Bimetallic CexVy-TiO2 and monometallic Zrx-TiO2 catalysts were systematically evaluated for the hydrogenation of furfural (FF) to furfuryl alcohol (FA). Notably, a FF conversion of 95% with 81% yield toward FA was achieved under optimized conditions. Reaction temperature and hydrogen pressure acted as key parameters governing product distribution, enabling tunable selectivity. In particular, enhanced H2 dissociation and activation occurred over the Ce and V oxide sites at elevated temperatures, which promoted hydrogenation while effectively suppressing the competing acetalization pathway. The performance of Ce4V1-TiO2 is attributed to its spherical nanoparticle morphology, an optimal Br empty set nsted-to-Lewis acid site ratio (0.06), high H2 uptake (230.34 mu mol g-1), substantial O2 consumption (71.24 mu mol g-1), and the presence of variable oxidation states of Ce and V that facilitate redox synergy. Density functional theory (DFT) calculations and H2-TPD revealed a synergistic catalytic effect between Ce and V on hydrogen adsorption and activation. Notably, V demonstrated stronger hydrogen adsorption and dissociation capacity compared to Ce. In addition, the adsorption of FF occurs more readily on the Ce2O3 (002) surface, while H2 dissociates more easily on the V2O5 (310) surface. Furthermore, the adsorption of dissociated hydrogen atoms is thermically more stable on Ce2O3 (002), indicating a cooperative mechanism where V sites primarily facilitated H2 activation, and Ce sites chiefly stabilized the reaction intermediates. Overall, the Ce-V-TiO2 catalytic system exhibits tunable reaction pathways and high catalytic activity, providing an efficient and sustainable strategy for biomass valorization toward value-added chemicals and renewable fuels in the context of green chemistry.
The distributed flow shop scheduling problem with limited waiting time constraints and multiple identical orders per job is a computationally challenging variant prevalent in modern multi-factory production systems. This study addresses this problem with the objective of minimizing the makespan. First, a position-based mixed integer linear programming (MILP) formulation is developed and solved using CPLEX to obtain exact solutions for small-scale instances. Subsequently, a new Q-learning-based metaheuristic with population diversity balance (QLM-PDB) is proposed. The main innovations of QLM-PDB include: (i) introducing a Q-learning mechanism that adaptively selects the destruction size (25%, 50%, or 75% of the critical factory’s sequence length), thereby enabling autonomous adjustment of perturbation intensity; (ii) proposing a novel diversity metric, termed total population dissimilarity (TPD), to quantify the distribution of solutions in the search space; (iii) designing a TPD-triggered perturbation and population restart strategy to actively prevent premature convergence; and (iv) integrating path relinking (PR) and variable neighborhood search (VNS) to further enhance solution quality. The proposed algorithm is validated on 150 benchmark instances of varying scales (up to 100 jobs and 20 machines) and factory configurations (2, 4, and 6 factories). Experimental results demonstrate that QLM-PDB achieves strong overall performance, significantly outperforming the compared metaheuristics on small- and medium-scale instances, while maintaining competitive results on large-scale instances given sufficient runtime.
This review compares trichome and trichome-derived epidermal appendage development across model glycophytes and halophytes, revealing that conserved regulatory modules are independently rewired into lineage specific circuits to produce diverse epidermal structures. In halophytes, salt glands and epidermal bladder cells further integrate these developmental programs with ion transport and stress physiology, offering entry points for engineering crop stress resilience. Trichome-derived epidermal structures have arisen repeatedly across angiosperms, yet the mechanisms by which conserved epidermal regulators are redeployed into lineage-specific developmental circuits remain incompletely understood. Here, we present a comparative synthesis of trichome and trichome-derived epidermal appendage development across representative glycophytes (Arabidopsis thaliana, Oryza sativa, Solanum lycopersicum, and Gossypium hirsutum) and extend this framework to halophytic species with specialized salt-handling structures. These systems reveal how MYB-bHLH-WD40, WOX-AP2/ERF-auxin, HD-ZIP IV-bHLH-JA, and expanded MYB/HD-ZIP networks have been independently rewired to produce unicellular hairs, secretory glands, and highly elongated fibers. In halophytes, these developmental modules are further integrated with ion transport, vesicle trafficking, and osmotic regulation pathways, enabling the emergence of salt glands and epidermal bladder cells with specialized physiological functions. By synthesizing these trajectories, we propose a unifying regulatory model for epidermal evolution. We additionally highlight potential entry points for engineering trichome traits, improved metabolite production, and synthetic salt-handling epidermal structures for crop stress resilience.
Large Language Models (LLMs) are increasingly used across many scientific domains, but their role in fisheries management research remains poorly defined. Here we provide an evidence-based overview of how LLMs might be used, and what risks they introduce, in fisheries management research. First, we review documented and emerging applications of LLMs across four main research tasks in fisheries science: literature review and knowledge synthesis, data collection and processing, developing and evaluating models, and science communication and stakeholder engagement. We then draw on selected examples from ecology, environmental science, and oceanography to identify potentially transferable applications and research gaps relevant to fisheries. Viewed in this cross-disciplinary context, fisheries have already begun to apply LLMs in data focused tasks, whereas applications for modeling support and stakeholder communication are still mostly at a conceptual stage. Second, we synthesize technical, operational, legal and compliance, and ethical and societal risks that are particularly relevant to fisheries, and outline practical options for mitigation. Based on this analysis, we propose a six-step, risk-aware workflow for incorporating LLMs into fisheries research and advisory processes as supporting tools rather than as autonomous decision makers. Our aim is to help fisheries scientists, managers and policymakers explore LLMs in a cautious and transparent way, so that the benefits to sustainable fisheries management are realized without undermining scientific integrity or trust.
The spectroscopy of the 3++ light-meson candidates, in particular the a3 and f3 families, remains an open issue. We compute the mass spectra in the modified Godfrey-Isgur model and evaluate the Okubo-Zweig-Iizuka-allowed two-body strong decays within the quark-pair-creation model. Our analysis favors the interpretation that a3(1875) and a3(2030) correspond to the same resonance, identified as the a3 ground state, while f3(2050) is the ground state of the f3 family; furthermore, a3(2275) and f3(2300) are assigned as their first radial excited states. For other higher-excitation states, we provide predictions for the decay behaviors and include the mass-induced model uncertainty.
