Abstract: Based on a previously validated head-to-tail dimer vaccine model, we designed a dimeric form of the Newcastle disease virus (NDV) HN protein expressed in rice endosperm (designated as Osr2HN) and initially characterized its molecular expression profile. Previous immunization studies in chickens demonstrated that two doses (0.5 μg) or a single dose (5 μg) of Osr2HN provided complete protection against viral challenge. To facilitate its commercialization, two transgenic rice lines (HN-1 and HN-2) were propagated for three generations to systematically evaluate their molecular characteristics, genetic stability and environmental safety. Insertion site analysis, combined with PCR, qRT-PCR and western blotting, confirmed that the exogenous HN gene was stably integrated into the nuclear genome without sequence variations. The transgenic lines exhibited germination rates, growth cycles and 12 agronomic traits comparable to those of the wild-type TP309, with the exception of increased grain chalkiness in HN-2. No horizontal transfer of the HN gene to weed species was detected, and pollen viability remained unchanged. Field-based biodiversity analysis revealed no adverse effects of the HN gene on pest or weed communities. Collectively, these findings from comprehensive molecular analyses and field evaluations confirm the genetic stability, agronomic performance, and environmental safety of Osr2HN-transgenic rice, providing essential data to support its commercialization as a plant-derived vaccine platform.

Abstract: Functional information measures how rare functional configurations are. Wong and colleagues argue that selection should drive a law of increasing functional information. This is often read as a claim that complexity must increase. We give a cleaner interpretation, which is that survivors tend to be the systems that did not overcommit. We model a system as a policy π, meaning a bundle of commitments expressed in a finite embodied vocabulary. New selection pressures arrive as a set of future requirements drawn from the unobserved outcome set U. A currently viable policy leaves an unobserved buffer B_π ⊆ U of outcomes it still permits. Under a maximally ignorant novelty model, the survival probability of π is exactly 2^|B_π|−|U|. Under any exchangeable novelty prior, survival remains monotone in |B_π|. So persistence favours weaker constraints on function, where weakness counts the compatible completions left open. We define degree of function as survival probability and functional information as Hazen and Szostak rarity among currently viable policies. Conditioning on persistence reweights the population toward larger buffers, hence higher functional information. This yields a formal version of Wong’s law under explicit assumptions. In fully enumerated toy worlds, weakness maximisation improves mean log survival probability by 1.674 bits relative to random choice. Weakness and simplicity are not the same thing. Weakness helps a system persist under novelty, because it keeps more futures compatible. Simplicity can help a system persist because there is less to break. That obviates the need for repair. Complexity requires self-repair to persist, increasing weakness. Life is persistent complexity. In between complex life and simple nonlife is the void of the unviable; complexity which is not alive.

Abstract: This study investigates the influence of circular-economy transparency (CET) on responsible purchase intention (RPI) within the electronics market, elucidating the mediating role of perceived green authenticity (PGA) and the boundary condition of greenwashing skepticism (GWS). We used PLS-SEM (SmartPLS 4) with bootstrapping to test direct effects, mediation, moderation, and moderated mediation on a cross-sectional online survey of 400 adult electronics customers in Saudi Arabia. The results indicate that CET positively predicts PGA and RPI, with PGA significantly enhancing RPI. This suggests that perceptions of authenticity convey a significant aspect of transparency's impact on responsible intentions. Nonetheless, GWS considerably diminishes the CET→PGA and PGA→RPI relationships and lessens the potency of the indirect CET→PGA→RPI pathway, indicating that skeptical consumers more rigorously disregard cues of transparency and authenticity. The model provides a strong description of the observed variance in both PGA and RPI, justifying its explanatory and predictive value. These results suggest that electronics brands and policymakers would do well to complement transparency programs with measurable, decision-relevant information disclosures and trust-enhancing procedures (e.g., traceability and third-party validation) in order to minimize distrust and enable responsible purchasing.

Abstract: Background: Childhood obesity has become a major global health concern and is increasingly recognized as a factor influencing skeletal development. Emerging evidence suggests that excess adiposity may alter craniofacial growth patterns, potentially affecting orthodontic diagnosis, treatment planning, and airway function. However, the extent to which obesity influences craniofacial morphology in growing individuals remains incompletely understood. Objective: To evaluate the relationship between body mass index (BMI) and craniofacial morphology in children and adolescents using selected sagittal and linear craniofacial parameters, and to determine the independent effects of age and sex on these associations. Methods: This cross-sectional orthodontic study included 130 healthy subjects aged 19 or younger. Anthropometric measurements were recorded, and BMI was calculated to classify participants into normal weight, overweight, and obese groups. Standardized lateral cephalometric radiographs were obtained, and twenty-one skeletal and soft-tissue parameters were analyzed. Statistical evaluation included tests of normality, one-way ANOVA, and post-hoc comparisons to assess differences according to BMI, sex, and age groups. Results: Obesity was significantly associated with increased sagittal skeletal dimensions. Mandibular body length, mandibular unit length, SNB angle, and maxillary unit length demonstrated progressive increases across BMI categories (p < 0.05). In contrast, vertical growth parameters showed no significant differences. Soft-tissue analysis revealed reduced facial convexity and lower facial height ratios in obese subjects. Age was strongly associated with increases in linear jaw dimensions, whereas sex differences were limited primarily to skeletal size rather than morphological relationships. Conclusions: Childhood obesity is associated with enhanced sagittal craniofacial growth, particularly involving mandibular structures, while vertical skeletal patterns remain largely unaffected. These findings highlight the importance of incorporating BMI assessment into orthodontic evaluation and suggest that obesity may influence growth timing, facial morphology, and airway-related risk factors.

Abstract: The Global Navigation Satellite System (GNSS) has emerged as a backbone of modern civilisation, industry, and society. Degradations and disruptions of the GNSS Positioning, Navigation, and Timing (PNT) service performance are caused by natural and adversarial sources. The ionospheric effects form the principal single class of the GNSS PNT performance degradation causes. Traditional GNSS ionospheric correction models appear unable to resolve the problem for their global nature, and the intrinsic lack of agility and flexibility. Here we contribute to the case with the proposal of concept and methodology for tailored GNSS ionospheric correction model development in support of GNSS resilience development, based on: (i) a massive dataset of long-term (annual) GNSS-derived total electron content TEC observations, as target variable (ii) a massive dataset of geomagnetic field density components, as predictors, and (iii) utilisation of statistical/machine learning predictive model development methods. The proposed approach emerges as a component of the previously introduced architecture-agnostic Ambient-Aware Application-Aligned (AA2) GNSS PNT concept, introducing the GNSS positioning environment situation awareness. Proposed concept and methodology is successfully demonstrated in the case of tailored GNSS ionospheric correction model development using the R environment for statistical computing in the case-scenario of mid-latitude single-frequency commercial-grade GNSS rover.

Abstract: Amid U.S. housing and labor shortages, Appalachia needs solutions that strengthen communities. This study examines how establishing an industrialized off-site construction (IOC) ecosystem can address regional housing, workforce, and construction challenges. From March–June 2024, we conducted seven participatory design workshops across Appalachia (n=129). Using a standardized prompt sequence (status quo, opportunities, IOC solutions), affinity clustering, and PICK chart prioritization, participants identified needs, capacities, and gaps, then ranked actions to advance IOC. Validity was tested through independent re-clustering with a shared codebook; inter-rater agreement was substantial (weighted κ=0.80). Five cross-cutting levers emerged: Education & Training; Policy & Regulation; Marketing & Awareness; Financing & Funding; and Technology & Innovation. Marketing & Awareness were consistently viewed as high-impact and easier to implement near term; Education & Training were high-impact but resource-intensive; Policy and Financing were impactful yet harder to shift; Technology & Innovation should be introduced incrementally to fit tradition-bound industry and regional norms. The resulting roadmap emphasizes near-term pilots, targeted talent pipelines, permitting/code alignment, and fit-for-purpose capital. The main contribution is a globally reproducible participatory protocol with transparent prompts, a shared codebook, independent re-clustering, and reliability metrics that enable replication and benchmarking across regions.

Abstract: Background: Autism spectrum disorder (ASD) affects approximately 1–2% of children worldwide, yet its etiology remains incompletely understood. Emerging evidence suggests that offspring of parents with autoimmune diseases show elevated autism prevalence. Notably, children of parents with psoriasis (OR 1.59), type 1 diabetes (OR 1.49–2.36), and rheumatoid arthritis (OR 1.51) demonstrate particularly strong associations. Hypothesis: I propose that autism is fundamentally an immune-metabolic disorder characterized by TNF-α–mediated mitochondrial dysfunction leading to cerebral energy deficiency. This energy deficit impairs three critical processes:(1) synaptic pruning during neurodevelopment,(2) real-time social cognition including gaze processing and emotion recognition, and(3) protein synthesis of critical synaptic scaffolding molecules. The primary mechanism involves TNF-α pathway dysregulation—through genetic inheritance from parents with autoimmune diseases such as psoriasis, type 1 diabetes, and rheumatoid arthritis, and/or through direct fetal exposure to elevated maternal TNF-α during pregnancy. I further propose that the well-documented “firstborn effect” in autism reflects maternal immune maladaptation during primigravid pregnancies. Additionally, for cases without parental autoimmune history, I propose a speculative secondary mechanism: mitonuclear immune conflict, wherein paternal immune genes may partially recognize maternal mitochondria as non-self, generating endogenous TNF-α.

Abstract: Background and Objectives: Anticholinergic burden (ACB) cumulatively leads to adverse outcomes and increased mortality. Taiwan's NHIRD prevalence studies indicate ~60% of elderly patients (≥65) annually receive anticholinergic medications. In those with polypharmacy, 60–80% were exposed to anticholinergic medications, which was linked to higher risks of pneumonia, myocardial infarction, and stroke. This study aims to survey physicians’ knowledge and attitudes on Anticholinergic Burden (ACB) in Taiwan, directly addressing a recognized gap in clinical practice. Materials and Methods: This nationwide, anonymized online 3-month survey (July–September 2025), used the KAP framework. Physicians from 92 hospitals across Taiwan were invited to participate via e-mail. The survey covered demographics, ACB knowledge, attitudes, practices, and feedback, utilizing branching logic. Data was analyzed and presented descriptively. Of 62 respondents, only 23% of physicians were aware of the term 'Anticholinergic Burden' (ACB). Knowledge of specific common medication ACB scores was low (average 1.86/10), and respondents showed significant uncertainty regarding the risks associated with high ACB. Despite 53% of physicians (33/62) rating ACB assessment as "Important/Very Important," this rarely translated into practice: most never calculated scores, and only one did so routinely. Fifty-six participants' overwhelming demand for increased ACB education emphasizes the critical need for training to close both the identified knowledge and knowledge-practice gaps. Conclusions: Physician’s knowledge of medicines with anticholinergic property is relatively low in Taiwan despite the awareness of its importance. There is a clear knowledge and knowledge-practice gap which can be addressed through targeted educational activities.

Abstract: This study conducts an economic evaluation of urban water demand and supply in a South African municipal water management system, using smart water meter technology and map-based analysis to identify spatial and economic patterns of water scarcity. Using purposive sampling and secondary data from municipal billing records, the study integrates water meter datasets with geographic information system (GIS) tools to analyse consumption behaviour, tariff payments, and geographic disparities in water access. The findings reveal distinct areas within the municipal distribution network where households experience both reduced water availability and tariff payment deficiencies, indicating heightened vulnerability to water insecurity and financial strain. Spatial patterns demonstrate that these shortfalls are unevenly distributed across income groups and geographic zones, providing a critical evidence base for targeted water management interventions. The economic assessment highlights the relationship between water tariffs, consumption levels, and affordability constraints, offering insights into the financial sustainability of the current water management framework. Overall, the study demonstrates the value of combining GIS-based techniques with water meter technologies to diagnose systemic weaknesses and to support more equitable and sustainable urban water management. The results provide actionable guidance for policymakers seeking to improve tariff design, strengthen demand management, and address the persistent socio-economic inequalities underpinning water access in Cape Town and similar urban contexts.

Abstract: The efficacy of postbiotics vary significantly comparing different strains and preparation processes. We aimed at evaluating the effect of an innovative postbiotic (iPB) generated through the sequential fermentation of Lacticaseibacillus rhamnosus GG and Lacticaseibacillus paracasei NPB-01, compared to single-strain postbiotics, on epithelial barrier integrity and innate immunity in human enterocytes. Comparative evaluation of the effects elicited by iPB or by single-strain postbiotics on gut epithelial barrier using a Caco-2 cells-based experimental model by measuring cell growth proliferation, tight junction proteins (occludin and zonula occludens 1, ZO-1), mucus protein Mucin-2 (Muc-2), and lactase expression. The modulatory action on the production of innate immunity peptide Human Beta-Defensin 2 (HBD-2) via RT-qPCR and ELISA was also comparatively assessed. iPB exposure resulted in a higher up-regulation of occludin, ZO-1, MUC2 and lactase expression, if compared with the single-strain postbiotics, suggesting a beneficial synergistic action in modulating epithelial gut barrier. Furthermore, iPB induced a significantly higher production of HBD-2, suggesting a synergistic enhancement of innate immune response. Our findings suggested that the sequential fermentation process acts as a biotechnological catalyst, optimizing the immunomodulatory action and gut barrier-protective properties of Lacticaseibacillus strains. This study introduces iPB as a high-performance postbiotic candidate for the prevention and management of conditions characterized by alterations of epithelial gut barrier and innate immunity.

Abstract: Soil physicochemical and biochemical properties are fundamental to soil processes and ecosystem functioning in forested landscapes. However, their responses to dominant tree species in humid montane regions remain unclear. This study examined how three widespread broadleaf species—Quercus pontica, Quercus petraea, and Fagus orientalis—influence the physical, chemical, and biochemical properties of the soil in natural forests in the Eastern Black Sea region. Fifteen soil samples (five from each forest type) were collected under comparable climatic and geological conditions and analyzed for texture, pH, electrical conductivity, organic carbon content, and key biochemical indicators of microbial activity. Significant differences in soil properties were observed among forest types. Soils beneath Q. pontica exhibited a lower pH level (3.26), a higher organic carbon content (3.82), microbial abundance, and enhanced biochemical activity. enhanced biochemical activity. In contrast, Pontic oak-dominated stands were characterized by distinct textural and chemical signatures. Multivariate analyses revealed that soil texture fractions, pH, and microbial carbon acted as the primary edaphic filters driving differentiation of soils among forest types. These patterns suggest that species-specific litter inputs and belowground processes regulate soil biochemical functioning by modifying resource availability and physical habitat conditions. Our results demonstrate that, even under similar environmental conditions, dominant tree species exert a strong influence over soil physicochemical and biochemical properties. Understanding these species-specific soil responses is essential for predicting ecosystem functioning, carbon cycling, and sustainable forest management in a changing environment.

Abstract: Companies frequently utilized multiple sales channels to ensure sustainability. However, attempts to fulfill all incoming orders without sufficient consideration of operational constraints resulted in significant challenges in planning and production processes. Therefore, effective order management was considered essential for optimizing overall business performance. The strategic evaluation of sales orders reduced post-acceptance difficulties, thereby improving both customer satisfaction and operational efficiency. In this context, a machine-learning-based model for sales order classification was proposed for a hybrid production environment accommodating both Make-to-Stock (MTS) and Make-to-Order (MTO) strategies. Initially, the attributes employed in sales order evaluation were identified through an extensive literature review and subsequently refined using a heuristic approach to determine the most relevant classification features. Based on these attributes, sales orders were first clustered into three groups using the k-means algorithm to generate meaningful class labels. The labeled datasets were then utilized to train three supervised machine learning algorithms: Random Forest (RF), Support Vector Machine (SVM), and K-Nearest Neighbor (KNN). The performance of these models was evaluated and compared, resulting in accuracy rates of 99.67%, 99.55%, and 99.49%, respectively. The findings demonstrated that the Random Forest algorithm achieved the highest classification performance.

Abstract: This paper presents a parametric modeling and aerodynamic optimization methodology for the second-stage stator of a multi-stage centrifugal compressor. Based on the geometric configuration of the two-stage components, a flexible parametric template is established for the second-stage stator. Numerical simulations are conducted to analyze the internal flow field and evaluate the performance of the initial design of this compressor, revealing performance deficits such as significant vortex-induced losses and a large outlet circumferential flow angle (-12.138°). To this end, an aerodynamic optimization framework integrating a Kriging surrogate model and a Genetic Algorithm (GA) is applied to the second-stage stator, targeting at the aerodynamic matching optimization under multiple operating conditions. The optimization objectives include maximizing the overall polytropic efficiency of compressor and static pressure ratio of second-stage stator, as well as minimizing the total pressure loss coefficient and the outlet circumferential flow angle of second-stage stator. The results demonstrate that the optimized design achieves a 2.17% improvement in the overall polytropic efficiency and a 12.01% improvement in the static pressure recovery coefficient at the design condition, along with a notable reduction in the outlet circumferential flow angle to 0.663°. Under multi-condition operation, the optimized stator exhibits enhanced the performance stability. The overall polytropic efficiency is improved by 2.06% and the static pressure recovery coefficient is improved by 23.31% at the low-flow condition, confirming the effectiveness of the proposed parametric modeling and sequential optimization approach.

Abstract: Graph Neural Networks (GNNs) have demonstrated exceptional performance in modeling structural dependencies within networked data. However, in complex decision-making environments, structural information alone often fails to capture the latent semantic logic and domain-specific heuristics. While Large Language Models (LLMs) excel in semantic reasoning, their integration with graph-structured data remains loosely coupled in existing literature. This paper proposes CSSA, a novel Cross-modal Semantic-Structural Alignment framework that synergizes the zero-shot reasoning of LLMs with the topological aggregation of GNNs through a contrastive learning objective. Specifically, we treat node attributes as semantic prompts for LLMs to distill high-level "risk indicators," while a GNN branch encodes the local neighborhood topology. A cross-modal alignment layer is then introduced to minimize the representational gap between semantic intent and structural behavior. We evaluate CSSA on a massive dataset of 2.84 million online transaction records. Experimental results demonstrate that CSSA achieves a superior F1-score and AUC compared to state-of-the-art GNNs, particularly in scenarios characterized by extreme class imbalance and covert adversarial patterns.

Abstract: Sexual objectification is the treatment of a person as a body or a collection of body parts that are valued primarily for their sexual appeal. The main purpose of this study was to determine the relevance of sexual objectification to women's health and well-being across the life cycle, from middle adolescence to old age. Additionally, the relevance of age and education to sexual objectification and its association with traditional gender role attitudes was examined. The study was cross-sectional and the sample consisted of 6,112 Spanish women between the ages of 16 and 85, who were assessed using seven questionnaires and scales. The results showed that lower age and lower number of children were associated with greater importance of sexual and physical attractiveness and with a more sexualized image, although there were no differences between adolescent and emerging adult women. Greater importance placed on sexual and physical attractiveness, as well as total sexual objectification, was associated with greater mental distress, lower psychological well-being, lower life satisfaction, and lower self-esteem at every life stage. Greater importance placed on sexual and physical attractiveness was associated with more traditional gender role attitudes among all age groups, except for older women. We conclude that sexual objectification is a threat to women's mental health and well-being.

Abstract: Background/Objectives: Metabolic alterations, including dyslipidemia, are increasingly recognized in patients with neuroendocrine tumors and may influence tumor biology and treatment outcomes. However, the clinical relevance of dyslipidemia and the potential impact of lipid-lowering therapies in bronchopulmonary neuroendocrine tumors (BP-NETs) treated with somatostatin analogues (SSAs) remain poorly defined. This study aimed to evaluate the progression-free survival (PFS) in patients with advanced BP-NETs receiving SSAs according to dyslipidemia as well as statin therapy. In addition, an exploratory in vitro analysis was performed to assess the combined biological effect of statins and SSAs. Methods: This study investigated the combined effects of atorvastatin and lanreotide therapy both in vitro and in a clinical setting. In NCI-H727 cells, we assessed cell viability, proliferation, apoptosis, DNA damage, and metabolic activity following single and combined treatments. Concurrently, we retrospectively evaluated the impact of dyslipidemia and statin therapy on progression-free survival (PFS) in patients with advanced BP-NETs receiving SSAs. Results: Combined treatment resulted in reduced cell viability, proliferation, and ATP production, alongside increased apoptosis and DNA damage, and was associated with impaired cellular energy metabolism compared with lanreotide alone and control conditions. In the clinical analysis, dyslipidemia was associated with shorter progression-free survival (PFS), whereas atorvastatin therapy in dyslipidemic patients showed a positive trend toward improved PFS. Conclusions: These findings support the potential relevance of lipid metabolism modulation as an adjunct strategy in advanced BP-NETs, warranting further validation in larger prospective studies and encouraging additional biochemical investigation of the underlying pathways.

Abstract: Public participation in planning, though a foundational democratic principle, faces implementation challenges across diverse planning systems worldwide. This study examines participatory planning practice in Ireland and Serbia – two contexts shaped by distinct planning traditions yet confronting similar tensions between democratic ideals and practice realities. Through comparative analysis of four local land-use planning instruments (Development Plans and Local Area Plans in Ireland; Spatial Plans and General Regulation Plans in Serbia), the research investigates how institutional design, power relations, and democratic commitments embedded within planning systems fundamentally shape participatory outcomes. Beyond external pressures such as neoliberalisation and democratic decline, the study demonstrates that the internal dynamics of participation, seen in the quality of dialogue, distribution of knowledge, strength of civic networks, and negotiation of power among stakeholders, ultimately determine whether participatory processes enable genuine democratic engagement or reproduce existing hierarchies. Methodologically, the research triangulates statutory regulations, public hearing documentation, and non-statutory participation records across multiple planning scales. Employing a four-dimensional analytical framework, including informing, consultation, collaboration, and monitoring, the analysis traces information dissemination strategies, consultation mechanisms, collaborative practices, and transparency structures. Findings reveal that, while both systems remain largely at the informing and consulting levels, critical differences emerge: Ireland demonstrates multi-channel, immersive approaches, feedback-oriented consultation, and structured collaborative experimentation, whereas Serbia exhibits statutory-minimal information provision, objection-based adversarial procedures, and exceptional rather than systematic collaboration. The study advances comparative European planning scholarship by identifying how planning cultures, legislative frameworks, and institutional responsiveness generate divergent participatory outcomes even under similar global pressures, offering practical insights for strengthening inclusive urban governance across varied institutional contexts.

Abstract: Virtual Reality (VR) is increasingly recognized as a valuable tool for sports training, providing immersive environments that support skill acquisition and performance improvement. Comparative studies across hand-intensive sports such as basketball, volleyball, and table tennis show substantial research on VR’s effectiveness in basketball and table tennis, yet volleyball remains relatively underexplored, particularly in terms of skill transfer to real-world play. Research in basketball and table tennis indicates that VR can improve motor coordination, tactical awareness, and user motivation. However, volleyball-specific literature is limited. Existing studies generally focus on areas such as eye–hand coordination and tactical decision-making but provide little evidence on whether VR-acquired skills translate effectively to the court. This paper addresses the gap in volleyball-focused VR research and emphasises the need for further investigation to maximise VR’s potential for volleyball training. Ten beginner-level volleyball players (mean age = 20.4 years) participated in this study, which examined the effectiveness of VR-based serving training. Participants completed an initial physical pre-test to determine their baseline serving performance, followed by a three-week VR training program consisting of structured serving drills. After the program, a post-test assessment was conducted to measure improvement. A paired t-test comparing pre- and post-training results showed a statistically significant improvement in serving performance (p = 0.0147), meeting the 0.05 significance threshold. This indicates that the observed performance gains were unlikely due to chance and demonstrates the positive impact of VR training on serving skills in beginner volleyball players.

Abstract: This report describes a 33-year-old male initially suspected of Inflammatory Bowel Disease (IBD) due to radiological findings, but finally diagnosed with Irritable Bowel Syndrome (IBS) based on the Rome IV criteria, normal colonoscopy findings and inflammatory biomarkers. When symptomatic pharmacotherapy for pain, constipation and heartburn alone did not bring lasting relief, he was referred for lifestyle therapy. Dietary, lifestyle advice, and physical activity are mainstay in the current guidelines on the management of IBS. However, beyond these generalities, patients receive little guidance on day-to-day decision making and essential elements of healthy living. We addressed the limitations in current guidelines on IBS by following the 21-point Health Building Guideline, along with Yoga and delivered through a seven-point protocol that uses the traffic light approach to promote and sustain behavioural changes in chronic diseases. After seven months of consistent adherence to intervention; following the traffic light approach, the patient achieved remission.

Abstract: Sustainable human resource management is critical in infrastructure sectors, yet firm-level resilience may conceal uneven health burdens within the workforce. This study examines a »resilience paradox« in a large Slovenian energy company using a two-level design. At the macro level (2012–2022), we explore associations between absenteeism categories and three efficiency ratios. At the micro level, we estimate a Poisson quasi-maximum-likelihood model with log planned hours as an exposure offset and cluster-robust inference on a balanced group-month panel (960 observations) built from 82,033 payroll records (2018–2022). Macro indicators remain stable, and we do not detect negative correlations between absenteeism and efficiency ratios, suggesting that operational continuity can be maintained despite absence shocks. However, micro-level estimates reveal pronounced inequalities: compared with employees aged ≤30, absenteeism rates are higher for ages 31–45 (incidence rate ratio—IRR 1.335), 46–55 (IRR 1.538), and >55 (IRR 1.829). Field/operational groups have higher rates than office/administrative groups (IRR 1.829), and female groups show higher rates than male groups (IRR 1.252). During COVID-19, absenteeism declined for office groups (IRR 0.840), while the additional effect for field groups was small and statistically uncertain (interaction IRR 1.179). The results call for targeted sustainable HRM interventions addressing aging, occupational risk, and equitable health protection across job types.