Design and Development of a Sub-Zero Fluid System for Demonstration of Orion's Phase Change Material Heat Exchangers on ISS

NASA's Orion Multipurpose Crew Vehicle's Exploration Mission 2 is expected to loiter in Lunar orbit for a relatively long period of time. In low Lunar orbit (LLO) the thermal environment is cyclic - extremely cold in the eclipse and relatively hot near the subsolar point. Phase change material heat exchangers (PCM HXs) are the best option for long term missions in these environments. A PCM HX allows a vehicle to store excess waste energy by thawing a phase change material such as n-pentadecane wax. During portions of the orbit that are extremely cold, the excess energy is rejected, resolidifying the wax. Due to the inherent risk of compromising the heat exchanger during multiple freeze and thaw cycles, a unique payload was designed for the International Space Station to test and demonstration the functions of a PCM HX. The payload incorporates the use of a pumped fluid system and a thermoelectric heat exchanger to promote the freezing and thawing of the PCM HX. This paper shall review the design and development undertaken to build such a system

Limitations of variable number of tandem repeat typing identified through whole genome sequencing of Mycobacterium avium subsp. paratuberculosis on a national and herd level

Background: Mycobacterium avium subsp. paratuberculosis (MAP), the causative bacterium of Johne’s disease in dairy cattle, is widespread in the Canadian dairy industry and has significant economic and animal welfare implications. An understanding of the population dynamics of MAP can be used to identify introduction events, improve control efforts and target transmission pathways, although this requires an adequate understanding of MAP diversity and distribution between herds and across the country. Whole genome sequencing (WGS) offers a detailed assessment of the SNP-level diversity and genetic relationship of isolates, whereas several molecular typing techniques used to investigate the molecular epidemiology of MAP, such as variable number of tandem repeat (VNTR) typing, target relatively unstable repetitive elements in the genome that may be too unpredictable to draw accurate conclusions. The objective of this study was to evaluate the diversity of bovine MAP isolates in Canadian dairy herds using WGS and then determine if VNTR typing can distinguish truly related and unrelated isolates.<p></p> Results: Phylogenetic analysis based on 3,039 SNPs identified through WGS of 124 MAP isolates identified eight genetically distinct subtypes in dairy herds from seven Canadian provinces, with the dominant type including over 80% of MAP isolates. VNTR typing of 527 MAP isolates identified 12 types, including “bison type” isolates, from seven different herds. At a national level, MAP isolates differed from each other by 1–2 to 239–240 SNPs, regardless of whether they belonged to the same or different VNTR types. A herd-level analysis of MAP isolates demonstrated that VNTR typing may both over-estimate and under-estimate the relatedness of MAP isolates found within a single herd.<p></p> Conclusions: The presence of multiple MAP subtypes in Canada suggests multiple introductions into the country including what has now become one dominant type, an important finding for Johne’s disease control. VNTR typing often failed to identify closely and distantly related isolates, limiting the applicability of using this typing scheme to study the molecular epidemiology of MAP at a national and herd-level.<p></p&gt

Validation of a screening method for the detection of colistin-resistant \u3ci\u3eE. coli\u3c/i\u3e containing mcr-1 in feral swine feces

A method was developed and validated for the detection of colistin-resistant Escherichia coli containing mcr-1 in the feces of feral swine. Following optimization of an enrichment method using EC broth supplemented with colistin (1 μg/mL) and vancomycin (8 μg/mL), aliquots derived from 100 feral swine fecal samples were spiked with of one of five different mcr-1 positive E. coli strains (between 100 and 104 CFU/g), for a total of 1110 samples tested. Enrichments were then screened using a simple boil-prep and a previously developed real-time PCR assay for mcr-1 detection. The sensitivity of the method was determined in swine feces, with mcr-1 E. coli inocula of 0.1–9.99 CFU/g (n=340), 10–49.99 CFU/g (n=170), 50–99 CFU/g (n=255), 100–149 CFU/g (n=60), and 200–2200 CFU/g (n=175), which were detected with 32%, 72%, 88%, 95%, and 98% accuracy, respectively. Uninoculated controls (n = 100) were negative for mcr-1 following enrichment

Gulls as Sources of Environmental Contamination by Colistin-resistant Bacteria

In 2015, the mcr-1 gene was discovered in Escherichia coli in domestic swine in China that conferred resistance to colistin, an antibiotic of last resort used in treating multi-drug resistant bacterial infections in humans. Since then, mcr-1 was found in other human and animal populations, including wild gulls. Because gulls could disseminate the mcr-1 gene, we conducted an experiment to assess whether gulls are readily colonized with mcr-1 positive E. coli, their shedding patterns, transmission among conspecifics, and environmental deposition. Shedding of mcr-1 E. coli by small gull flocks followed a lognormal curve and gulls shed one strain \u3e101 log10 CFU/g in their feces for 16.4 days, which persisted in the environment for 29.3 days. Because gulls are mobile and can shed antimicrobial-resistant bacteria for extended periods, gulls may facilitate transmission of mcr-1 positive E. coli to humans and livestock through fecal contamination of water, public areas and agricultural operations

The global carbon budget 1959-2011

Accurate assessments of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere is important to better understand the global carbon cycle, support the climate policy process, and project future climate change. Present-day analysis requires the combination of a range of data, algorithms, statistics and model estimates and their interpretation by a broad scientific community. Here we describe datasets and a methodology developed by the global carbon cycle science community to quantify all major components of the global carbon budget, including their uncertainties. We discuss changes compared to previous estimates, consistency within and among components, and methodology and data limitations. CO2 emissions from fossil fuel combustion and cement production (EFF) are based on energy statistics, while emissions from Land-Use Change (ELUC), including deforestation, are based on combined evidence from land cover change data, fire activity in regions undergoing deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. Finally, the global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms. For the last decade available (2002–2011), EFF was 8.3 ± 0.4 PgC yr−1, ELUC 1.0 ± 0.5 PgC yr−1, GATM 4.3 ± 0.1PgC yr−1, SOCEAN 2.5 ± 0.5 PgC yr−1, and SLAND 2.6 ± 0.8 PgC yr−1. For year 2011 alone, EFF was 9.5 ± 0.5 PgC yr−1, 3.0 percent above 2010, reflecting a continued trend in these emissions; ELUC was 0.9 ± 0.5 PgC yr−1, approximately constant throughout the decade; GATM was 3.6 ± 0.2 PgC yr−1, SOCEAN was 2.7 ± 0.5 PgC yr−1, and SLAND was 4.1 ± 0.9 PgC yr−1. GATM was low in 2011 compared to the 2002–2011 average because of a high uptake by the land probably in response to natural climate variability associated to La Niña conditions in the Pacific Ocean. The global atmospheric CO2 concentration reached 391.31 ± 0.13 ppm at the end of year 2011. We estimate that EFF will have increased by 2.6% (1.9–3.5%) in 2012 based on projections of gross world product and recent changes in the carbon intensity of the economy. All uncertainties are reported as ±1 sigma (68% confidence assuming Gaussian error distributions that the real value lies within the given interval), reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. This paper is intended to provide a baseline to keep track of annual carbon budgets in the future

Microfinance and entrepreneurship:An introduction

As microfinance gains increasing attention and application as a financing mechanism for entrepreneurs at the base of the economic pyramid, this Special Issue of International Small Business Journal aims to enhance scholarly understanding of how microfinance fosters entrepreneurial activity. Microfinance brings a range of financial services, including microcredit loans, savings, and insurance, within the reach of millions of poor households not served by traditional banks. This introduction summarizes the articles in this Special Issue of International Small Business Journal on ‘Microfinance’, which address a range of topics in this important domain of research and practice

DMD: A Large-Scale Multi-Modal Driver Monitoring Dataset for Attention and Alertness Analysis

Vision is the richest and most cost-effective technology for Driver Monitoring Systems (DMS), especially after the recent success of Deep Learning (DL) methods. The lack of sufficiently large and comprehensive datasets is currently a bottleneck for the progress of DMS development, crucial for the transition of automated driving from SAE Level-2 to SAE Level-3. In this paper, we introduce the Driver Monitoring Dataset (DMD), an extensive dataset which includes real and simulated driving scenarios: distraction, gaze allocation, drowsiness, hands-wheel interaction and context data, in 41 hours of RGB, depth and IR videos from 3 cameras capturing face, body and hands of 37 drivers. A comparison with existing similar datasets is included, which shows the DMD is more extensive, diverse, and multi-purpose. The usage of the DMD is illustrated by extracting a subset of it, the dBehaviourMD dataset, containing 13 distraction activities, prepared to be used in DL training processes. Furthermore, we propose a robust and real-time driver behaviour recognition system targeting a real-world application that can run on cost-efficient CPU-only platforms, based on the dBehaviourMD. Its performance is evaluated with different types of fusion strategies, which all reach enhanced accuracy still providing real-time response.Comment: Accepted to ECCV 2020 workshop - Assistive Computer Vision and Robotic