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Recent work suggests combining physical activity with cognitive tasks may have been critical to human evolution and may be beneficial to human brain health today. These combined tasks are key elements of foraging, a lifestyle employed by human ancestors for over 2 My. However, it is unclear whether cognitive engagement during foraging-like tasks impacts endurance, and therefore foraging performance, and whether cognitive adaptations may mitigate these effects. We tested the hypothesis that cognitive engagement during endurance walking increases perceived physical effort without influencing physiological responses, and that enhanced cognition mitigates these effects. Thirty healthy adults (n_female= 17; aged 18 to 53) underwent nonlocomotor cognitive testing and completed two separate randomized endurance tests: one without (Ex) and one with simultaneous executive function tasks (ExCog). For each condition, participants walked on a treadmill for up to 30-min while physiological responses were recorded, and perception of effort was assessed every 2-min using Borg’s rating of perceived exertion (RPE) scale. During the ExCog condition, RPE was significantly greater (P= 0.005), while energy expenditure was significantly lower (P= 0.008) compared to the Ex condition. Additionally, we observed significant interactions between cognitive abilities and endurance performance—for example, individuals with greater visuospatial abilities experienced a smaller increase in perceived effort (RPE) in the ExCog condition compared to the Ex condition (FDRP= 0.039). These results indicate that cognitive demands and cognitive abilities associated with foraging distinctly influence endurance, suggesting that evolutionary shifts in human cognitive capacities may have relaxed constraints on endurance foraging performance. 

Abstract Neutron tagging is a fundamental technique for electron anti-neutrino detection via the inverse beta decay channel. A reported discrepancy in neutron detection efficiency between observational data and simulation predictions prompted an investigation into neutron capture modeling in Geant4. The study revealed that an overestimation of the thermal motion of hydrogen atoms in Geant4 impacts the fraction of captured nuclei. By manually modifying the Geant4 implementation, the simulation results align with calculations based on evaluated nuclear data and show good agreement with observables derived from the SK-Gd data. 

Neutral atom arrays have become a promising platform for quantum computing, especially the field programmable qubit array (FPQA) endowed with the unique capability of atom movement. This feature allows dynamic alterations in qubit connectivity during runtime, which can reduce the cost of executing long-range gates and improve parallelism. However, this added flexibility introduces new challenges in circuit compilation. Inspired by the placement and routing strategies for FPGAs, we propose to map all data qubits to fixed atoms while utilizing movable atoms to route for 2-qubit gates between data qubits. Coined flying ancillas, these mobile atoms function as ancilla qubits, dynamically generated and recycled during execution. We present Q-Pilot, a scalable compiler for FPQA employing flying ancillas to maximize circuit parallelism. For two important quantum applications, quantum simulation and the Quantum Approximate Optimization Algorithm (QAOA), we devise domain-specific routing strategies. In comparison to alternative technologies such as superconducting devices or fixed atom arrays, Q-Pilot effectively harnesses the flexibility of FPQA, achieving reductions of 1.4x, 27.7x, and 6.3x in circuit depth for 100-qubit random, quantum simulation, and QAOA circuits, respectively. 

Abstract Vast amounts of carbon are stored beneath the seafloor in the form of methane hydrate. Hydrate is stable at moderate pressure and low temperature at a depth extending several hundred meters beneath the seafloor to the base of gas hydrate stability (BGHS) often marked by bottom simulating reflections (BSRs) in seismic profiles. However, data from logging‐while‐drilling and coring during Integrated Ocean Discovery Program Expeditions 372 and 375 offshore New Zealand identified hydrate ∼60 m beneath the BSR. This hydrate appears to be dissociating over thousands of years following a gradual temperature increase from sediment burial modulated by changes in bottom‐water temperature and sea‐level fluctuations. Slow hydrate dissociation significantly buffers the release of methane and therefore, carbon through glacial cycles. Dissociating hydrate beneath the BGHS may also increase estimated global budgets of methane stored in hydrate. 

The daytime oxidation of biogenic hydrocarbons is attributed to both OH radicals and O3, while nighttime chemistry is dominated by the reaction with O3 and NO3 radicals. Here, the diurnal pattern of Secondary Organic Aerosol (SOA) originating from biogenic hydrocarbons was intensively evaluated under varying environmental conditions (temperature, humidity, sunlight intensity, NOx levels, and seed conditions) by using the UNIfied Partitioning Aerosol phase Reaction (UNIPAR) model, which comprises multiphase gas-particle partitioning and in-particle chemistry. The oxidized products of three different hydrocarbons (isoprene, α-pinene, and β-caryophyllene) were predicted by using near explicit gas mechanisms for four different oxidation paths (OH, O3, NO3, and O(3P)) during day and night. The gas mechanisms implemented the Master Chemical Mechanism (MCM v3.3.1), the reactions that formed low volatility products via peroxy radical (RO2) autoxidation, and self- and cross-reactions of nitrate-origin RO2. In the model, oxygenated products were then classified into volatility-reactivity base lumping species, which were dynamically constructed under varying NOx levels and aging scales. To increase feasibility, the UNIPAR model that equipped mathematical equations for stoichiometric coefficients and physicochemical parameters of lumping species was integrated with the SAPRC gas mechanism. The predictability of the UNIPAR model was demonstrated by simulating chamber-generated SOA data under varying environments day and night. Overall, the SOA simulation decoupled to each oxidation path indicated that the nighttime isoprene SOA formation was dominated by the NO3-driven oxidation, regardless of NOx levels. However, the oxidation path to produce the nighttime α-pinene SOA gradually transited from the NO3-initiated reaction to ozonolysis as NOx levels decreased. For daytime SOA formation, both isoprene and α-pinene were dominated by the OH-radical initiated oxidation. The contribution of the O(3P) path to all biogenic SOA formation was negligible in daytime. Sunlight during daytime promotes the decomposition of oxidized products via photolysis and thus, reduces SOA yields. Nighttime α-pinene SOA yields were significantly higher than daytime SOA yields, although the nighttime α-pinene SOA yields gradually decreased with decreasing NOx levels. For isoprene, nighttime chemistry yielded higher SOA mass than daytime at the higher NOx level (isoprene/NOx > 5 ppbC/ppb). The daytime isoprene oxidation at the low NOx level formed epoxy-diols that significantly contributed SOA formation via heterogeneous chemistry. For isoprene and α-pinene, daytime SOA yields gradually increased with decreasing NOx levels. The daytime SOA produced more highly oxidized multifunctional products and thus, it was generally more sensitive to the aqueous reactions than the nighttime SOA. β-Caryophyllene, which rapidly oxidized and produced SOA with high yields, showed a relatively small variation in SOA yields from changes in environmental conditions (i.e., NOx levels, seed conditions, and diurnal pattern), and its SOA formation was mainly attributed to ozonolysis day and night. To mimic the nighttime α-pinene SOA formation under the polluted urban atmosphere, α-pinene SOA formation was simulated in the presence of gasoline fuel. The simulation suggested the growth of α-pinene SOA in the presence of gasoline fuel gas by the enhancement of the ozonolysis path under the excess amount of ozone, which is typical in urban air. We concluded that the oxidation of the biogenic hydrocarbon with O3 or NO3 radicals is a source to produce a sizable amount of nocturnal SOA, despite of the low emission at night. 

The prediction of Secondary Organic Aerosol (SOA) in regional scales is traditionally performed by using gas-particle partitioning models. In the presence of inorganic salted wet aerosols, aqueous reactions of semivolatile organic compounds can also significantly contribute to SOA formation. The UNIfied Partitioning-Aerosol phase Reaction (UNIPAR) model utilizes the explicit gas mechanism to better predict SOA formation from multiphase reactions of hydrocarbons. In this work, the UNIPAR model was incorporated with the Comprehensive Air Quality Model with Extensions (CAMx) to predict the ambient concentration of organic matter (OM) in urban atmospheres during the Korean-United States Air Quality (2016 KORUS-AQ) campaign. The SOA mass predicted with the CAMx-UNIPAR model changed with varying levels of humidity and emissions and in turn, has the potential to improve the accuracy of OM simulations. The CAMx-UNIPAR model significantly improved the simulation of SOA formation under the wet condition, which often occurred during the KORUS-AQ campaign, through the consideration of aqueous reactions of reactive organic species and gas-aqueous partitioning. The contribution of aromatic SOA to total OM was significant during the low-level transport/haze period (24-31 May 2016) because aromatic oxygenated products are hydrophilic and reactive in aqueous aerosols. The OM mass predicted with the CAMx-UNIPAR model was compared with that predicted with the CAMx model integrated with the conventional two product model (SOAP). Based on estimated statistical parameters to predict OM mass, the performance of CAMx-UNIPAR was noticeably better than the conventional CAMx model although both SOA models underestimated OM compared to observed values, possibly due to missing precursor hydrocarbons such as sesquiterpenes, alkanes, and intermediate VOCs. The CAMx-UNIPAR model simulation suggested that in the urban areas of South Korea, terpene and anthropogenic emissions significantly contribute to SOA formation while isoprene SOA minimally impacts SOA formation.