Georgios Priniotakis

In the transition toward Industry 5.0, physical human–robot interaction (pHRI) operates as an open bio-technical system far from thermodynamic equilibrium. Traditional industrial automation relies on quasi-static anthropometry and post-hoc checklists, failing to capture continuous neuro-kinematic instability and the systemic cost of assembly defects. This study develops and computationally benchmarks a closed-loop Prescriptive Digital Twin (PDT) that unifies non-linear biomechanics, Explainable Artificial Intelligence (XAI), and cyber–physical shop-floor execution. Leveraging open-source empirical kinematics (N = 8151 observations), the edge sensory tier reconstructs the human motor manifold via Takens delay coordinate embedding. By coupling Largest Lyapunov Exponents (LyE) with fixed-grid Shannon entropy (H), the system detects orbital trajectory divergence and compensatory muscular stiffening in real time. Rather than operating as an opaque black box, a game-theoretic TreeSHAP supervisory engine decomposes failure risk within 2.12 ms, autonomously dispatching multi-tier prescriptive policies: dynamic FABRIK-A^* Cartesian handover waypoint elevation, non-linear hyperbolic tangent (tanh) cobot admittance damping, and asynchronous REST-API payloads to plant MES/ERP systems for line pacing and recovery scheduling. As an in silico computational proof-of-concept benchmarked through Latin Hypercube Sampling Monte Carlo simulations (n = 1000), prescriptive waypoint elevation restores spinal posture, reducing median L5/S1 compressive loading by 48.4% and eliminating NIOSH action limit exceedances (from 18.9% open-loop down to 0.0%), while attenuating cobot velocity tremor by 63.6%. The empirical input derives from a single healthy operator (N = 1) and the Monte Carlo analysis varies mechanical rather than biological parameters, so the findings establish computational feasibility, not population-level generalizability. While physical validation on shop-floor robotic hardware and empirical process-level Life Cycle Assessment (LCA) remain prospective, treating dynamic human biomechanical stability as an endogenous control parameter outlines a candidate architecture for vulnerable-worker protection and, prospectively, resource-efficient manufacturing.

The moderate-magnitude (Mw 4.5) 26 May 2026 Jalalpur Sharif earthquake in northern Pakistan caused localized severe damage, one fatality, and a maximum Modified Mercalli Intensity (MMI) of VII. Field observations documented liquefaction-related ground deformation, transient groundwater turbidity, differential settlement, tilted utility poles, and earthquake-induced landslides in Quaternary deposits. Moment tensor inversion indicates shallow (~3 km) oblique-thrust faulting, with NE–SW strike direction (strike 217°, dip 55°, rake 46°). Gravity modeling reveals a ~20 mGal residual anomaly aligned with the Pabbi Anticline, supporting structural complexity and the presence of shallow faulting, although the causative fault cannot be uniquely resolved. Regional seismicity is concentrated at 10–15 km depth, with a peak near 12 km, indicating depth-dependent deformation within the sedimentary cover and deeper regional thrust system. Coulomb stress modeling shows negligible static stress changes (~0.001 bar) at Jalalpur Sharif from the 2019 Mw 5.8 Mirpur and 2024 Mw 5.0 Kharian earthquakes, providing little support for direct static triggering. The localized damage likely resulted from the combined effects of shallow faulting, potentially liquefiable sediments and vulnerable buildings. These findings highlight the importance of incorporating shallow seismogenic structures and local ground conditions into seismic hazard assessments across the eastern Potwar foreland.

Transport electrification can reduce climate impacts, but its environmental performance depends on vehicle production, energy supply, operation, and end-of-life treatment. This study compares battery electric vehicles (BEVs), non-plug-in gasoline hybrid electric vehicles (HEVs), and gasoline internal combustion engine vehicles (ICEVs) using Greek electricity supply and explicitly defined vehicle operating parameters. A cradle-to-grave life cycle assessment was implemented in openLCA using the ReCiPe 2016 endpoint (H), with a functional unit of 150,000 vehicle-kilometres. Climate impacts are reported as ReCiPe endpoint damage to human health and ecosystems. Both electrified configurations exhibited lower impacts than the ICEV across all 18 indicators with positive results. The BEV achieved reductions of 43.2% in global-warming damage to human health, 44.8% in fine particulate-matter formation, and 45.1% in terrestrial acidification relative to the ICEV. The HEV achieved reductions of 51.5% and 55.8% in fossil and mineral resource scarcity, respectively. Each electrified technology recorded the lowest value in nine positive indicators. The BEV–HEV ranking-margin analysis identified equal-impact thresholds of 9.05% for global-warming damage to human health and 4.25% for human carcinogenic toxicity. Negative water-consumption indicators were retained without interpretation as physical water savings. The findings identify category-specific trade-offs and support coordinated vehicle-efficiency and electricity-decarbonization measures without establishing overall environmental superiority.

Human hair discarded by salons, barbershops and households is a dispersed keratin-rich resource whose recovery requires more than identifying a technically possible application. This critical narrative review examines published evidence on human hair valorization, with emphasis on textile and related material systems. It connects collection and material variability with preprocessing, demonstrated applications, environmental assessment and social acceptance. Published studies support oil sorption, metal-ion removal, polymer reinforcement and keratin-based insulation, but these routes differ substantially in processing requirements and evidence maturity. Performance measured for selected fibers, synthetic solutions or laboratory composites cannot establish the effectiveness of mixed salon waste under service conditions. Likewise, results for extracted keratin or animal-derived fibers cannot be transferred directly to untreated human hair. The synthesis identifies opportunities for fiber-preserving technical products while showing that chemical extraction and carbonization require separate environmental justification. Functional equivalence, processing inventories, durability, contaminant management and end-of-life scenarios are essential to substantiate sustainability claims. Transparent collection arrangements and product-specific acceptance studies are equally necessary. Human hair valorization is best pursued through application-specific pilots that verify material performance and net environmental benefit before wider implementation.

Transport electrification can reduce climate impacts, but its environmental performance depends on vehicle production, energy supply, operation, and end-of-life treatment. This study compares battery electric vehicles (BEVs), non-plug-in gasoline hybrid electric vehicles (HEVs), and gasoline internal combustion engine vehicles (ICEVs) using model parameters relevant to Greece. A cradle-to-grave life cycle assessment was implemented in openLCA using ReCiPe 2016 Endpoint (H), with a functional unit of 150,000 vehicle-kilometres. Both electrified configurations exhibited lower impacts than the ICEV across all 18 indicators with positive results. The BEV achieved reductions of 43.2% in global-warming damage to human health, 44.8% in fine particulate matter formation, and 45.1% in terrestrial acidification relative to the ICEV. The HEV achieved reductions of 51.5% and 55.8% in fossil and mineral resource scarcity, respectively. Each electrified technology recorded the lowest value in nine positive indicators. The BEV–HEV ranking-margin analysis identified equal-impact thresholds of 9.05% for global-warming damage to human health and 4.25% for human carcinogenic toxicity. Negative water-consumption indicators were retained without interpretation as physical water savings. The findings identify category-specific trade-offs and support coordinated vehicle-efficiency and electricity-decarbonization measures without establishing overall environmental superiority.

Perovskite solar cells (PSCs) represent a promising alternative to conventional crystalline silicon photovoltaics (Si PV), but their commercialization requires simultaneous consideration of environmental performance, operational lifetime, end-of-life (EoL) management, and technology-development priorities. This study develops an integrated life-cycle and decision-support assessment of PSC and Si PV systems. Life Cycle Assessment (LCA) models were developed in openLCA on a functional basis of 1 m² of PV system, considering production, use, and EoL stages and applying ReCiPe 2016 Endpoint (H) and CML-IA Baseline. The environmental results were further integrated into a multi-criteria decision-support framework using cost-criterion normalization, Simple Additive Weighting, and scenario-based sensitivity analysis. Literature-derived techno-economic parameters provided contextual information rather than a harmonized quantitative techno-economic assessment; the Decision-Support Scores (DSS) were based exclusively on environmental indicators. In the area-based assessment, PSC exhibited substantially lower climate-related impacts than Si PV, with reductions of 57.04% for global warming–human health (ReCiPe) and 57.35% for GWP100a (CML-IA), together with 48.53–53.41% lower fossil-resource-related impacts. However, pronounced trade-offs were identified, including higher stratospheric ozone depletion (+132.50%), mineral resource scarcity (+22.06%), land use (+754.03%), photochemical oxidation (+5747.52%), and terrestrial ecotoxicity (+731.95%). Under equal weighting in the area-based assessment, Si PV achieved higher DSS for both ReCiPe (78.88 vs. 67.33) and CML-IA (67.05 vs. 62.75). The area-based sensitivity analysis showed stable ordering under all ReCiPe scenarios, whereas the CML-IA ordering reversed under climate- and resource-priority scenarios. A parallel electricity-based assessment reduced the PSC climate-related advantages to approximately 18% and yielded higher DSS values for Si PV under all scenarios and both LCIA methods. Although PSCs offer important opportunities associated with lower-energy manufacturing, their sustainable commercialization depends on extending operational lifetime, reducing material- and toxicity-related hotspots, implementing scalable and resource-efficient manufacturing, and developing effective recycling and material-recovery systems. The proposed framework demonstrates how LCA combined with multi-criteria decision support can provide a transparent basis for evaluating environmental trade-offs and guiding the sustainable development of emerging photovoltaic technologies.

Musculoskeletal injuries constitute a critical industrial challenge, yet predictive ergonomic methodologies have remained largely stagnant. Conventional assessments are primarily limited to static, linear snapshots of posture, resulting in a failure to capture the inherently dynamic and chaotic nature of human movement over time. To address this limitation, the present study introduces an innovative approach grounded in nonlinear dynamical systems and robust statistics. The objective was to determine whether information-theoretic and dynamic metrics, specifically Shannon Entropy and the Largest Lyapunov Exponent (LyE), can accurately quantify the structural stability of the cervical spine during a fatigue-inducing isometric protocol. To mitigate the inherent noise of field-derived biomechanical data and prevent algorithmic singularities during phase-space reconstruction, zero-phase Butterworth filtering as well as uniform Gaussian noise injection (Gaussian dither) were systematically applied. The analysis revealed a clear, quantifiable topological shift: as localized muscular fatigue accumulates, the biomechanical system abruptly transitions from a state of stable, organized kinematic flow directly into chaotic instability. Furthermore, these interpretable nonlinear metrics demonstrate high suitability for integration into Explainable Artificial Intelligence (XAI) safety architectures. By transforming complex, stochastic biomechanical data into clear diagnostic biomarkers, this research establishes a foundational framework for proactive, real-time preventive safety measures, thereby advancing the paradigm of Syntropic Bioergonomics.

Perovskite solar cells (PSCs) represent a promising alternative to conventional crystal-line silicon photovoltaics (Si PV), but their commercialization requires simultaneous consideration of environmental performance, operational lifetime, end-of-life (EoL) management, and technology-development priorities. This study develops an inte-grated life-cycle and decision-support assessment of PSC and Si PV systems. Life Cycle Assessment (LCA) models were developed in OpenLCA on a functional basis of 1 m² of PV system, considering production, use, and EoL stages and applying ReCiPe 2016 Midpoint (H) and CML-IA Baseline. The environmental results were further integrated into a multi-criteria decision-support framework using cost-criterion normalization, Simple Additive Weighting, and scenario-based sensitivity analysis. PSC exhibited substantially lower climate-related impacts than Si PV, with reductions of 57.04% for global warming–human health (ReCiPe) and 57.35% for GWP100a (CML-IA), together with 48.53–53.41% lower fossil-resource-related impacts. However, pronounced trade-offs were identified, including higher stratospheric ozone depletion (+132.50%), mineral resource scarcity (+22.06%), land use (+754.03%), photochemical oxidation (+5747.52%), and terrestrial ecotoxicity (+731.95%). Under equal weighting, Si PV achieved higher Decision-Support Scores (DSS) for both ReCiPe (78.88 vs. 67.33) and CML-IA (67.05 vs. 62.75). Sensitivity analysis showed stable ordering under all ReCiPe scenarios, whereas the CML-IA ordering reversed under climate- and resource-priority scenarios, demonstrating the influence of environmental priorities on aggregated technology assessment. Although PSCs offer important opportunities associated with lower-energy manufacturing, their sustainable commercialization depends on extend-ing operational lifetime, reducing material- and toxicity-related hotspots, implement-ing scalable and resource-efficient manufacturing, and developing effective recycling and material-recovery systems. The proposed framework demonstrates how LCA combined with multi-criteria decision support can provide a transparent basis for evaluating environmental trade-offs and guiding the sustainable development of emerging photovoltaic technologies.

The 26 May 2026, Mw 4.5 Jalalpur earthquake, Pakistan, caused considerable damages around its epicentre. Investigations indicated a VII maximum intensity of the Modified Mercalli Intensity (MMI) scale, diminishing rapidly away from the source. Several earthquake-induced ground effects occurred, including liquefaction, temporary groundwater turbidity, differential settlement, tilting of utility poles and numerous landslides within the Quaternary deposits of the Tilla-Jogian Mountains. Observed pronounced North–South (N–S) ground motion was consistent with coseismic deformation within damaged infrastructure. Moment tensor inversion revealed that the earthquake originated at approximately 3 km depth, was characterized by predominant thrust faulting with a minor left-lateral strike-slip component, indicative of a transpressional tectonic regime. This mechanism is associated with a blind thrust beneath the Pabbi-Anticline and is supported by gravity modeling. Coulomb-stress analysis suggested that the Pabbi-Anticline was brought closer to failure after the 2019 Mw 5.8 Mirpur earthquake. However, seismic activation was delayed due to sustained increase in seismicity beginning in 2022. Both 2024 Mw 5.0 Kharian and 2026 Jalalpur earthquakes, occurred within this prolonged period of seismic activity. These observations suggest that stress transfer from the 2019 Mirpur earthquake, combined with progressive strain accumulation and localization along active structures, contributed to increased seismic hazard.

The growing environmental impacts associated with conventional plastics and textiles have intensified interest in bio-based and circular material alternatives. This study presents a qualitative and structured literature review of the valorization of fruit and nut agricultural residues as sustainable feedstocks for biomaterials and biotextiles, with a strategic focus on Greece. Drawing on international literature, regional agricultural production data, and validated processing technologies, the review synthesizes existing evidence on residue availability, conversion routes, environmental performance, and market trends. The reviewed literature indicates that residues such as grape pomace, olive by-products, citrus peels, and nut shells have been widely reported as suitable sources of cellulose, lignin, and pectin for the development of fibers, films, and composite materials. Findings from published life cycle assessment (LCA) studies suggest potential reductions in water use, greenhouse gas emissions, and land-use intensity compared with conventional cotton and synthetic textiles, although results vary depending on system boundaries and processing conditions. The review further highlights enabling factors, technical limitations, and policy considerations relevant to the Greek context. This study provides a qualitative integrative perspective on the opportunities and constraints associated with agricultural residue valorization, identifying key research gaps and strategic directions for future development within Greece and similar Mediterranean regions.