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High-Throughput Computational Framework for High-Order Anharmonic Thermal Transport in Cubic and Tetragonal Crystals
No full textAccurate first-principles prediction of lattice thermal conductivity (κ L) remains challenging in identifying materials with extreme thermal behavior. While the harmonic approximation with three-phonon scattering (HA + 3ph) is now routine, reliable κ L prediction often requires higher-order anharmonic effects, including self-consistent phonon renormalization, three- and four-phonon scattering, and off-diagonal heat flux (SCPH + 3, 4ph + OD). We present a state-of-the-art high-throughput workflow that unifies these effects and apply it to 773 cubic and tetragonal crystals spanning diverse chemistries and structures. From 562 dynamically stable compounds, we assess the hierarchical impacts of higher-order anharmonicity. For around 60% of materials, HA + 3ph predictions closely match those from SCPH + 3, 4ph + OD. SCPH generally increases κ L, by over 8 times in extreme cases, whereas four-phonon scattering universally suppresses κ L, sometimes to 15% of the HA + 3ph value. Off-diagonal contributions are negligible in high-κ L systems but can rival diagonal terms in highly anharmonic low-κ L compounds. We highlight four case studies, Rb2TlAlH6, Cu3VSe4, CuBr, and KTlCl4, that exhibit distinct extreme behaviors. This work delivers not only a robust workflow for high-fidelity κ L dataset but also a quantitative framework to determine when higher-order effects are essential. The hierarchy of κ L results, from the HA + 3ph to SCPH + 3, 4ph + OD level, offers a scalable, interpretable route to discovering next-generation extreme thermal materials
Estimating Sediment Properties Using a New Source Level Function for Wind-Driven Underwater Sound Derived from Long-Term Archival Data
No full textWind-driven breaking waves generate the background sound throughout the ocean. An accurate source level for wind-driven breaking waves is needed for estimating the ambient sound levels needed for sound exposure modeling, environmental assessments, and assessing the detection performance of sonars. Previous models applied a constant roll-off of sound levels at -16 dB/decade at all wind speeds, and these models\u27 source levels were flat at frequencies below ∼1000 Hz due to a lack of measurements. Here, we analyzed 16 long-term archival datasets with limited anthropogenic sound sources to estimate the wind-driven source level down to 100 Hz. We estimated the site-specific areic propagation loss (APL) using a ray-based model and then added the APL to the median received levels at each wind speed to obtain the source level. An equation for the areic dipole source level is provided that increases as wind speed cubed, like most other air-ocean coupling processes. The model may be used to estimate sediment properties (given a wind speed history and measured sound levels) or to estimate wind speeds (given the sediment type and measured sound levels). It is well suited for estimating ambient sound levels from wind for soundscape modeling. An open-source implementation is available
Clustering of Temporal and Visual Data: Recent Advancements
No full textClustering plays a central role in uncovering latent structure within both temporal and visual data. It enables critical insights in various domains including healthcare, finance, surveillance, autonomous systems, and many more. With the growing volume and complexity of time-series and image-based datasets, there is an increasing demand for robust, flexible, and scalable clustering algorithms. Although these modalities differ—time-series being inherently sequential and vision data being spatial—they exhibit common challenges such as high dimensionality, noise, variability in alignment and scale, and the need for interpretable groupings. This survey presents a comprehensive review of recent advancements in clustering methods that are adaptable to both time-series and vision data. We explore a wide spectrum of approaches, including distance-based techniques (e.g., DTW, EMD), feature-based methods, model-based strategies (e.g., GMMs, HMMs), and deep learning frameworks such as autoencoders, self-supervised learning, and graph neural networks. We also survey hybrid and ensemble models, as well as semi-supervised and active clustering methods that leverage minimal supervision for improved performance. By highlighting both the shared principles and the modality-specific adaptations of clustering strategies, this work outlines current capabilities and open challenges, and suggests future directions toward unified, multimodal clustering systems
Auto-Photovoice: A Reflexive Extension of Photovoice Methodology and Its Practice in a Covid-Quarantined Community Psychology Course
No full textThis article introduces auto-photovoice, a novel self-reflexive extension of photovoice methodology where participant-researchers turn the camera on themselves to explore their personal experiences and observations of a phenomenon. In our exemplar project, students and faculty codesigned and implemented auto-photovoice methodology during a 10-week online community psychology graduate seminar during the COVID-19 pandemic quarantine. Our photos addressed the prompt, What inequities do we experience and witness in well-being related to COVID-19? The initial analysis of weekly discussions of the photos identified 24 themes regarding COVID-19 impacts, which we later synthesized into four more general themes: (1) systemic social injustices, (2) abuses of power, (3) inequitable access, and (4) differential experiences among workers. As participant-researchers practicing auto-photovoice, we created a sense of community and an empowering pedagogy in our first remote online class during the initial weeks of the COVID-19 pandemic. As a methodology rooted in epistemologies that value reflexive and participatory knowledge creation, auto-photovoice facilitates us working empathically and authentically with communities in projects characterized by epistemic respect and justice
On the Need of Pluralism and Common Ground in SLA
No full textHyperbolic claims that SLA is in crisis (!), that a unifying theory is overdue, or that research must be oriented toward pedagogy have resurfaced once again—most recently in the response by Lantolf et al. (2025) to the Special Issue on Synergies in Second Language Acquisition and Teaching (SLA/T) (Atkinson et al., 2025). Our own position is diametrically opposed to such claims
Reader-Character Identity Interdependence: An Empirical Investigation of Congruence in Identity and Reading
No full textThis article examines the mutually constitutive relationship between identity, social participation, and reading, through a survey of 3089 readers in the United States, United Kingdom and Australia conducted in 2022. This is driven by an intersectional call to take seriously individualised experiences of identity including diverse and overlapping identities, consider multiple marginalisations, and interrogate normative modes of thinking. This connects to a commitment shared with other scholars of reading practice to undertake research that is simultaneously descriptive and critical. This forms the basis for our survey design, comprehending substantial engagement with readers’ reporting of their own reading practices. We work through multifaceted understandings of identity in our survey, and use this as the basis for examining specific patterns of identity formation through reading practice, and considering how individual experiences connect to larger systemic power dynamics. We find that all readers read for identification with the characters in the books that they read. However, readers who belong to multiply marginalised groups must go against the grain of dominant structures of representation to seek out opportunities for identification in their reading, and still also tend to read across dominant spaces of normativity, whereas readers who belong to dominant identity groups do not similarly read against the grain. Income and education complicate this by potentially dictating access to diverse books. Select readers were confronted by the survey’s interest in identity and reading; while a survey is inherently normative, interesting trends of counter-cultural pushback emerged in free-text spaces as readers navigated the limitations of the tool
The RISC-V FPGA (rvfpga) Teaching Package
No full textRISC-V is a free and open-standard ISA based on RISC principles, allowing anyone to design, manufacture, and sell RISC-V chips and software. Its flexibility and growing ecosystem have made it popular in research, education, and industry, increasing the need for educational materials. This paper provides an in-depth description of the RVfpga course, which offers a solid introduction to computer architecture using the RISC-V instruction set and FPGA technology. It focuses on providing hands-on experience with real-world RISC-V cores, the VeeR EH1 and EL2 cores, developed by Western Digital and hosted by ChipsAlliance. The course targets students and educators in computing-related fields, enabling them to integrate practical RISC-V knowledge into their curricula. The course materials, which include detailed labs, setup guides, and the full SoC source code in System Verilog, are available for free. Students learn to compile, debug, and run C and assembly programs, to interact with built-in peripherals, to extend the SoC, and to explore microarchitectural features
we\u27re Going to Tear Up the Caldera So We Can Have an Electric Car : Wrestling with Prospective Lithium Mining in the Oregon Desert
No full textExtraction of lithium, a key ingredient for renewable energy transitions, is a land- and water-intensive process. In this study, we use qualitative, place-based research to explore socio-environmental imaginaries surrounding a landscape on the verge of change due to lithium mining. We examine the ways that different actors are wrestling with the costs, benefits, and uncertainties of potential open-pit lithium mining in Oregon’s section of the McDermitt Caldera. In contrast to previous research which has described support for mining amongst those closest to the mine site, we find that in this case, perceptions of mining are characterized by ambivalence, uncertainty, and recognition of complexity and nuance. We note the ways in which tradeoffs, scalar tensions, connections to the local landscape, and uncertainty and unknowns are generating a prevailing sense of ambivalence around mining futures in the McDermitt Caldera. As the demand for critical minerals continues to rise, there is a growing need for place-based research to understand specific impacts of and reactions to potential extraction in areas on the verge of transformation. The expansion of critical mineral extraction for energy transitions generates internal conflicts and competing socio-environmental imaginaries
The Hottest Areas in U.S. Cities Are Losing the Most Greenery
No full textDue to the significantly increasing impacts of urban heat, cities are seeking to expand tree canopy, parks and other forms of greenery to reduce temperatures. Despite these efforts, few studies have examined the relationship between neighborhood-scale thermal conditions and changes in green spaces. The present study drew on high-resolution, near-surface air temperature measurements in 33 U.S. cities to answer two research questions: (1) to what extent did these cities’ greenery change from 2013 to 2022? and (2) did these study areas have an increase in greenery within neighborhoods exhibiting the hottest air temperatures? Results suggest that 72.7% of cities are losing their greenery, and that areas with the hottest air temperatures in the city are consistently losing a greater proportion of their greenery than their cooler counterparts. These results highlight the need for preservation of the existing greenery, particularly in areas with the hottest temperatures
Global Shocks, Institutional Development, and Trade Restrictions: What Can We Learn from Crises and Recoveries Between 1990 and 2022?
No full textThe Global Financial Crisis and the COVID-19 pandemic were two major shocks to the world economy in the 21st century. In this study, we analyze the patterns of recessions and recoveries of 101 advanced and developing economies. We identify the turning points of recessions and expansions between 1990 and 2022, and perform cross-country analysis of domestic and external drivers of economic recovery. In addition to the standard independent variables, we include institutional development, political stability, the extent of democracy, and trade restrictions indexes, and explore their roles in explaining recessions and recovery patterns. For the whole sample, we find that deeper recessions are followed by stronger recoveries, in line with Friedman’s plucking model of the business cycle. However, the empirical evidence for the plucking model becomes weaker if institutional development is limited and trade restrictions are high. We show that recessions that create conflict and trade tensions differ sharply from those that do not, a relevant finding in the current global climate of heightened trade tensions and geopolitical uncertainty. Finally, since developing countries tend to have weaker institutions and higher trade barriers, our evidence suggests that countercyclical monetary and fiscal policy will have to play a bigger role in cushioning global shocks in those countries. This, in turn, requires more robust and credible monetary and fiscal policy frameworks