Ethanol-water distillation is typically a carbon intensive operation in the agricultural, food and drinks industries. Three heat pump technologies (vapour compression VC, vapour recompression VRC and bottoms flashing BF) for supplying heat to the distillation process were quantitatively investigated and compared to a natural gas boiler. The focus of the study was to investigate the effect of electric grid carbon intensity and carbon pricing on system economics and carbon footprints. The heat pump systems had much lower carbon footprints due to their ability to utilise heat from the vapour leaving the top of the column. As heat pumps require electric power, transforming the grid to a lower carbon intensity decreases their carbon footprints which could facilitate processors in their drive towards net-zero carbon emissions. For example, with a low grid carbon intensity of 0.1 kg CO2 kWh-1, the VC, VRC and BF heat pumps have carbon footprints that are 9.9%, 5.4% and 6.9%, respectively, of that of the gas boiler. The heat pumps had lower annual energy costs at about 30 to 60% of the gas boiler but had higher capital costs being around 2 to 6 times higher. The study showed that the introduction of carbon pricing coupled with transforming the grid to a lower carbon intensity makes heat pumps progressively more economically competitive than the gas boiler. This incentivises the deployment of heat pumps for achieving their important environmental advantage of greatly reducing carbon emissions, which enables processors to play their role in alleviating their impact on climate change.
Structural loads, internal forces, deformations, and surrounding environmental monitoring of shield tunnels are critical for understanding structural response and construction risk. However, the complex construction environments and confined spaces in shield tunneling projects often hinder the effective implementation of monitoring equipment and methodologies. This paper proposes an intelligent perception monitoring system based on IoT technology. By constructing perception, transmission, and application layers, the system achieves intelligent and automated real-time monitoring of structural loads, internal forces, deformations, and surrounding environmental conditions in shield tunnels. Its reliability and stability are validated through an engineering case study. The results demonstrate that the monitoring system enables comprehensive tunnel surveillance, with advantages including high reliability, scalability, compact size, and ease of maintenance, making it suitable for both short-term and long-term monitoring. Implementation in practical project shows that measured data for external loads, segment ring misalignment, and longitudinal joint opening accurately reflect tunnel load and deformation states, confirming the system’s robustness. However, exposed sensors in tunnel layouts are susceptible to interference from construction machinery or personnel; thus, developing miniaturized sensors with rapid installation/removal capabilities can mitigate this issue. The proposed intelligent perception monitoring system provides foundational data support for intelligent shield tunnel construction and structural health assessment.
To holistically understand the biology of animals, we must unravel the complexities and specificities of host-microbe interactions across animal taxa. Birds represent enigmatic and scientifically compelling hosts in which to understand these interactions. Here, we present a brief summary of a series of conversations among avian microbiome researchers regarding methodological challenges facing the avian microbiome field, where most research to date has focused on bacterial communities of the gut. Collectively, we acknowledged a commonly shared but underreported issue facing the avian microbiome field: that of difficulty in obtaining high-quality and high-yield microbial DNA from avian fecal samples. We discuss some of the potential reasons underlying low DNA yields, such as inhibitory compounds and rapid DNA degradation, and provide recommendations for how researchers in the avian microbiome field might cope with these methodological challenges. Collective and dedicated efforts to address these challenges will be required for a robust understanding of host-microbe interactions in avian systems.
An interlaboratory comparison study was conducted among five laboratories for determining 24,25-dihydroxyvitamin D3 (24,25(OH)2D3) in human serum using liquid chromatography-tandem mass spectrometry (LC-MS/MS) methods. The Centers for Disease Control and Prevention (CDC), Imperial College Healthcare NHS Trust, University College Cork, University of Liège, and University of Washington analyzed 50 single-donor samples and two new Standard Reference Materials (SRMs®). The results from each laboratory were compared with target values assigned by the National Institute of Standards and Technology (NIST) using a reference measurement procedure (RMP) and evaluated using Ordinary Deming linear regression and Bland-Altman analysis. Three of the five laboratory methods provided results that were in good agreement with the NIST RMP results showing linear regression slopes ranging from 0.972 to 1.003 and Bland-Altman mean bias of −0.092 nmol/L, 0.025 nmol/L, and 0.035 nmol/L. Two laboratories demonstrated a significant positive bias with linear regression slopes of 1.158 and 1.214 and Bland-Altman mean bias of 0.162 nmol/L and 0.708 nmol/L. The CDC method is currently used to assign “information only” values for 24,25(OH)2D3 in the quarterly distributions of the Vitamin D External Quality Assessment Scheme (DEQAS). Given the agreement (linear regression slope = 0.984, R2 = 0.996 and mean bias of −0.092 nmol/L) between the CDC method and the NIST RMP observed in this study, the CDC-assigned 24,25(OH)2D3 values in DEQAS may provide a more accurate reference than the current participant consensus mean values.
