Characterization of the subcortical interactions between larvae of the southern pine sawyer Monochamus titillator (F.) and the larvae of the southern pine beetle guild using molecular gut analyses

The southern pine beetle guild (Coleoptera: Curculionidae: Scolytinae) is arguably the most destructive group of forest pests in the Southeastern United States. Laboratory assays suggest that larvae of wood borer associates from the genus Monochamus (Coleoptera: Cerambycidae) may be facultative intraguild predators of southern pine beetle guild. In this study the dynamics of the subcortical interactions between M. titillator (F.) and members of the southern pine beetle guild were examined using PCR-based molecular gut content analyses. Species-specific PCR primer sets were developed to work under multiplex PCR conditions to detect DNA of members of southern pine beetle guild in the gut contents of M. titillator larvae. The molecular half-life of the bark beetle Ips grandicollis (Eichhoff) was calculated as 6.89 hours post-consumption in the gut contents of M. titillator larvae under laboratory conditions. Comparison of the proportion of M. titillator larvae testing positive for each bark beetle species at 6.9 hours post-consumption showed that the proportion fed Dendroctonus terebrans (Olivier) differed significantly. A field study was performed to determine the detection frequencies of southern pine beetle guild DNA in the gut contents of M. titillator larvae under semi-natural conditions. A total of 271 M. titillator larvae were collected from experimental boles in the field. Twenty-six (9.6%) of the field-collected M. titillator larvae tested positive for DNA of members of the southern pine beetle guild. Of these larvae, 25 (96.2%), 1 (3.8%), 0 (0%), and 0 (0%) tested positive for I. grandicollis, I. calligraphus (Germar), D. terebrans, and D. frontalis (Zimmerman) DNA respectively. The species compositions of the southern pine beetle guild within the gut contents of the field-caught M. titillator larvae reflected those within the host, suggesting random predation. Results from this study support the hypothesis that Monochamus species may be facultative intraguild predators of bark beetle larvae in the field. Additionally, this study demonstrates the capabilities of PCR in elucidating the predator-prey interactions of cryptic forest insects and provides a powerful tool to better understand mechanisms driving southern pine beetle guild population fluctuations

Using Artificial Intelligence and Cybersecurity in Medical and Healthcare Applications

Healthcare fields have made substantial use of cybersecurity systems to provide excellent patient safety in many healthcare situations. As dangers increase and hackers work tirelessly to elude law enforcement, cybersecurity has been a rapidly expanding field in the news over the past ten years. Although the initial motivations for conducting cyberattacks have generally remained the same over time, hackers have improved their methods. It is getting harder to identify and stop evolving threats using conventional cybersecurity tools. The development of AI methodologies offers hope for equipping cybersecurity professionals to fend against the ever-evolving threat posed by attackers. Therefore, an artificial intelligence- based Convolutional Neural Network (CNN) is introduced in this paper in which the cyberattacks are detected with more excellent performance. This paper presents unique conditions using the Ant Colony Optimization based Convolutional Neural Network (ACO-CNN) mechanism. This model has been built and supplied collaboratively with a dataset containing samples of web attacks for detecting cyberattacks in the healthcare sector. The results show that the created framework performs better than the modern techniques by detecting cyberattacks more accurately

Drones: Innovative Technology for Use in Precision Pest Management.

Arthropod pest outbreaks are unpredictable and not uniformly distributed within fields. Early outbreak detection and treatment application are inherent to effective pest management, allowing management decisions to be implemented before pests are well-established and crop losses accrue. Pest monitoring is time-consuming and may be hampered by lack of reliable or cost-effective sampling techniques. Thus, we argue that an important research challenge associated with enhanced sustainability of pest management in modern agriculture is developing and promoting improved crop monitoring procedures. Biotic stress, such as herbivory by arthropod pests, elicits physiological defense responses in plants, leading to changes in leaf reflectance. Advanced imaging technologies can detect such changes, and can, therefore, be used as noninvasive crop monitoring methods. Furthermore, novel methods of treatment precision application are required. Both sensing and actuation technologies can be mounted on equipment moving through fields (e.g., irrigation equipment), on (un)manned driving vehicles, and on small drones. In this review, we focus specifically on use of small unmanned aerial robots, or small drones, in agricultural systems. Acquired and processed canopy reflectance data obtained with sensing drones could potentially be transmitted as a digital map to guide a second type of drone, actuation drones, to deliver solutions to the identified pest hotspots, such as precision releases of natural enemies and/or precision-sprays of pesticides. We emphasize how sustainable pest management in 21st-century agriculture will depend heavily on novel technologies, and how this trend will lead to a growing need for multi-disciplinary research collaborations between agronomists, ecologists, software programmers, and engineers

Ant colonies: building complex organizations with minuscule brains and no leaders

Thus far the articles in the series JOD calls the “Organization Zoo” have employed the notion of a “zoo” metaphorically to describe an array of human institutions. Here we take the term literally to consider the design of the most complex organizations in the living world beside those of humans, a favorite of insect zoos around the world: ant colonies. We consider individuality and group identity in the functioning of ant organizations; advantages of a flat organization without hierarchies or leaders; self-organization; direct and indirect communication; job specialization; labor coordination; and the role of errors in innovation. The likely value and limitations of comparing ant and human organizations are briefly examined

ChatGPT in the context of precision agriculture data analytics

In this study we argue that integrating ChatGPT into the data processing pipeline of automated sensors in precision agriculture has the potential to bring several benefits and enhance various aspects of modern farming practices. Policy makers often face a barrier when they need to get informed about the situation in vast agricultural fields to reach to decisions. They depend on the close collaboration between agricultural experts in the field, data analysts, and technology providers to create interdisciplinary teams that cannot always be secured on demand or establish effective communication across these diverse domains to respond in real-time. In this work we argue that the speech recognition input modality of ChatGPT provides a more intuitive and natural way for policy makers to interact with the database of the server of an agricultural data processing system to which a large, dispersed network of automated insect traps and sensors probes reports. The large language models map the speech input to text, allowing the user to form its own version of unconstrained verbal query, raising the barrier of having to learn and adapt oneself to a specific data analytics software. The output of the language model can interact through Python code and Pandas with the entire database, visualize the results and use speech synthesis to engage the user in an iterative and refining discussion related to the data. We show three ways of how ChatGPT can interact with the database of the remote server to which a dispersed network of different modalities (optical counters, vibration recordings, pictures, and video), report. We examine the potential and the validity of the response of ChatGPT in analyzing, and interpreting agricultural data, providing real time insights and recommendations to stakeholdersComment: 33 pages, 21 figure

Odor stimuli: not just chemical identity

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