A microreactor approach for chemoselective capture and analysis of carbonyl compounds in air and exhaled breath.

Detection of volatile organic compounds (VOCs) at trace level (parts per billion volume (ppbv) to parts per trillion (pptv)) has become an important research area because of demanding applications in homeland security, environmental monitoring, and noninvasive diagnosis of diseases. The analysis of trace VOCs challenges existing analytical instruments because their concentrations are beyond current instrument limits of detection. In this dissertation, we have investigated an innovative microreactor that is suitable for quantitative analysis of volatile carbonyl compounds in ambient air as well as in human exhaled breath. The approach is based on microreactor chips fabricated from four inch silicon wafers. The chips have thousands of micropillars in the microfluidic channels for uniformly distributing gaseous samples flowing through the microreactors. The surfaces of the micropillars are functionalized with a quaternary ammonium aminooxy salt 2-(aminooxy)-N,N,N-trimethylethanammonium (ATM) iodide for trapping trace ketones and aldehydes by means of oximation reactions. ATM adducts and unreacted ATM are eluted from the microreactor with less than 40µL of methanol and directly analyzed by nanoelectrospray Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS). Capture efficiencies of above 98% have been achieved for ketones and aldehydes. Carbonyl compounds at levels of 1 ppbv have been detected using the microreactor for capture. Ambient air samples from indoor and outdoor areas were collected using Tedlar bags, and analyzed using the microreactor and FTICR-MS. The analysis of air samples provides the reference for analysis of exhaled breath samples. Finally, exhaled breath samples from patients with untreated lung cancer (LC) patients, patients with benign pulmonary nodules and healthy volunteers (smokers and non-smokers) were collected and analyzed using the same method. The FTICR-MS spectra showed that the exhaled breath samples from LC patients have a unique pattern of VOCs, in comparison with healthy controls and patients with benign pulmonary nodules. 2-Butanone, hydroxy-acetaldehyde, 3-hydroxy-2-butanone, and 4-hydroxy-hexenal (4-HHE) were found to have significant higher concentrations for LC patients. A simple diagnosis method based on four elevated VOCs could easily discriminate lung cancer patients from healthy controls and patients with pulmonary nodules with 90.6% diagnosis sensitivity and 81.3% specificity

Relationships between building attributes and COVID-19 infection in London

In the UK, all domestic COVID-19 restrictions have been removed since they were introduced in March 2020. After illustrating the spatial-temporal variations in COVID-19 infection rates across London, this study then particularly aimed to examine the relationships of COVID-19 infection rates with building attributes, including building density, type, age, and use, since previous studies have shown that the built environment plays an important role in public health. Multisource data from national health services and the London Geomni map were processed with GIS techniques and statistically analysed. From March 2020 to April 2022, the infection rate of COVID-19 in London was 3159.28 cases per 10,000 people. The spatial distribution across London was uneven, with a range from 1837.88 to 4391.79 per 10,000 people. During the whole COVID-19 control period, it was revealed that building attributes played a significant role in COVID-19 infection. It was noted that higher building density areas had lower COVID-19 infection rates in London. Moreover, a higher percentage of historic or flat buildings tended to lead to a decrease in infection rates. The percentage of residential buildings had a positive relationship with the infection rate. Variations in the infection rate were more sensitive to building type; in particular, the percentage of residents living in flats contributed the most to variations in COVID-19 infection rates, with a value of 2.5%. This study is expected to provide support for policy and practice towards pandemic-resilient architectural design

Behavior-oriented numerical modeling of nearshore oceanic current and application on sea harbor

590-602The West Guangdong longshore current (WG current) is a unique oceanic current system. Plenty of field survey datasets indicated that it flows uni-directionally from north-east to south-west in the entire year even during the south-west monsoon season. At present, the natural formation mechanism of the WG current remains controversial, and the traditional process-oriented modeling method could not deal with the dilemma of the scaling mismatch between the regional ocean circulation (several thousand kilometers) and harbor structure (several hundred meters). To solve this problem, in this paper, a behavior-oriented modeling concept was developed, wherein the contribution of the WG current was considered by incorporating additional net flow flux in the hydrodynamic model to separate it from the tidal currents. Through rigorous validations according to the site observed datasets, the proposed modeling concept was found to have good precision. Using the Jida Harbor as a real-life case, the modeling results showed that after the combination of the tidal current and WG current, the westward cross-flow speed in the approach channel could exceed 0.5 m/s, and at the harbor entrance the WG current induces an intense local circulation cell while ebbing, which may bring in additional maneuver risk to the ships

MA2CL:Masked Attentive Contrastive Learning for Multi-Agent Reinforcement Learning

Recent approaches have utilized self-supervised auxiliary tasks as representation learning to improve the performance and sample efficiency of vision-based reinforcement learning algorithms in single-agent settings. However, in multi-agent reinforcement learning (MARL), these techniques face challenges because each agent only receives partial observation from an environment influenced by others, resulting in correlated observations in the agent dimension. So it is necessary to consider agent-level information in representation learning for MARL. In this paper, we propose an effective framework called \textbf{M}ulti-\textbf{A}gent \textbf{M}asked \textbf{A}ttentive \textbf{C}ontrastive \textbf{L}earning (MA2CL), which encourages learning representation to be both temporal and agent-level predictive by reconstructing the masked agent observation in latent space. Specifically, we use an attention reconstruction model for recovering and the model is trained via contrastive learning. MA2CL allows better utilization of contextual information at the agent level, facilitating the training of MARL agents for cooperation tasks. Extensive experiments demonstrate that our method significantly improves the performance and sample efficiency of different MARL algorithms and outperforms other methods in various vision-based and state-based scenarios. Our code can be found in \url{https://github.com/ustchlsong/MA2CL

Using multi-sourced big data to correlate sleep deprivation and road traffic noise: A US county-level ecological study

Background: Road traffic noise is a serious public health problem globally as it has adverse psychosocial and physiologic effects (i.e., sleep). Since previous studies mainly focused on individual levels, we aim to examine associations between road traffic noise and sleep deprivation on a large scale; namely, the US at county level. Methods: Information from a large-scale sleep survey and national traffic noise map, both obtained from Government's open data, were utilized and processed with GIS techniques. To examine the associations between traffic noise and sleep deprivation, we used a hierarchical Bayesian spatial modelling framework to simultaneously adjust for multiple socioeconomic factors while accounting for spatial correlation. Findings: With 62.90% of people not getting enough sleep, a 10 dBA increase in average sound-pressure level (SPL) or SPL of the relatively noisy area in a county, was associated with a 49% (OR: 1.49; 95% CrIs:1.19–1.86) or 8% (1.08; 1.00–1.16) increase in the odds of a person in a particular county not getting enough sleep. A 10% increase in noise exposure area or population ratio was associated with a 3% (1.03; 1.01–1.06) or 4% (1.04; 1.02–1.06) increase in the odds of a person within a county not getting enough sleep. Interpretation: Traffic noise can contribute to variations in sleep deprivation among counties. This study suggests that policymakers could set up different noise-management strategies for relatively quiet and noisy areas (i.e., different limiting SPLs) and incorporate geo-spatial noise indicators, such as exposure population or area ratio. Furthermore, urban planners should consider urban sprawl patterns differently

PO-163 Aerobic exercise activates myocardial FGF21/FGFR1/PI3K-AKT signaling pathway and inhibits cardiomyocyte apoptosis in post-myocardial infarction rats

Objective To investigate the effect of aerobic exercise on the expression of fibroblast growth factor 21 (FGF21) and cardiomyocyte apoptosis in Myocardial Infarction (MI) rats. Methods male SD rats were randomly divided into three groups：the sham operation (S), sedentary MI group (MI) and MI with aerobic exercise group (ME). The MI model was established by ligation of the left anterior descending branch of the left coronary artery. ME group were trained four weeks after the operation. LVSP, LVEDP and ±dp/dtmax were used to evaluate cardiac function. H9C2 cardiomyocytes were stimulated by 400 μmol/L H2O2 for 4h to simulate myocardial apoptosis mode. AMPK agonist AICAR and FGF21 receptor inhibitor PD166866 were used to interfere with H9C2. Myocardial collagen volume fraction was calculated by Masson staining and myocardium FGF21, FGFR1, Bax, Bcl-2 and PI3K-AKT pathway by western blotting or RT-Qpcr. Cardiomyocytes apoptosis was evaluated by TUNEL. Results Compared with S, the expression of FGF21, FGFR1, Bax, Bcl-2 and PI3K, AKT increased significantly in MI group, the apoptotic cardiomyocytes and collagen fibers increased significantly, but the cardiac function decreased. Compared to MI, myocardium FGF21, FGFR1 and PI3K, AKT were further increased in ME group, the Bax/Bcl-2 and the apoptotic cardiomyocytes decreased significantly. The percentage of collagen fibers decreased and the cardiac function was improved. Myocardium FGF21 was positively correlated with the inhibition of cardiomyocyte apoptosis and the improvement of cardiac function. Furthermore, the expression of Bax/Bcl-2, TNF-α/IL-10 and the apoptotic cardiomyocytes was significantly increased by PD166866, but PI3K-AKT pathway decreased significantly by PD166866. However, AICAR single intervention or PD166866 simultaneous intervention also can reverse this adverse effects. Conclusions Exercise can increase myocardial FGF21/FGFR1 with MI. The one of the mechanisms is to activate PI3K-AKT pathway to inhibit cardiaomyocyte apoptosis and inflammatory. It indicates that FGF21/FGFR1/PI3K-AKT signaling pathway plays an important role in inhibiting myocardial apoptosis and improving cardiac function