Oregon State University

Physics, as a discipline, has long struggled with pervasive stereotypes and biases about who is capable and can excel in it. Physics also ranks among the least diverse among all science, technology, engineering, and mathematics (STEM) disciplines, often cultivating and fostering learning environments that lack inclusivity and equity. Moreover, stereotypes about brilliance, inequitable physics learning environments and the overall physics culture not only impact the experiences and outcomes of students who major in physics, but also those from other STEM disciplines who must take physics courses. Here we undertake a narrative review, delving into research concerning diversity, equity, and inclusion within undergraduate physics education. We concentrate on the experiences of women and persons excluded due to their ethnicity or race in physics, aiming to shed light on the alarming current situation. The review begins with a few concrete examples of exclusionary experiences that research shows are common for women in physics and can reduce their interest or motivation to pursue a physics major. Then, we provide our conceptualization of equity in physics learning environments and describe the frameworks informing the perspective taken in the review. We then discuss issues related to inequities in physics learning environments, including but not limited to inequities in academic performance, participation, and persistence in physics, as well as psychological factors such as physics self-efficacy, perceived recognition, social belonging, mindset beliefs, and others. We also review research on factors commonly associated with the lack of diversity, equity, and inclusion in physics including the lack of role models, stereotypes associating physics with brilliance, and the overall prototypical culture of physics. We emphasize that addressing these systemic issues in physics requires a holistic approach. We conclude with a list of recommendations for physics departments and instructors on how they can play an important role in transforming the physics culture and making the learning environments equitable and inclusive so that all students can engage in learning physics and enjoy it while feeling supported.

Tropical peat swamp forests provide many important ecosystem services, especially their function as global carbon sinks. These carbon‐rich wetlands are widespread in South America, yet few studies have examined carbon stocks or losses due to land use change. In the lower Amazon, they are being converted to pastures largely utilized by domestic water buffalo (Bubalus bubalis). We quantified carbon stocks in intact peat forests and recently converted pastures (<10 years) at the Lago Piratuba Biosphere Reserve (LPBR) in the lower Amazon of Brazil. The soils of intact forests were typified by shallow organic (peat) horizons at the soil surface. The mean total ecosystem carbon stock (TECS) in intact forests was 354 ± 28 Mg C ha⁻¹. In contrast, the TECS of disturbed sites was significantly lower (p = 0.02) with a mean of 248 ± 17 Mg C ha⁻¹. We estimated greenhouse gas (GHG) emissions from water buffalo (due to enteric fermentation and manure deposition) to be 7.5 Mg CO2e ha⁻¹ year⁻¹. Considering GHG emissions from this land use, the social carbon costs (SCCs) arising from the degradation of coastal Amazon peatlands are as high as US$2742 ha⁻¹ year⁻¹. The SCC of meat produced from this land use is as high as US$100/kg of meat produced, which far exceeds the economic returns from livestock. Based on the estimated numbers of water buffalo for the southern portion of the LPBR and the time since initial disturbance, the annual GHG emissions from this land use are estimated to be 602,846 Mg CO2e year⁻¹ with an SCC as high as US$111,526,524 million year⁻¹. This land use also eliminates opportunity values and services of carbon storage and biodiversity that would be possible from a regenerating biosphere reserve.

Science is increasingly dependent on large teams working well together. Co-creating knowledge in this way, usually across disciplines and institutions, requires team members to feel comfortable taking interpersonal risks with each other; in other words, to have what is known as “psychological safety”. Although the importance of psychological safety for team functioning is increasingly well understood, the behaviours necessary to foster psychological safety are harder to define. We suggest that science facilitation expertise offers a path forward for scientific teams—particularly through the integration of outside facilitators or team members taking on the facilitation role—to identify dynamics that can promote or curtail psychological safety, interpret those dynamics accurately, and intervene appropriately to shift a group towards greater psychological safety. We describe how specific practices can support this cycle of observation, interpretation, and action to promote psychological safety across the team process and at key moments. We conclude with ideas for how research teams might embed these facilitation practices into their work, and how institutions can drive more widespread recognition and development of the expertise needed to cultivate psychologically safe scientific teams.

Interruption of frequent burning in dry forests across western North America and the continued impacts of anthropogenic climate change have resulted in increases in fire size and severity compared to historical fire regimes. Recent legislation, funding, and planning have emphasized increased implementation of mechanical thinning and prescribed burning treatments to decrease the risk of undesirable ecological and social outcomes due to fire. As wildfires and treatments continue to interact, managers require consistent approaches to evaluate treatment effectiveness at moderating burn severity. In this study, we present a repeatable, remote sensing–based, analytical framework for conducting fire‐scale assessments of treatment effectiveness that informs local management while also supporting cross‐fire comparisons. We demonstrate this framework on the 2021 Bootleg Fire in Oregon and the 2021 Schneider Springs Fire in Washington. Our framework used (1) machine learning to identify key bioclimatic, topographic, and fire weather drivers of burn severity in each fire, (2) standardized workflows to statistically sample untreated control units, and (3) spatial regression modeling to evaluate the effects of treatment type and time since treatment on burn severity. The application of our framework showed that, in both fires, recent prescribed burning treatments were the most effective at reducing burn severity relative to untreated controls. In contrast, thinning‐only treatments only produced low/moderate‐severity effects under the more moderate fire weather conditions in the Schneider Springs Fire. Our framework offers a robust approach for evaluating treatment effects on burn severity at the scale of individual fires, which can be scaled up to assess treatment effectiveness across multiple fires. As climate change brings increased uncertainty to dry forest ecosystems of western North America, our framework can support more strategic management actions to reduce wildfire risk and foster resilience.

Many frequency-based electronic measurement applications require a sinusoidal stimulus with high linearity, such for accurate impedance measurement systems used in chemistry, biology, and physical sensing. In this work, we present a highly linear sinusoidal-signal generator (SSG) on chip for use in such impedance measurement systems. Building upon prior digital SSG approaches that use a digital multi-stage noise-shaping (MASH) modulator to achieve high linearity while using a small digital-to-analog converter (DAC), we introduce delta-sigma modulation directly to the look-up table, achieving similarly high linearity without requiring a MASH modulator in the signal chain, which adds both design complexity and in-band errors. A prototype integrated circuit was fabricated using 180 nm CMOS and measured while generating a 20 kHz, 140 mVpp sine wave. It achieves 0.088% THD through the 20th harmonic and 63.5 dB SFDR. The approach is highly digital in nature and therefore amenable to implementation using automated synthesis and place and route, which makes it a promising approach for future scalability in advanced CMOS process nodes.

This paper presents a 3rd-order continuous-time (CT) incremental ADC that uses a pseudo-differential current-controlled-oscillator quantizer (CCOQ). The approach combines the complementary aspects of CCO-based quantization and incremental ADC operation. The CCOQ, used as a frequency quantizer, improves the efficiency of high-order incremental operation as it provides multi-bit quantization, intrinsic dynamic element matching, and an additional order of residual accumulation. At the same time, the CCOQ conveniently does not require reset in the analog domain, thus simplifying oscillator design. A prototype IC was fabricated in 180 nm CMOS process. Clocked at 3.2 MHz with a Nyquist sampling rate of 50 kHz, based on measurements it achieves 87.1 dB SNDR, 99.1 dB SFDR, and 89.7 dB DR and consumes 204 μ W at 1.4 V supply. This results in a competitive 168 dB SNDR-based Schreier FoM, and it demonstrates the potential for leveraging CCOQ benefits within an IADC topology.

Hydrokinetic turbine (HKT) shows promise as a renewable energy source, but high maintenance costs and low energy output hinder their widespread adoption. Limited literature investigates HKT electric drivetrain designs, resulting in a knowledge gap towards increasing generation efficiency and lowering cost. Multi-physics and multi-timescale modeling of HKT energy conversion system focusing on power converters is an essential tool to be developed. This paper first presents an integrated HKT energy conversion system using a MATLAB average model that incorporates electrical, mechanical, and thermal domains as well as aging behaviors across different time frames, such as fixed-point and mission profiles. A power electronics switching enabled PLECS model is then introduced, including maximum power point tracking control for the HKT, d-q reference framed modeling for the AC-DC-AC power converters, and a dynamic thermal framework, all together to predict fast transients and accurately maintain system stability. The developed models facilitate component-level optimization and improve the integrated performance of the system. Average and dynamic multi-physics models are validated through hardware experiments, hardware-in-the-loop testing, and various simulations.

Eastern filbert blight (EFB) and pacific flatheaded borer (PFB) are two problems of Pacific Northwest orchard and nursery production. Fungicides and insecticides used to manage these issues are typically applied to plant tissues with minimal foliage present that can result in considerable spray waste or drift. The Intelligent Spray System (ISS) is a laser-guided, variable-rate sprayer that detects objects in the target zone and releases spray volumes proportional to the density of plant tissues, thereby increasing application efficiency and reducing waste. However, the ISS has not been tested when targeting low-foliage plant tissues such as emerging shoots and trunks. Three experiments were conducted from 2018 to 2021 to evaluate the potential use of the ISS for EFB and PFB management by assessing spray coverage on emerging hazelnut shoot tips, hazelnut tree trunks, and maple tree trunks. On hazelnut shoot tips, coverage was <10% of the shoot on both adaxial and abaxial sides, with the highest coverage on the adaxial side (9.5%) resulting from spraying in standard mode (no sensors) at 3.1 kph. On hazelnut trunks, application at the slowest tested speed (3.1 kph) in intelligent mode resulted in spray coverage greater than or equal to that applied in standard mode at 5.1 kph. In addition, coverage was significantly higher on cards placed on the ground between trees when the sprayer was used in standard mode, indicating higher amounts of wasted spray and drift over intelligent mode. On maple trunks, the slowest speed tested (3.1 kph) resulted in the highest coverage of tree trunks facing the sprayer that were two and three rows away from the sprayer, with the highest coverage levels on the row of trees closest to the sprayer occurring at the highest tested speed of 6.4 kph. On cards placed on trunk sides not facing the sprayer, the slowest tested speed of 3.2 kph resulted in significantly higher coverage than both treatments at 6.4 kph and intelligent mode at 4.8 kph in the tree row closest to the sprayer. This work has demonstrated a baseline of coverage that hazelnut buds receive when spraying for EFB, illustrates that the ISS was able to effectively target trunks, and could be an alternative to drenches for PFB control.

Chapter 5, by Sullivan et al, discusses the complexities of the interplay of groundwater and Critical Zone dynamics. Water—and especially groundwater—is one of the “pillars” of Critical Zone functioning. Groundwater, both in the saturated and unsaturated layers, controls the dynamics of many terrestrial ecosystems and it is crucial to humans as a primary source of freshwater. Here they explore how the structure of the CZ interacts with groundwater to regulate recharge, evapotranspiration, groundwater-surface water interactions, groundwater flow paths (even km deep), chemical weathering, interbasin groundwater flow, and finally coastal and submarine groundwater discharge dynamics. Altogether they provide a holistic understanding of how CZ processes and structure help to regulate one of Earth's most vital resources.

Long before the term ‘critical zone’ (CZ) was coined to encompass Earth’s biological and geological features from the top of the vegetative canopy to the depths of circulating groundwater, many scientists have recognized that both biotic and abiotic actors are centrally important for understanding many of Earth’s most fundamental processes. Contemporary CZ scientists continue this legacy. We describe findings that emphasize how life, emphasizing vegetation and microbes, responds to and shapes the physical environment in which it persists, yielding feedbacks for Earth’s climate, primarily through modifications to hydrologic functioning. We focus on the interactions of biota and the physical and chemical features of soil pedons and landscapes as they drive ecosystem-scale hydrologic fluxes. We focus on hydrologically-relevant features because of the long history of individual disciplines telling us about the large-scale importance of these processes, and because of emerging research highlighting the importance of the intersection of these disciplines for projecting future ecosystem functioning on a rapidly changing Earth. The knowledge we spotlight reveals Earth’s CZ as a fundamentally ecological problem.

The influence of substrate homogenization on the taxonomic structure of benthic macroinvertebrate assemblages is well known worldwide. However, understanding the response thresholds of macroinvertebrate assemblages to a fine sediment deposition gradient is rarely reported for neotropical regions. Furthermore, most studies focus on taxonomic indicators, without considering the functional aspects of benthic macroinvertebrates. Therefore, we used taxonomic and functional analyses to assess the threshold responses of macroinvertebrate assemblages to fine sediments in 40 neotropical savanna streams in the hydrological unit of the Furnas hydropower reservoir. We found that stream locations with increased fine sediment supported lower taxonomic and functional composition, negatively selecting for the functional traits of gill respiration and flattened and streamlined body shape. In contrast, integument respiration and spherical body characterized macroinvertebrates positively associated with fine sediments. We also found that taxonomic (Shannon and Simpson indices) and functional (functional richness and functional evenness) indicators were sensitive to habitat homogenization resulting from increased fine sediments. We strongly recommend that energy companies monitor hydropower basins by identifying areas with accumulations of fine sediments, using the taxonomic and functional components of macroinvertebrates in the biomonitoring of neotropical streams. This information is of critical importance for future rehabilitation efforts to avoid siltation of tropical hydropower dams. Besides intense unplanned urbanization and agriculture, the climate crisis is predicted to increase intense tropical rains and sediment transport in headwater streams. Benthic structure and functional composition are early warning signals of environmental degradation and important indicators for long-term monitoring and rehabilitation investments worldwide.

We use a combination of primary and secondary data to investigate and quantify the impacts of the COVID-19 pandemic on the California specialty crop sector. We demonstrate that the specialty crop sector was highly resilient during the pandemic and aftermath in terms of output. For many crops, production fell somewhat between 2019 and 2021, but not to an extent that is outside of normal annual variation for fruits and vegetables. However, prices increased dramatically for many commodities. Contrary to conventional wisdom, most input costs did not surge during the pandemic, and some fell. But both the primary and secondary data identify labor and truck transportation as the major issues facing producers and driving up prices. Trade associations played a vital role in disseminating solutions to growers throughout the pandemic.

Many integrable stochastic particle systems in one space dimension (such as TASEP—Totally Asymmetric Simple Exclusion Process—and its q-deformation, the q-TASEP) remain integrable if we equip each particle with its own speed parameter. In this work, we present intertwining relations between Markov transition operators of particle systems which differ by a permutation of the speed parameters. These relations generalize our previous works (Petrov and Saenz in Probab Theory Relat Fields 182:481–530, 2022), (Petrov in SIGMA 17(021):34, 2021), but here we employ a novel approach based on the Yang-Baxter equation for the higher spin stochastic six vertex model. Our intertwiners are Markov transition operators, which leads to interesting probabilistic consequences. First, we obtain a new Lax-type differential equation for the Markov transition semigroups of homogeneous, continuous-time versions of our particle systems. Our Lax equation encodes the time evolution of multipoint observables of the q-TASEP and TASEP in a unified way, which may be of interest for the asymptotic analysis of multipoint observables of these systems. Second, we show that our intertwining relations lead to couplings between probability measures on trajectories of particle systems which differ by a permutation of the speed parameters. The conditional distribution for such a coupling is realized as a “rewriting history” random walk which randomly resamples the trajectory of a particle in a chamber determined by the trajectories of the neighboring particles. As a byproduct, we construct a new coupling for standard Poisson processes on the positive real half-line with different rates.

High‐resolution tri‐axial accelerometry biologging tags have quantitatively described behaviors in baleen whale species that forage using lunges and continuous ram filtration. However, detailed quantitative descriptions of foraging behaviors do not exist for gray whales, a unique baleen whale species that primarily uses benthic suction feeding with a rolling component. We deployed suction cup biologging tags on Pacific Coast Feeding Group (PCFG) gray whales to quantify foraging behavior at the broad state (dive) and foraging tactic (roll event) scales. Hidden Markov models were used to describe three distinct states using turn angle, dive duration, pseudotrack tortuosity, and presence of roll events that can be interpreted as forage, search, and transit behavior. Classification and Regression Tree models best described foraging tactics (headstands, benthic digs, and side swims) using median pitch, depth to total length ratio, and absolute value of the median roll. On average, PCFG gray whales spent more time searching and performed more left‐rolled foraging tactics at shallower depths at night compared to during the day, potentially to track prey above them in the water column. Describing foraging behavior in PCFG gray whales enables examination of links between behavioral budgets, energetics, and the physiological impact of threats facing this group.