University of Nevada, Reno

Numerous toxic substances are directly and indirectly discharged by humans into water bodies, causing distress to the organisms living on it. 6PPD, an amino antioxidant from tires reacts with ozone to form 6PPD-Q, which has garnered global attention due to its lethal nature to various organisms. This review aims to provide an understanding of the sources, transformation, and fate of 6PPD-Q in water and the current knowledge on its effects on aquatic organisms. Furthermore, we discuss research gaps pertaining to the mechanisms by which 6PPD-Q acts within fish bodies. Previous studies have demonstrated the ubiquitous presence of 6PPD-Q in the environment, including air, water, and soil. Moreover, this compound has shown high lethality to certain fish species while not affecting others. Toxicological studies have revealed its impact on the nervous system, intestinal barrier function, cardiac function, equilibrium loss, and oxidative stress in various fish species. Additionally, exposure to 6PPD-Q has led to organ injury, lipid accumulation, and cytokine production in C. elegans and mice. Despite studies elucidating the lethal dose and effects of 6PPD-Q in fish species, the underlying mechanisms behind these symptoms remain unclear. Future studies should prioritize investigating the mechanisms underlying the lethality of 6PPD-Q in fish species to gain a better understanding of its potential effects on different organisms.

Multispectral mapping data from the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) provide a unique opportunity to characterize south polar ice deposits at higher spectral sampling, spatial resolution, or spatiotemporal coverage than previous work. This new perspective can help constrain the nature and distribution of different mixtures of CO2 ice, H2O ice, and dust that influence the formation, evolution, and preservation of Mars climate records. We processed 1,103 CRISM observations spanning the southern summer of six Mars Years (MYs) through a combination of k‐means clustering and random forest classification. Using a set of 12 spectral endmembers directly tied to previous work with high‐resolution CRISM targeted data, we made a series of temporally restricted mosaics showing surface spectral variation over time. The mosaics show the effects of the MY 28 dust storm on the removal of the seasonal CO2 ice cap that year and reveal how this process differed from the years that followed. A mosaic showing residual ice surfaces displays broad agreement with previous compositional maps while resolving new details in the distribution of H2O ice‐rich material around the periphery of the bright CO2 ice cap. By showing how surface composition varies across a broad swath of the south polar region through time, the endmember set and classified mosaics produced in this work can provide critical context for future studies of the dynamic processes that shape south polar ice deposits.

Given the multitude of factors to consider, selecting a home to buy or rent is a significant decision, and consumer behaviour plays a crucial role in this process. This study aims to shed light on consumer needs, choices, and preferences that influence the decision making of homebuyers in Islamabad, Pakistan. To achieve this objective, a questionnaire was designed that incorporated factors extracted from existing literature on household needs, neighbourhood characteristics, consumer engagement and marketing factors, and investment determinants. Data was collected from 450 households in selected housing schemes in Islamabad, Pakistan, using a random sampling technique. Descriptive analysis, Kendell's W, and chi-square tests to understand needs, choices, and preferences. Analysis revealed that water availability and a proper drainage system were critical factors consumers consider when purchasing a property, followed by the proximity to public transport, workplaces , shopping centres, and airports. The results indicate that billboard marketing significantly impacted people's decision to purchase a particular property, followed by social media, the brand reputation of the developer/builder, marketing through television channels, and newspaper advertisements. Regarding investment determinants, affordability was the most critical factor that consumers considered when making a purchasing decision.

On January 6th, 2021, a mob of more than 2,000 Trump supporters stormed the Capital—at his urging—in an effort to halt counting of electoral college votes from the 2020 Presidential Election. Vandalism, injury, and loss of life ensued. Although the actions of Trump and the insurrectionists were alarming, the structural factors that gave rise to this offense are arguably even more troubling. In this paper, we outline three “criminogenic antecedents” that provided individual actors an opportunity to incite insurrection: (1) a lack of clarity and consensus in conceptualizations of crime, which has resulted in an ambiguous, contentious, and limited foundation from which to respond to crimes of the powerful; (2) a resultant pattern of symbolic punishments that fails to control these offenses; and (3) Congressional deviance, which virtually ensures that this environment of nonfeasance will continue. We conclude the analysis by proposing policy ideas that will hopefully strengthen our democracy and reduce the risk of something similar happening in the future.

Utilizing existing temperature and structural geology information around Granite Springs Valley, Nevada, we build 3D stochastic temperature models with the aims of evaluating the 3D uncertainty of temperature and choosing between candidate exploration well locations. The data used to support the modeling are measured temperatures and structural proxies from 3D geologic modeling (distance to fault, distance to fault intersections and terminations, Coulomb stress change and dilation tendency), the latter considered “secondary” data. Two stochastic geostatistical techniques are explored for incorporating the structural proxies: cosimulation and local varying mean. With both the cosimulation and local varying mean methods, many equally-likely temperature models (i.e., realizations) are produced, from which temperature probability profiles are calculated at candidate well locations. To aid in choosing between the candidate locations, two quantities summarize the temperature probabilities: V prior and entropy. V prior quantifies the likelihood for economic temperatures at each candidate location, whereas entropy identifies where new information has the most potential to reduce uncertainty. In general, the cosimulation realizations have smoother spatial structure, and extrapolate high temperatures at candidate locations that are located along the direction of the longest spatial correlation, which are down dip from existing temperature logs. The smooth realizations result in tight temperature probability profiles that are easier to interpret, but they have unrealistic temperature reversals in some locations because of the dipping ellipsoid shape created and that the cosimulation technique does not enforce a conductive geothermal gradient as a baseline (i.e., linearly increasing temperature with depth). The local varying mean results produce realizations with more realistic geothermal gradients, with temperatures increasing downward since a depth-temperature relationship is included. However, because they have much noisier spatial nature compared to cosimulation, it is harder to interpret the temperature probability profiles. The different local varying mean results allow the geologist to determine which proxy (e.g., dilation versus distance to fault termination) should be used given the specific geothermal system. In general, V prior from local varying mean results identify locations that are close to high values for the structural proxies: areas with higher probabilities for higher temperatures. The entropy results identify where uncertainty is greatest and therefore new drilling information could be most useful. Though these techniques provide useful information, even when applied to areas of sparse data, our comparison of these two techniques demonstrates the need for new geothermal geostatistics techniques that combine the advantages of these two methods and that are tailored to the spatial uncertainty issues inherent in geothermal exploration.

Blockchains are one of the prominent disruptive technologies that are being implemented in several disciplines. The application of blockchains in the mining and mineral industry can provide utility for several processes especially when the industry is undertaking digital transformation. The governing principles of blockchain technology are applicable in undertaking transformation in several processes within the mining industry. This study investigates the applications of blockchain technology within the realms of the mining industry and identifies key areas of implementation. A systematic review of publications on academic platforms relating to blockchain technology in the mining industry did not retrieve a considerable number of articles. Consequently, a thorough review of white papers and articles authored by individuals on use cases within the mining industry is compiled and presented in this manuscript. This paper identifies all the potential areas within the mining industry where blockchains could provide value and improve processes through their implementation. The broad area of implementation of blockchains includes supply chain, traceability in spare parts, contract management, regulatory compliance, and cyber security.

Climate change is contributing to declines of insects through rising temperatures, altered precipitation patterns, and an increasing frequency of extreme events. The impacts of both gradual and sudden shifts in weather patterns are realized directly on insect physiology and indirectly through impacts on other trophic levels. Here, we investigated direct effects of seasonal weather on butterfly occurrences and indirect effects mediated by plant productivity using a temporally intensive butterfly monitoring dataset, in combination with high‐resolution climate data and a remotely sensed indicator of plant primary productivity. Specifically, we used Bayesian hierarchical path analysis to quantify relationships between weather and weather‐driven plant productivity on the occurrence of 94 butterfly species from three localities distributed across an elevational gradient. We found that snow pack exerted a strong direct positive effect on butterfly occurrence and that low snow pack was the primary driver of reductions during drought. Additionally, we found that plant primary productivity had a consistently negative effect on butterfly occurrence. These results highlight mechanisms of weather‐driven declines in insect populations and the nuances of climate change effects involving snow melt, which have implications for ecological theories linking topographic complexity to ecological resilience in montane systems.

Gastrointestinal (GI) organs display spontaneous, non‐neurogenic electrical, and mechanical rhythmicity that underlies fundamental motility patterns, such as peristalsis and segmentation. Electrical rhythmicity (aka slow waves) results from pacemaker activity generated by interstitial cells of Cajal (ICC). ICC express a unique set of ionic conductances and Ca ²⁺ handling mechanisms that generate and actively propagate slow waves. GI smooth muscle cells lack these conductances. Slow waves propagate actively within ICC networks and conduct electrotonically to smooth muscle cells via gap junctions. Slow waves depolarize smooth muscle cells and activate voltage‐dependent Ca ²⁺ channels (predominantly CaV1.2), causing Ca ²⁺ influx and excitation–contraction coupling. The main conductances responsible for pacemaker activity in ICC are ANO1, a Ca ²⁺ ‐activated Cl ⁻ conductance, and CaV3.2. The pacemaker cycle, as currently understood, begins with spontaneous, localized Ca ²⁺ release events in ICC that activate spontaneous transient inward currents due to activation of ANO1 channels. Depolarization activates Ca V 3.2 channels, causing the upstroke depolarization phase of slow waves. The upstroke is transient and followed by a long‐duration plateau phase that can last for several seconds. The plateau phase results from Ca ²⁺ ‐induced Ca ²⁺ release and a temporal cluster of localized Ca ²⁺ transients in ICC that sustains activation of ANO1 channels and clamps membrane potential near the equilibrium potential for Cl ⁻ ions. The plateau phase ends, and repolarization occurs, when Ca ²⁺ stores are depleted, Ca ²⁺ release ceases and ANO1 channels deactivate. This review summarizes key mechanisms responsible for electrical rhythmicity in gastrointestinal organs. image

This paper introduces an innovative and streamlined design of a robot, resembling a bicycle, created to effectively inspect a wide range of ferromagnetic structures, even those with intricate shapes. The key highlight of this robot lies in its mechanical simplicity coupled with remarkable agility. The locomotion strategy hinges on the arrangement of two magnetic wheels in a configuration akin to a bicycle, augmented by two independent steering actuators. This configuration grants the robot the exceptional ability to move in multiple directions. Moreover, the robot employs a reciprocating mechanism that allows it to alter its shape, thereby surmounting obstacles effortlessly. An inherent trait of the robot is its innate adaptability to uneven and intricate surfaces on steel structures, facilitated by a dynamic joint. To underscore its practicality, the robot's application is demonstrated through the utilization of an ultrasonic sensor for gauging steel thickness, coupled with a pragmatic deployment mechanism. By integrating a defect detection model based on deep learning, the robot showcases its proficiency in automatically identifying and pinpointing areas of rust on steel surfaces. The paper undertakes a thorough analysis, encompassing robot kinematics, adhesive force, potential sliding and turn‐over scenarios, and motor power requirements. These analyses collectively validate the stability and robustness of the proposed design. Notably, the theoretical calculations established in this study serve as a valuable blueprint for developing future robots tailored for climbing steel structures. To enhance its inspection capabilities, the robot is equipped with a camera that employs deep learning algorithms to detect rust visually. The paper substantiates its claims with empirical evidence, sharing results from extensive experiments and real‐world deployments on diverse steel bridges, situated in both Nevada and Georgia. These tests comprehensively affirm the robot's proficiency in adhering to surfaces, navigating challenging terrains, and executing thorough inspections. A comprehensive visual representation of the robot's trials and field deployments is presented in videos accessible at the following links: https://youtu.be/Qdh1oz_oxiQ and https://youtu.be/vFFq79O49dM .

Before the colonial period, California harboured more language variation than all of Europe, and linguistic and archaeological analyses have led to many hypotheses to explain this diversity¹. We report genome-wide data from 79 ancient individuals from California and 40 ancient individuals from Northern Mexico dating to 7,400–200 years before present (bp). Our analyses document long-term genetic continuity between people living on the Northern Channel Islands of California and the adjacent Santa Barbara mainland coast from 7,400 years bp to modern Chumash groups represented by individuals who lived around 200 years bp. The distinctive genetic lineages that characterize present-day and ancient people from Northwest Mexico increased in frequency in Southern and Central California by 5,200 years bp, providing evidence for northward migrations that are candidates for spreading Uto-Aztecan languages before the dispersal of maize agriculture from Mexico2–4. Individuals from Baja California share more alleles with the earliest individual from Central California in the dataset than with later individuals from Central California, potentially reflecting an earlier linguistic substrate, whose impact on local ancestry was diluted by later migrations from inland regions1,5. After 1,600 years bp, ancient individuals from the Channel Islands lived in communities with effective sizes similar to those in pre-agricultural Caribbean and Patagonia, and smaller than those on the California mainland and in sampled regions of Mexico.

Post-9/11 visual and textual art representing the day-to-day lives of Muslims often reflects the condition of living within a global ideological order that hails them as dangerous threats. We often see this in scenes of interpellation at airport security. This chapter examines literary and popular cultural illustrations of the ramifications of checkpoint interpellation in Mohsin Hamid’s The Reluctant Fundamentalist (2007), Kamila Shamsie’s Home Fire (2017), and Riz Ahmed’s rap lyrics and personal essay “Auditions and Airports” (2016). These texts demonstrate the various ways individual border-crossing subjects are hailed as “Muslim” qua threat, terrorist, and enemy through the assessment of incidental features of dress, grooming, taste, as well as politically charged confrontations about national and religious affiliation. In turn, these texts also represent the anticipation of interrogation and the strategic performance of compliance that have necessarily become a quotidian aspect of Muslim life in Europe and the United States. The airport, as these authors show, has become one of the most important sites that determines not only who is a “Muslim,” but also what the consequences of that determination mean in our contemporary moment. And perhaps even more significantly, these texts illustrate how being hailed into the post-9/11 ideological order means that the border itself migrates along with anyone interpellated as Muslim—that is, Muslim with all its attendant pejorative connotations of potential sedition and treachery. The condition of being perceived as a Muslim in the twenty-first century, I argue, is to be always on the border, at the checkpoint, in a perpetual state of migration.

Unmanned aerial vehicles (UAVs) suffer from intolerable sensor drifts in global positioning system (GPS)-denied environments, leading to potentially dangerous situations. This chapter proposes a safety-constrained control framework that adapts UAVs at a path re-planning level to support resilient state estimation in GPS-denied environments. The proposed framework consists of an anomaly detector, a resilient state estimator, a robust controller, a pursuer location tracker (PLT), and an escape controller (EsC). The detector ensures anomaly detection and provides a switching criterion between the robust control and emergency control modes. PLT is developed to track the pursuer’s location by the unscented Kalman filter with sliding window outputs. Using the estimates from PLT, we design an EsC based on the model predictive controller such that the UAV escapes from the effective range of the spoofing device within the escape time that is defined as the safe time within which the estimation errors remain in a tolerable region with high probability. Subsequently, the proposed framework is extended for the multi-UAV systems that perform the time-critical coordination task.