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UC Santa Barbara Previously Published Works

Cover page of Chimpanzees steal less from their friends and expect them to do the same

Chimpanzees steal less from their friends and expect them to do the same

(2026)

Are chimpanzees able to inhibit anti-social behavior towards their friends? And how do they react when a friend acts anti-socially towards them? Past work has demonstrated that chimpanzees are selectively prosocial towards their friends: they groom them more, help them more, and share more food with them. However, the influence of friendship on anti-social behavior remains underexplored. Here, we use food theft as a test case to examine (1) the influence of friendship on anti-social behavior and (2) emotional responses to anti-social behavior. We assigned 26 chimpanzees to pairs of friends (friend condition) and non-friends (non-friend condition) based on 800 h of observations of naturally occurring interactions. The pairs then participated in a stealing task, in which one chimpanzee (the “thief”) could pull a tray with pieces of pineapple, on which the other was feeding (the “victim”). Friends and non-friends were matched on sex and dominance rank. We found that chimpanzees stole less from their friends. When theft did occur, chimpanzees tended to initially express more negative emotions in the friend condition than in the non-friend condition, but then attenuated this response with increasing trial number. Thieves, meanwhile, expressed more negative emotions in the non-friend condition, suggesting that they treated interactions with non-friends as more hostile. These results speak to the complex role of friendship in regulating anti-social behavior and emotional responses to it.

Cover page of Spatial statistics for detecting mechanical interactions among fiber fractures

Spatial statistics for detecting mechanical interactions among fiber fractures

(2026)

Inferring mechanical interactions from the spatial organization of discrete damage events is a fundamental inverse problem in the mechanics of heterogeneous materials. This work develops a statistical framework for extracting load-transfer interactions from three-dimensional fiber fracture data in unidirectional fiber-reinforced composites. Conventional micromechanical models typically assume global load sharing (GLS), implying statistically independent fiber fracture events, whereas growing experimental evidence suggests that load redistribution can become localized, producing spatially autocorrelated fracture. To distinguish these effects, classical second-order spatial statistics are extended by decomposing pairwise separations into transverse and axial components, reflecting the directional asymmetry of stress redistribution in fiber composites. Analytical solutions are derived for two canonical GLS models that establish a mechanics-based null hypothesis for mechanical independence. Unlike conventional approaches based on complete spatial randomness, this null hypothesis explicitly accounts for both the underlying fiber arrangement and the observed axial break intensity profile, allowing arbitrary fracture distributions to be analyzed without assuming a particular axial form. A normalized fiber interaction statistic is then introduced to remove these contributions, enabling direct assessment of mechanically induced coupling between neighboring fibers and meaningful comparison among datasets with different fiber arrangements and break distributions. Monte Carlo simulations quantify estimator variability and demonstrate that localized interactions can be detected with high statistical power even when only a modest fraction of fiber breaks are mechanically coupled. The resulting framework provides a rigorous methodology for interpreting volumetric fracture data and establishes a quantitative bridge between experimentally observed spatial damage patterns and micromechanical load-sharing models. Although demonstrated for fiber fracture in unidirectional composites, the underlying methodology is broadly applicable to heterogeneous materials in which damage evolves through discrete spatial events.

Cover page of Macropa derivatives for radiopharmaceutical and rare-earth element separation

Macropa derivatives for radiopharmaceutical and rare-earth element separation

(2026)

Recognition of large f-block ions underlies advances in targeted radionuclide therapy and rare-earth element separations. Like the lanthanide-binding protein lanmodulin, the 18-membered macrocycle macropa displays reverse-size selectivity characterized by its preference for binding large metal ions. Its diaza-18-crown-6 scaffold enables efficient complexation of therapeutically relevant radiometals, such as 225Ac, 223Ra, and 213Bi, while accommodating diagnostic partners, including 203Pb and radiolanthanides. In parallel, systematic differences in stability constants across the lanthanide series enable size-based discrimination in separation chemistry. Macropa and its derivatives have been deployed in different strategies to recover and purify rare-earth elements and minor actinides. This manuscript describes recent studies on modifications of macropa, including cavity expansion, alteration of donor atoms, backbone rigidification, chelator-embedded 18F incorporation, and acyclic variants to demonstrate that effective selectivity arises from balancing preorganization, donor strength, and conformational adaptability. These studies establish macropa-based scaffolds as synthetic systems that bridge radiopharmaceutical coordination chemistry and rare-earth element separations.

Cover page of Cognitive integration or separation? Innovation-driven urban redevelopment in urban villages

Cognitive integration or separation? Innovation-driven urban redevelopment in urban villages

(2026)

In the context of a knowledge economy and innovation-driven development, innovation districts have emerged as place-based urban development tools increasingly embedded within the urban redevelopment of old districts. While this economically and industrially oriented redevelopment pattern revitalizes urban spaces, it also raises concerns about social integration and community inclusion. This study proposes using cognitive regions as a key lens to assess whether urban redevelopment trends toward social integration or segregation, examining the cognitive coupling that occurs when innovation-driven selective redevelopment is inserted into the context of Chinese urban villages. Using Tangdong Village in Guangzhou as a case study, we apply an enhanced cognitive interview (ECI) method combined with visual and spatial analyses to identify cognitive disconnections between different groups toward original residential and innovation spaces, manifested in differences in cognitive elements, focal points, core ranges, and meaning interpretations. At the same time, the transitional streets and environmental improvements surrounding the innovation spaces are weakening the perceived boundaries between the two. We further outline the potential phased evolution of the cognitive impacts of this pattern and highlight that balancing the needs of different groups throughout this process is key to achieving inclusive and sustainable redevelopment.

Cover page of Forensic hydrological assessment of flood response under land use/land cover (LULC) change using ANN and HEC–HMS

Forensic hydrological assessment of flood response under land use/land cover (LULC) change using ANN and HEC–HMS

(2026)

This study develops an integrative methodological framework that combines forensic hydrology, artificial neural networks (ANNs), and physically-based hydrological modeling to assess the cascading impacts of projected land use/land cover (LULC) changes on future flood dynamics in the upstream watershed of Golestan Dam, Iran. A large-magnitude flood event analogous to the destructive 2019 flood was simulated under evolving LULC scenarios for three future horizons: 2030, 2040, and 2050. The curve number (CN) and lag time (Tlag) were reconstructed using linear and nonlinear interpolation and projected with ANN-based regression modeling. Mann-Kendall trend analysis was applied to assess the temporal consistency of ANN-predicted CN and Tlag series and support the selection of the most reliable synthetic datasets. The simulations revealed highly non-linear growth in peak discharges, with the Qarah Shur sub-basin projected to experience a 163.78% increase in flood intensity by 2050, resulting from a substantial increase in the contribution of barren land to flood intensification (from 22.89% to 78.88%) and a threefold increase in the contribution of sparse vegetation (from 9.04% to 31.13%). These two factors, individually and in combination, were identified as the most critical contributors to flood amplification in this sub-basin. The Galikesh sub-basin followed with a 68.99% increase by 2050, being the only sub-basin where the contribution of road expansion (from 8.88% to 27.41%) emerged as the dominant factor driving flood intensification. The Tamar Gorgan and Tangerah sub-basins demonstrated more moderate increases in discharge, 13.89% and 10.44%, respectively, driven by modest land degradation and road building. This work’s findings underscore growing risks to infrastructure, including embankment instability, bridge scour, and urban inundation, and to groundwater recharge, aquatic ecosystems, and water quality through the mobilization of pollutants and sediments under increasing flood risk. The spatial comparison of sub-basin-level responses captures the heterogeneity of flood vulnerability and the urgency of instituting adaptive land use policies grounded in hydrological sensitivity, riparian corridor protection, and nature-based flood mitigation.

Cover page of The history of classics in California Community Colleges: a study of curricular shifts, 1992–2024

The history of classics in California Community Colleges: a study of curricular shifts, 1992–2024

(2026)

Abstract: We present the first long-term analysis of Classics instruction in California’s community colleges, drawing on a dataset of nearly 47,000 course sections offered between 1993 and 2024. While the field of Classics has been the subject of ongoing discussion and restructuring in four-year institutions, its presence in two-year colleges, where nearly 40% of US undergraduates are enrolled, has received far less attention. We identify three distinct phases in the curricular history of Classics in the California Community Colleges (CCC) system: growth through the 1990s and early 2000s; a sharp contraction in 2007–2008; and a prolonged period of reduced offerings from 2008 to 2024. The data reveal a 38% overall decline in annual Classics-related course sections since 2008, with steep reductions in Latin, which fell by 86%. Our analysis shows that specialised areas with limited general education alignment were disproportionately affected. We argue that institutional changes triggered by budget cuts, policy reforms, and a shift towards transfer credit efficiency and workforce alignment have narrowed the curricular space for the humanities, particularly in disciplines lacking perceived vocational application. The erosion of Classics offerings raises urgent questions about educational equity, transfer access, and the future of humanities education in open-access institutions. This article is the first in an envisaged series of articles about Classics in California community colleges.

Combination of ATLAS and CMS Searches for Higgs Boson Pair Production at s=13 TeV

(2026)

This Letter presents a combination of searches for Higgs boson pair ( ) production performed by the ATLAS and CMS Collaborations using proton-proton collision datasets recorded at during the Large Hadron Collider Run 2, corresponding to integrated luminosities ranging between 126 and . The upper limit at the 95% confidence level on the total signal strength, defined as the ratio of the measured cross section to the standard model (SM) prediction, corresponds to 2.5, with an expected value of 1.7 (2.8) assuming the absence (presence) of the SM signal. The strength of the signal is measured to be relative to the SM prediction. The observed significance is found to be 1.1 standard deviations whereas 1.3 are expected for the SM signal. Constraints are set on the Higgs boson trilinear self-coupling and on the couplings of two Higgs bosons to two vector bosons, both normalized to the SM predictions and denoted as and , respectively. The observed individual constraints at the 95% confidence level are and , while the expected constraints assuming the presence of the SM signal are and .

Cover page of Beyond the Autistic Strengths Narrative: How Autonomy, Anxiety, and Attention Constrain Participation and Recognition in Neurodiverse Teams

Beyond the Autistic Strengths Narrative: How Autonomy, Anxiety, and Attention Constrain Participation and Recognition in Neurodiverse Teams

(2026)

Background: Strengths-based narratives of autism often presume that autistic individuals’ expertise will naturally translate into better outcomes for the teams they work with. However, such perspectives overlook the fundamentally relational nature of collaborative work, in which teams infer, evaluate, and recognize members’ knowledge and abilities through social interaction. When autistic communication and cognitive styles diverge from neurotypical teamwork norms, autistic individuals’ expertise may remain unrecognized in team contexts. Methods: Our data consist of semi-structured interviews with 35 autistic adults from a larger study and two newly collected serial focus groups with five additional autistic adults, all of whom had experience with team-based collaboration in academic or workplace settings. Using phronetic iterative qualitative data analysis, we identified recurring patterns in participants’ lived experiences of teamwork. Results: We identified three predominant structural barriers that limit autistic people’s access to and participation in teamwork: (a) Autonomy , reflecting a preference for independent work often arising from mismatches with dominant collaborative norms; (b) anxiety , shaped by lifelong experiences of stigma and neuronormative social expectations that constrain knowledge sharing; and (c) attention , referring to the cognitive, social, and sensory demands of teamwork that limit sustained engagement. Together, these barriers can operate incrementally, filtering out autistic individuals’ contributions before teams integrate them into their collective knowledge. Conclusion: These findings reframe autistic individuals’ challenges in neurodiverse teamwork as structural rather than individual. By highlighting how neuronormative team environments constrain the visibility of autistic expertise, this study contributes to autism and organizational research as well as team cognition theory. The findings also suggest the need for structural changes in team environments that normalize diverse communication styles, work preferences, and approaches to collaboration to foster more neuroinclusive teamwork. Community Brief Why is this an important issue? Many organizations and universities say they value the strengths autistic individuals bring. But autistic individuals still face barriers when working in teams—barriers that limit how much they can participate and whether their contributions get noticed. What was the purpose of this study? We wanted to understand teamwork from autistic individuals’ lived experiences, focusing on what makes it difficult for them to fully contribute their knowledge and have it recognized by teammates. What did the researchers do? We analyzed interviews from a larger study involving 35 autistic adults with teamwork experience and combined these insights with newly collected focus group data from five autistic adults. Across two focus group sessions held 2 weeks apart, participants completed hands-on activities to reflect on positive and challenging experiences working in teams. What were the results and conclusions of the study? We found three barriers that can make it harder for autistic people to participate fully and have their contributions noticed in teams. First, many participants wanted autonomy , or more control over how and when they completed their work, which would create an initial hurdle to engaging in teamwork. Second, anxiety around change (e.g., new members) and being misunderstood often led participants to hold back ideas or participate less. Third, fast-moving team environments that demand constant attention can be exhausting and make it hard to stay engaged over time. We argue that these are not simply personal challenges stemming from autistic traits. Rather, common expectations about how teams should work (e.g., constant availability, thinking out loud, making small talk, adapting quickly to change) can make participation more difficult for autistic people. What is new or controversial about these findings? This study shows that challenges autistic individuals face in teams are not just personal but they are built into how teams work. When every team member is expected to think and communicate the same way, autistic people can be left out, even when they have the knowledge, skills, and abilities the team needs. What are potential weaknesses in the study? This study used a small sample, and most participants had lower support needs. It also focused on teamwork involving sharing ideas, solving problems, and completing academic or professional projects. The findings may not apply to all autistic people or all types of teams. How will these findings help autistic adults now or in the future? These findings suggest that supporting autistic people requires changing how teams are designed and work, rather than asking autistic individuals to adapt or improve their social skills. Organizations and universities can create room for different ways of communicating and working. For example, teams can let people contribute at different times, protect time for uninterrupted work, and switch between short team check-ins and independent work. Recognizing autistic strengths is an important first step. Meaningful inclusion also requires team environments where autistic people can contribute fully and be recognized for what they bring.

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Cover page of Degradation Mechanisms of Fluorinated Disordered Rocksalt Cathodes: Effects of Electrolyte Chemistry and Discharge Voltage

Degradation Mechanisms of Fluorinated Disordered Rocksalt Cathodes: Effects of Electrolyte Chemistry and Discharge Voltage

(2026)

Cation-disordered rock-salt (DRX) oxides have emerged as a promising class of high energy density cathodes for next-generation lithium-ion batteries. Fluorination has been widely employed to tune the redox chemistry and structural stability of these materials, leading to enhanced electrochemical performance. However, the degradation mechanisms of fluorinated DRX (F-DRX) cathodes during electrochemical cycling remain poorly understood. Here, we investigate the degradation behavior of an F-DRX cathode cycled in a conventional carbonate-based electrolyte and a localized high-concentration electrolyte (LHCE). By correlating electrochemical performance with interfacial and bulk structural evolution, we elucidate the role of electrolyte chemistry and deep discharge voltage in governing structural transformation and degradation. The results reveal more pronounced surface and bulk structural changes in the conventional LiPF6-carbonate electrolyte relative to LiFSI-LHCE, indicating accelerated degradation in the former. Lowering the discharge cutoff voltage from 2.0 to 1.5 V further promotes interfacial degradation in both electrolyte systems. This work demonstrates that the LHCE offers superior compatibility with F-DRX cathodes, enabling stable cycling by mitigating surface and bulk structural degradation. These insights clarify the interplay between electrolyte chemistry and voltage window in F-DRX degradation and highlight the critical importance of advanced electrolyte designs for unlocking the full potential of DRX cathodes.