative to the available sensing platform. Of the 27 discrete visualization elements proposed across both groups, the majority were classified as directly addressable using smartphone and smartwatch sensor data. Visualizations covering physical activity and sedentary behaviour, heart rate, environmental noise exposure, and postural load were implemented in Python using real-world data collected from office workers. The follow-up session confirmed the interpretability and clarity of the developed visualizations. The generative co-design framework proved well-suited to the occupational health visualization context, enabling structured translation of stakeholder requirements into technically feasible and interpretable visualization outputs.

Abstract: A finite hypergraph generalizes an ordinary graph by permitting a hyperedge to connect any nonempty subset of vertices, thereby representing genuine multiway interactions. Extending this idea, a finite SuperHyperGraph is obtained through an iterated powerset construction, so that set-valued objects formed at one level may function as vertices or edge endpoints at the next, providing a natural framework for hierarchical and multilayer relational structures. In contrast, a line graph transforms each edge of a graph into a vertex, with two such new vertices adjacent precisely when the corresponding original edges share an endpoint. In this paper, we introduce the notion of a MultiLine Graph, in which multiple edges can be assigned to a vertex, and then develop its higher-order extensions, namely the MultiLine HyperGraph and the MultiLine Super HyperGraph. We further investigate their fundamental properties and structural characteristics.

Abstract: Structural Health Monitoring (SHM) is essential for the safety and long-term performance of civil and mechanical infrastructure, yet traditional vibration-based approaches often struggle with nonlinear behavior and environmental variability. Koopman operator theory provides a promising alternative by enabling linear analysis of nonlinear structural dynamics through observable functions. This review examines 67 peer-reviewed studies published between 2010 and 2025 and selected using Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. We outline the development of Koopman-based methods from Dynamic Mode Decomposition (DMD) and Extended-DMD (EDMD) to recent applications in civil, mechanical, and aerospace systems. The review clarifies the mathematical foundations of Koopman analysis and its relationship to structural dynamics. It also identifies major research gaps, including limited damage-sensitive observable design, insufficient use of structural mechanics constraints, the absence of quantitative links between Koopman spectra and physical damage, inadequate benchmarking, and the need for real-time deployment strategies. We conclude by outlining a hybrid Koopman framework that integrates physics-based information with data-driven learning to support interpretable and scalable SHM.

Abstract: Background/Objectives: Patient safety culture represents a holistic approach to ensuring the safety of patient care. When nurses experience abusive behaviors, patient safety culture is undermined. Methods: A cross-sectional study was conducted in Greece, and data were collected via an online survey between October and December 2025. Workplace gaslighting and patient safety culture were measured using the Gaslighting at Work Scale and the Safety Organizing Scale, respectively. Multivariable linear regression analyses were performed using IBM SPSS Statistics 28.0. The level of statistical significance was set at 0.05. Results: The sample included 448 nurses. Almost nine out of ten of the participants (87.3%) were women, with an average age of 38.04 years (SD = 10.27). Regarding educational level, 42.2% held a MSc or PhD degree. Respondents reported moderate perceived workplace gaslighting with a mean score of 2.37 (SD = 1.04) on the Gaslighting at Work Scale. For safety culture, the Safety Organizing Scale yielded a mean score of 5.00 (SD = 0.91). In the univariable analysis, workplace gaslighting was significantly and negatively associated with safety culture (beta = -0.195, 95% CI = -0.275 to -0.115, p < .001), indicating that higher levels of workplace gaslighting were related to worse safety culture behaviors. This association was still significant even when potential confounding variables were considered (adjusted beta = -0.223, 95% CI = -0.305 to -0.142, p < 0.001). Conclusions: This study highlighted the negative impact of workplace gaslighting on patient safety culture. Healthcare organizational leadership is urged to establish and enforce zero-tolerance policies toward gaslighting behaviors and to foster an environment in which nurses are encouraged to speak up openly and report such behaviors.

Abstract: The Phillips curve remains central to monetary policy, yet its functional form has been intensely debated following the 2021–2023 inflation surge. This paper offers novel empirical evidence by providing the first symmetric comparison of regime-dependent nonlinearities in the inflation–slack relationship between the United States and the Euro Area, using identical threshold and smooth-transition frameworks on quarterly data extending through 2025Q4, the most recent available. Core PCE inflation (US) and core HICP excluding energy, food, alcohol, and tobacco (Euro Area) are modeled as functions of unemployment and output gaps, with controls for oil shocks and inflation expectations. TAR/SETAR and LSTAR estimations uncover statistically significant steepening in tight labor-market regimes. In the US, the slope more than doubles when the unemployment gap falls below –0.61 percentage points. In the Euro Area, a comparable kink emerges near zero (–0.048 pp), with smoother transitions reflecting greater wage and price rigidities. Post-2019 subsamples exhibit amplified nonlinearity, consistent with supply-shock transmission in high-pressure conditions. Extensive robustness checks affirm these findings. The results establish a state-dependent sacrifice ratio, with sharply higher disinflation costs in tight regimes, and highlight substantial risks of monetary policy miscalibration in future high-pressure episodes.

Abstract: Predictive climate machine learning is increasingly good at forecasting hazards, but hazard maps alone do not decide what to do, where, when, for whom, and under which futures. We argue that climate ML remains insufficient for adaptation unless interventions are treated as first-class, versioned, and auditable objects. This matters because many climate digital twins still prioritize state estimation and simulation, while adaptation requires intervention observability, counterfactual effect estimation, and constrained portfolio choice. We propose PCA-OS (Planetary Climate Adaptation Operating System), a decision-support operating abstraction that uses an intervention-aware global causal knowledge graph and standardizes object schemas, versioned updates, query primitives, and audit interfaces across three core system objects: (1) an Adaptation Intervention Ledger that records measurable interventions with provenance and uncertainty; (2) a Causal Effect Atlas that stores scenario-indexed, spillover-aware estimands, identification assumptions, diagnostics, and sensitivity bounds; and (3) a Robust Portfolio Decision Layer that optimizes intervention portfolios under budget, equity, and no-harm constraints. We argue that foundation models and intervention-aware world models should support, rather than replace, identification-aware causal analysis by surfacing candidate confounders, mechanisms, and spillover pathways for human review. Finally, we outline AdaptBench, an evaluation suite in which systems can fail for inequitable or maladaptive recommendations even when predictive accuracy is high. The result is a field-level provocation: move climate ML from read-only hazard intelligence to auditable decision support for adaptation.

Abstract: Background/Objectives: Intracerebral hemorrhage (ICH) is a severe subtype of stroke characterized by extensive secondary brain injury driven by oxidative stress, inflammation, and progressive neuronal loss, leading to poor neurological outcomes. Thymoquinone, a bioactive compound derived from Nigella sativa, has demonstrated potent antioxidant and neuroprotective properties, but its integrated effects in hemorrhagic stroke remain insufficiently explored. This study aimed to evaluate the antioxidant and neuroregenerative effects of thymoquinone in a rat model of ICH. Methods: Male Wistar rats with experimentally induced ICH were randomized into untreated controls and two treatment groups receiving thymoquinone (150 mg/kg and 250 mg/kg) for three consecutive days. Oxidative injury and antioxidant responses were assessed using membrane blebbing, malondialdehyde (MDA), superoxide dismutase (SOD) activity, and nuclear factor erythroid 2–related factor 2 (Nrf2) expression, while neuroprotection was evaluated by neuronal counts in perihematomal tissue. Results: Thymoquinone treatment significantly reduced membrane blebbing and MDA levels, while markedly increasing SOD activity and Nrf2 expression in a dose-dependent manner. These biochemical improvements were accompanied by significant preservation of neuronal morphology and increased neuronal survival, with the 250 mg/kg dose showing the strongest effects. Conclusions: In conclusion, thymoquinone confers robust antioxidant and neuroprotective benefits in experimental ICH and represents a promising candidate for mitigating secondary brain injury following intracerebral hemorrhage.

Abstract: An elementary and self-contained proof of the existence of the Euler-Mascheroni constant γ is presented, based solely on the Simpson quadrature formula and the convexity of the function f\( x \mapsto 1/x \). The local logarithmic increments are approximated as follows: \( \int_{2n-1}^{2n+1} \frac{dx}{x} \) Using Simpson’s rule, a discrete approximation expressed as a finite linear combination of reciprocal integers is constructed. Exploiting the monotonic and convex nature of the function \( 1/x \), sharp two-sided inequalities relating the numerical approximation to exact logarithmic increments are established. These inequalities imply that the accumulated quadrature errors form a convergent series. Consequently, the following classical limits \( \gamma = \lim_{N \to \inf} \left( \sum_{k=1}^{N} \frac{1}{k} - \log{[N]} \right) \) are proven to exist. This approach provides a conceptually simple alternative to traditional proofs based on the Euler-Maclaurin formula, highlighting the direct connection between numerical integration, convexity, and the analytical nature of γ. I further show that λ can be expressed as \( (\log{[2]}+1)/3 + \delta \), where both \( (\log{[2]}+1)/3 \) and \( \delta \) are irrational, and where \( \delta \) arises as the limit of a rational sequence derived from as Simpson-type approximation.

Abstract: The question of how consciousness arises from physical systems remains one of the most profound challenges in neuroscience and philosophy. This essay examines two leading models that attempt to explain the emergence of consciousness from both biological and synthetic neural networks: Integrated Information Theory (IIT) and Global Workspace Theory (GWT). Each offers a distinct approach—one grounded in intrinsic informational structure, the other in functional accessibility and cognitive architecture. By comparing their principles, empirical support, and criticisms, this essay aims to clarify how these models contribute to our understanding of consciousness and its potential replication in artificial systems. Recent adversarial testing reveals that both theories face substantial empirical challenges, suggesting the field may need to resolve fundamental conceptual questions before definitive adjudication between theories becomes possible.

Abstract: This study as part of a postdoctoral research takes a critical look into Corporate business incubators (CBIs) value co-creation by adopting an integrative and meta-model approach. An integrative review aids the aggregation of studies fragmented with diverse views and perspective or approaches without a cogent agreeable framework; while meta-modelling aids the development of new models from an existing one. Based on paradigms with meta models from different perspectives and areas of studies (philosophical, entrepreneurial, psychological, innovation), this study aggregates them into a compounded framework of study for easier audience digest. Based on this, the study uses a multi-level analyses for the methodological synthesis of CBI value co-creation concepts capturing the holistic view based on CBIs classifications taxonomy and typology, scope and pathways based on CBI activities with an outlook on CBI Business Models. In addition to this, an emerging and captivating concept of cognitive schema of CBI actors is applied to the model capturing the attributes, relationships and CBI sub-schemas and their value co-creation outcomes based on response to environmental conditions and innate organizational capabilities. The study identifies three meta models which are based on CBIs core components and functions, CBIs Value Co￾creation and UBI (University Business Incubators), CBIs Core Business Models, Classifications and Value Co-creation and also addresses the complementarities towards a compounded CBI framework. The evolving model(s) would serve as the conceptual framework on which further CBIs co-creation research study with UBIs would be built.

Abstract: Background: Subacute sclerosing panencephalitis (SSPE) is a chronic, progressive disease of the central nervous system (CNS) caused by persistent infection at this level with the wild measles virus. Its incidence is correlated with measles vaccination coverage. The pathogenesis isn't fully understood, but infection before the age of 2 is an important risk factor. Methods: This is a retrospective observational study conducted at the Louis Turcanu Children's Hospital in Timisoara, Romania, based on the analysis of the medical records of patients diagnosed with SSPE between January 2021 and December 2025. We analyzed demographic and epidemiological factors, clinical and paraclinical findings, management, and outcomes. Results: Seven children were diagnosed during the study period, with a mean age of 8.4 years (range 7-11 years). Six of them had contracted measles during their first year of life, and one at the age of four. The mean latency period was 7.1 years (range 4-9 years). On admission, all patients presented symptoms consistent with clinical stage II, with periodic slow wave discharges on electroencephalogram (EEG). The initial brain Magnetic Resonance Imaging (MRI) was normal in two cases, while revealing varied abnormalities in all others. Despite complex treatment with isoprinosine and anticonvulsants, progressive cognitive and neurological deterioration continued in all patients. Conclusions: SSPE is a rare but serious, debilitating disease despite its complex, multidisciplinary care. Following a 10-year SSPE-free period, the reappearance of these pediatric cases constitutes a public health alert, unequivocally demonstrating the importance of measles vaccination.

Abstract: Background: Sleep disorders like insomnia, obstructive sleep apnea (OSA), REM behavior disorder etc. are nowadays diagnosed through the Internet of Things (IoT)-enabled sys-tems that monitor and analyze the subject's sleep data. Health IoT networks are rife with communications of sensitive physiological data from wearable EEG, ECG, SpO₂ and res-piratory sensors. However, these networks face threats from anomalous traffic flows, sig-nal sabotage and data integrity violation. In this paper, an AI-based hybrid detection and classification framework is proposed for secure Sleep Health IoT (S-HIoT) networks. The integrated CNN, BiLSTM and RF model provides a proposed framework for joint sleep-stage classification and network anomaly detection. To this end, a multi-objective loss function is proposed for jointly optimizing the physiological state prediction and se-cure traffic monitoring. Experimental validation using the Sleep-EDF and CICIoMT2024 datasets demonstrate a classification accuracy of 97.8% for sleep staging, and 98.6% for network detection with low inference latency (

Abstract: Short tandem repeat (STR) expansions are a major cause of neurodegenerative disorders; however, their genetic and clinical heterogeneity complicates diagnosis. STR detection remains limited in routine short-read next-generation sequencing (NGS) workflows. We evaluated the diagnostic yield and clinical utility of computational STR genotyping in a large Turkish neurodegenerative disease cohort. ExpansionHunter was applied to NGS data from 3,150 patients and 146 controls, targeting 15 disease-associated STR loci. To improve genotyping of poorly captured exonic regions in exome data, the default locus coverage threshold was reduced from 10X to 3X. Candidate expansions were visually inspected using REViewer and validated by conventional molecular methods. Computational analysis identified 28 pathogenic and 160 intermediate expansions. Of these, 23 were confirmed as pathogenic, and eight initially classified as intermediate were reclassified as pathogenic after conventional validation, resulting in 31 pathogenic cases across 28 families: HTT (n=8), ATXN2 (n=5), ATXN1 (n=4), DMPK (n=3), PABPN1 (n=3), TBP (n=2), and single cases in AR, ATN1, and CACNA1A. Lowering the coverage threshold markedly increased genotyping rates at low-coverage loci in exome, particularly in ATXN2. Genetic findings were largely consistent with clinical pre-diagnosis and the additional diagnostic yield was 0.95%. These findings support integrating STR analysis into routine neurogenetic diagnostics.

Abstract: Illyrian helmets represent a key element of Iron Age martial culture in the western Bal-kans, reflecting technological knowledge, workshop traditions, and long-distance cultural exchange. Based on the currently available archaeological record, Illyrian helmets are first attested in contexts dating to the 8th-7th centuries BC, with finds concentrated in Greece and the central and western Balkans, including Macedonia, Albania, Dalmatia, and the wider interior. Over time, the form developed into several variants (Types I-IIIB). This study presents the elemental characterization of the total set of 27 Illyrian helmets exca-vated in Albania and currently preserved in local museum collections, a region where the later types are particularly well attested. As the helmets are intact and exhibited in mu-seums, non-destructive micro-XRF analysis was employed. The main research questions addressed how the alloy composition, including minor and trace elements, reflects local metallurgical practices and distinguishes Illyrian helmets from similar helmets in neigh-boring regions. The results indicate the consistent use of bronze alloys dominated by cop-per (89-95.3%) with low tin contents (3.5-9.9%), consistent with established alloying prac-tices for durable protective equipment. Minor and trace elements, including iron (up to 1.5%), lead (up to 0.76%), arsenic (up to 0.09%), zinc (up to 1.17%), and antimony (up to 2.36%), likely reflect metallurgical choices, recycling practices, or impurities linked to re-gional copper deposits. These elemental signatures, particularly the association of arsenic, antimony, zinc, and iron, suggest regional metallurgical characteristics and offer addi-tional insight into Illyrian bronze production, while helping to distinguish these helmets from contemporaneous finds in other parts of the Balkans and Europe.

Abstract: Fibromyalgia (FM) syndrome is typified by constant and pervasive musculoskeletal pain and may be comorbid with obesity. Glucagon Peptide 1 Receptor Agonists (GLP-1RAs) are relatively new pharmacotherapies developed for the treatment of type 2 diabetes mellitus (T2DM) and repurposed for the treatment of obesity. In addition to their well-established impact on glucose balance, new evidence indicates that GLP-1RA may have anti-inflammatory properties beyond glycaemic regulation. Modulation of central pain pathways by GLP-1RAs has been proposed in patients with FM, but few studies have directly evaluated the effects of GLP-1RAs on central pain. Hence, the purpose of this study is to review the relationship between FM and obesity and explore the potential role of GLP-1RAs in the management of FM.A literature search was conducted across four da-tabases - PubMed/Medline, Cochrane, Google Scholar, and PEDro, up to May 2025. The literature was sparse, and no formal evaluation process was performed; however, papers were excluded if they failed to address either FM or GLP-1RA. There was no formal risk-of-bias assessment for each included paper. Key characteristics of each study were extracted and summarized in table form to enable efficient narrative synthesis. Of the 56 included studies, 24 were preclinical reviews, 16 were clinical reviews, 8 were preclinical animal models, and only 8 focused on human data, limited to retrospective analyses of data and self-report. There is some evidence that GLP-1RAs may reduce neuronal excita-bility, inhibit pain signalling, and decrease inflammation. However, given the lack of clinical trials, it is difficult to draw firm conclusions regarding the potential role of GLP-1RA in the management of FM with comorbid obesity.

Abstract: The heel-strike (HS) paradigm of human gait originates from 19th-century chronophotographic studies conducted on Georges Demeny,a gymnasium instructor whose performed, exaggerated gait was never representative of natural locomotion. A compounding martial bias further normalised HS through military marching drill. A multi-disciplinary convergent argument analysis is conducted, integrating philological, zoological, anatomical, biomechanical, neurological and socioeconomic lines of evidence. All seven lines of argument support a forefoot-first model in which the centre of mass (CoM) leads the movement, stabilisers control equilibrium proactively, and the Triceps surae works in continuous eccentric mode—its natural functional state. Heel-strike generates impact forces up to 700 N with an ascending braking vector, under-recruits Gluteus maximus, progressively impoverishes plantar mechanoreceptors, and transmits repeated microtraumatic impulses up to the brain. Natural human gait is organised around forefoot contact, progressive CoM advance, and continuous eccentric stabiliser activity. The proposed model rediscovers lightness: a dance with gravity rather than a war against it. The HS paradigm is a culturally conditioned artefact with measurable pathological consequences for joints, the lumbar spine, and beyond.