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The present study examines the assumptions, modeling structure, and results of DICE-2023, the revised Dynamic Integrated Model of Climate and the Economy (DICE), updated to 2023. The revision contains major changes in the treatment of risk, the carbon and climate modules, the treatment of nonindustrial greenhouse gases, discount rates, as well as updates on all the major components. Noteworthy changes are a significant reduction in the target for the optimal (cost-beneficial) temperature path, a lower cost of reaching the 2 °C target, an analysis of the impact of the Paris Accord, and a major increase in the estimated social cost of carbon. [ABSTRACT FROM AUTHOR]

Carbon-based single-atom catalysts, a promising candidate in electrocatalysis, offer insights into electron-donating effects of metal center on adjacent atoms. Herein, we present a practical strategy to rationally design a model catalyst with a single zinc (Zn) atom coordinated with nitrogen and sulfur atoms in a multilevel carbon matrix. The Zn site exhibits an atomic interface configuration of ZnN4S1, where Zn's electron injection effect enables thermal-neutral hydrogen adsorption on neighboring atoms, pushing the activity boundaries of carbon electrocatalysts toward electrochemical hydrogen evolution to an unprecedented level. Experimental and theoretical analyses confirm the low-barrier Volmer-Tafel mechanism of proton reduction, while the multishell hollow structures facilitate the hydrogen evolution even at high current intensities. This work provides insights for understanding the actual active species during hydrogen evolution reaction and paves the way for designing high-performance electrocatalysts. [ABSTRACT FROM AUTHOR]

While scientific researchers often aim for high productivity, prioritizing the quantity of publications may come at the cost of time and effort dedicated to individual research. It is thus important to examine the relationship between productivity and disruption for individual researchers. Here, we show that with the increase in the number of published papers, the average citation per paper will be higher yet the mean disruption of papers will be lower. In addition, we find that the disruption of scientists' papers may decrease when they are highly productive in a given year. The disruption of papers in each year is not determined by the total number of papers published in the author's career, but rather by the productivity of that particular year. Besides, more productive authors also tend to give references to recent and high-impact research. Our findings highlight the potential risks of pursuing productivity and aim to encourage more thoughtful career planning among scientists. [ABSTRACT FROM AUTHOR]

There is growing recognition of the potential of migration to contribute to climate-change adaptation. Yet, there is limited evidence to what degree, under what conditions, for whom, and with which limitations this is effectively the case. We argue that this results from a lack of recognition and systematic incorporation of sociospatiality--the nested, networked, and intersectional nature of migration-as-adaptation. Our central objective is to utilize the translocal social-resilience approach to overcome these gaps, to identify processes and structures that shape the social resilience of translocal livelihood systems, and to illustrate the mechanisms behind the multiplicity of possible resilience outcomes. Translocal livelihood constellations anchored in rural Thailand as well as in domestic and international destinations of Thai migrants serve as illustrative empirical cases. Data were gathered through a multisited and mixed-methods research design. This paper highlights the role of the distinct but interlinked situations and operational logics at places of origin and destination, as well as the different positionalities and resulting vulnerabilities, roles, commitments, and practices of individuals and households with regard to resilience. Based on the empirical results, the paper distills a generalized typology of five broad categories of resilience outcomes, which explicitly considers sociospatiality. Our approach helps to grasp the complexity of migration-as-adaptation and to avoid simplistic conclusions about the benefits and costs of migration for adaptation--both of which are necessary for sound, evidence-based, migration-as-adaptation policymaking. [ABSTRACT FROM AUTHOR]

This paper exploits the potential of Global Positioning System datasets sourced from mobile phones to estimate the racial composition of road users, leveraging data from their respective Census block group. The racial composition data encompasses approximately 46 million trips in the Chicago metropolitan region. The research focuses on the relationship between camera tickets and racial composition of drivers vs. police stops for traffic citations and the racial composition in these locations. Black drivers exhibit a higher likelihood of being ticketed by automated speed cameras and of being stopped for moving violations on roads, irrespective of the proportion of White drivers present. The research observes that this correlation attenuates as the proportion of White drivers on the road increases. The citation rate measured by cameras better matches the racial composition of road users on the links with cameras than do stops by police officers. This study therefore presents an important contribution to understanding racial disparities in moving violation stops, with implications for policy interventions and social justice reforms. [ABSTRACT FROM AUTHOR]

This document is a correction to the supporting information for a medical sciences article titled "MEK1 mutations confer resistance to MEK and B-RAF inhibition." The authors acknowledge an error in one of the images in the supporting information, but assure that it does not affect the experiment's results or the overall paper. The corrected version of the supporting information is available online. The article provides detailed information on various aspects of the study, including cell lines, MEK1 expression constructs, mutagenesis screen, sequencing, growth inhibition assays, Western blot analysis, kinase assays, and colony formation assays. The document includes figures and tables presenting the experimental findings. [Extracted from the article]

In this paper, we present findings from four separate studies using different data sources and methods to examine Chinese attitudes toward the United States amid the COVID-19 pandemic. The empirical results consistently indicate a marked and significant decline in Chinese attitudes toward the US between late 2019 and the end of 2022. Using a quasi-experimental design and granular survey data that exploit daily variations in public opinion, we offer additional evidence that the decline in Chinese attitudes toward the United States followed a distinct pattern not true for Chinese attitudes toward other countries. Specifically, the rise in Chinese unfavorability toward the United States closely corresponded to the heightened Chinese attention to the pandemic's progression in the United States. These results collectively suggest a causal effect of COVID-19, shedding light on how public health crises, international relations, and media jointly shape the increasing enmity between the two great powers. [ABSTRACT FROM AUTHOR]

The reaction kinetics of photocatalytic CO2 reduction is highly dependent on the transfer rate of electrons and protons to the CO2 molecules adsorbed on catalytic centers. Studies on uncovering the proton effect in catalysts on photocatalytic activity of CO2 reduction are significant but rarely reported. In this paper, we, from the molecular level, revealed that the photocatalytic activity of CO2 reduction is closely related to the proton availability in catalysts. Specifically, four dinuclear Co(II) complexes based on Robson-type ligands with different number of carboxylic groups (-nCOOH; n = 0, 2, 4, 6) were designed and synthesized. All these complexes show photocatalytic activity for CO2 reduction to CO in a water-containing system upon visible-light illumination. Interestingly, the CO yields increase positively with the increase of the carboxylic-group number in dinuclear Co(II) complexes. The one containing -6COOH shows the best photocatalytic activity for CO2 reduction to CO, with the TON value reaching as high as 10,294. The value is 1.8, 3.4, and 7.8 times higher than those containing -4COOH, -2COOH, and -0COOH, respectively. The high TON value also makes the dinuclear Co(II) complex with -6COOH outstanding among reported homogeneous molecular catalysts for photocatalytic CO2 reduction. Control experiments and density functional theory calculation indicated that more carboxylic groups in the catalyst endow the catalyst with more proton relays, thus accelerating the proton transfer and boosting the photocatalytic CO2 reduction. This study, at a molecular level, elucidates that more carboxylic groups in catalysts are beneficial for boosting the reaction kinetics of photocatalytic CO2 reduction. [ABSTRACT FROM AUTHOR]

Molecular chaperones assist in protein refolding by selectively binding to proteins in their nonnative states. Despite progress in creating artificial chaperones, these designs often have a limited range of substrates they can work with. In this paper, we present molecularly imprinted flexible polymer nanoparticles (nanoMIPs) designed as customizable biomimetic chaperones. We used model proteins such as cytochrome c, laccase, and lipase to screen polymeric monomers and identify the most effective formulations, offering tunable charge and hydrophobic properties. Utilizing a dispersed phase imprinting approach, we employed magnetic beads modified with destabilized whole-protein as solid-phase templates. This process involves medium exchange facilitated by magnetic pulldowns, resulting in the synthesis of nanoMIPs featuring imprinted sites that effectively mimic chaperone cavities. These nanoMIPs were able to selectively refold denatured enzymes, achieving up to 86.7% recovery of their activity, significantly outperforming control samples. Mechanistic studies confirmed that nanoMIPs preferentially bind denatured rather than native enzymes, mimicking natural chaperone interactions. Multifaceted analyses support the functionality of nanoMIPs, which emulate the protective roles of chaperones by selectively engaging with denatured proteins to inhibit aggregation and facilitate refolding. This approach shows promise for widespread use in protein recovery within biocatalysis and biomedicine. [ABSTRACT FROM AUTHOR]

This paper studies the effect of air pollution on voting outcomes. We use data from 60 federal and state elections in Germany from 2000 to 2018 and exploit plausibly exogenous fluctuations in ambient air pollution within counties across election dates. Higher air pollution on election day shifts votes away from incumbent parties and toward opposition parties. An increase in the concentration of particulate matter (PM10) by 10 g/m3--around two within-county SDs--reduces the vote share of incumbent parties by two percentage points, which is equivalent to 4% of the mean vote share. We generalize these findings by documenting similar effects with data from a weekly opinion poll and a large-scale panel survey. We provide further evidence that poor air quality leads to more negative emotions such as anger, worry, and unhappiness, which, in turn, may reduce the support for the political status quo. Overall, these results suggest that poor air quality affects decision-making in the population at large, including consequential political decisions. [ABSTRACT FROM AUTHOR]

Over the past few years, machine learning models have significantly increased in size and complexity, especially in the area of generative AI such as large language models. These models require massive amounts of data andcomputecapacitytotrain,totheextentthatconcerns over the training data (such as protected or private content)cannotbepracticallyaddressedbyretrainingthe model"fromscratch"withthequestionabledataremoved or altered. Furthermore, despite significant efforts and controls dedicated to ensuring that training corpora are properly curated and composed, the sheer volume re- quiredmakesitinfeasibletomanuallyinspecteachdatum comprising a training corpus. One potential approach to training corpus data defects is model disgorgement, by which we broadly mean the elimination or reduction of not only any improperly used data, but also the effects of improperly used data on any component of an ML model. Model disgorgement techniques can be used to address a wide range of issues, such as reducing bias or toxicity, increasing fidelity, and ensuring responsible use of intellectual property. In this paper, we survey the land- scape of model disgorgement methods and introduce a taxonomyofdisgorgementtechniquesthatareapplicable to modern ML systems. In particular, we investigate the variousmeaningsof"removingtheeffects"ofdataonthe trained model in a way that does not require retraining from scratch [ABSTRACT FROM AUTHOR]

G protein- coupled receptors (GPCRs) transduce the effects of many neuromodulators including dopamine, serotonin, epinephrine, acetylcholine, and opioids. The localization of synthetic or endogenous GPCR agonists impacts their action on specific neuronal pathways. In this paper, we show a series of single- protein chain integrator sensors that are highly modular and could potentially be used to determine GPCR agonist localization across the brain. We previously engineered integrator sensors for the mu- and kappa- opioid receptor agonists called M- and K- Single- chain Protein- based Opioid Transmission Indicator Tool (SPOTIT), respectively. Here, we engineered red versions of the SPOTIT sensors for multiplexed imaging of GPCR agonists. We also modified SPOTIT to create an integrator sensor design platform called SPOTIT for all GPCRs (SPOTall). We used the SPOTall platform to engineer sensors for the beta 2- adrenergic receptor (B2AR), the dopamine receptor D1, and the cholinergic receptor muscarinic 2 agonists. Finally, we demonstrated the application of M- SPOTIT and B2AR- SPOTall in detecting exogenously administered morphine, isoproterenol, and epinephrine in the mouse brain via locally injected viruses. The SPOTIT and SPOTall sensor design platform has the potential for unbiased agonist detection of many synthetic and endogenous neuromodulators across the brain. [ABSTRACT FROM AUTHOR]

Anti-microbial resistance (AMR) is one of the greatest threats to global health. The continual battle between the emergence of AMR and the development of drugs will be extremely difficult to stop as long as traditional anti-biotic approaches are taken. In order to overcome this impasse, we here focused on the type III secretion system (T3SS), which is highly conserved in many Gram-negative pathogenic bacteria. The T3SS is known to be indispensable in establishing disease processes but not essential for pathogen survival. Therefore, T3SS inhibitors may be innovative anti-infective agents that could dramatically reduce the evolutionary selective pressure on strains resistant to treatment. Based on this concept, we previously identified a polyketide natural product, aurodox (AD), as a specific T3SS inhibitor using our original screening system. However, despite its promise as a unique anti-infective drug of AD, the molecular target of AD has remained unclear. In this paper, using an innovative chemistry and genetic biology-based approach, we show that AD binds to adenylosuccinate synthase (PurA), which suppresses the production of the secreted proteins from T3SS, resulting in the expression of bacterial virulence both in vitro and in vivo experiments. Our findings illuminate the potential of PurA as a target of anti-infective drugs and vaccination and could open a avenue for application of PurA in the regulation of T3SS. [ABSTRACT FROM AUTHOR]

This paper presents quasiexperimental evidence of Covid-19 transmission through casual contact between customers in retail stores. For a large sample of individuals in Denmark, we match card payment data, indicating exactly where and when each individual made purchases, with Covid-19 test data, indicating when each individual was tested and whether the test was positive. The resulting dataset identifies more than 100,000 instances where an infected individual made a purchase in a store and, in each instance, allows us to track the infection dynamics of other individuals who made purchases in the same store around the same time. We estimate transmissions by comparing the infection rate of exposed customers, who made a purchase within 5 min of an infected individual, and nonexposed customers, who made a purchase in the same store 16 to 30 min before. We find that exposure to an infected individual in a store increases the infection rate by around 0.12 percentage points (P < 0.001) between day 3 and day 7 after exposure. The estimates imply that transmissions in stores contributed around 0.04 to the reproduction number for the average infected individual and significantly more in the period where Omicron was the dominant variant. [ABSTRACT FROM AUTHOR]

In the past three decades, there has been a rise in young academy movements in the Global North and South. Such movements, in at least Germany and the Netherlands, have been shown to be quite effective in connecting scientific work with society. Likewise, these movements share a common goal of developing interdisciplinary collaboration among young scientists, which contributes to the growth of a nation's--but also global--scientific endeavors. This paper focuses on the young academy movement in the fourth-largest country hosting the biggest Muslim population in the world, which is also the third-most populous democracy: Indonesia. We observe that there has been rising awareness among the young generation of scientists in Indonesia of the need to advocate for the use of sciences in responding to upcoming and current multidimensional crises. Science advocacy can be seen in their peer-based identification of Indonesia's future challenges, encompassing the fundamental areas for scientific inquiry, discovery, and intervention. We focus on the Indonesian Young Academy of Sciences (ALMI) and its network of young scientists. We describe ALMI's science communication practice, specifically SAINS45 and Science for Indonesia's Biodiversity, and how they have been useful for policymakers, media, and school engagements. The article closes with a reflection on future directions for the young academy movement in Indonesia and beyond. [ABSTRACT FROM AUTHOR]

The past 15 y has seen much development in documentation of domestication of plants and animals as gradual traditions spanning millennia. There has also been considerable momentum in understanding the dispersals of major domesticated taxa across continents spanning thousands of miles. The two processes are often considered within different theoretical strains. What is missing from our repertoire of explanations is a conceptual bridge between the protracted process over millennia and the multiregional, globally dispersed nature of domestication. The evidence reviewed in this paper bears upon how we conceptualize domestication as an episode or a process. By bringing together the topics of crop domestication and crop movement, those complex, protracted, and continuous outcomes come more clearly into view. [ABSTRACT FROM AUTHOR]

The U.S. federal government is unbalanced in its capacity to recognize, manage, and engage cultural heritage as part of its response to climate change. Legislation from the 1906 Antiquities Act to Executive Order (EO) 13990 signed in 2021 has set an overarching approach in which heritage is understood to be primarily tangible places and things that should be conserved, foremost through monument and park boundaries and significance designations. Such conservation, however, does not protect heritage from impacts of climate change and how to manage these components of heritage is nearly invisible in recent climate-focused publications of the two agencies assigned by legislation to serve as leads for cultural heritage in the U.S. government. Yet further, the long-standing tangible approach to heritage does not incorporate emerging understandings of its intangible components and the diverse connections of all forms of heritage to place, meaning, identity, and global change goals of sustainability and equity. In contrast, analysis of 27 federal agency climate adaptation plans prepared in response to 2021 EO 14008 shows that multiple agencies not assigned lead roles for heritage recognize a range of responsibilities that include heritage as part of climate adaptation, mitigation, equity, and coordination with Indigenous communities. This paper explores U.S. heritage legislative history, the definition it helped create for heritage, more recent understandings of heritage, and relationships of these to climate change and how these are represented in climate work and plans across U.S. federal agencies. On these bases, recommendations are provided for research and policy steps. [ABSTRACT FROM AUTHOR]

The self-assembly of spheres into geometric structures, under various theoretical conditions, offers valuable insights into complex self-assembly processes in soft systems. Previous studies have utilized pair potentials between spheres to assemble maximum contact clusters in simulations and experiments. The morphometric approach to solvation free energy that we utilize here goes beyond pair potentials; it is a geometrybased theory that incorporates a weighted combination of geometric measures over the solvent accessible surface for solute configurations in a solvent. In this paper, we demonstrate that employing the morphometric model of solvation free energy in simulating the self-assembly of sphere clusters results, under most conditions, in the previously observed maximum contact clusters. Under other conditions, it unveils an assortment of extraordinary sphere configurations, such as double helices and rhombohedra. These exotic structures arise specifically under conditions where the interactions take multibody potentials into account. This investigation establishes a foundation for comprehending the diverse range of geometric forms in self-assembled structures, emphasizing the significance of the morphometric approach in this context. [ABSTRACT FROM AUTHOR]

In ecological contexts, it is conventionally expected that increased food availability would boost consumption, particularly when animals prioritize maximizing their food intake. This paper challenges this conventional wisdom by conducting an in-depth game-theoretic analysis of a basic foraging model, in which animals must choose between intensive food searching as producers or moderate searching while relying on group members as scroungers. Our study reveals that, under certain circumstances, increasing food availability can amplify the inclination to scrounge to such an extent that it leads to a reduction in animals' food consumption compared to scenarios with limited food availability. We further illustrate a similar phenomenon in a model capturing free-riding dynamics among workers in a company. We demonstrate that, under certain reward mechanisms, enhancing workers' production capacities can inadvertently trigger a surge in free-riding behavior, leading to both diminished group productivity and reduced individual payoffs. Our findings provide intriguing insights into the complex relationships between individual and group performances, as well as the intricate mechanisms underlying the emergence of free-riding behavior in competitive environments. [ABSTRACT FROM AUTHOR]

The bad metallic phase with resistivity above the Mott-Ioffe-Regel (MIR) limit, which appears also in cuprate superconductors, was recently understood by cold atom and computer simulations of the Hubbard model via charge susceptibility and charge diffusion constant. However, since reliable simulations can be typically done only at temperatures above the experimental temperatures, the question for cuprate superconductors is still open. This paper addresses this question by resorting to heat transport, which allows for the estimate of electronic diffusion and it further combines it with the resistivity to estimate the charge susceptibility. The doping and temperature dependencies of diffusion constant and charge susceptibilities are shown and discussed for two samples of YBa2Cu3O6+x. Results indicate strongly incoherent transport, mean free path corresponding to the MIR limit for the underdoped sample at temperatures above ~200 K and significant effect of the charge susceptibility on the resistivity. [ABSTRACT FROM AUTHOR]

Since its emergence in late 2019, SARS-CoV-2 has diversified into a large number of lineages and caused multiple waves of infection globally. Novel lineages have the potential to spread rapidly and internationally if they have higher intrinsic transmissibility and/or can evade host immune responses, as has been seen with the Alpha, Delta, and Omicron variants of concern. They can also cause increased mortality and morbidity if they have increased virulence, as was seen for Alpha and Delta. Phylogenetic methods provide the "gold standard" for representing the global diversity of SARS-CoV-2 and to identify newly emerging lineages. However, these methods are computationally expensive, struggle when datasets get too large, and require manual curation to designate new lineages. These challenges provide a motivation to develop complementary methods that can incorporate all of the genetic data available without down-sampling to extract meaningful information rapidly and with minimal curation. In this paper, we demonstrate the utility of using algorithmic approaches based on word-statistics to represent whole sequences, bringing speed, scalability, and interpretability to the construction of genetic topologies. While not serving as a substitute for current phylogenetic analyses, the proposed methods can be used as a complementary, and fully automatable, approach to identify and confirm new emerging variants. [ABSTRACT FROM AUTHOR]

Higher-order network models are becoming increasingly relevant for their ability to explicitly capture interactions between three or more entities in a complex system at once. In this paper, we study homophily, the tendency for alike individuals to form connections, as it pertains to higher-order interactions. We find that straightforward extensions of classical homophily measures to interactions of size 3 and larger are often inflated by homophily present in pairwise interactions. This inflation can even hide the presence of anti-homophily in higher-order interactions. Hence, we develop a structural measure of homophily, simplicial homophily, which decouples homophily in pairwise interactions from that of higher-order interactions. The definition applies when the network can be modeled as a simplicial complex, a mathematical abstraction which makes a closure assumption that for any higher-order relationship in the network, all corresponding subsets of that relationship occur in the data. Whereas previous work has used this closure assumption to develop a rich theory in algebraic topology, here we use the assumption to make empirical comparisons between interactions of different sizes. The simplicial homophily measure is validated theoretically using an extension of a stochastic block model for simplicial complexes and empirically in large-scale experiments across 16 datasets. We further find that simplicial homophily can be used to identify when node features are valuable for higher-order link prediction. Ultimately, this highlights a subtlety in studying node features in higher-order networks, as measures defined on groups of size k can inherit features described by interactions of size ℓ< k. [ABSTRACT FROM AUTHOR]

Mutations at a highly conserved homologous residue in three closely related muscle myosins cause three distinct diseases involving muscle defects: R671C in β-cardiac myosin causes hypertrophic cardiomyopathy, R672C and R672H in embryonic skeletal myosin cause Freeman-Sheldon syndrome, and R674Q in perinatal skeletal myosin causes trismus-pseudocamptodactyly syndrome. It is not known whether their effects at the molecular level are similar to one another or correlate with disease phenotype and severity. To this end, we investigated the effects of the homologous mutations on key factors of molecular power production using recombinantly expressed human β, embryonic, and perinatal myosin subfragment-1. We found large effects in the developmental myosins but minimal effects in β myosin, and magnitude of changes correlated partially with clinical severity. The mutations in the developmental myosins dramatically decreased the step size and load-sensitive actin-detachment rate of single molecules measured by optical tweezers, in addition to decreasing overall enzymatic (ATPase) cycle rate. In contrast, the only measured effect of R671C in β myosin was a larger step size. Our measurements of step size and bound times predicted velocities consistent with those measured in an in vitro motility assay. Finally, molecular dynamics simulations predicted that the arginine to cysteine mutation in embryonic, but not β, myosin may reduce pre-powerstroke lever arm priming and ADP pocket opening, providing a possible structural mechanism consistent with the experimental observations. This paper presents direct comparisons of homologous mutations in several different myosin isoforms, whose divergent functional effects are a testament to myosin's highly allosteric nature. [ABSTRACT FROM AUTHOR]

This study investigates Black and White consumers' preferences for Black versus White people in United States advertising contexts over 66 y, from 1956 until 2022, a time in which the United States has experienced significant ethno-racial diversification. Examining Black and White consumers' reactions to visual advertising over more than half a century offers a unique and dynamic view of interracial preferences. Mass advertising reaches an audience of billions and can shape people's attitudes and behavior, emphasizing the relevance of clarifying the influence of race in advertising, how it has evolved over time, and how it may contribute to mitigating discrimination based on racial perceptions. A meta-analysis of extant experiments into the relationship between the depicted endorser's race (i.e., the model in a visual ad) and the reaction of Black and White viewers pertains to 332 effect sizes from 62 studies reported in 52 scientific papers, comprising 10,186 Black and White participants. Our results are anchored in a conceptual framework, including a comprehensive set of perceiver (viewer), target (endorser), social/societal context, and publication characteristics. Without accounting for temporal dynamics, the results indicate ingroup favoritism, such that White viewers prefer White models and Black viewers prefer Black models. But by controlling for the publication year, it is possible to observe a time-dependent trend: Historically, White consumers preferred endorsers of the same race, but this preference has significantly shifted toward Black endorsers in recent years. In contrast, the level of Black consumers' reactions to endorsers of the same race remains largely unchanged over time. [ABSTRACT FROM AUTHOR]

Mechanical grasping and holding devices depend upon a firm and controlled grip. The possibility to improve this gripping performance is severely limited by the need for miniaturization in many applications, such as robotics, microassembly, or surgery. In this paper, we show how this gripping can be improved in one application (the endoscopic needle holder) by understanding and imitating the design principles that evolution has selected to make the mandibles of an ant a powerful natural gripping device. State-of-the-art kinematic, morphological, and engineering approaches show that the ant, in contrast to other insects, has considerable movement within the articulation and the jaw's rotational axis. We derived three major evolutionary design principles from the ant's biting apparatus: 1) a mobile joint axis, 2) a tilted orientation of the mandibular axis, and 3) force transmission of the adductor muscle to the tip of the mandible. Application of these three principles to a commercially available endoscopic needle holder resulted in calculated force amplification up to 296% and an experimentally measured one up to 433%. This reduced the amount of translations and rotations of the needle, compared to the needle's original design, while retaining its size or outer shape. This study serves as just one example showing how bioengineers might find elegant solutions to their design problems by closely observing the natural world. [ABSTRACT FROM AUTHOR]

In problems such as variable selection and graph estimation, models are characterized by Boolean logical structure such as the presence or absence of a variable or an edge. Consequently, false-positive error or false-negative error can be specified as the number of variables/edges that are incorrectly included or excluded in an estimated model. However, there are several other problems such as ranking, clustering, and causal inference in which the associated model classes do not admit transparent notions of false-positive and false-negative errors due to the lack of an underlying Boolean logical structure. In this paper, we present a generic approach to endow a collection of models with partial order structure, which leads to a hierarchical organization of model classes as well as natural analogs of false-positive and false-negative errors. We describe model selection procedures that provide false-positive error control in our general setting, and we illustrate their utility with numerical experiments. [ABSTRACT FROM AUTHOR]

As the world moves away from fossil fuels, there is growing recognition of the need for a just transition of those working in carbon-intensive industries and for policy to support this transition. While recent policies such as the U.S. Inflation Reduction Act (IRA) have begun to incorporate support for energy-intensive regions, little work has thoroughly investigated which communities are most vulnerable to economic disruption in the energy transition and therefore require policy support. This paper analyzes the distribution of employment vulnerability in the U.S. by calculating the average "employment carbon footprint" of close-to every job in the U.S. economy at high geographic and sectoral granularity. The measure considers employment vulnerability across the entire economy and captures both fossil fuel consumption and production effects, with the sectors covered in our analysis accounting for 86% of total U.S. employment and 94% of U.S. carbon emissions outside of the transportation sector. We find that existing efforts to identify at-risk communities both in the literature and the IRA exclude regions of high employment vulnerability, and thereby risk leaving these communities behind in the energy transition. This work underscores the importance of proactive and continuous measures of employment vulnerability, presents policymakers with much-needed data to incorporate such measures into just transition policy and makes the case for place-based policy approaches when considering how best to support communities through the energy transition. [ABSTRACT FROM AUTHOR]

The loss of elastic stability (buckling) can lead to catastrophic failure in the context of traditional engineering structures. Conversely, in nature, buckling often serves a desirable function, such as in the prey-trapping mechanism of the Venus fly trap (Dionaea muscipula). This paper investigates the buckling-enabled sound production in the wingbeat-powered (aeroelastic) tymbals of Yponomeuta moths. The hindwings of Yponomeuta possess a striated band of ridges that snap through sequentially during the up- and downstroke of the wingbeat cycle--a process reminiscent of cellular buckling in compressed slender shells. As a result, bursts of ultrasonic clicks are produced that deter predators (i.e. bats). Using various biological and mechanical characterization techniques, we show that wing camber changes during the wingbeat cycle act as the single actuation mechanism that causes buckling to propagate sequentially through each stria on the tymbal. The snap-through of each stria excites a bald patch of the wing's membrane, thereby amplifying sound pressure levels and radiating sound at the resonant frequencies of the patch. In addition, the interaction of phased tymbal clicks from the two wings enhances the directivity of the acoustic signal strength, suggesting an improvement in acoustic protection. These findings unveil the acousto-mechanics of Yponomeuta tymbals and uncover their buckling-driven evolutionary origin. We anticipate that through bioinspiration, aeroelastic tymbals will encourage novel developments in the context of multi-stable morphing structures, acoustic structural monitoring, and soft robotics. [ABSTRACT FROM AUTHOR]

Atomically dispersed catalysts are a promising alternative to platinum group metal catalysts for catalyzing the oxygen reduction reaction (ORR), while limited durability during the electrocatalytic process severely restricts their practical application. Here, we report an atomically dispersed Co-doped carbon−nitrogen bilayer catalyst with unique dual-axial Co–C bonds (denoted as Co/DACN) by a smart phenyl-carbon-induced strategy, realizing highly efficient electrocatalytic ORR in both alkaline and acidic media. The corresponding half-wave potential for ORR is up to 0.85 and 0.77 V (vs. reversible hydrogen electrode (RHE)) in 0.5 M H2SO4 and 0.1 M KOH, respectively, representing the best ORR activity among all non-noble metal catalysts reported to date. Impressively, the Zn–air battery (ZAB) equipped with Co/DACN cathode achieves outstanding durability after 1,688 h operation at 10 mA cm−2 with a high current density (154.2 mA cm−2) and a peak power density (210.1 mW cm−2). Density functional theory calculations reveal that the unique dual-axial cross-linking Co−C bonds of Co/DACN significantly enhance the stability during ORR and also facilitate the 4e− ORR pathway by forming a joint electron pool due to the improved interlayer electron mobility. We believe that axial engineering opens a broad avenue to develop high-performance heterogeneous electrocatalysts for advanced energy conversion and storage. [ABSTRACT FROM AUTHOR]

During the last decades, macroecology has identified broad-scale patterns of abundances and diversity of microbial communities and put forward some potential explanations for them. However, these advances are not paralleled by a full understanding of the dynamical processes behind them. In particular, abundance fluctuations of different species are found to be correlated, both across time and across communities in metagenomic samples. Reproducing such correlations through appropriate population models remains an open challenge. The present paper tackles this problem and points to sparse species interactions as a necessary mechanism to account for them. Specifically, we discuss several possibilities to include interactions in population models and recognize Lotka-Volterra constants as a successful ansatz. For this, we design a Bayesian inference algorithm to extract sets of interaction constants able to reproduce empirical probability distributions of pairwise correlations for diverse biomes. Importantly, the inferred models still reproduce well-known single-species macroecological patterns concerning abundance fluctuations across both species and communities. Endorsed by the agreement with the empirically observed phenomenology, our analyses provide insights into the properties of the networks of microbial interactions, revealing that sparsity is a crucial feature. [ABSTRACT FROM AUTHOR]

Photoelectrochemical (PEC) carbon dioxide (CO2) reduction (CO2R) holds the potential to reduce the costs of solar fuel production by integrating CO2 utilization and light harvesting within one integrated device. However, the CO2R selectivity on the photocathode is limited by the lack of catalytic active sites and competition with the hydrogen evolution reaction. On the other hand, serious parasitic light absorption occurs on the front-side--illuminated photocathode due to the poor light transmittance of CO2R cocatalyst films, resulting in extremely low photocurrent density at the CO2R equilibrium potential. This paper describes the design and fabrication of a photocathode consisting of crystal phase-modulated Ag nanocrystal cocatalysts integrated on illumination-reaction decoupled heterojunction silicon (Si) substrate for the selective and efficient conversion of CO2. Ag nanocrystals containing unconventional hexagonal close-packed phases accelerate the charge transfer process in CO2R reaction, exhibiting excellent catalytic performance. Heterojunction Si substrate decouples light absorption from the CO2R catalyst layer, preventing the parasitic light absorption. The obtained photocathode exhibits a carbon monoxide (CO) Faradaic efficiency (FE) higher than 90% in a wide potential range, with the maximum FE reaching up to 97.4% at --0.2 V vs. reversible hydrogen electrode. At the CO2/CO equilibrium potential, a CO partial photocurrent density of -2.7 mA cm-2 with a CO FE of 96.5% is achieved in 0.1 M KHCO2 electrolyte on this photocathode, surpassing the expensive benchmark Au-based PEC CO2R system. [ABSTRACT FROM AUTHOR]

Noncoding transcription induces chromatin changes that can mediate environmental responsiveness, but the causes and consequences of these mechanisms are still unclear. Here, we investigate how antisense transcription (termed COOLAIR) interfaces with Polycomb Repressive Complex 2 (PRC2) silencing during winter-induced epigenetic regulation ofArabidopsis FLOWERING LOCUS C (FLC). We use genetic and chromatin analyses on lines ineffective or hyperactive for the antisense pathway in combination with computational modeling to define the mechanisms underlying FLC repression. Our results show that FLC is silenced through pathways that function with different dynamics: a COOLAIR transcription-mediated pathway capable of fast response and in parallel a slow PRC2 switching mechanism that maintains each allele in an epigenetically silenced state. Components of both the COOLAIR and PRC2 pathways are regulated by a common transcriptional regulator (NTL8), which accumulates by reduced dilution due to slow growth at low temperature. The parallel activities of the regulatory steps, and their control by temperature-dependent growth dynamics, create a flexible system for registering widely fluctuating natural temperature conditions that change year on year, and yet ensure robust epigenetic silencing of FLC. [ABSTRACT FROM AUTHOR]

The notion of common sense is invoked so frequently in contexts as diverse as everyday conversation, political debates, and evaluations of artificial intelligence that its meaning might be surmised to be unproblematic. Surprisingly, however, neither the intrinsic properties of common sense knowledge (what makes a claim commonsensical) nor the degree to which it is shared by people (its "commonness") have been characterized empirically. In this paper, we introduce an analytical framework for quantifying both these elements of common sense. First, we define the commonsensicality of individual claims and people in terms of the latter's propensity to agree on the former and their awareness of one another's agreement. Second, we formalize the commonness of common sense as a clique detection problem on a bipartite belief graph of people and claims, defining pq common sense as the fraction q of claims shared by a fraction p of people. Evaluating our framework on a dataset of 2,046 raters evaluating 4,407 diverse claims, we find that commonsensicality aligns most closely with plainly worded, fact-like statements about everyday physical reality. Psychometric attributes such as social perceptiveness influence individual common sense, but surprisingly demographic factors such as age or gender do not. Finally, we find that collective common sense is rare: At most, a small fraction p of people agree on more than a small fraction q of claims. Together, these results undercut universalistic beliefs about common sense and raise questions about its variability that are relevant both to human and artificial intelligence. [ABSTRACT FROM AUTHOR]

Aging in an individual refers to the temporal change, mostly decline, in the body's ability to meet physiological demands. Biological age (BA) is a biomarker of chronological aging and can be used to stratify populations to predict certain age-related chronic diseases. BA can be predicted from biomedical features such as brain MRI, retinal, or facial images, but the inherent heterogeneity in the aging process limits the usefulness of BA predicted from individual body systems. In this paper, we developed a multimodal Transformer-based architecture with cross-attention which was able to combine facial, tongue, and retinal images to estimate BA. We trained our model using facial, tongue, and retinal images from 11,223 healthy subjects and demonstrated that using a fusion of the three image modalities achieved the most accurate BA predictions. We validated our approach on a test population of 2,840 individuals with six chronic diseases and obtained significant difference between chronological age and BA (AgeDiff) than that of healthy subjects. We showed that AgeDiff has the potential to be utilized as a standalone biomarker or conjunctively alongside other known factors for risk stratification and progression prediction of chronic diseases. Our results therefore highlight the feasibility of using multimodal images to estimate and interrogate the aging process. [ABSTRACT FROM AUTHOR]

This paper examines whether school COVID-19 policies influenced enrollment differently by student age and race/ethnicity. Unlike much prior research, we i) analyze enrollments for virtually the entire U.S. public school population for both the 2020- 2021 and 2021-2022 school years, ii) compare enrollment trends within districts in order to isolate subgroup heterogeneity from district characteristics, and iii) account for district selection into preferred learning modes. Analyzing data on over 9,000 districts that serve more than 90% of public school students in the United States, we find enrollment responses to COVID policies differed notably. We find that White enrollments declined more than Black, Hispanic, and Asian enrollments in districts that started the 2020-2021 school year virtually, but in districts that started in-person the reverse was true: Non-White enrollments declined more than White enrollments. Moreover, Black, Hispanic, and Asian families responded more than White families to higher COVID-19 death rates in the months preceding the start of the 2021 school year. In 2021-2022, enrollment differences by the previous year's learning mode persisted. Racial/ethnic differences did not vary by whether the district required masking in classrooms. These findings are consistent with the greater risk faced by communities of color during the pandemic and demonstrate an additional source of disparate impact from COVID policies. [ABSTRACT FROM AUTHOR]

Concern over democratic erosion has led to a proliferation of proposed interventions to strengthen democratic attitudes in the United States. Resource constraints, however, prevent implementing all proposed interventions. One approach to identify promising interventions entails leveraging domain experts, who have knowledge regarding a given field, to forecast the effectiveness of candidate interventions. We recruit experts who develop general knowledge about a social problem (academics), experts who directly intervene on the problem (practitioners), and nonexperts from the public to forecast the effectiveness of interventions to reduce partisan animosity, support for undemocratic practices, and support for partisan violence. Comparing 14,076 forecasts submitted by 1,181 forecasters against the results of a megaexperiment (n = 32,059) that tested 75 hypothesized effects of interventions, we find that both types of experts outperformed members of the public, though experts differed in how they were accurate. While academics' predictions were more specific (i.e., they identified a larger proportion of ineffective interventions and had fewer false-positive forecasts), practitioners' predictions were more sensitive (i.e., they identified a larger proportion of effective interventions and had fewer false-negative forecasts). Consistent with this, practitioners were better at predicting best-performing interventions, while academics were superior in predicting which interventions performed worst. Our paper highlights the importance of differentiating types of experts and types of accuracy. We conclude by discussing factors that affect whether sensitive or specific forecasters are preferable, such as the relative cost of false positives and negatives and the expected rate of intervention success. [ABSTRACT FROM AUTHOR]

The genome of an individual from an admixed population consists of segments originated from different ancestral populations. Most existing ancestry inference approaches focus on calling these segments for the extant individual. In this paper, we present a general ancestry inference approach for inferring recent ancestors from an extant genome. Given the genome of an individual from a recently admixed population, our method can estimate the proportions of the genomes of the recent ancestors of this individual that originated from some ancestral populations. The key step of our method is the inference of ancestors (called founders) right after the formation of an admixed population. The inferred founders can then be used to infer the ancestry of recent ancestors of an extant individual. Our method is implemented in a computer program called PedMix2. To the best of our knowledge, there is no existing method that can practically infer ancestors beyond grandparents from an extant individual’s genome. Results on both simulated and real data show that PedMix2 performs well in ancestry inference. [ABSTRACT FROM AUTHOR]

Despite a sea of interpretability methods that can produce plausible explanations, the field has also empirically seen many failure cases of such methods. In light of these results, it remains unclear for practitioners how to use these methods and choose between them in a principled way. In this paper, we show that for moderately rich model classes (easily satisfied by neural networks), any feature attribution method that is complete and linear—for example, Integrated Gradients and Shapley Additive Explanations (SHAP)—can provably fail to improve on random guessing for inferring model behavior. Our results apply to common end-tasks such as characterizing local model behavior, identifying spurious features, and algorithmic recourse. One takeaway from our work is the importance of concretely defining end-tasks: Once such an end-task is defined, a simple and direct approach of repeated model evaluations can outperform many other complex feature attribution methods. [ABSTRACT FROM AUTHOR]

Networks allow us to describe a wide range of interaction phenomena that occur in complex systems arising in such diverse fields of knowledge as neuroscience, engineering, ecology, finance, and social sciences. Until very recently, the primary focus of network models and tools has been on describing the pairwise relationships between system entities. However, increasingly more studies indicate that polyadic or higher-order group relationships among multiple network entities may be the key toward better understanding of the intrinsic mechanisms behind the functionality of complex systems. Such group interactions can be, in turn, described in a holistic manner by simplicial complexes of graphs. Inspired by these recently emerging results on the utility of the simplicial geometry of complex networks for contagion propagation and armed with a large-scale synthetic social contact network (also known as a digital twin) of the population in the U.S. state of Virginia, in this paper, we aim to glean insights into the role of higher-order social interactions and the associated varying social group determinants on COVID-19 propagation and mitigation measures. [ABSTRACT FROM AUTHOR]

Many studies anticipate that carbon capture and sequestration (CCS) will be essential to decarbonizing the U.S. economy. However, prior work has not estimated the time required to develop, approve, and implement a geologic sequestration site in the United States. We generate such an estimate by identifying six clearance points that must be passed before a sequestration site can become operational. For each clearance point (CP), we elicit expert judgments of the time required in the form of probability distributions and then use stochastic simulation to combine and sum the results. We find that, on average, there is a 90% chance that the time required lies between 5.5 and 9.6 y, with an upper bound of 12 y. Even using the most optimistic expert judgements, the lower bound on time is 2.7 y, and the upper bound is 8.3 y. Using the most pessimistic judgements, the lower bound is 3.5 y and the upper bound is 19.2 y. These estimates suggest that strategies must be found to safely accelerate the process. We conclude the paper by discussing seven potential strategies. [ABSTRACT FROM AUTHOR]

This article explores the emergence of AI as a new frontier in behavioral science. It discusses a study that compares the decision-making of AI chatbots, specifically ChatGPT-3 and ChatGPT-4, with that of humans using classical behavioral assessments. The study reveals that AI models have distinct preferences and behaviors, leading to the development of a new research direction called "AI Behavioral Science." The article also examines the potential benefits and challenges of studying AI behavior, including its impact on human decision-making, bias correction, and policy design. It emphasizes the need for a comprehensive behavioral assessment framework and the engineering of AI behavior. Furthermore, the article discusses the potential impact of AI integration on human behavior and culture, such as algorithmic bias, cognitive decline, and the promotion of equality. The document includes references to various research papers and studies on biased programmers, biased data, AI ethics, recommender systems, social media, news consumption, and polarization, making it a valuable resource for library patrons researching these specific topics. [Extracted from the article]

This document is a correction for an article titled "Evidence of strain structure in Plasmodium falciparum var gene repertoires in children from Gabon, West Africa." The correction states that incorrect primers and conditions were used in the PCR amplification for var DBLα typing, which resulted in longer PCR products. The correct method, as published in a previous paper, should have been used. The correction does not affect the conclusions of the article. [Extracted from the article]

Tremendous attention has been paid to the water-associated side reactions and zinc (Zn) dendrite growth on the electrode-electrolyte interface. However, the Zn pulverization that can cause continuous depletion of active Zn metal and exacerbate hydrogen evolution is severely neglected. Here, we disclose that the excessive Zn feeding that causes incomplete crystallization is responsible for Zn pulverization formation through analyzing the thermodynamic and kinetics process of Zn deposition. On the basis, we introduce 1-ethyl-3-methylimidazolium cations (EMIm+) into the electrolyte to form a Galton-board-like three-dimensional inert-cation (3DIC) region. Modeling test shows that the 3DIC EMIm+ can induce the Zn2+ flux to follow in a Gauss distribution, thus acting as elastic sites to buffer the perpendicular diffusion of Zn2+ and direct the lateral diffusion, thus effectively avoiding the local Zn2+ accumulation and irreversible crystal formation. Consequently, anti-pulverized Zn metal deposition behavior is achieved with an average Coulombic efficiency of 99.6% at 5 mA cm-2 over 2,000 cycles and superb stability in symmetric cell over 1,200 h at -30 °C. Furthermore, the Zn||KVOH pouch cell can stably cycle over 1,200 cycles at 2 A g-1 and maintain a capacity of up to 12 mAh. [ABSTRACT FROM AUTHOR]

This document is a retraction notice published in the Proceedings of the National Academy of Sciences of the United States of America. The retraction is for a neuroscience paper titled "Neurexin-2 restricts synapse numbers and restrains the presynaptic release probability by an alternative splicing-dependent mechanism." The authors of the paper have retracted it due to discrepancies between the original raw data and the published data source file, as well as copy-paste errors and shifted data points in one of the figures. The retraction notice includes a thank you to Dr. Daniel Matus of Stanford University for independently analyzing the primary raw data. The article is distributed under a Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0. [Extracted from the article]

This document is a retraction notice from the authors of a medical sciences paper titled "Endothelial expression of hypoxia-inducible factor 1 protects the murine heart and aorta from pressure overload by suppression of TGF-β signaling." The authors state that they are retracting the paper due to concerns with the presentation of data in immunoblot assays. Specifically, there were issues with the use of different blots and splicing of lanes in the analysis of phosphorylated ERK1/2. The authors apologize for any inconvenience caused and note that they were unable to locate the raw data files from over 10 years ago. The retraction notice was published on February 26, 2024. [Extracted from the article]

This document is a correction for a scientific article titled "Proofreading does not result in more reliable ligand discrimination in receptor signaling due to its inherent stochasticity." The authors note that there were errors in Figures 2B and 4C, and they provide the corrected versions of these figures. The corrections do not affect the main results and conclusions of the paper. The authors express gratitude to individuals who alerted them to the errors. The corrected figures and their legends are included in the document. [Extracted from the article]

This document is a correction notice for an article titled "New voices for a better society" published in the Proceedings of the National Academy of Sciences of the United States of America. The correction adds Umut A. Gurkan to the list of authors and credits him with writing the paper. The corrected author line, affiliation line, and author contributions are provided. The article is distributed under a Creative Commons Attribution-NonCommercial-NoDerivatives License. [Extracted from the article]

The article is a response to a critique of a previous paper on scientific censorship. The authors clarify that their intention was to explain, not blame, and that they did not make claims about people from diverse backgrounds. They also address concerns about low response rates in one study and emphasize the need for more research. The authors argue for greater transparency and academic audits to identify discrimination and protect minority perspectives. They acknowledge the lack of data on the costs and benefits of censorship and caution against assuming that involving community members in research will eliminate harm-avoidant censorship. The authors disagree with the critique's demand for active participation of specific communities in all research, stating that it is impractical and unnecessarily restrictive. They conclude by highlighting the need for metascientific investigation to inform discussions on scientific censorship. [Extracted from the article]

This document is a reply to three letters from Muralidhar et al., Kenny et al., and Hotz et al. regarding a recent paper by Jarmin et al. The authors express gratitude for the feedback and engagement from these scholars, which has led to improvements in the Census Bureau's disclosure avoidance system. They emphasize the importance of continued discussion and debate to further benefit the Census Bureau and its statistical products. The authors provide their affiliations and state that they are employed by the U.S. Census Bureau, except for one author who is retired. The document is published under a Creative Commons Attribution License. [Extracted from the article]