National Taiwan Normal University

56 watersheds distributed across the island of Taiwan. Using a time-varying Budyko framework, this study aims to: 1) quantify shifts in catchment water storage capacity (represented by the landscape parameter, m ); 2) decompose runoff variations into climate-induced and landscape-induced components to identify the drivers of streamflow reduction; and 3) assess the implications of using time-invariant versus time-varying landscape parameters for future water resource projections. This study provides the first quantitative evidence of a widespread “decoupling” between precipitation and streamflow in Taiwan; while 79.6% of watersheds show upward precipitation trends, only 60.7% show upward runoff trends, with many showing significant landscape-driven reductions; 2) Decomposition analysis reveals that enhanced watershed water storage capacity (an increasing m ) has offset climate-driven runoff gains in the majority of watersheds. This increase in storage capacity is strongly correlated with forest expansion, which acts as a primary driver for reduced runoff despite increasing rainfall.; 3) The assumption of stationarity in the Budyko landscape parameter leads to significant biases. Using a time-invariant parameter results in an overestimation of future runoff by up to 240 mm under RCP8.5 scenarios, highlighting the necessity of incorporating time-varying parameters for accurate hydrological projections in changing environments. • Reveal widespread decoupling of precipitation and streamflow trends across Taiwan. • Quantify shifts in water storage capacity via a time-varying Budyko framework. • Enhanced water storage capacity offsets climate-driven runoff gains. • Forest expansion is a primary driver of landscape-induced runoff reduction. • A plausible estimate of future runoff requires time-varying parameterization.

Background: Problem-Based Learning (PBL) promotes higher-order thinking, but in cell biology its implementation often produces cognitive overload because students must coordinate abstract organelle structures, invisible intracellular processes, and interconnected metabolic pathways across multiple representations. Existing studies rarely integrate structured problem design and task sequencing to address these specific cognitive demands. This study addressed that gap by combining the 3C3R and 4C/ID frameworks within a PBL environment. Objective: This study aimed to develop and evaluate an integrated PBL-3C3R-4C/ID instructional model for cell biology in terms of validity, practicality, and effectiveness in managing students’ cognitive load. Methods: Using a Research and Development approach based on Hannafin and Peck, followed by a pretest-posttest control group design, the study involved 231 secondary school students. Cognitive load was measured through a multidimensional scale covering intrinsic, extraneous, and germane load. Data were analyzed using descriptive statistics and paired t-tests. Results: The model demonstrated high validity and strong reliability (α = 0.91). Post-intervention results showed significant improvement in learning outcomes, accompanied by reduced extraneous load and increased germane load. Conclusion: Integrating 3C3R and 4C/ID within PBL offers a theoretically grounded and empirically supported approach for teaching complex cell biology while managing students’ working memory demands more effectively.

Purpose Despite growing research on human–AI collaboration, practical methods for building effective human–AI partnerships that maximize organizational performance remain limited. The study addresses this gap by developing an applied model grounded in economic theory to optimize task allocation between humans and AI within organizations and to guide human capital investments that strategically leverage and amplify unique human strengths. Design/methodology/approach The study uses theory-based conceptual analysis combined with mathematical modeling to operationalize Ricardo's comparative advantage theory for optimizing human–AI collaboration outcomes. Mathematical models were developed to optimize task allocation and identify human capital investment priorities. Validation was conducted using simulated data of semiconductor processing technicians, comparing the comparative advantage model's performance against random task assignment baselines. Findings The comparative advantage model demonstrates 63% higher productivity compared to random task assignments when validated with semiconductor processing technician data. Results confirm that strategic alignment of human and AI capabilities through comparative advantage principles significantly enhances collective performance, validating economic theory application in AI-era human resource management (HRM). Practical implications The study equips HRM practitioners with systematic methodologies for optimizing human–AI collaboration through strategic task allocation and targeted human capital investments. The mathematical models provide actionable tools for workforce planning, training needs assessment and performance optimization in AI-integrated work environments. Originality/value This study demonstrates the first systematic application of comparative advantage theory to human–AI collaboration, introducing a fresh analytical lens for allocating tasks between humans and AI to maximize organizational effectiveness. By integrating economic theory into HRM, an area where scholarly work remains limited, this interdisciplinary study makes a novel contribution that advances theory, informs future empirical research and provides HR professionals with actionable models to prepare the future workforce in the AI era.

Abstract In this work, we investigate the coupling between a strong impurity and the topological boundary of an SSH heterojunction, composed of two SSH chains belonging to different topological classes. We show that impurity–boundary coupling gives rise to bonding and antibonding states within the SSH bulk gap. This coupling produces an interference effect in the local density of states, as the impurity approaches the boundary the LDOS evolves from a single sharp peak to a characteristic double-peak structure. Moreover, the interference strength can be quantified by the decay length of the bonding or antibonding wavefunction and by the energy splitting of the LDOS resonance peaks near the Fermi energy.

Abstract We report the detection of methanol (CH 3 OH) toward interstellar comet 3I/ATLAS using the Atacama Compact Array of the Atacama Large Millimeter/submillimeter Array (ALMA) on UT 2025 August 28, September 18 and 22, and October 1 and of hydrogen cyanide (HCN) on September 12 and 15. These observations spanned pre-perihelion heliocentric distances ( r H ) of 2.6–1.7 au. The molecules showed outgassing patterns distinct from one another, with HCN production being depleted in the sunward hemisphere of the coma, whereas CH 3 OH was enhanced in that direction. Statistical analysis of molecular scale lengths in 3I/ATLAS indicated that CH 3 OH included production from coma sources at L p &gt; 258 km at 99% confidence. However, low signal-to-noise ratio (S/N) on long baselines, which sample emission on small spatial scales closest to the nucleus, prevented definitively ruling out CH 3 OH as purely a parent species. In contrast, HCN production was indistinguishable from direct nucleus sublimation. The CH 3 OH production rate increased sharply from August through October, including an uptick near the inner edge of the H 2 O sublimation zone at r H = 2 au. Compared to comets measured to date at radio wavelengths, the derived CH 3 OH/HCN ratios in 3I/ATLAS of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mn>12</mml:mn> <mml:msubsup> <mml:mrow> <mml:mn>4</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>34</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>+</mml:mo> <mml:mn>30</mml:mn> </mml:mrow> </mml:msubsup> </mml:math> and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:mn>7</mml:mn> <mml:msubsup> <mml:mrow> <mml:mn>9</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>−</mml:mo> <mml:mn>14</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>+</mml:mo> <mml:mn>11</mml:mn> </mml:mrow> </mml:msubsup> </mml:math> on September 12 and 15, respectively, are among the most enriched values measured in any comet, surpassed only by anomalous solar system comet C/2016 R2 (Pan-STARRS).