Search Results (1,100)

To resolve the inherent coupling conflict between trajectory tracking and lateral stability in distributed electric drive buses, this paper proposes a hierarchical cooperative control framework. A simplified two-degree-of-freedom (2-DOF) vehicle model is first established, and kinematically derived reference states for stable motion are computed. At the upper level, a model predictive controller (MPC) generates real-time steering commands while explicitly minimizing lateral tracking error. At the lower level, a proportional integral derivative (PID)-based roll moment controller and a linear quadratic regulator (LQR)-based direct yaw moment controller are designed, with four-wheel torque distribution achieved via quadratic programming subject to friction circle and vertical load constraints. Co-simulation results using TruckSim and MATLAB/Simulink demonstrate that, during high-speed single-lane-change maneuvers, peak lateral error is reduced by 11.59–18.09%, and root-mean-square (RMS) error by 8.67–14.77%. Under medium-speed double-lane-change conditions, corresponding reductions of 3.85–12.16% and 4.48–11.33% are achieved, respectively. These results fully validate the effectiveness of the proposed strategy. Compared with the existing MPC–direct yaw moment control (DYC) decoupled control framework, the coordinated control strategy proposed in this paper achieves the optimal trade-off between trajectory tracking and lateral stability while maintaining the quadratic programming solution delay below 0.5 milliseconds. Full article

The transportation sector plays a pivotal role in economic development but is also a major contributor to environmental degradation due to its reliance on fossil fuels. This study explores the relationship between transport-related CO₂ emissions, economic growth, road and rail freight transport, industry, trade openness, fossil fuel consumption, financial development, and renewable energy in ten landlocked countries from 1990 to 2022. Using panel cointegration tests and PMG-ARDL techniques, the findings reveal a bidirectional causality between CO₂ emissions, road freight, financial development, and industry. Road freight transport significantly boosts economic growth but also intensifies emissions, while renewable energy effectively mitigates transport-related CO₂. The results emphasize the need for policymakers to balance economic advancement with sustainable energy and emission reduction strategies. Achieving economic-energy sustainability is essential for fostering a green and clean environment without compromising growth. Full article

Non-food geographical indications (GIs) are emerging as strategic policy instruments in the European Union after Regulation (EU) 2023/2411 extended protection to craft and industrial products. While the literature on agri-food GIs is extensive, empirical and comparative evidence on non-food GIs remains scarce and fragmented. This study addresses this gap by constructing a harmonised dataset, combining 132 registered and 380 potential non-food GIs identified by EUIPO (512 in total across the EU). Using secondary institutional data, descriptive and comparative statistics, and a hierarchical clustering (Ward, squared Euclidean distance) on normalised indicators total GIs, GIs per million inhabitants (GI/POP), and GIs per € billion of GDP (GI/GDP), the analysis identifies three country typologies differing by scale and intensity. Results reveal a strong geographical concentration in Southern Europe but also unexpectedly high intensity in smaller or mid-sized economies such as Portugal, Cyprus, and Slovenia. A forward-looking scenario analysis based on Cost of Non-Europe (CoNE) estimates suggests that the full implementation of the new Regulation could generate 284,000–338,000 new jobs and € 37–50 billion in additional intra-EU trade. The study contributes to EU policy debates by introducing comparative indicators (GI/POP, GI/GDP) as monitoring tools for evidence-based policymaking and by highlighting the role of non-food GIs as hybrid institutions connecting industrial competitiveness, cultural identity, and sustainability transitions. Full article

The flaring of associated gas in oil and gas operations contributes significantly to greenhouse gas emissions and represents a loss of valuable hydrocarbon resources. While amine absorption is widely applied for acid gas removal, the use of supercritical carbon dioxide (sc-CO₂) for flare gas treatment remains largely unexplored, despite its proven selectivity for hydrocarbons in other industries such as natural product extraction and polymer processing. Conventional flare gas treatment methods face trade-offs: amine absorption achieves high acid gas removal efficiency but offers limited selectivity for heavier hydrocarbons, whereas sc-CO₂ extraction enables efficient recovery of higher hydrocarbons but does not fully remove acid gases. This study addresses these gaps by evaluating three two-stage flare gas treatment configurations—dual-stage amine absorption, dual-stage sc-CO₂ absorption, and a hybrid of sc-CO₂ followed by amine absorption—using Aspen HYSYS V12.1 simulations, with recycling processes considered in each case. The dual-stage sc-CO₂ process achieved nearly complete hydrocarbon recovery (100%) and complete H₂S removal, but CO₂ remained at elevated concentrations in the treated gas. The dual-stage amine process completely removed CO₂ and H₂S, though with higher energy demand for solvent regeneration. The hybrid configuration combined the advantages of both approaches, achieving complete H₂S removal, 100% hexane recovery, 95.02% methane recovery, and a drastic reduction in CO₂ concentration (to 0.0012 mole fraction). These results demonstrate that integrating sc-CO₂ with amine absorption resolves the trade-off between hydrocarbon selectivity and acid gas removal, establishing a technically viable pathway for flare gas utilization with potential application in gas-to-liquids (GTL) and carbon management strategies Full article

Mealybugs are high-priority quarantine pests in fresh-produce trade due to cryptic habits, broad host ranges, and market-access risks. Phytosanitary irradiation (PI) provides a non-residual, process-controlled option that is increasingly integrated with modified-atmosphere (MA/MAP) logistics. Because molecular oxygen enhances indirect radiation damage (oxygen enhancement ratio, OER), oxygen limitation may modulate PI outcomes in mealybugs. The Jack Beardsley mealybug (Pseudococcus jackbeardsleyi) has an IPPC-adopted PI treatment of 166 Gy (ISPM 28, PT 45). We exposed adult females to 166 Gy under air and 1% O₂ and generated whole-transcriptome profiles across treatments. Differentially expressed genes and co-differentially expressed genes (co-DEGs) were integrated with protein–protein interaction (PPI) and regulatory networks, and ten hubs were validated by reverse transcription quantitative PCR (RT-qPCR). Hypoxia attenuated irradiation-induced transcriptional disruption. Expression programs shifted toward transport, redox buffering, and immune readiness, while morphogen signaling (Wnt, Hedgehog, BMP) was coherently suppressed; hubs including wg, hh, dpp, and ptc showed stronger down-regulation under hypoxia + irradiation than under irradiation alone. Despite these molecular differences, confirmatory bioassays at 166 Gy under both atmospheres (air and 1% O₂) achieved complete control. These results clarify how oxygen limitation modulates PI responses in a quarantine mealybug while confirming the operational efficacy of the prescribed 166 Gy dose. Practically, they support the current international standard and highlight the value of documenting oxygen atmospheres and managing dose margins when PI is applied within MA/MAP supply chains. Full article

This study presents a comparative investigation of combustion and emission characteristics in a two-stroke MAN 5S35ME-B9.5 marine diesel engine equipped with a Controllable Pitch Propeller and an Exhaust Gas Recirculation system. Experimental data were obtained from both factory shop tests conducted under the IMO NOx Technical Code 2008 E2 cycle and sea trials performed onboard the T/S Baek-Kyung. Engine performance was evaluated under Tier II-FB, ecoEGR, and Tier III modes, focusing on specific fuel oil consumption, peak cylinder pressure, exhaust gas temperature, and regulated emissions. Results indicate that Tier III achieved the greatest NOx abatement, reducing emissions by up to 76.4% (1464 to 346 ppm), but with penalties of 16.8% higher SFOC and 45.2% higher CO₂ concentration. EcoEGR provided a more favorable compromise, reducing NOx by 52.3% while limiting SFOC increases to ≤15.4% and CO₂ increases to ≤30.9%. Strong correlations were observed between NOx, Pmax, and exhaust gas temperature, reaffirming fundamental trade-offs, while O₂ and CO correlations showed greater variability under sea operation. Despite operational scatter, sea trial results reproduced the key patterns observed in shop tests, confirming robustness across conditions. Overall, this correlation-based analysis provides quantified evidence of performance–emission trade-offs and offers a practical foundation for optimizing CPP-equipped two-stroke engines under varying EGR strategies. Full article

Oxidative reactions accelerate quality loss in emulsified meats. This study evaluated a clean-label strategy in goat meat pates by co-fortifying Portulaca oleracea powder 1% and honey 4%. Control and treatment batches were cooked to 72 °C and stored as opened packs at ≤6 °C for 10 days. Oxidative stability of lipid and protein was monitored by peroxide value (PV), TBARS, acid value, and baseline protein carbonyls; total antioxidant capacity was assessed by FRAP and DPPH; color was quantified in CIE Lab; fatty acids were profiled by GC-FID; and protein integrity was examined by SDS-PAGE. The treatment modestly increased α-linolenic acid (ALA) (1.2% vs. 0.8%) in the control and markedly enhanced antioxidant status (FRAP 10.5 ± 0.04 mg GAE/g vs. not detected; DPPH 33.02 ± 0.009% vs. 22.33 ± 0.007%; IC₅₀ 106.10 ± 10.01 vs. 138.25 ± 11.15 µg/mL). Across storage, PV showed a small, non-significant delay on day 10 (13.0 ± 0.9 vs. 14.0 ± 0.9 meq/kg), while secondary and hydrolytic indices were consistently lower (TBARS day 10: 1.91 ± 0.13 vs. 3.29 ± 0.23 mg MDA/kg; acid value day 10: 7.0 ± 0.5 vs. 8.5 ± 0.6 mg KOH/g). Protein carbonyls at baseline were comparable (99.19 vs. 95.73 nmol/mg). L* and b* remained similar before and after light exposure, with a modest, non-significant reduction in color stability and greater a* loss in the treatment. These results show that purslane–honey co-fortification nutritionally enriches pates and attenuates oxidative spoilage during refrigerated storage, with minor color trade-offs that merit process optimization. Full article

This study evaluates the techno-economic feasibility of integrating wind power with hydrogen-based storage to decarbonize the Raglan Mine in northern Canada. Using HOMER simulations with real 2021 operational data, six progressive scenarios were modeled, ranging from partial substitution of diesel generators to complete site-wide electrification, including heating, transport, and mining equipment. Results show that complete decarbonization (Scenario 6) is technically achievable and could avoid up to 143,000 tCO₂eq annually (~2.15 Mt over 15 years), but remains economically prohibitive under current technology costs. In contrast, Scenario 2 Case 2, which combines solid oxide fuel cells with thermal charge controllers, emerges as the most viable near-term pathway, avoiding ~61,000 tCO₂eq annually (~0.91 Mt over 15 years) while achieving improved return on investment. A qualitative multi-criteria framework highlights this configuration as the best trade-off between technical feasibility, environmental performance, and economic viability. At the same time, complete decarbonization remains a longer-term target contingent on cost reductions and policy support. Overall, the findings provide clear evidence that hydrogen storage, when coupled with wind power, can deliver substantial and measurable decarbonization benefits for Arctic mining operations. Full article

Hydrogen is increasingly recognized as a clean energy vector and storage medium, yet its viability and strategic role in the Western Balkans remain underexplored. This study provides the first comprehensive techno-economic, environmental, and strategic evaluation of hydrogen production pathways in Albania. Results show clear trade-offs across options. The levelized cost of hydrogen (LCOH) is estimated at 8.76 €/kg H₂ for grid-connected, 7.75 €/kg H₂ for solar, and 7.66 €/kg H₂ for wind electrolysis—values above EU averages and reliant on lower electricity costs and efficiency gains. In contrast, fossil-based hydrogen via steam methane reforming (SMR) is cheaper at 3.45 €/kg H₂, rising to 4.74 €/kg H₂ with carbon capture and storage (CCS). Environmentally, Life Cycle Assessment (LCA) results show much lower Global Warming Potential (<1 kg CO₂-eq/kg H₂) for renewables compared with ~10.39 kg CO₂-eq/kg H₂ for SMR, reduced to 3.19 kg CO₂-eq/kg H₂ with CCS. However, grid electrolysis dominated by hydropower entails high water-scarcity impacts, highlighting resource trade-offs. Strategically, Albania’s growing solar and wind projects (electricity prices of 24.89–44.88 €/MWh), coupled with existing gas infrastructure and EU integration, provide strong potential. While regulatory gaps and limited expertise remain challenges, competition from solar-plus-storage, regional rivals, and dependence on external financing pose additional risks. In the near term, a transitional phase using SMR + CCS could leverage Albania’s gas assets to scale hydrogen production while renewables mature. Overall, Albania’s hydrogen future hinges on targeted investments, supportive policies, and capacity building aligned with EU Green Deal objectives, with solar-powered electrolysis offering the potential to deliver environmentally sustainable green hydrogen at costs below 5.7 €/kg H₂. Full article

Biomass gasification, a key waste-to-energy technology, is a complex thermochemical process with many input variables influencing the yield and quality of syngas. In this study, data-driven machine learning models are developed to capture the nonlinear relationships between feedstock properties, operating conditions, and syngas composition, in order to optimize process performance. Random Forest (RF), CatBoost (Categorical Boosting), and an Artificial Neural Network (ANN) were trained to predict key syngas outputs (syngas composition and syngas yield) from process inputs. The best-performing model (ANN) was then integrated into a multi-objective optimization framework using the open-source Optimization & Machine Learning Toolkit (OMLT) in Pyomo. An optimization problem was formulated with two objectives—maximizing the hydrogen-to-carbon monoxide (H₂/CO) ratio and maximizing the syngas yield simultaneously, subject to operational constraints. The trade-off between these competing objectives was resolved by generating a Pareto frontier, which identifies optimal operating points for different priority weightings of syngas quality vs. quantity. To interpret the ML models and validate domain knowledge, SHapley Additive exPlanations (SHAP) were applied, revealing that parameters such as equivalence ratio, steam-to-biomass ratio, feedstock lower heating value, and fixed carbon content significantly influence syngas outputs. Our results highlight a clear trade-off between maximizing hydrogen content and total gas yield and pinpoint optimal conditions for balancing this trade-off. This integrated approach, combining advanced ML predictions, explainability, and rigorous multi-objective optimization, is novel for biomass gasification and provides actionable insights to improve syngas production efficiency, demonstrating the value of data-driven optimization in sustainable waste-to-energy conversion processes. Full article

This work extends our previous research on spectral clustering for mitigating nonlinear phase noise in optical communication systems by presenting the first complete FPGA implementation of the algorithm, including on-chip eigenvector computation with parallelization strategies. The implementation addresses the computational complexity challenges of spectral clustering through a heterogeneous CPU/FPGA co-design approach that partitions algorithmic stages between ARM processors and the FPGA fabric. While the achieved processing speeds of approximately 36 symbols per second do not yet meet the requirements for commercial optical transceivers, our hardware prototype demonstrates the feasibility and practical challenges of deploying advanced clustering algorithms on real-time hardware architectures. We detail the parallel Jacobi method for eigenvector computation, the Greedy K-means++ initialization strategy, and the comprehensive hardware mapping of all clustering stages. The system processes streaming m-QAM data through a windowed architecture and integrates a demapper to ensure label consistency, demonstrating improved bit error rate performance compared to K-means under severe phase noise conditions of −90 dBc/Hz at a 1 MHz offset. This implementation offers valuable insights into memory bandwidth limitations and resource utilization trade-offs, underscoring the crucial role of FPGAs as a bridge between algorithm development and high-speed optical system deployment. Full article

Lipid nanoparticles are a clinically validated platform for delivering nucleic acids, but performance is constrained by multiscale physiological barriers spanning circulation, vascular interfaces, extracellular matrices, cellular uptake, and intracellular trafficking. This review links composition–structure–function relationships for ionizable lipids, helper phospholipids, cholesterol, and PEG-lipids to systemic fate, endothelial access, endosomal escape, cytoplasmic stability, and nuclear transport. We outline strategies for tissue and cell targeting, including hepatocyte ligands, immune and tumor selectivity, and selective organ targeting through compositional tuning, together with approaches that modulate escape using pH-responsive chemistries or fusion-active peptides and polymers. We further examine immunomodulatory co-formulation, route and schedule effects on biodistribution and immune programming, and manufacturing and stability levers from microfluidic mixing to lyophilization. Across these themes, we weigh trade-offs between stealth and engagement, potency and tolerability, and potency and manufacturability, noting that only a small fraction of endosomes supports productive release and that protein corona variability and repeat dosing can reshape tropism and clearance. Convergence of standardized assays for true cytosolic delivery, biomarker-guided patient selection, and robust process controls will be required to extend LNP therapeutics beyond the liver while sustaining safety, access, and scale. Full article

Solid oxide electrolysis cells (SOECs) have emerged as a promising technology for efficient energy storage and CO₂ utilization via H₂O–CO₂ co-electrolysis. While most previous studies focused on planar or tubular configurations, this work investigated a novel flat, tubular SOEC design using a comprehensive 3D multi-physics model developed in COMSOL Multiphysics 5.6. This model integrates charge transfer, gas flow, heat transfer, chemical/electrochemical reactions, and structural mechanics to analyze operational behavior and thermo-mechanical stress under different voltages and pressures. Simulation results indicate that increasing operating voltage leads to significant temperature and current density inhomogeneity. Furthermore, elevated pressure improves electrochemical performance, possibly due to increased reactant concentrations and reduced mass transfer limitations; however, it also increases temperature gradients and the maximum first principal stress. These findings underscore that the design and optimization of flat tubular SOECs in H₂O–CO₂ co-electrolysis should take the trade-off between performance and durability into consideration. Full article

This study focuses on optimizing the composting process through advanced multiobjective optimization techniques, aiming to minimize both operational costs and CO₂ emissions by efficiently allocating tasks to specialized machinery. It introduces three novel multiobjective models that uniquely integrate cost minimization, CO₂ emission reduction, and maximized waste processing, addressing a critical gap in sustainable composting. The first model prioritizes cost reduction, providing a foundational framework for optimizing resource allocation. Building on this, the second model integrates environmental considerations, balancing cost minimization with the reduction of CO₂ emissions to achieve a sustainable trade-off. The third model takes a broader approach by maximizing the volume of organic waste processed within a workday while simultaneously minimizing emissions. These models incorporate real-world constraints, such as machinery capacity, operational work hours, and required rest periods for compost piles. The findings underscore the potential of multiobjective optimization to tackle complex industrial challenges. This research offers a practical and sustainable solution that harmonizes economic efficiency with environmental stewardship, demonstrating its applicability to processes as intricate as composting. Full article

Achieving selective, direct conversion of methane into value-added chemicals requires catalysts that can navigate the intrinsic trade-off between C–H bond activation and over-dehydrogenation. Transition metal phosphides (TMPs) have emerged as promising catalysts that can tune this selectivity. This work utilizes density functional theory (DFT) to systematically assess how the transition metal’s identity (M = Fe, Co, Ni) in isostructural M₂P phosphides governs this balance. The findings reveal that the high reactivity of Fe₂P and Co₂P, which facilitates initial methane activation, also promotes facile deep dehydrogenation pathways to coke precursors like CH*. In stark contrast, Ni₂P exhibits a moderated reactivity that kinetically hinders CH* formation while simultaneously exhibiting the lowest activation barrier for the C–C coupling of CH₂* intermediates to form ethylene. This revealed trade-off between the high reactivity of Fe/Co phosphides and the high selectivity of Ni₂P offers a guiding principle for the rational design of advanced bimetallic phosphides for efficient methane upgrading. Full article