Estimating the Rates of Acquisition and loss of Resistance of Enterobacteriaceae to Antimicrobial Drugs in Pre-Weaned Dairy Calves

The objective of this study was to investigate the effect of the antimicrobial drugs (AMD) on the shedding of resistant Enterobacteriaceae in feces of pre-weaned dairy calves. The AMD considered were ceftiofur, administered parenterally, and neomycin sulfate added in milk replacer and fed to calves during the first 20 days of life. Fifty-five calves, aged one to three days, were enrolled and followed to 64 days. Fecal samples were collected three times/week and treatments recorded daily. Enterobacteriaceae were quantified for a subset of 33 calves using spiral plating on plain, ceftiofur supplemented, and neomycin supplemented MacConkey agar. Negative binomial models were used to predict the association between treatment with AMD and the gain and loss of Enterobacteriaceae resistance over time. Acquisition of resistance by the Enterobacteriaceae occurred during treatment and peaked between days three to four post-treatment before decreasing to below treatment levels at days seven to eight post-treatment. Acquisition of neomycin resistance was observed on the first sampling day (day four from the start of feeding medicated milk replacer) to day eight, followed by cyclical peaks until day 29, when the Enterobacteriaceae counts decreased below pre-treatment. Enterobacteriaceae resistance against both AMD increased after AMD administration and didn’t return to pre-therapeutic status until seven or more days after therapy had been discontinued. The study findings provide valuable insights into the dynamics of Enterobacteriaceae under routine AMD use in calves.

A changing demographic – Ten years of HIV care

We aimed to benchmark the quality of care and describe characteristics of patients newly attending the HIV clinic at differing time points over the past 10 years, against the Infectious Disease Society of America HIV/AIDS performance measures. We performed a retrospective analysis of records for patients newly attending the HIV clinic in 2011, 2016 and 2018. There was an increase in male attendees in 2018 and 2016 compared to 2011 (88%, 88% vs. 59% p < .001), viral suppression rates were 97%, 83% and 99% ( p < .001), respectively. We observed an increase in patients of South American origin over time. Acquisition risk changed, with increased proportion of MSM (24% in 2011 vs 78% in 2018, p < .001), lower rates of heterosexual (20% in 2018 vs 48% in 2011, p < .001) and IDU transmission (1.5% in 2018 vs 24% in 2011, p < .001). There were lower rates of Chlamydia trachomatis and Neisseria gonorrhoeae testing in 2018 (72%, p < .001), compared to 2016 (84%) and 2011 (83%). Hepatitis B virus vaccination and pneumococcal vaccine rates are declining ( p < .001). We demonstrate the changes in both ethnicity and risk of acquisition over time, high rates of antiretroviral therapy prescription and viral suppression, and highlight the importance of health prevention with sexual health screening and vaccination in this population.

Using Cloud-Based Array Electromagnetics on the Path to Zero Carbon Footprint during the Energy Transition

Fluid imaging is one of the key geophysical technologies for the energy industry during energy transition to zero footprint. We propose better Cloud-based fluid distribution imaging to allow better, more optimized production, thus reducing carbon dioxide (CO2) footprint per barrel produced. For CO2 storage, the location knowledge of the stored fluids is mandatory. Electromagnetics is the preferred way to image reservoir fluids due to its strong coupling to the fluid resistivity. Unfortunately, acquiring and interpreting the data takes too long to contribute significantly to cost optimization of field operations. Using artificial intelligence and Cloud based data acquisition we can reduce the operational feedback to near real time and even, for the interpretation, to close to 24 h. This then opens new doors for the breakthrough of this technology from exploration to production and monitoring. It allows the application envelope to be enlarged to much noisier environments where real time acquisition can be optimized based on the acquired data. Once all components are commercialized, the full implementation could become a real game changer by providing near real time 3-dimensional subsurface images in support of the energy transition.

A changing landscape in collection development

Ryerson University Library has been exploring different just-in-time acquisition models that provide us with cost-effective ways to purchase monograph titles with guaranteed usage. Based on our experience with Ebrary on the PDA (Patron Driven Acquisitions) Pilot, and with YBP on the DDA (Demand Driven Acquisitions) project, this discussion will focus on the theory behind our approach, the technicalities of implementation, and implications for future collection development strategies.

Using Cloud-Based Array Electromagnetics on the Path to Zero Carbon Footprint during the Energy Transition

One of the key geophysical technologies for the energy industry during energy transition to zero footprint is fluid imaging. Knowledge of fluid distribution allows better, more optimized production reducing thus CO2 footprint per barrel produced and for CO2 storage the knowledge of where stored fluids go is mandatory to monitor reservoir seals. Electromagnetic is the preferred way to image fluid due to its strong coupling to the fluid resistivity. Unfortunately, acquiring and interpreting the data takes too long to contribute significantly to field operation and cost optimization. Using artificial intelligence and Cloud based data acquisition we can reduce the operational feedback to near real time and for the interpretation to close to 24 h. This then opens new door for the usefulness of this technology from exploration, monitoring and allows the application envelope to be enlarged to much noisier environment where real time acquisition can be optimized based on the acquired data.

Kinect-Based Real-Time Acquisition Algorithm of Crop Growth Depth Images

Kinect 3D sensing real-time acquisition algorithm that can meet the requirements of fast, accurate, and real-time acquisition of image information of crop growth laws has become the trend and necessary means of digital agricultural production management. Based on this, this paper uses Kinect real-time image generation technology to try to monitor and study the depth map of crop growth law in real time, use Kinect to obtain the algorithm of crop growth depth map, and conduct investigation and research. Real-time image acquisition research on crop growth trends provides a basis for in-depth understanding of the application of Kinect real-time image generation technology in research. Kinect image real-time acquisition algorithm is a very important information carrier in agricultural information engineering. The research results show that the real-time Kinect depth image acquisition algorithm can obtain good 3D image data information and can provide valuable data basis for the 3D reconstruction of the later crop growth model, growth status analysis, and real-time monitoring of crop diseases. The data shows that, using Kinect, the real-time feedback speed of crop growth observation can be increased by 45%, the imaging accuracy is improved by 37%, and the related operation steps are simplified by 30%. The survey results show that the crop yield can be increased by about 12%.

Real-time imaging of cellular forces using optical interference

Important dynamic processes in mechanobiology remain elusive due to a lack of tools to image the small cellular forces at play with sufficient speed and throughput. Here, we introduce a fast, interference-based force imaging method that uses the illumination of an elastic deformable microcavity with two rapidly alternating wavelengths to map forces. We show real-time acquisition and processing of data, obtain images of mechanical activity while scanning across a cell culture, and investigate sub-second fluctuations of the piconewton forces exerted by macrophage podosomes. We also demonstrate force imaging of beating neonatal cardiomyocytes at 100 fps which reveals mechanical aspects of spontaneous oscillatory contraction waves in between the main contraction cycles. These examples illustrate the wider potential of our technique for monitoring cellular forces with high throughput and excellent temporal resolution.

Proposed implementation of various imaging modes of OCT on FPGA

Optical Coherence Tomography (OCT) is three-dimensional imaging technique, capable of producing high resolution cross-sectional images through homogeneous samples, such as biological tissue. Real-time acquisition rates are a significant advantage in OCT. However, when images are generated by first acquiring data and then postprocessed on PC to extract information this advantage is cancelled out. In this project a system which can provide estimation of pixel values for three imaging modes: Structural, Color-flow Doppler and Velocity Variance is designed. The proposed system is standalone data processor using FPGA. The system was designed to process recorded data for verification purposes; however, it can be easily modified to process real-time data. Since the system has three modes of visualization it can be used for detecting in vivo blood flow. The proposed system was completed at MATLAB, Xilinx System Generator (XSG) and VHDL levels and the results show consistency between theoretical results, MATLAB, XSG and VHDL.

Proposed implementation of various imaging modes of OCT on FPGA

Optical Coherence Tomography (OCT) is three-dimensional imaging technique, capable of producing high resolution cross-sectional images through homogeneous samples, such as biological tissue. Real-time acquisition rates are a significant advantage in OCT. However, when images are generated by first acquiring data and then postprocessed on PC to extract information this advantage is cancelled out. In this project a system which can provide estimation of pixel values for three imaging modes: Structural, Color-flow Doppler and Velocity Variance is designed. The proposed system is standalone data processor using FPGA. The system was designed to process recorded data for verification purposes; however, it can be easily modified to process real-time data. Since the system has three modes of visualization it can be used for detecting in vivo blood flow. The proposed system was completed at MATLAB, Xilinx System Generator (XSG) and VHDL levels and the results show consistency between theoretical results, MATLAB, XSG and VHDL.