Characterization of catalytic chemical vapor-deposited SiCN thin film coatings

Silicon carbonitride thin films of 480 to 730-nm thicknesses were grown on silicon substrate using ammonia and hexamethyldisilazane gas sources using catalytic chemical vapor deposition process. Compositions of silicon, carbon and nitrogen in the SiCN films were varied by changing the flow rate of ammonia gas. The effect of deposition conditions on the structural, optical and mechanical properties of SiCN thin films was examined. X-ray photoelectron spectroscopy analysis indicated that the higher flow rate of ammonia gas results in higher nitrogen and lower carbon content in the deposited thin films. The measurement of stress as a function of substrate temperature in the SiCN film showed that the stress changes from compressive to tensile in the range of 275°C to 325°C. With these preliminary characterization tests, it is expected that SiCN nano-thin films can be used for developing sensors for harsh environment

In vitro synergism of fosfomycin and clarithromycin antimicrobials against methicillin-resistant Staphylococcus pseudintermedius

BACKGROUND: Bacterial biofilms are of tremendous concern for clinicians, as they can compromise the ability of the immune system and antimicrobial therapy to resolve chronic and recurrent infections. Novel antimicrobial therapies or combinations targeted against biofilm establishment and growth subsequently represent a promising new option for the treatment of chronic infectious diseases. In this study, we treated bacterial biofilms produced by methicillin-resistant Staphylococcus pseudintermedius (MRSP) with a combination of fosfomycin and clarithromycin. We selected these agents, because they prevent biofilm formation and induce antimicrobial synergism that may also target other staphylococci. RESULTS: We determined that the combination of fosfomycin and clarithromycin better impairs S. pseudintermedius biofilm formation compared to treatment with either therapy alone (P < 0.05). Morphological examination of these biofilms via scanning electron microscopy demonstrated that fosfomycin alone does impact biofilm formation on orthopaedic implants. However, this activity is enhanced in the presence of clarithromycin. We propose that the bacteriostatic activity of clarithromycin is accentuated when fosfoymcin is present, as it may allow better penetration into the biofilm matrix, allowing fosfomycin access to sessile bacteria near the surface of attachment. CONCLUSIONS: Here, we demonstrate that the combination of fosfomycin and clarithromycin may be a useful therapy that could improve the clinical outcomes of treating antimicrobial resistant MRSP biofilms

In vitro synergism of fosfomycin and clarithromycin antimicrobials against methicillin-resistant Staphylococcus pseudintermedius

Abstract Background: Bacterial biofilms are of tremendous concern for clinicians, as they can compromise the ability of the immune system and antimicrobial therapy to resolve chronic and recurrent infections. Novel antimicrobial therapies or combinations targeted against biofilm establishment and growth subsequently represent a promising new option for the treatment of chronic infectious diseases. In this study, we treated bacterial biofilms produced by methicillin-resistant Staphylococcus pseudintermedius (MRSP) with a combination of fosfomycin and clarithromycin. We selected these agents, because they prevent biofilm formation and induce antimicrobial synergism that may also target other staphylococci. Results: We determined that the combination of fosfomycin and clarithromycin better impairs S. pseudintermedius biofilm formation compared to treatment with either therapy alone (P &lt; 0.05). Morphological examination of these biofilms via scanning electron microscopy demonstrated that fosfomycin alone does impact biofilm formation on orthopaedic implants. However, this activity is enhanced in the presence of clarithromycin. We propose that the bacteriostatic activity of clarithromycin is accentuated when fosfoymcin is present, as it may allow better penetration into the biofilm matrix, allowing fosfomycin access to sessile bacteria near the surface of attachment. Conclusions: Here, we demonstrate that the combination of fosfomycin and clarithromycin may be a useful therapy that could improve the clinical outcomes of treating antimicrobial resistant MRSP biofilms

Developments in nanoparticles for use in biosensors to assess food safety and quality

The following will provide an overview on how advances in nanoparticle technology have contributed towards developing biosensors to screen for safety and quality markers associated with foods. The novel properties of nanoparticles will be described and how such characteristics have been exploited in sensor design will be provided. All the biosensor formats were initially developed for the health care sector to meet the demand for point-of-care diagnostics. As a consequence, research has been directed towards miniaturization thereby reducing the sample volume to nanolitres. However, the needs of the food sector are very different which may ultimately limit commercial application of nanoparticle based nanosensors

ASAS–NANP Symposium: Mathematical Modeling in Animal Nutrition: Opportunities and Challenges of Confned and Extensive Precision Livestock Production

Modern animal scientists, industry, and managers have never faced a more complex world. Precision livestock technologies have altered management in confned operations to meet production, environmental, and consumer goals. Applications of precision technologies have been limited in extensive systems such as rangelands due to lack of infrastructure, electrical power, communication, and durability. However, advancements in technology have helped to overcome many of these challenges. Investment in precision technologies is growing within the livestock sector, requiring the need to assess opportunities and challenges associated with implementation to enhance livestock production systems. In this review, precision livestock farming and digital livestock farming are explained in the context of a logical and iterative fve-step process to successfully integrate precision livestock measurement and management tools, emphasizing the need for precision system models (PSMs). This fve-step process acts as a guide to realize anticipated benefts from precision technologies and avoid unintended consequences. Consequently, the synthesis of precision livestock and modeling examples and key case studies help highlight past challenges and current opportunities within confned and extensive systems. Successfully developing PSM requires appropriate model(s) selection that aligns with desired management goals and precision technology capabilities. Therefore, it is imperative to consider the entire system to ensure that precision technology integration achieves desired goals while remaining economically and managerially sustainable. Achieving long-term success using precision technology requires the next generation of animal scientists to obtain additional skills to keep up with the rapid pace of technology innovation. Building workforce capacity and synergistic relationships between research, industry, and managers will be critical. As the process of precision technology adoption continues in more challenging and harsh, extensive systems, it is likely that confned operations will beneft from required advances in precision technology and PSMs, ultimately strengthening the benefts from precision technology to achieve short- and long-term goals

Developments in nanoparticles for use in biosensors to assess food safety and quality

The following will provide an overview on how advances in nanoparticle technology have contributed towards developing biosensors to screen for safety and quality markers associated with foods. The novel properties of nanoparticles will be described and how such characteristics have been exploited in sensor design will be provided. All the biosensor formats were initially developed for the health care sector to meet the demand for point-of-care diagnostics. As a consequence, research has been directed towards miniaturization thereby reducing the sample volume to nanolitres. However, the needs of the food sector are very different which may ultimately limit commercial application of nanoparticle based nanosensors. © 2014 Elsevier Ltd

AI in Sustainable Pig Farming: IoT Insights into Stress and Gait

This paper pioneers a novel exploration of environmental impacts in livestock farming, focusing on pig farming’s intersection with climate change and sustainability. It emphasizes the transformative potential of data-driven Artificial Intelligence (AI) methodologies, specifically the Internet of Things (IoT) and multimodal data analysis, in promoting equitable and sustainable food systems. The study observes five pigs aged 86 to 108 days using a tripartite sensor that records heart rate, respiration rate, and accelerometer data. The unique experimental design alternates between periods of isolation during feeding and subsequent pairing, enabling the investigation of stress-induced changes. Key inquiries include discerning patterns in heart rate data during isolation versus paired settings, fluctuations in respiration rates, and behavioral shifts induced by isolation or pairing. The study also explores the potential detection of gait abnormalities, correlations between pigs’ age and their gait or activity patterns, and the evolution of pigs’ walking abilities with age. The paper scrutinizes accelerometer data to detect activity changes when pigs are paired, potentially indicating increased stress or aggression. It also examines the adaptation of pigs to alternating isolation and pairing over time and how their heart rate, respiration rate, and activity data reflect this process. The study considers other significant variables, such as time of day and isolation duration, affecting the pigs’ physiological parameters. Sensor data are further utilized to identify behavioral patterns during periods of feeding, isolation, or pairing. In conclusion, this study harnesses IoT and multimodal data analysis in a groundbreaking approach to pig welfare research. It underscores the compelling potential of technology to inform about overall pig welfare, particularly stress levels and gait quality, and the power of data-driven insights in fostering equitable, healthy, and environmentally conscious livestock production systems

Net Zero Dairy Farming—Advancing Climate Goals with Big Data and Artificial Intelligence

This paper explores the transformative potential of Big Data and Artificial Intelligence (AI) in propelling the dairy industry toward net zero emissions, a critical objective in the global fight against climate change. Employing the Canadian dairy sector as a case study, the study extrapolates its findings to demonstrate the global applicability of these technologies in enhancing environmental sustainability across the agricultural spectrum. We begin by delineating the environmental challenges confronting the dairy industry worldwide, with an emphasis on greenhouse gas (GHG) emissions, including methane from enteric fermentation and nitrous oxide from manure management. The pressing need for innovative approaches in light of the accelerating climate crisis forms the crux of our argument. Our analysis delves into the role of Big Data and AI in revolutionizing emission management in dairy farming. This includes applications in optimizing feed efficiency, refining manure management, and improving energy utilization. Technological solutions such as predictive analytics for feed optimization, AI in herd health management, and sensor networks for real-time monitoring are thoroughly examined. Crucially, the paper addresses the wider implications of integrating these technologies in dairy farming. We discuss the development of benchmarking standards for emissions, the importance of data privacy, and the essential role of policy in promoting sustainable practices. These aspects are vital in supporting the adoption of technology, ensuring ethical use, and aligning with international climate commitments. Concluding, our comprehensive study not only suggests a pathway for the dairy industry towards environmental sustainability but also provides insights into the role of digital technologies in broader agricultural practices, aligning with global environmental sustainability efforts

The role of sensors, big data and machine learning in modern animal farming

Ever since man began domesticating animals several thousand years ago, we have always relied on our intuition, collective knowledge, and sensory signals to make effective animal production decisions. So far, this has helped us make significant gains in animal husbandry and farming. Together the growing demand for food and the advancement in sensing technology have the potential to make animal farming more centralized, large scale and efficient. It has the potential to change animal farming as we know it. At a broader level, this paper explores the challenges and opportunities that sensor technologies present in terms of helping animal farmers produce more meat and animal products. More specifically, this paper explores the role of sensors, big data, artificial intelligence and machine learning in helping animal farmers to lower production costs, increase efficiencies, enhance animal welfare and grow more animals per hectare. It also explores the challenges and limitations of technology. The paper reviews various animal farming technology applications to understand its value in helping farmers improve animal health, increase profits and lower environmental footprint