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Many organisms leave evidence of their former occurrence, such as scat, abandoned burrows, middens, ancient eDNA or fossils, which indicate areas from which a species has since disappeared. However, combining this evidence with contemporary occurrences within a single modeling framework remains challenging. Traditional binary species‐distribution modeling reduces occurrence to two temporally coarse states (present/absent), so thus cannot leverage the information inherent in temporal sequences of evidence of past occurrence. In contrast, ordinal modeling can use the natural time‐varying order of states (e.g. never occupied versus previously occupied versus currently occupied) to provide greater insights into range shifts. We demonstrate the power of ordinal modeling for identifying the major influences of biogeographic and climatic variables on current and past occupancy of the American pikaOchotona princeps, a climate‐sensitive mammal. Sampling over five years across the species' southernmost, warm‐edge range limit, we tested the effects of these variables at 570 habitat patches where occurrence was classified either as binary or ordinal. The two analyses produced different top models and predictors – ordinal modeling highlighted chronic cold as the most‐important predictor of occurrence, whereas binary modeling indicated primacy of average summer‐long temperatures. Colder wintertime temperatures were associated in ordinal models with higher likelihood of occurrence, which we hypothesize reflect longer retention of insulative and meltwater‐provisioning snowpacks. Our binary results mirrored those of other past pika investigations employing binary analysis, wherein warmer temperatures decrease likelihood of occurrence. Because both ordinal‐ and binary‐analysis top models included climatic and biogeographic factors, results constitute important considerations for climate‐adaptation planning. Cross‐time evidences of species occurrences remain underutilized for assessing responses to climate change. Compared to multi‐state occupancy modeling, which presumes all states occur in the same time period, ordinal models enable use of historical evidence of species' occurrence to identify factors driving species' distributions more finely across time. 

Abstract Most fine ambient particulate matter (PM_2.5)-based epidemiological models use globalized concentration-response (CR) functions assuming that the toxicity of PM_2.5is solely mass-dependent without considering its chemical composition. Although oxidative potential (OP) has emerged as an alternate metric of PM_2.5toxicity, the association between PM_2.5mass and OP on a large spatial extent has not been investigated. In this study, we evaluate this relationship using 385 PM_2.5samples collected from 14 different sites across 4 different continents and using 5 different OP (and cytotoxicity) endpoints. Our results show that the relationship between PM_2.5mass vs. OP (and cytotoxicity) is largely non-linear due to significant differences in the intrinsic toxicity, resulting from a spatially heterogeneous chemical composition of PM_2.5. These results emphasize the need to develop localized CR functions incorporating other measures of PM_2.5properties (e.g., OP) to better predict the PM_2.5-attributed health burdens. 

Abstract Air pollution in Africa is a significant public health issue responsible for 1.1 million premature deaths annually. Sub-Saharan Africa has the highest rate of population growth and urbanization of any region in the world, with substantial potential for future emission growth and worsening air quality. Accurate and extensive observations of meteorology and atmospheric composition have underpinned successful air pollution mitigation strategies in the Global North, yet Africa in general and East Africa in particular remain among the most sparsely observed regions in the world. This paper is based on the discussion of these issues during two international workshops, one held virtually in the United States in July 2021 and one in Kigali, Rwanda, in January 2023. The workshops were designed to develop a measurement, capacity building, and collaboration strategy to improve air quality-relevant measurements, modeling, and data availability in East Africa. This paper frames the relevant scientific needs and describes the requirements for training and infrastructure development for an integrated observing and modeling strategy that includes partnerships between East African scientists and organizations and their counterparts in the developed world. 

Beliefs teachers hold influence the judgments they make about their students, and opportunities they provide for engaging them in rigorous mathematics. While math-related beliefs have been widely studied, less is known about teachers’ attributional beliefs (i.e., beliefs about people’s actions or behaviors) for mathematical success. In this study we investigated in-service elementary teachers’ stated beliefs about mathematical success. Findings show that teachers attribute mathematical success to factors that are both internal and external to the student. Although teachers explicitly stated that race and gender were not factors, many used descriptors that served as proxies for students’ demographic markers. 

This paper presents a framework based on either iterative simulation or iterative experimentation for constructing an optimal, open-loop maneuver to regulate the aerodynamic force on a wing in the presence of a known flow disturbance. The authors refer to the method as iterative maneuver optimization and apply it in this paper to regulate lift on a pitching wing during a transverse gust encounter. A candidate maneuver is created by performing an optimal control calculation on a surrogate model of the wing–gust interaction. Execution of the proposed maneuver in a high-fidelity simulation or experiment provides an error signal based on the difference between the force predicted by the surrogate model and the measured force. The error signal provides an update to the reference signal used by the surrogate model for tracking. A new candidate maneuver is calculated such that the surrogate model tracks the reference force signal, and the process repeats until the maneuver adequately regulates the force. The framework for iterative maneuver optimization is tested on a discrete vortex model as well as in experiments in a water towing tank. Experimental results show that the proposed framework generates a maneuver that reduces the magnitude of lift overshoot by 92% for a trapezoidal gust with peak velocity equal to approximately 0.7 times the freestream flow speed. 

This paper experimentally investigates the flow field development and unsteady loading of three force-mitigating pitch manoeuvres during a transverse gust encounter. The manoeuvres are constructed using varying levels of theoretical and simulation fidelity and implemented as open-loop kinematics in a water towing tank. It is found that pitch actuation during a gust encounter results in two important changes in flow topology: (i) early detachment of the leading-edge vortex (LEV) and (ii) formation of an LEV on the pressure side of the wing upon gust exit. Each of the pitch manoeuvres is found to mitigate a significant portion of the circulatory contribution of the lift force while only manoeuvres with accurate modelling of the added-mass force are found to adequately mitigate the total lift force. The penalty of aerodynamic lift mitigation using pitch manoeuvres was a twofold increase in the pitching moment transients experienced by the wing for all cases. By quantifying changes in the vertical gust momentum before and after the encounter, lift-mitigating manoeuvres were found to reduce the disturbance to the gust's flow field, thereby reducing the momentum exchange between the gust and the wing.