Wild oat is a significant weed of cropping systems in the Canadian Prairies. Wild oat resistance to herbicides has increased interest in the use of nonchemical management strategies. Harvest weed seed control techniques such as impact mills or chaff collection have been of interest in Prairie crops, with wild oat identified as a key target. To evaluate the effects of crop rotation maturity, harvest management, and harvest weed seed control on wild oat, a study was conducted from 2016 to 2018 at four locations in the Canadian Prairies. Two-year crop rotations with either early, normal, or late-maturing crops were implemented before barley was seeded across all rotations in the final year. In addition, a second factor of harvest management (swathing or straight cut) was included in the study. Chaff collection was used in this study to quantify wild oat seeds that were targetable by harvest weed seed control techniques. The hypothesis was that earlier maturing crops would result in increased wild oat capture at harvest and, therefore, lower wild oat populations. Wild oat density and wild oat biomass were lowest in the early maturing rotations. In addition, wild oat exhibited lower biomass in swathed crops than straight-cut crops. Wild oat seedbank levels reflected a similar trend with the lowest densities occurring in early maturing rotation, then the normal maturity rotation, and the late maturing rotation, which had the highest seedbank densities. Wild oat densities increased in all crop rotations; however, only harvest weed seed control and crop rotation were implemented as control measures. Wild oat numbers in the chaff were not reflective of the earliness of harvest. Crop yields suggest that competitive winter wheat stands contributed to the success of the early maturing rotations compared to other treatments. Early maturing rotations resulted in reduced wild oat populations, likely through a combination of crop competitiveness and rotational diversity, and harvest weed seed control management effects from earlier maturing crops.

Uncontrolled weeds can cause billions of dollars in yield loss in corn and soybean production fields in the United States. Growers often use herbicides to control weeds to avoid yield loss. The objective of this study was to estimate the cost of herbicides used in corn and soybean production in the United States. On-farm herbicide usage data were extracted from surveys of corn production costs in 2021 and soybean production costs in 2023, carried out by the U.S. Department of Agriculture–National Agricultural Statistics Service (USDA-NASS) through the Agricultural Chemical Use Program. Commonly used or known products were assumed for each reported herbicide. Based on the USDA-NASS surveys, approximately 107.8 and 89.1 million kg of herbicides were used in corn and soybean production in 2021 and 2023, respectively, in the United States. Glyphosate (33.8 million kg; in various salt forms), atrazine (26.8 million kg), and mesotrione (2.4 million kg) were the most widely applied herbicides, applied to 79%, 65%, and 47% of corn production areas, respectively, planted in 2021. Similarly, glyphosate (in various salt forms) was the most widely applied herbicide in soybean production, followed by 2,4-D (15.9 million kg; in various salt forms) and glufosinate-ammonium (4.4 million kg), which were applied to 58% and 23% of soybean hectarage, respectively, planted in 2023. Using the average retail price of herbicide products from Kansas State University, University of Nebraska−Lincoln, and North Dakota State University publications, herbicides (excluding adjuvants and application costs) would have cost approximately US$3.2 and US$4.1 billion in corn and soybean production in 2021 and 2023, respectively.

Hybrid yoghurts combining dairy and plant-based derivatives present a novel approach to enhancing consumer acceptance of plant-based products, which is increasingly significant due to dietary trends and lactose intolerance. This study investigates the production of hybrid yoghurt blending cow's milk (CM) with soy (C:S) and oat (C:O) drinks in various ratios (90%, 70%, and 50% cow's milk), assessing their acceptability and quality. Notably, the C:S (70:30) and C:O (70:30) ratios resulted improved viscosity over time, although still less than CM. The hybrid yoghurts exhibited a favourable pH gradient, enhancing the acidic environment critical for flavour. Sensory analysis revealed that C:O (70:30) offered more favourable attributes on the just-about-right scale, scoring overall 6.86/10. Importantly, microbial analysis confirmed the safety of all hybrid products for consumption, with no harmful microorganisms detected.

The North American Heritage at Risk (NAHAR) collaborative, which formed during the COVID-19 pandemic, allowed for heritage-at-risk partners to shift from reactive to proactive strategies. The result was the creation of the NAHAR research pipeline to respond to landscapes at risk. The pipeline includes modeling of environmental changes to the landscape; monitoring sites to verify location and assess condition; meeting with the public, descendant community, land managers, and transdisciplinary experts in their field to discuss climate change impacts to their heritage in the next 10 years; methodizing by means of a workflow organizer using data from the modeling, monitoring, and meeting; and when appropriate, mitigating areas identified during the methodizing process. In 2020, the Florida Public Archaeology Network—along with partners in Georgia, South Carolina, Washington, Texas, and Louisiana—began the Science Collaborative People of Guana project at the Guana Tolomato Matanzas Estuarine Research Reserve (GTM NERR) north of St. Augustine, Florida. Using a collaborative science mindset, the project team applied the NAHAR pipeline to gain a better sense of how resources were used in the past and how they currently are being used by communities to ensure responsive resource management and relationship building with visitors, descendants, and other community stakeholders, such as the Gullah/Geechee Nation. This article will provide the building blocks for other collaborative teams to follow the NAHAR pipeline and share lessons learned from the two-year project.

Mobile apps provide archaeologists a way to engage the public and local communities in efforts to protect heritage at risk. This article discusses community engagement apps used by archaeologists who specialize in collecting data about climate change and its impact on cultural sites. It provides an overview of the process by which the Florida Public Archaeology Network (FPAN) developed various workflows over the last few years to engage community member–scientists using digital tools. FPAN based this work on examples from cultural heritage management practice in Scotland. Because we were unable to directly adapt Scotland's app to our US context, we experimented with multiple other apps and tools to implement our workflows, including Arches, Solocator, ArcGIS Field Maps, and the Arrow GNSS receiver.

Since 2020, the conflict between Armenia and Azerbaijan over Nagorno-Karabakh has intensified, culminating in a 44-day war in 2020 and an Azerbaijani military offensive in September 2023 when Azerbaijan reclaimed control over the Nagorno-Karabakh territory. This has ushered in a new phase of the Karabakh peace process amidst a transformed security landscape in the Caucasus. Against the background of a more general reconceptualization of Armenia’s role in the region, shifting away from its traditional alliance with Russia towards closer ties with the West, the article examines the role of women in Armenia in this peace process and their postwar opportunities for agency. The analysis reveals that women’s substantive inclusion in Armenia’s peace process remains limited due to (1) elite-dominated hard power negotiation structures and militarized discourses, (2) societal and economic factors, and (3) “self-exclusion” of women and the need for empowerment. Despite these challenges, the article identifies opportunities for women to assert agency in Armenia’s new security environment, contributing to a more effective, sustainable, and inclusive peace process.

Mexico's war on drugs is increasingly characterized by small, local groups rather than large cartels. This research note introduces new data developed from a narcoblog—a citizen journalism website—on more than 450 criminal organizations operating in Mexico between 2009 and 2020. I use the data to test prominent theories of fragmentation, providing suggestive evidence that drug war policies contributed to a more complex conflict: kingpin removals were correlated with the emergence of smaller groups; profit opportunities (in this case, fuel theft) then attracted these organizations to new territories. This research contributes to our understanding of criminal control and informs debates over violence reduction policies.

Bayesian model updating (BMU) is frequently used in Structural Health Monitoring to investigate the structure’s dynamic behavior under various operational and environmental loadings for decision-making, e.g., to determine whether maintenance is required. Data collected by sensors are used to update the prior of some physics-based model’s latent parameters to yield the posterior. The choice of prior may significantly affect posterior predictions and subsequent decision-making, especially under the typical case in engineering applications of little informative data. Therefore, understanding how the choice of prior affects the posterior prediction is of great interest. In this article, a robust Bayesian inference technique evaluates the optimal and worst-case prior in the vicinity of a chosen nominal prior and their corresponding posteriors. This technique derives an interacting Wasserstein gradient flow that minimizes and maximizes/minimizes the KL divergence between the posterior and the approximation to the posterior, with respect to the approximation to the posterior and the prior. Two numerical case studies are used to showcase the proposed algorithm: a double-banana-posterior and a double-beam structure. Optimal and worst-case priors are modeled by specifying an ambiguity set containing any distribution at a statistical distance to the nominal prior, less than or equal to the radius. The resulting posteriors may be used to yield the lower and upper bounds on subsequent calculations of an engineering metric (e.g., failure probability) used for decision-making. If the metric used for decision-making is not sensitive to the resulting posteriors, it may be assumed that decisions taken are robust to prior uncertainty.

A newly discovered Neolithic site at Al-Khashbah KHS-A (Oman) reveals local adaptations to climate change in the Holocene. Results from radiocarbon dating show repeated occupations over 1000 years and key artefacts indicate coastal connections. KHS-A served as a short-term camp, enhancing our understanding of Neolithic lifeways in Arabia.

Legumes are a large and diverse family of plants that provide us with food, feed, fuel and feedstocks for industry. They can use atmospheric di-nitrogen for growth, via symbiotic nitrogen fixation (SNF) with bacteria called rhizobia, making them key to sustainable agricultural systems. There are opportunities to increase SNF in legumes to help tackle critical challenges related to the overuse of fertilizer nitrogen in agriculture. The last two decades have seen enormous progress in our understanding of the genetics of SNF, although this is yet to be leveraged to improve SNF in legumes. In principle, two main plant-based approaches exist to improve SNF, one involving genetic engineering and the other using existing natural variation in this complex trait. These approaches are not mutually exclusive and now is an opportune time to attempt to increase SNF in legumes via plant genetics and genomics.