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Collaboration is highly emphasized in engineering design education. While it offers various advantages in fostering learning and professional development, it is imperative to acknowledge the adverse factors that can disrupt collaborative efforts. By far, one of the most frequently cited challenges in student teamwork is perceived contribution inequity, which often leads to frustration during collaboration and strains peer relationships. Much work has been done to investigate effective team collaboration. Still, few studies have empirically delved into perceived contribution fairness or contribution equity from the lens of team diversity in engineering design. This study aims to investigate the complex relationship between team diversity (in terms of differences in gender composition and self-perceptions about one’s ability and interests) and contribution equity in student teams. Data were collected from 26 teams in a sophomore-level engineering design course across two semesters. Findings suggest that gender-diverse teams demonstrated a higher tendency for contribution fairness, whereas teams with greater homogeneity in design interests and teamwork preferences were more likely to contribute fairly. These results highlight the importance of a strategic approach to team formation, considering diversity dimensions to promote equitable collaboration in engineering design education. 

Over the past three decades, assessments of the contemporary global carbon budget consistently report a strong net land carbon sink. Here, we review evidence supporting this paradigm and quantify the differences in global and Northern Hemisphere estimates of the net land sink derived from atmospheric inversion and satellite-derived vegetation biomass time series. Our analysis, combined with additional synthesis, supports a hypothesis that the net land sink is substantially weaker than commonly reported. At a global scale, our estimate of the net land carbon sink is 0.8 ± 0.7 petagrams of carbon per year from 2000 through 2019, nearly a factor of two lower than the Global Carbon Project estimate. With concurrent adjustments to ocean (+8%) and fossil fuel (−6%) fluxes, we develop a budget that partially reconciles key constraints provided by vegetation carbon, the north-south CO₂gradient, and O₂trends. We further outline potential modifications to models to improve agreement with a weaker land sink and describe several approaches for testing the hypothesis. 

Abstract CRISPR–Cas9 (clustered regularly interspaced short palindromic repeats–CRISPR-associated protein 9) has been revolutionizing genome engineering, and in-depth understanding of mechanisms governing its DNA discrimination is critical for continuing technology advances. An arginine-rich bridge helix (BH) connecting the nuclease lobe and the recognition lobe, which is conserved across the Cas9 family, exists in a helix–loop–helix conformation in the apo wild-type protein but converts to a long contiguous helix in the Cas9/RNA binary complex. In this work, distances measured with spin labels were utilized to investigate BH’s conformational transitions in the solution state upon single-guide RNA (sgRNA) binding, which is a critical early event preceding DNA binding and cleavage. Analyses show that sgRNA binding drives BH conformational changes in the wild-type SpyCas9 (SpyCas9WT) as well as in two BH-loop variants, SpyCas92Pro and SpyCas92Ala. Each Cas9–sgRNA binary complex, however, exhibits distinct BH features that reveal mutation-specific effects on helical integrity versus side-chain interactions. In addition, the BH conformational variations can be correlated to the observed changes in the mismatch cleavage profiles of the Cas9 variants. The work represents the first use of distances measured by site-directed spin labeling to investigate Cas9 protein conformational changes in the solution state and advances our understanding on the structure–dynamic–function relationship governing DNA target discrimination by Cas9. 

Opening up data produced by the Internet of Things (IoT) and mobile devices for public utilization can maximize their economic value. Challenges remain in the trustworthiness of the data sources and the security of the trading process, particularly when there is no trust between the data providers and consumers. In this paper, we propose DEXO, a decentralized data exchange mechanism that facilitates secure and fair data exchange between data consumers and distributed IoT/mobile data providers at scale, allowing the consumer to verify the data generation process and the providers to be compensated for providing authentic data, with correctness guarantees from the exchange platform. To realize this, DEXO extends the decentralized oracle network model that has been successful in the blockchain applications domain to incorporate novel hardware-cryptographic co-design that harmonizes trusted execution environment, secret sharing, and smart contract-assisted fair exchange. For the first time, DEXO ensures end-to-end data confidentiality, source verifiability, and fairness of the exchange process with strong resilience against participant collusion. We implemented a prototype of the DEXO system to demonstrate feasibility. The evaluation shows a moderate deployment cost and significantly improved blockchain operation efficiency compared to a popular data exchange mechanism. 

Societal Impact StatementForest ecosystems absorb and store about 25% of global carbon dioxide emissions annually and are increasingly shaped by human land use and management. Climate change interacts with land use and forest dynamics to influence observed carbon stocks and the strength of the land carbon sink. We show that climate change effects on modeled forest land carbon stocks are strongest in tropical wildlands that have limited human influence. Global forest carbon stocks and carbon sink strength may decline as climate change and anthropogenic influences intensify, with wildland tropical forests, especially in Amazonia, likely being especially vulnerable. SummaryHuman effects on ecosystems date back thousands of years, and anthropogenic biomes—anthromes—broadly incorporate the effects of human population density and land use on ecosystems. Forests are integral to the global carbon cycle, containing large biomass carbon stocks, yet their responses to land use and climate change are uncertain but critical to informing climate change mitigation strategies, ecosystem management, and Earth system modeling.Using an anthromes perspective and the site locations from the Global Forest Carbon (ForC) Database, we compare intensively used, cultured, and wildland forest lands in tropical and extratropical regions. We summarize recent past (1900‐present) patterns of land use intensification, and we use a feedback analysis of Earth system models from the Coupled Model Intercomparison Project Phase 6 to estimate the sensitivity of forest carbon stocks to CO₂and temperature change for different anthromes among regions.Modeled global forest carbon stock responses are positive for CO₂increase but neutral to negative for temperature increase. Across anthromes (intensively used, cultured, and wildland forest areas), modeled forest carbon stock responses of temperate and boreal forests are less variable than those of tropical forests. Tropical wildland forest areas appear especially sensitive to CO₂and temperature change, with the negative temperature response highlighting the potential vulnerability of the globally significant carbon stock in tropical forests.The net effect of anthropogenic activities—including land‐use intensification and environmental change and their interactions with natural forest dynamics—will shape future forest carbon stock changes. These interactive effects will likely be strongest in tropical wildlands. 

A<sc>bstract</sc> We review the effective field theory (EFT) bootstrap by formulating it as an infinite-dimensional semidefinite program (SDP), built from the crossing symmetric sum rules and the S-matrix primal ansatz. We apply the program to study the large-Nchiral perturbation theory (χPT) and observe excellent convergence of EFT bounds between the dual (rule-out) and primal (rule-in) methods. This convergence aligns with the predictions of duality theory in SDP, enabling us to analyze the bound states and resonances in the ultra-violet (UV) spectrum. Furthermore, we incorporate the upper bound of unitarity to uniformly constrain the EFT space from the UV scaleMusing the primal method, thereby confirming the consistency of the large-Nexpansion. In the end, we translate the large-N χPT bounds to constrain the higher derivative corrections of holographic QCD models. 

High entropy alloy (HEA) nanoparticles hold promise as active and durable (electro)catalysts. Understanding their formation mechanism will enable rational control over composition and atomic arrangement of multimetallic catalytic surface sites to maximize their activity. While prior reports have attributed HEA nanoparticle formation to nucleation and growth, there is a dearth of detailed mechanistic investigations. Here we utilize liquid phase transmission electron microscopy (LPTEM), systematic synthesis, and mass spectrometry (MS) to demonstrate that HEA nanoparticles form by aggregation of metal cluster intermediates. AuAgCuPtPd HEA nanoparticles are synthesized by aqueous co-reduction of metal salts with sodium borohydride in the presence of thiolated polymer ligands. Varying the metal : ligand ratio during synthesis showed that alloyed HEA nanoparticles formed only above a threshold ligand concentration. Interestingly, stable single metal atoms and sub-nanometer clusters are observed by TEM and MS in the final HEA nanoparticle solution, suggesting nucleation and growth is not the dominant mechanism. Increasing supersaturation ratio increased particle size, which together with observations of stable single metal atoms and clusters, supported an aggregative growth mechanism. Direct real-time observation with LPTEM imaging showed aggregation of HEA nanoparticles during synthesis. Quantitative analyses of the nanoparticle growth kinetics and particle size distribution from LPTEM movies were consistent with a theoretical model for aggregative growth. Taken together, these results are consistent with a reaction mechanism involving rapid reduction of metal ions into sub-nanometer clusters followed by cluster aggregation driven by borohydride ion induced thiol ligand desorption. This work demonstrates the importance of cluster species as potential synthetic handles for rational control over HEA nanoparticle atomic structure.