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\"\"As a man, I'm flesh and blood, I can be ignored, I can be destroyed; but as a symbol... as a symbol I can be incorruptible, I can be everlasting\". In the 2005 reboot of the then dormant Batman film franchise, Batman Begins, Bruce Wayne articulates how the figure of the superhero can serve as a transcendent icon. It is hard to imagine a time when superheroes have been more pervasive in our culture. Today, superheroes are intellectual property jealously guarded by media conglomerates, icons co-opted by grassroots groups as a four-color rebuttal to social inequities, masks people wear to more confidently walk convention floors and city streets, and bulletproof banners that embody regional and national identities. From activism to cosplay, understanding how these different groups and interests have made use of this powerful icon is essential to unmasking the appeal of superheroes and their wider impact. To address this interest, The Superhero Symbol brings together scholars from a range of disciplines, alongside key industry figures. Collectively, these contributions provide fresh perspectives on how these costume-clad heroes have engaged with media, culture, and politics, thereby becoming the \"everlasting\" symbols to which a wayward Bruce Wayne once aspired\"-- Provided by publisher.

Based on the most recently published data, we definitively estimated that the annual global production of sewage sludge may rise from ~ 53 million tons dry solids currently to ~ 160 million tons if global wastewater were to be treated to a similar level as in the 27 European Union countries/UK. It is widely accepted that the agricultural application is a beneficial way to recycle the abundant organic matter and plant nutrients in sewage sludge. However, land application may need to be limited due to the presence of metals. This work presents a meticulous and systematic review of the sources, concentrations, partitioning, and speciation of metals in sewage sludge in order to determine the impacts of sludge application on metal behavior in soils. It identifies that industrial wastewater, domestic wastewater and urban runoff are main sources of metals in sludge. It shows conventional treatment processes generally result in the partitioning of over 70% of metals from wastewater into primary and secondary sludge. Typically, the order of metal concentrations in sewage sludge is Zn > Cu > Cr ≈ Pb ≈ Ni > Cd. The proportion of these metals that are easily mobilised is highest for Zn and Ni, followed by Cd and Cu, then Pb and Cr. Sludge application to land will lead to elevated metal concentrations, and potentially to short-term changes to the dominant metal species in soils. However, the speciation of sludge-associated metals will change over time due to interactions with plant roots and soil minerals and as organic matter is mineralised by rhizo-microbiome.

Knowledge of the temperature-dependent concentration of ice-nucleating particles (INPs) is crucial to understanding the properties of mixed-phase clouds. However, the sources, transport and removal of INPs around the globe, and particularly in the Arctic region, are poorly understood. In the Arctic winter and spring, when many local sources are covered by ice and snow, it is not clear which INP types are important. In this study, we present a new dataset of aircraft-based immersion mode INP measurements and aerosol size-resolved composition in the western North American Arctic from 11 to 21 March 2018. Aerosol samples were collected between ∼ 70 and 600 m above the surface on filters that were analysed using both a freezing droplet-based assay and scanning electron microscopy with energy dispersive spectroscopy (SEM-EDS). The measured INP concentrations were at or close to the limit of detection, with concentrations at −20 ∘C of 1 L−1 or below. The size-resolved composition measurements indicates that the aerosol concentrations were low, dominated mostly by sea spray aerosol and mineral dust. Further analysis shows that mineral dust is important for the ice-nucleating properties of our samples, dominating over the sea spray aerosol particles in the four cases we analysed, suggesting that mineral dust is a relevant type of INP in the Alaskan springtime Arctic. Furthermore, the INP concentrations are more consistent with fertile soil dusts that have an ice-active biological component than what would be expected for the ice-active mineral K-feldspar alone. While we cannot rule out local high-latitude sources of dust, the relatively small size of the mineral dust implies that the dust was from distant sources.

Metals such as Zn and Cu present in sewage sludge applied to agricultural land can accumulate in soils and potentially mobilise into crops. Sequential extractions and X-ray absorption spectroscopy results are presented that show the speciation changes of Cu and Zn sorbed to anaerobic digestion sludge after mixing with soils over three consecutive 6-week cropping cycles, with and without spring barley ( Hordeum vulgare ). Cu and Zn in digested sewage sludge are primarily in metal sulphide phases formed during anaerobic digestion. When Cu and Zn spiked sludge was mixed with the soil, about 40% of Cu(I)-S phases and all Zn(II)-S phases in the amended sludge were converted to other phases (mainly Cu(I)-O and outer sphere Zn(II)-O phases). Further transformations occurred over time, and with crop growth. After 18 weeks of crop growth, about 60% of Cu added as Cu(I)-S phases was converted to other phases, with an increase in organo-Cu(II) phases. As a result, Cu and Zn extractability in the sludge-amended soil decreased with time and crop growth. Over 18 weeks, the proportions of Cu and Zn in the exchangeable fraction decreased from 36% and 70%, respectively, in freshly amended soil, to 28% and 59% without crop growth, and to 24% and 53% with crop growth. Overall, while sewage sludge application to land will probably increase the overall metal concentrations, metal bioavailability tends to reduce over time. Therefore, safety assessments for sludge application in agriculture should be based on both metal concentrations present and their specific binding strength within the amended soil.

Crop losses from weed interference have a significant effect on net returns for producers. Herein, potential corn yield loss because of weed interference across the primary corn-producing regions of the United States and Canada are documented. Yield-loss estimates were determined from comparative, quantitative observations of corn yields between nontreated and treatments providing greater than 95% weed control in studies conducted from 2007 to 2013. Researchers from each state and province provided data from replicated, small-plot studies from at least 3 and up to 10 individual comparisons per year, which were then averaged within a year, and then averaged over the seven years. The resulting percent yield-loss values were used to determine potential total corn yield loss in t ha−1 and bu acre−1 based on average corn yield for each state or province, as well as corn commodity price for each year as summarized by USDA-NASS (2014) and Statistics Canada (2015). Averaged across the seven years, weed interference in corn in the United States and Canada caused an average of 50% yield loss, which equates to a loss of 148 million tonnes of corn valued at over U.S.$26.7 billion annually. Nomenclature: Corn, Zea mays L.

Herbicide resistance is often viewed as a complex problem in need of innovative management solutions. Because of the transboundary mobility of many weeds, resistance to herbicides is also viewed as a community-scale issue. Consequently, the idea of greater coordination among resource users—especially growers—is often promoted as a management approach. Recently, scholars have framed herbicide resistance as a commons problem in need of collective action. Specifically, social scientists have explored the utility of adopting bottom-up, community-based approaches to help solve the growing problem of herbicide resistance through a framework for interpreting the commons known as common pool resource theory. This article analyzes how herbicide resistance fits—and fails to fit—within common pool resource theory and offers an updated conceptual framework from which to build future work. We argue that the application of common pool resource theory to herbicide-resistance management is underdeveloped, and approaches based on this theory have shown little success. The relevance of common pool resource theory for informing herbicide-resistance management is less settled than existing scholarship has suggested, and other frameworks for approaching transboundary resource problems—such as co-production of knowledge and participatory action research—warrant consideration.

Weeds are one of the most significant, and controllable, threats to crop production in North America. Monetary losses because of reduced soybean yield and decreased quality because of weed interference, as well as costs of controlling weeds, have a significant economic impact on net returns to producers. Previous Weed Science Society of America (WSSA) Weed Loss Committee reports, as chaired by Chandler (1984) and Bridges (1992), provided snapshots of the comparative crop yield losses because of weeds across geographic regions and crops within these regions after the implementation of weed control tactics. This manuscript is a second report from the current WSSA Weed Loss Committee on crop yield losses because of weeds, specifically in soybean. Yield loss estimates were determined from comparative observations of soybean yields between the weedy control and plots with greater than 95% weed control in studies conducted from 2007 to 2013. Researchers from each US state and Canadian province provided at least three and up to ten individual comparisons for each year, which were then averaged within a year, and then averaged over the seven years. These percent yield loss values were used to determine total soybean yield loss in t ha−1 and bu acre−1 based on average soybean yields for each state or province as well as current commodity prices for a given year as summarized by USDA-NASS (2014) and Statistics Canada (2015). Averaged across 2007 to 2013, weed interference in soybean caused a 52.1% yield loss. Based on 2012 census data in the US and Canada soybean was grown on 30,798,512 and 1,679,203 hectares with production of 80 million and 5 million tonnes, respectively. Using an average soybean price across 2007 to 2013 of US $389.81 t−1 ($10.61 bu−1), farm gate value would be reduced by US $16.2 billion in the US and $1.0 billion in Canada annually if no weed management tactics were employed. Nomenclature: Soybean, Glycine max (L.) Merr Las malezas son una de las amenazas más significativas y controlables para la producción agrícola en Norteamérica. Las pérdidas monetarias producto de la reducción en el rendimiento de la soja y la disminución en la calidad debido a la interferencia de malezas y al costo de controlar a estas, tiene un impacto económico significativo en la rentabilidad de los productores. Reportes previos del comité de pérdidas por malezas de la Sociedad Americana de la Ciencia de Malezas (WSSA), bajo la dirección de Chandler (1984) y Bridges (1992) brindaron imágenes temporales de las pérdidas de rendimiento comparativas causadas por malezas en diferentes regiones geográficas y cultivos dentro de estas regiones después de la implementación de tácticas de control de malezas. Este manuscrito es un segundo reporte del comité actual de pérdidas por malezas de WSSA sobre pérdidas en rendimiento causadas por malezas, específicamente en soja. Los estimados de pérdida en rendimiento fueron determinados a partir de observaciones comparativas de rendimientos de soja entre testigos con malezas y parcelas con más de 95% de control en estudios realizados desde 2007 a 2013. Investigadores de cada estado de Estados Unidos y de cada provincia de Canada brindaron al menos tres y hasta 10 comparaciones individuales para cada año, las cuales fueron promediadas dentro de cada año, y luego promediadas para los siete años. Estos valores de porcentaje de rendimiento fueron usados para determinar la pérdida total en soja en t ha−1 y bu acre−1 con base en el promedio de rendimiento de soja para cada estado o provincia y el precio de grano para cada año como lo resumen USDA-NASS (2014) y Statistics Canada (2015). Promediando los años de 2007 a 2013, la interferencia de malezas en soja causó un 52,1% de pérdidas de rendimiento. Con base en los datos del censo de 2012 en Estados Unidos y Canada, se produjo soja en 30,798,512 y 1,679,203 hectáreas para una producción de 80 millones y 5 millones de toneladas, respectivamente. Usando una precio de la soja promedio para 2007 a 2013 de US $389.81 t−1 ($10,61 bu−1), el valor en puerta de finca se hubiera reducido en US $16.6 miles de millones en los Estados Unidos y $1.0 mil millones en Canada anualmente si no se hubieran empleado tácticas de manejo de malezas.

Knowledge of weed seeds present in the soil seedbank is important for understanding population dynamics and forecasting future weed infestations. Quantification of the weed seedbank has historically been laborious, and few studies have attempted to quantify seedbanks on the scale required to make management decisions. An accurate, efficient, and ideally automated method to identify weed seeds in field samples is needed. To achieve sufficient precision, we leveraged YOLOv8, a machine learning object detection to accurately identify and count weed seeds obtained from the soil seedbank and weed seed collection. The YOLOv8 model, trained and evaluated using high-quality images captured with a digital microscope, achieved an overall accuracy and precision exceeding 80% confidence in distinguishing various weed seed species in both images and real-time videos. Despite the challenges associated with species having similar seed morphology, the application of YOLOv8 will facilitate rapid and accurate identification of weed seeds for the assessment of future weed management strategies.

Yield losses due to weeds are a major threat to wheat production and economic well-being of farmers in the United States and Canada. The objective of this Weed Science Society of America (WSSA) Weed Loss Committee report is to provide estimates of wheat yield and economic losses due to weeds. Weed scientists provided both weedy (best management practices but no weed control practices) and weed-free (best management practices providing >90% weed control) average yield from replicated research trials in both winter and spring wheat from 2007 to 2017. Winter wheat yield loss estimates ranged from 2.9% to 34.4%, with a weighted average (by production) of 25.6% for the United States, 2.9% for Canada, and 23.4% combined. Based on these yield loss estimates and total production, the potential winter wheat loss due to weeds is 10.5, 0.09, and 10.5 billion kg with a potential loss in value of US$2.19, US$0.19, and US$2.19 billion for the United States, Canada, and combined, respectively. Spring wheat yield loss estimates ranged from 7.9% to 47.0%, with a weighted average (by production) of 33.2% for the United States, 8.0% for Canada, and 19.5% combined. Based on this yield loss estimate and total production, the potential spring wheat loss is 4.8, 1.6, and 6.6 billion kg with a potential loss in value of US$1.14, US$0.37, and US$1.39 billion for the United States, Canada, and combined, respectively. Yield loss in this analysis is greater than some previous estimates, likely indicating an increasing threat from weeds. Climate is affecting yield loss in winter wheat in the Pacific Northwest, with percent yield loss being highest in wheat-fallow systems that receive less than 30 cm of annual precipitation. Continued investment in weed science research for wheat is critical for continued yield protection. Nomenclature: wheat; Triticum aestivum L.