Search Results (1,446)

This study presents a comprehensive investigation into the application of Life Cycle Assessment (LCA) for advanced manufacturing and recycling processes, with a focus on achieving sustainability goals. The environmental and economic impacts of additive manufacturing (AM) and innovative recycling strategies for materials like carbon fiber-reinforced plastics (CFRPs) and 3D printing polymers are analyzed. Experimental efforts detail the preparation of recycled plastic–carbon fiber composite filaments suitable for Fused Filament Fabrication (FFF). The composite exhibits enhanced mechanical, thermal, and flame-resistant properties through optimal blending of plastic waste and carbon fibers. Sustainability assessments using Open LCA 2.2.0 and SolidWorks 2022 demonstrate significant environmental benefits aligned with circular economy principles. The analysis highlights that the weight reduction results in lifetime fuel savings combined with end-of-life credits of −1.32 kg CO₂-eq for composite core versus +0.10 kg CO₂-eq for plastic parts. The recycled composite achieves a net global warming potential of −12.55 kg CO₂-eq, compared to +2.44 kg CO₂-eq for plastic components. The study emphasizes challenges such as recyclability, material degradation, and regional applicability of global LCA models, while proposing pathways for future advancements. Full article

Local path tracking is a critical challenge for autonomous vehicles, requiring precise trajectory following under nonlinear dynamics, strict constraints, and real-time execution. While Nonlinear Model Predictive Control (NMPC) has emerged as a leading approach, many existing methods decouple velocity planning from tracking, lack formal stability guarantees, or do not demonstrate feasibility on embedded platforms. We present a unified NMPC framework that integrates curvature-aware velocity adaptation directly into the cost function. The controller makes use of cubic spline paths, recursive feasibility constraints, and Lyapunov-based terminal costs to ensure stability. The nonlinear optimization problem is implemented in CasADi and solved using IPOPT, with warm-starting and efficient discretization techniques enabling real-time performance. Our approach has been validated in the CARLA simulator across a variety of urban scenarios, including straight roads, intersections, and roundabouts. The controller achieves a mean cross-track error of 0.10 m on straight roads, 0.44 m on roundabouts, and 1.36 m on tight intersections, while maintaining smooth control inputs and bounded actuator effort. A curvature-aware cost term yields a 14.4% reduction in lateral tracking error compared to the curvature-unaware baseline. Benchmarking results indicate that the Raspberry Pi 5 outperforms the NVIDIA Xavier AGX by 1.5–1.6×, achieving mean execution times of 38–45 ms across all scenarios. This demonstrates that advanced NMPC can run in real time on low-cost consumer hardware ($80 vs. $700). Systematic ablation studies reveal the critical role of state weighting (Q) and input regularization (R): removing Q degrades tracking by 10% and destabilizes control effort (+54% acceleration, +477% steering), while omitting R induces oscillatory behavior with +907% acceleration effort. Euler integration provides no computational benefit (+8% solver time) while degrading accuracy by 25%, confirming RK4 as strictly superior. Sensitivity analysis via Latin Hypercube Sampling identifies the prediction horizon (N) and discretization timestep ($\mathrm{\Delta }t$) as dominant parameters. Per-scenario Pareto analysis yields a balanced operating point ($N=15, \mathrm{\Delta }t=0.055$ s) used for all primary evaluations, while a global sweep identifies a robust alternative ($N=12, \mathrm{\Delta }t=0.086$ s) suitable for general deployment tuning. This framework bridges the gap between spline-based local planning and stability-guaranteed NMPC, offering a simulation-validated, real-time solution for embedded autonomous driving research. Future work will focus on hardware-in-the-loop and full-vehicle deployment, integration with high-level decision-making, and learning-enhanced MPC. Full article

Currently, hydrogen is considered a primary option for replacing fossil fuels across various processes, which can reduce greenhouse gas emissions and mitigate global warming. To achieve these goals, hydrogen should be produced using non-polluting processes, such as water electrolysis powered by renewable energy sources. This method requires feeding the converter with an unregulated voltage source. A quadratic step-down converter can be connected between a DC source and a Proton Exchange Membrane (PEM) electrolyzer to produce hydrogen. To mitigate variations in the generated output voltage and intermittent power supply to a PEM electrolyzer, a DC-DC converter is used as an interface. A converter model can be combined with a static or dynamic model of the PEM electrolyzer to yield switched models and, after averaging, linear state-space models. These models can be used to design robust controllers for green hydrogen production, thus significantly reducing greenhouse gas emissions. This work presents experimental and simulation results. Full article

Miniaturised proximity Time-of-Flight (ToF) sensors are attractive for robotics applications due to their low cost, compact size, and low power consumption, which makes them suitable for direct distribution on the robot body. However, both the accuracy and the reliability of their measurements are influenced by operating conditions and target properties. These aspects are not fully investigated in the manufacturer’s datasheet, yet they play a crucial role in downstream robotic tasks. To address this gap, we mounted three VL53L5CX sensors, an Ambient Light Sensor, and a thermistor on a robotic manipulator in a controlled laboratory setup and executed a series of experiments to characterise sensor performance. Specifically, experiments were conducted to quantify sensor drift over time, the influence of ambient illumination under three office lighting conditions, within-frame beam variability, depth accuracy over the 20–800 mm range for different materials, orientation sensitivity at different distances, and an empirical signal-to-noise ratio. The results reveal a transient warm-up effect at startup, after which measurements stabilise, a near-linear range-dependent bias with substantially larger uncertainty for dark targets, limited within-frame variability, and an invalid measurement rate consistently below 10%. Overall, the VL53L5CX provides repeatable measurements, and the findings of this work can be leveraged to derive more faithful sensor models, apply range bias correction, and broaden the range of robotic applications. Full article

The present pilot study explored associations between moral competence, personality structure and perceived parenting experiences. While previous research on moral competence has mainly emphasized educational and cognitive determinants, this work represents a novel psychoanalytically informed investigation of this ability. A sample of 88 young adults aged 18 to 21 completed an online survey including the Moral Competence-Test, OPD-Structure-Questionnaire, and Zurich Brief Questionnaire for the Assessment of Parental Behaviors. Exploratory analyses revealed a positive association between moral competence and overall integration of personality structure. Perceived parenting behaviors showed observable relationships with both constructs: warm and supportive parenting was associated with higher structural integration and greater moral competence, whereas parental control, particularly psychological control, was linked to lower personality structural and moral abilities. An exploratory mediation analysis further suggested that paternal warmth may indirectly affect moral competence via personality structure. This finding aligns with psychoanalytic theory proposing that father–child experiences, conceptualized as triangulation, create a cognitive and emotional space that fosters reflection and the development of moral competence. Overall, these exploratory findings underscore the need for longitudinal research examining the interplay between parenting experiences, personality structure, and moral development. Full article

Despite the significant environmental impact of the healthcare sector, with Germany’s system accounting for a large proportion of national emissions, quantitative sustainability research on specific medical procedures, such as those in dentistry, is critically scarce. This study aimed to address this issue by conducting a Life Cycle Assessment to quantify and compare the Global Warming Potential of the conventional analog and the digital (intraoral scanner) impression techniques for the manufacturing of single-tooth crowns in a German dental practice. The methodology employed a cradle-to-grave approach, defining a positive dental model as the functional unit and focusing on material consumption, waste streams, and equipment usage while excluding patient travel and facility energy. The results revealed that the digital impression procedure offers significant environmental advantages, with its average carbon footprint (approx. 550 CO₂-eq) being nearly threefold lower than the analog impression (approx. 1620 g CO₂-eq). This difference is primarily driven by the analog impression technique’s intensive use of disposable materials and the generation of contaminated waste requiring incineration. In contrast, the digital impression’s burden shifts to the manufacturing of the intraoral scanner, highlighting the importance of high clinical utilization to achieve the ecological benefit. This work concludes that the adoption of digital impression taking is a critical step towards more sustainable dentistry by promoting material avoidance and waste reduction, provided that high equipment utilization rates can be ensured. It should be noted that these results are specific to the regional context, particularly the German energy mix and national waste management standards, and may vary in different geographical settings Full article

Assisted reproductive technologies (ART) use has increased over the past decades. However, reports concerning ART’s low efficiency continue to emerge, citing causes related to lower embryo quality and pregnancy rates compared to their in vivo counterparts. One of the setbacks of ART is oxidative stress, which can impair embryo developmental rates. Mitochondrial redox and energetic homeostasis determine both cell survival and death, so mitochondria are a key target for therapeutic intervention strategies. In the present work, our objective was to improve the quality of viable embryos by adding new mitochondria-targeted antioxidants in the embryo culture media to reduce oxidative stress. Two naturally derived antioxidants synthesized by our team, AntiOxBEN₂ and AntiOxCIN₄, based on hydroxybenzoic and hydroxycinnamic scaffolds, respectively, were studied in two different experimental protocols (here called experiments). The first experiment investigated the effects of the antioxidants on embryo development to determine their optimal concentrations. The first assay of the first experiment focused on the effects of AntiOxCIN₄ at concentrations of 1, 2.5, and 10 μM, while the second assay focused on the effects of AntiOxBEN₂ at the same concentrations. A control group without supplementation was run simultaneously. The second experiment aimed to compare the best concentrations of these antioxidant molecules in the embryo culture media and their effect on embryos’ resistance to vitrification/warming. In each experiment, the embryos were morphologically evaluated, and the total and viable cell numbers were examined. Reactive oxygen species (ROS) and mitochondrial polarization were also evaluated using specific fluorescent dyes. In experiment 1, an increased embryo quality was identified by using 2.5 μM AntiOxCIN₄ (p = 0.03) and 2.5 μM AntiOxBEN₂ (p = 0.001). Moreover, blastocysts supplemented with 2.5 μM AntiOxCIN₄ had higher viability (p = 0.008), while those supplemented with 2.5 μM AntiOxBEN₂ presented a greater total cell number (p = 0.01). An improvement in embryo cryosurvival following the supplementation during the culture process with either antioxidant was identified in experiment 2, with superior expansion scores after vitrification/warming and culture (2.5 μM AntiOxCIN₄, p = 0.056 and 2.5 μM AntiOxBEN₂, p = 0.059). In conclusion, both AntiOxCIN₄ and AntiOxBEN₂ had a beneficial effect on embryo development and cryosurvival, suggesting a potential intervention to reduce oxidative stress in assisted reproductive technologies. Full article

Q-method analysis is used to determine participants’ subjective viewpoints on a given subject. A review of the extant literature revealed a paucity of research examining participants’ viewpoints on environmental awareness within Education for Sustainable Development (ESD) using Q-method analysis. The aim of this study is to uncover teachers’ viewpoints on environmental awareness within ESD using Q method analysis. Accordingly, the study employed Q-method analysis as a mixed research methodology. Issues related to ESD are addressed in primary and secondary school curricula in Türkiye, primarily within the scope of science and social studies courses. The participants in the study consist of science, social studies, and primary school teachers working in the Gaziantep province of Türkiye. The data collection instrument, developed through criterion sampling, was a Q-method form created by the researchers based on insights from the relevant literature and field specialists. Quantitative and qualitative data were analyzed using PQ Method 2.35 statistical software. The findings indicate that participants’ viewpoints on environmental awareness within ESD were grouped into two factors and were predominantly positive (93%), showing consistency across gender and teaching field variables. While all 66 participants in Factor 1 demonstrated wholly positive attitude towards ESD, the 5 participants in Factor 2 exhibited partially positive attitudes. Participants expressed the most positive viewpoints regarding the protection of forests, energy resources, and recycling, whereas the least positive viewpoints were related to the ozone layer, climate change, and the economical use of resources. Based on these findings, it is recommended that teachers’ awareness of issues such as the ozone layer, global warming, and the economical use of resources be enhanced. Full article

The main objective of this work is to characterize Sudden Stratospheric Warming (SSW) conditions and their impact on local weather forecasting and climate change, using SSW definition criteria. The SSWs strongly affect Arctic vortex structure and midlatitude weather conditions. This work evaluates the frequency, amplitude, and dynamical–thermal characteristics of SSWs under historical and Representative Concentration Pathway (RCP) 4.5 scenarios, focusing on stratospheric air temperature (T_s) and zonal wind speed (U_h) at the 10° N and 60° N latitudes. The fifth-generation ECMWF atmospheric reanalysis (ERA5) is employed as the reference dataset. Simulations of five Coupled Model Intercomparison Project Phase 5 (CMIP5) models, represented by M1 to M5, are analyzed. The primary group of models included 1) the Australian Community Climate and Earth-System Simulator, version 1.3 (ACCESS1-3, M1), 2) the Hadley Center Global Environmental Model, version 2—Carbon Cycle (HadGEM2-CC, M2), and 3) the Max Planck Institute Earth System Model—Medium Resolution (MPI-ESM-MR, M3). The analysis period covers SSW events related to the Quasi-Biennial Oscillation (QBO) in the Northern Hemisphere (NH) from 1980 to 2100. The key findings indicate that while M1, M2, and M3 simulate SSW occurrence correctly for the 21st century, they exhibit significant systematic deficiencies in capturing the structural dynamics of SSW events. Specifically, the M1, M2, and M3 models underestimate the polar stratospheric temperature amplitude (T_amp) by approximately 75–80% and zonal wind amplitude (U_amp) by more than 60% compared to the ERA5 analysis. Furthermore, ERA5 exhibits a strong negative correlation (R ≈ −0.8) between U_h and T_s that is not estimated accurately using the present models. The importance of the horizontal resolution of the models and wave–mean flow interactions in determining SSW intensity and occurrence is also found to be a critical metric. Results suggest that SSW definition criteria affect Arctic and midlatitude weather system prediction at a rate of 61–82%. It is concluded that the primary configurations of CMIP5 models for accurately capturing the dynamical structure and evolution of QBO–SSW interactions are needed, and that they affect future projections of SSW events. Full article

The AA7075 holds significant importance in the aerospace field. Understanding its microstructure evolution and constitutive relationships during warm deformation is crucial for optimizing forming processes. To this end, isothermal compression experiments were conducted at different temperatures and strain rates to analyze their flow stress behavior. The microstructure evolution was characterized using electron backscatter diffraction (EBSD) and transmission electron microscopy (TEM). Microstructural analysis confirmed that dynamic recovery constitutes the predominant softening mechanism under warm forming conditions. The results indicate that flow stress is highly sensitive to deformation parameters, decreasing with increasing temperature and rising with increasing strain rate. To accurately describe the flow behavior, two distinct constitutive models were formulated: (1) a phenomenological Hensel–Spittel–Garofalo (HSG) model; (2) a novel hybrid machine-learning model that innovatively integrates the Harris Hawks Optimization (HHO) algorithm with an LSTM model. Both constitutive models demonstrate reasonable predictive accuracy. In comparison, the HHO-LSTM model demonstrated a superior ability to capture complex nonlinear relationships, achieving highly precise predictions of flow stress across the full range of deformation conditions tested in this work. The hybrid machine-learning model proposed in this study provides a highly accurate method for describing and predicting the flow behavior of the AA7075 during warm forming, offering a powerful predictive tool for engineering applications. Full article

Carbon dioxide (CO₂) and methane (CH₄) are major greenhouse gases, and their increasing emissions contribute significantly to global warming. Dry reforming of methane (DRM) offers a promising route to mitigate these emissions by simultaneously utilizing both CO₂ and CH₄ and converting them into syngas, a valuable intermediate for producing fuels and chemicals. Nickel-based catalysts are widely used in DRM due to their high activity and cost-effectiveness. However, their performance depends strongly on metal loading and support properties. This study aims to investigate the effect of different NiO loadings (40, 50, and 60 wt%) on the structural and morphological characteristics of NiO-YSZ and NiO-SDC catalysts synthesized via the impregnation method. In this method, yttria-stabilized zirconia (YSZ) and samarium-doped ceria (SDC) powders were dispersed into a nickel precursor solution to form supported catalysts, which were then characterized to evaluate their structural integrity, crystallinity, and surface morphology. The results showed that higher NiO loadings generally improved the structural and morphological features, with NiO-SDC demonstrating better characteristics than NiO-YSZ. These findings provide essential insights that will guide future work on fabricating membranes using these catalysts for the CO₂-CH₄ dry reforming process. Full article

Greenhouse gases (GHG), accumulated in the atmosphere, are the main cause of climate change. In 2017, the increase in average temperature was about 1 °C (between 0.8 °C–1.2 °C) above pre-industrial levels. Global warming refers to the increase in air surface, sea surface, and soil surface temperature and according to IPCC (Intergovernmental Panel Climate Change), since the industrial revolution, C emissions are due to land use changes like deforestation, biomass burning, conversion of natural lands, drainage of wetlands, soil cultivation, and tillage. As the world population has increased, world food production has risen too with a subsequent increase in GHG emissions and agricultural production, which is worsened by climate change. Negative consequences are well known such as the loss in water availability and in soil fertility, and pest infestations which are climate change’s effects on agriculture activity. Climate change’s main aftermath is the frequency of extreme weather events influencing crop yields. As climate change exacerbates degradation processes, land management can mitigate its impact and aid adaptation strategies for climate change. About 21–37% of GHGs have been caused by the agriculture activity, so the application of Nature-based Solutions (NbS) like sustainable agriculture could be a way to reduce GHGs worldwide. The aim of this article is to review how NbS may mitigate GHG emissions from soil, with solutions defined as an integrated approach to tackle climate change and to sustainably restore and manage ecosystems, delivering multiple benefits. NbS is a low-cost tool working within and with nature, which holds many benefits for people and the environment. Full article

Global warming (GW) contributions from feedbacks and feedback loops are projected to rise from ≈54% (loops: 29%) in 2024 to ≈71% (loops: 50%) under faltering RCP pathways without Solar Geoengineering (SG) by about 2100. A critical threshold, RCP_Critical, defined as the point at which feedback loops account for more than half of GW, is projected to occur between 2075 and 2125. Beyond this point, reversing warming becomes severely constrained, and climate tipping points become more likely. From these trends, an average mitigation difficulty and cost increase rate (MDCR) of ≈1.33–1.5% per year is estimated. By 2100, absent mitigation, the effort required to offset global warming would roughly double relative to today, approaching an unsustainable mitigation critical threshold. Current feedback levels may already be driving nonlinear warming behavior. These diagnostic estimates align with three key indicators: a minimum-feedback baseline from 1870, an equilibrium climate sensitivity (ECS) range of 3.1 °C–4.3 °C (potentially reached by ≈2082), and consistency with IPCC AR6 confidence bounds. In response, this study proposes Annual Solar Geoengineering-PLUS pathways (ASG+Ps) as supplemental measures. These include Earth Brightening, targeted Arctic Stratospheric Aerosol Injection (SAI), and feasible L1 Space Sunshade systems designed to reduce feedback amplification and extend mitigation timelines. The “PLUS” component refers to the use of increased mitigation levels with a focus on high-amplification regions, particularly the Arctic and the tropics, to help reverse local feedbacks and promote negative feedback loops. These moderate ASG+P pathways directly address AR6 concerns while avoiding many governance challenges of full-scale SG. ASG+Ps are less controversial and provide ≈14× stronger cooling potential per Wm⁻² than Carbon Dioxide Removal (CDR), while allowing variable regional targeting. Meanwhile, RCP2.6 has already been missed, placing RCP4.5 and RCP6 at risk. In 2024, atmospheric CO₂ rose by ≈23 Gt (≈3 ppm), while forest tree losses exceeded afforestation gains by 2×, yielding a 2 GtCO₂ sink loss, further diminishing CDR’s effectiveness. Declines in planetary albedo since 1998 continue to amplify warming. Urbanization accounts for roughly 13% of total surface GW, affecting 60% of the population, underscoring the mitigation potential of urban Earth Brightening. New results here also show major Space Sunshading area reductions, at ≈32× less than prior flawed estimates (detailed here) and ≈1600× less under the ASG+P method, substantially improving feasibility and the importance of space agencies’ needed mitigation role. A coordinated global ASG+P strategy, supported by IPCC working groups and space agencies like NASA/SpaceX, are needed to provide a critical supplemental pathway for climate stabilization. Given the shrinking intervention window, rising MDCR, and the escalating risks to civilization, prioritizing timely work in this area is essential; the investment is minor compared to the trillions in climate financial damages that could be avoided. Full article

Mission-oriented supply chains involve multi-phase tasks, strong resource interdependencies, and stringent reliability requirements, which make demand planning complex and uncertain. This study develops a structured demand modeling framework to support multi-phase mission-oriented supply chains under budget and reliability constraints by integrating digital twin technology with an adaptive inertia weight particle swarm optimization (AIW-PSO) algorithm. The supply support process is decomposed into four sequential phases—storage, transportation, preparation, and execution—and phase-specific demand models are constructed based on system reliability theory, explicitly incorporating redundancy, maintainability, and repairability. In this work, digital twin technology functions as a data acquisition and virtual experimentation layer that supports parameter calibration, state-aware scenario simulation, and event-triggered re-optimization rather than continuous real-time control. Physical-state updates are mapped to model parameters such as phase durations, failure rates, repair rates, and instantaneous availability, after which the integrated optimization model is re-solved using a warm-start strategy to generate updated demand plans. The resulting multi-phase demand optimization problem is solved using AIW-PSO to enhance global search performance and mitigate premature convergence. The proposed method is validated using a representative mission-oriented supply support scenario with operational and simulated data. Simulation results demonstrate that, under identical budget constraints, the proposed approach achieves higher mission completion capability than conventional PSO-based methods, providing effective and practical decision support for multi-phase mission-oriented supply chain planning. Full article

Citrus canker, caused by bacterium Xanthomonas citri subsp. citri (Xcc), affects the citrus industry by making the fruit unmarketable due to unsightly lesions on the fruit. Citrus canker caused by a relatively new A^Wstrain of Xcc was reported on the citrus trees in the residential areas of the Lower Rio Grande Valley (LRGV) of South Texas. Xcc A^W has a limited host range, predominantly affecting limes and a few other citrus species. Previous work has reported prevailing environmental conditions that influence the incidence and spread of the citrus canker caused by the Asiatic A strain. However, no information is available on the environmental factors impacting the incidence of canker caused by A^W strain. In this study, monthly data on temperature, humidity, rainfall, and wind speed were grouped into biologically meaningful categories, and corresponding disease incidence was examined descriptively. Disease incidence was highest under high temperatures, humid conditions, and particularly during periods of rainfall and high wind speeds, which likely facilitated bacterial dispersal. These observed patterns indicate that warm, humid, rainy conditions, and stronger winds are associated with increased citrus canker incidence in the LRGV. This study provides insights into environmental conditions conducive to disease incidence and may serve as a foundation for developing explanatory and predictive models leading to management strategies for protecting citrus production in South Texas. Full article