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Changes in learning strategies contribute to negative reactivity of immediate judgments of learning
No full textThere is evidence that asking people to predict their own memory performance during learning (immediate judgments of learning, JOLs) can alter memory. Changes in the use of learning strategies have been proposed to contribute to these reactive effects of JOLs. This study addresses the impact of making JOLs on the use of learning strategies and the contribution of learning strategies to JOL reactivity. Across six experiments, participants studied related and unrelated word pairs and did or did not make JOLs during study, completed a cued-recall test, and reported the learning strategies they had used for each word pair. When we manipulated the requirement to make JOLs between participants, making JOLs enhanced memory for related pairs and impaired memory for unrelated pairs. Further, the learning strategies participants used differed across the JOL and no-JOL groups, and these differences mediated the detrimental effects of making JOLs on memory for unrelated pairs. In contrast, when we manipulated the requirement to make JOLs within participants, making JOLs enhanced recall performance for related pairs but did not impact recall for unrelated pairs or the use of learning strategies. Overall, our findings indicate that changes in the use of learning strategies underlie detrimental effects of making JOL on memory for unrelated pairs but only play a minor role in positive effects of making JOLs for related word pairs
Leveraging Digital Trace Data in Teaching to Improve Students’ Technology Use and Well-Being
No full textRecovery of forest structural complexity during secondary succession in a human‐modified neotropical landscape
No full textForest structural complexity is an essential determinant of forest ecosystem functions and biodiversity. The natural dynamics of structural complexity of tropical forests remain largely unexplored, especially for naturally regenerating forests during secondary succession. Better understanding the trajectories of forest structural complexity recovery is crucial to inform the development of forest landscape restoration strategies and to predict the reassembly of ecological networks during secondary succession.
Here, we investigate the recovery of forest structural complexity during secondary succession following land use abandonment in a human‐modified landscape in Ecuador. We employ a terrestrial laser scanning‐based index of forest structural complexity to quantify the three‐dimensional vegetation structure of agricultural lands (cacao plantations and pastures, n = 10), naturally regenerating sites ( n = 30) and primary old‐growth forests ( n = 16) along a chrono‐sequence of secondary succession.
We find that sites recovering after land use abandonment attain levels of forest structural complexity comparable to old‐growth forest within 40 years. Changes in forest structural complexity along the successional gradient follow a saturating pattern, with rapid increases in the first years and only minor potential for further increases after 40 years. Increasing tree species diversity during secondary succession is identified as a major driver of the recovery of forest structural complexity. Using a structural equation modelling approach, we find that the effects of tree species diversity on forest structural complexity are mediated by its effects on vertical stratification, as the effective number of canopy layers increases with increasing recovery age.
Our results suggest that land use abandonment and subsequent natural regeneration facilitate the restoration of forest structural complexity in human‐modified neotropical landscapes. Increasing tree species diversity during secondary succession is an important driver of forest structural complexity recovery. To better understand the role of tree species diversity in shaping the three‐dimensional structure of recovering forests, future studies should address the role of intra‐ and interspecific differences in crown morphology and functional traits as potential drivers of forest structural complexity
Effect of the [Fe(salen)]2-μ-oxo catalyst electronic structure on reductive hydroamination
No full textPatch-MLP-Based Predictive Control: Simulation of Upstream Pointing Stabilization for PHELIX Laser System
No full textHow semiconducting are ferroelectrics: the fundamental, optical and transport gaps of Na0.5Bi0.5TiO3-BaTiO3 and NaNbO3
No full textThe energy gap is a fundamental property of materials, directly related to their optical and electronic properties. The energy gap of ferroelectric compounds and its adjustment by compositional variation has particularly attracted attention in recent years due to potential application in energy conversion and/or catalytic devices. It is demonstrated that it is necessary to distinguish between the fundamental gap, Eg 0, the optical gap, Eg opt, and the transport gap, Eg tr, of ferroelectrics, which can differ significantly. The situation is comparable to those in organic semiconductors and emerges from the presence of localized charges. The fundamental gap is a ground state property, i.e. the energy difference between the maximum of the fully occupied valence band and the minimum of the completely empty conduction band. In contrast, the optical and transport gaps are excited state properties involving localized (polaronic) electrons and/or holes at energies considerably different from the band edges. This work illustrates how the different energy gaps of ferroelectrics can be determined by combining optical measurements, X-ray photoelectron spectroscopy and temperature and oxygen partial pressure dependent electrical conductivity measurements. We determine fundamental gaps of ≈ 4.5 eV for both materials, optical gaps of 3.25-3.45 eV/3.5 eV and electrical gaps of ≈ 1.4 eV/3.3 eV for Na0.5Bi0.5TiO3-BaTiO3/NaNbO3, respectively
Reynolds number effects in turbulent premixed precracked ammonia-hydrogen flames
No full textPrecracked ammonia–hydrogen (NH3/H2) mixtures, particularly under fuel-rich conditions, are highly at tractive for applications as they enable low-NOx combustion while producing hydrogen in situ, offering a controllable, carbon-free fuel pathway compatible with existing high-temperature energy and propulsion sys tems. However, their fundamental combustion behavior is still insufficiently understood, especially regarding turbulence-chemistry interaction and pollutant formation mechanisms. Therefore, this study aims to characterize the influence of turbulence on the internal flame structure, thermochemical state, and NO formation mecha nisms in piloted, fuel-rich, turbulent premixed precracked NH3/H2/N2 jet flames by combining simultaneous 1D Raman/Rayleigh spectroscopy with Direct Numerical Simulations (DNS) using detailed chemical kinetics. Quantitative scalar measurements of instantaneous flame structure and thermochemical states were used to assess NH3/H2 interactions, differential diffusion, and NO formation. Increasing the Reynolds number from Re = 5900 to 17,700 results in an increase in global turbulent flame speed by a factor of 1.9 and a corresponding rise in mean NO concentrations. At low and intermediate Reynolds numbers, the increase in turbulent flame speed is primarily governed by f lame surface area, whereas at the highest Reynolds number an additional enhancement of mean reactivity is observed. This is reflected by an increase in the observed heat release rate conditioned on reaction progress, indicating increasingly strong differential diffusion effects at elevated turbulence intensities. While no NH3 is detected downstream of the main reaction zone, residual H2 levels are observed in the products. Due to residual O2 in the pilot exhaust gas, a secondary reaction zone forms downstream where H2 undergoes further oxidation under near-stoichiometric conditions. At high Reynolds numbers, regions of negative flame curvature exhibit increased NO production and up to a factor of 4 higher local heat release rates compared to one-dimensional laminar flames, highlighting the strong coupling between flame topology, diffusive transport, and pollutant formation. Based on the combined experimental and numerical findings, reactant-to-product counterflow flames are identified as a suitable canonical configuration for future flamelet manifold modeling of fuel-rich NH3/H2 combustion
Mental model evolvement during drivers' first experience with conditionally automated driving systems in real-world traffic
No full textThis study examines the development of drivers' general mental models during their first real-world experience with the SAE Level 3 conditionally automated driving system (CADS) Drive Pilot. While previous research has primarily investigated mental model formation in simulators or on test tracks, little is known about how accuracy and completeness evolve during initial use in naturalistic traffic. Twenty-nine participants without prior CADS experience completed a within-subject on-road study with three measurement points: before receiving any information about the CADS (t1), after a short instructional video (t2), and after a real-world drive on a German motorway (t3). Mental models were assessed with a system-specific self-report questionnaire designed to evaluate both accuracy and completeness. Qualitative and statistical analyses showed high initial accuracy for core functions, alongside considerable misconceptions and knowledge gaps regarding limitations and operational aspects. The instructional video improved both accuracy and completeness, including for some limitations not explicitly covered. Real-world driving further increased accuracy across categories. However, completeness declined, particularly for limitations not encountered during the drive. Statistical analyses confirmed significant improvements in accuracy from t1 to t2, t1 to t3 and t2 to t3. Findings suggest that short, targeted instructions combined with immediate real-world exposure can effectively enhance the accuracy of drivers' mental models. However, knowledge about seldom-encountered limitations decays rapidly without reinforcement, highlighting the need for specific instruction and in-vehicle systems that sustain awareness of rare but safety-critical constraints over time
Overcoming the sensitivity of sodium bismuth titanate towards sintering in a reducing atmosphere by defect chemistry engineering
No full textThere has recently been a surge in demand for lead-free multilayer ceramic actuators and capacitors. A central concern has been controlling manufacturing costs, primarily attributed to the use of precious metal electrodes, such as Pt, Pd, and Ag, as internal electrode materials. To address this challenge, the incorporation of base metal electrodes such as Cu and Ni has emerged as a desirable option. For these electrode materials to be utilised successfully, the co-sintering of both the electrode and dielectric must take place within a lower oxygen partial pressure (PO2 ) range. This step is crucial to prevent the oxidation of Cu or Ni electrodes. Sodium-bismuth-titanate (NBT)-based ceramics have proven to be excellent candidates for ferroelectric applications. However, NBT’s sensitivity to the formation of oxygen vacancies or reduction of Bi at lower PO2 poses a significant challenge to achieving this goal. Consequently, in this research, donor dopants such as Nb, Ta, V, Wo, and Mo were used to
induce the pinning of defect levels. The results showed that Nb and Ta help suppress the formation of oxygen vacancies and increase the phase stability during sintering in low PO2 whereas V, Wo, and Mo failed to do so.
Without Nb and Ta, NBT becomes conductive (three orders of magnitude higher) when sintered in low PO2 and its polarization and strain are severely suppressed. The modified NBT retains its electrical properties and is therefore an excellent candidate for co-sintering with Cu
Commitment Checklist: Auditing Author Commitments in Peer Review
No full textPeer review author responses often include commitments to add experiments, release code, or clarify content in the final paper. Yet, there is currently no systematic mechanism to ensure authors fulfill these promises. In this position paper, we present a large-scale audit of author commitments using large language models (LLMs) to compare rebuttals against camera-ready versions. Analyzing the commitments from ICLR-2025 and EMNLP-2024, we find that while a majority of promised changes are implemented, a significant share (about 25%) are not, with "missing experiments" and other high-impact items among the most frequently unfulfilled. We demonstrate that LLM-based tools can feasibly detect the promises. Finally, we propose the idea of Author Commitment Checklist, which would alert authors and organizers to unaddressed promises, increasing accountability and strengthening the integrity of the peer review process. We discuss the benefits of this practice and advocate for its adoption in future conferences