Carolina geranium (Geranium carolinianum L.) infestation is a concern for Florida strawberry [Fragaria × ananassa (Weston) Duchesne ex Rozier (pro sp.) [chiloensis × virginiana]] producers. Current control measures rely on hand weeding or clopyralid applications when the weed is small. Unfortunately, early detection tends not to occur due to occlusion by the canopy. Coordinating postemergence control with emergence timing could improve control. Therefore, the objective of this study was to model the cumulative emergence of G. carolinianum in the row middles and transplant holes on the plastic-mulched beds of Florida strawberry fields using accumulated growing degree days (GDD) (thermal or hydrothermal time) as a predictive variable. A 7-yr study was conducted in two strawberry fields within Hillsborough County, FL, for row middles and a 2-yr study was conducted for bed tops. Emergence was modeled as a function of accumulated standard and restricted GDD. The model was calibrated using 5 randomly selected site-years of data and validated with 2 additional site-years for row middles, while only calibration was done for bed tops. Annual variation in emergence timing was driven by both temperature and moisture in the row middles, whereas emergence on the bed tops was influenced by temperature alone. Incorporating restrictions on GDD accumulation reduced overestimation of GDD and improved model prediction (standard GDD model with adjusted R2 = −0.10, RMSE = 37.31; restricted GDD model with adjusted R2 = 0.90, RMSE = 11.46) and enhanced the model’s applicability for row middles over space and time. In contrast, no improvement in model performance was observed for the bed tops. Emergence began simultaneously, but 50% and 90% cumulative emergence occurred at least a week later on bed tops compared with row middles. Overall, G. carolinianum primarily emerged from mid-October to mid-December, which allows implementation of control measures before harvest initiation.

The 2025 report by the Association for Clinical Research Professionals summarizes the state of crisis for the global clinical research workforce and proposes key solutions. These include increased awareness of clinical research professions, access to jobs through expanded training and internships, and advancement opportunities for professional staff and site support. To increase access to these professions, multiple Academic Medical Centers (AMCs) expanded training programs and internships leveraging approaches described in this manuscript, and in some cases, established formal apprenticeships in their respective States. This manuscript summarizes direct experiences of nine Clinical and Translational Science Award Centers for decreasing the barriers to entry into the clinical research profession, specifically focusing on clinical research coordinator role. This special communication describes methods for increased awareness, establishing training/internship opportunities, while addressing internal and external collaborations, administrative barriers, and funding necessary to implement an innovative pathway program. The authors hope that this material will be valuable to other AMCs that wish to undertake development of similar programs.

West Nile virus (WNV) is a zoonotic mosquito-borne Flavivirus, with bird populations reservoirs. Although often asymptomatic, infection in humans can cause febrile symptoms and, more rarely, severe neurological symptoms. Previous studies assessed environmental drivers of WNV infections, but most overlooked areas with potential WNV circulation despite no reported human case, and mixed mechanisms affecting hosts vs. vectors. Our objective was to generate a WNV Bird Risk Index (BRI) mapping the potential of WNV circulation in bird communities across Europe. We first used a bird traits-based model to estimate WNV seroprevalence in European wild bird species and identify eco-ethological characteristics associated with it. This allowed us to build a map of the WNV BRI that showed a strong spatial heterogeneity across Europe. To validate this metric, using a Besag-York-Mollie 2 spatial model in a Bayesian framework, we showed a positive association between the BRI and the number of years with notified WNV human cases between 2016 and 2023, at the NUTS administrative region scale. To conclude, we provide a map quantifying the suitability for WNV to circulate in the bird reservoir. This allows to target surveillance efforts in areas at risk for WNV zoonotic infections in the future.

The paper introduces a deep‐learning model fine‐tuned for detecting authoritarian discourse in political speeches. Set up as a regression problem with weak supervision logic, the model is trained for the task of classification of segments of text for being/not being associated with authoritarian discourse. Rather than trying to define what an authoritarian discourse is, the model builds on the assumption that authoritarian leaders inherently define it. In other words, authoritarian leaders talk like authoritarians. When combined with the discourse defined by democratic leaders, the model learns the instances that are more often associated with authoritarians on the one hand and democrats on the other. The paper discusses several evaluation tests using the model and advocates for its usefulness in a broad range of research problems. It presents a new methodology for studying latent political concepts and positions as an alternative to more traditional research strategies.

This article examines the idea that the EU could export its promotion of the public sphere. The Commission perception of the public sphere is unclear and the EU is not exporting a public sphere paradigm in any comprehensive manner. The EU nevertheless continues to attempt to export its integration experience. The concept of a public sphere is particularly pertinent to certain advanced democratic societies. Its exportability and relevance for other parts of the world are limited.

Socio-environmental challenges such as climate change and biodiversity loss necessitate political action and transformative educational responses. Education for Environmental Citizenship (EEC) offers a promising framework for addressing these issues in school settings. However, there is a lack of reported structured teacher professional development (TPD) programmes that support EEC. This study presents a systematic literature review (SLR) of empirical studies and supranational frameworks, synthesising the results into a model for in-service TPD in EEC. The analysis identified core competencies such as critical thinking, systems thinking and global citizenship alongside with dimensions including socio-emotional and cultural-territorial competencies, which address context-specific educational needs. These are mapped to pedagogical strategies such as outdoor learning, reflective practice and community-based learning. The resulting model seeks to align global sustainability goals with local realities. This research lays the groundwork for fostering EEC by providing educators with the competencies and strategies essential to drive social and environmental change.

The integration of unmanned aerial vehicles (UAVs) into agriculture has emerged as a transformative approach to enhance resource efficiency and enable precision farming. UAVs are used for various agricultural tasks, including monitoring, mapping and spraying of pesticides, providing detailed data that support targeted and sustainable practices. However, effective deployment of UAVs in these applications faces complex control challenges. This paper presents a comprehensive review of UAVs in agricultural applications, highlighting the sophisticated control strategies required to address these challenges. Key obstacles, such as modelling inaccuracies, unstable centre of gravity (COG) due to shifting payloads, fluid sloshing within pesticide tanks and external disturbances like wind, are identified and analysed. The review delves into advanced control methodologies, with particular focus on adaptive algorithms, backstepping control and machine learning-enhanced systems, which collectively enhance UAV stability and responsiveness in dynamic agricultural environments. Through an in-depth examination of flight dynamics, stability control and payload adaptability, this paper highlights how UAVs can achieve precise and reliable operation despite environmental and operational complexities. The insights drawn from this review underscore the importance of integrating adaptive control frameworks and real-time sensor data processing, enabling UAVs to autonomously adjust to changing conditions and ensuring optimal performance in agriculture. Future research directions are proposed, advocating for the development of control systems that enhance UAV resilience, accuracy and sustainability. By addressing these control challenges, UAVs have the potential to significantly advance precision agriculture, offering practical and environmental benefits crucial to sustaining global food production demands.

Suicidal and self-harming behaviours present a significant challenge for mental health services. Recent national guidelines advocate abandoning tools based on box-ticking and a move towards a personalised psychosocial assessment. This article examines evidence from theoretical and empirical research in this area and attempts to integrate it by introducing the source–problem–solution–motive (SPSM) model. The model, which builds on the contributions of other suicidologists, specially Jean Baechler, could be used as a framework for the assessment and management of these behaviours. The four stages of the model provide a comprehensive approach that enables an exploration of the internal logic of the behaviour. The model covers ‘because’ and ‘in-order-to’ motives. This allows a personalised approach, but also a structured one that can be taught and generalised.