Influences of the mixed LiCl-CaCl 2 liquid desiccant solution on a membrane-based dehumidification system: parametric analysis and mixing ratio selection

The membrane-based liquid desiccant dehumidification system has high energy efficiency without the traditional liquid system carry-over problem. The performance of such a system strongly depends on solution's temperature and concentration, which have direct relationship to the solution surface vapour pressure. Compared with the pure liquid desiccant solution, the mixed liquid desiccant solution has lower surface vapour pressure, better system performance and lower material cost. In this paper, the performance of a flat-plate membrane-based liquid desiccant dehumidification system with the mixed solution (LiCl and CaCl2) is investigated through theoretical and experimental approaches. A mathematical model is established to predict the system performance, while the electrolyte non-random two-liquid (NRTL) method is applied to calculate the mixed solution properties. The influences of the solution mixing ratio, temperature Tsol and concentration Csol are evaluated, and it is found that the regeneration heat Qreg can be dramatically reduced by either applying a high concentration solution or increasing CaCl2 content in the mixed solution. Compared with the pure LiCl solution system, the mixed solution system COP can be improved up to 30.23% by increasing CaCl2 content for a 30% concentration solution. The optimum mixing ratio varies with the solution concentration. For the mixed LiCl-CaCl2 solution, the system highest COPs appear at the mixing ratios of 3:1, 2:1 and 1:1 for 20%, 30% and 40% concentrations respectively

Online Metro Origin-Destination Prediction via Heterogeneous Information Aggregation

Metro origin-destination prediction is a crucial yet challenging time-series analysis task in intelligent transportation systems, which aims to accurately forecast two specific types of cross-station ridership, i.e., Origin-Destination (OD) one and Destination-Origin (DO) one. However, complete OD matrices of previous time intervals can not be obtained immediately in online metro systems, and conventional methods only used limited information to forecast the future OD and DO ridership separately. In this work, we proposed a novel neural network module termed Heterogeneous Information Aggregation Machine (HIAM), which fully exploits heterogeneous information of historical data (e.g., incomplete OD matrices, unfinished order vectors, and DO matrices) to jointly learn the evolutionary patterns of OD and DO ridership. Specifically, an OD modeling branch estimates the potential destinations of unfinished orders explicitly to complement the information of incomplete OD matrices, while a DO modeling branch takes DO matrices as input to capture the spatial-temporal distribution of DO ridership. Moreover, a Dual Information Transformer is introduced to propagate the mutual information among OD features and DO features for modeling the OD-DO causality and correlation. Based on the proposed HIAM, we develop a unified Seq2Seq network to forecast the future OD and DO ridership simultaneously. Extensive experiments conducted on two large-scale benchmarks demonstrate the effectiveness of our method for online metro origin-destination prediction

Spatio-temporal characteristics of PM\u3csub\u3e2.5\u3c/sub\u3e, PM\u3csub\u3e10\u3c/sub\u3e, and AOD over the central line project of China’s South-NorthWater diversion in Henan Province (China)

© 2021 by the authors. Licensee MDPI, Basel, Switzerland. The spatio-temporal characteristics of particulate matter with a particle size less than or equal to 2.5 µm (PM2.5), particulate matter with a particle size less than or equal to 10 µm (PM10), meteorological parameters from September 2018 to September 2019, and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) aerosol optical depth (AOD) from 2007 to 2019 were investigated over the Central Line Project of China’s South-North Water Diversion (CSNWD) in Henan Province. To better understand the characteristics of the atmospheric environment over the CSNWD, air quality monitoring stations were installed in Nanyang (in the upper reaches), Zhengzhou (in the middle reaches), and Anyang (in the lower reaches). In this study, daily, monthly, and seasonal statistical analyses of PM2.5 and PM10 concentrations were performed and their relationship with meteorological parameters was investigated. The results show extremely poor air quality conditions over the Zhengzhou Station compared with the Nanyang and Anyang Stations. The annual average PM2.5 concentration did not meet China’s ambient air secondary standard (35 µg/m3 annual mean) over all the stations, while the annual average PM10 concentration satisfied China’s ambient air secondary standard (100 µg/m3 annual mean) over the Anyang and Nanyang Stations, except for the Zhengzhou Station. The highest PM2.5 and PM10 concentrations were observed during winter compared with the other seasons. The results show that PM2.5 and PM10 concentrations were negatively correlated with wind speed and temperature at the Nanyang and Zhengzhou Stations, but positively correlated with relative humidity. However, no significant negative or positive correlation was observed at Anyang Station. There is a strong linear positive correlation between PM2.5 and PM10 (R = 0.99), which indicates that the particulate matter at the three stations was mainly caused by local emissions. Additionally, the AOD values at the three stations were the highest in summer, which may be related to the residues of crops burned in Henan Province in summer

Steady-state performance evaluation and energy assessment of a complete membrane-based liquid desiccant dehumidification system

A complete membrane-based liquid desiccant dehumidification system is investigated under the steady operating condition, which mainly consists of a dehumidifier, a regenerator, three heat exchangers, a cold and a hot water supply units. A finite difference mathematical model is developed for the complete system to investigate the system dehumidification performance and energy requirement, and validated by experimental data. The dehumidification performance is evaluated by the system sensible and latent effectiveness and moisture flux rate, while its energy performance is assessed by the total cooling capacity and coefficient of performance. It is found that the number of heat transfer units in the dehumidifier side and solution to air mass flow rate ratio have the most considerable impact on the system performance, while the number of heat transfer units in the regenerator side and solution inlet concentration in the dehumidifier have comparatively weak influences. The system sensible and latent effectiveness can be improved by increasing the dehumidifier side number of heat transfer units before reaching its critical value of 6. However, the amount of moisture being absorbed, total cooling capacity and coefficient of performance decrease with the dehumidifier side number of heat transfer units at the low air flow rate. The critical value of solution to air mass flow rate ratio varies with number of heat transfer units, and it is preferable to keep the flow rate ratio at or below its critical value as further increasing solution flow rate would reduce the system coefficient of performance

Antibacterial, Antioxidant and Toxicological Properties of Artemisia annua Essential Oil

The essential oil of Artemisia annua grown in the Beijing area was extracted by hydrodistillation, and then its volatile components were analyzed by gas chromatography-mass spectrometry (GC-MS). The in vitro antioxidant activity of the Artemisia annua essential oil was determined by measuring the scavenging rate of DPPH and hydroxyl radicals, its antibacterial activity by using the agar diffusion method, and its toxicological properties by perfusing mice with different doses of the essential oil. The results showed that the extraction rate of the Artemisia annua essential oil was 1.04‰, with 332 essential oil components being identified by GC-MS analysis. Of these, 22 components accounted for 71.09% of the total volatiles, with relatively high contents of artemisinone (19.34%) and (+)-α-pinene (6.10%). The Artemisia annua essential oil exhibited good scavenging activities of the DPPH and hydroxyl radicals in a dose-dependent relationship. The highest scavenging rates of the DPPH and hydroxyl radicals were 40.03% and 92.97%, respectively, at an essential oil concentration of 10 mg/mL. The Artemisia annua essential oil significantly inhibited the growth of both Staphylococcus aureus and Escherichia coli, with inhibitory zones of 12.67±0.29 mm and 9.27±0.25 mm, respectively. The LD50 value of the Artemisia annua essential oil was 7491 mg/kg, indicating that it was not toxic. This study can provide a theoretical reference for the extraction and use of Artemisia annua and other Artemisia plants

A Consumer-tier based Visual-Brain Machine Interface for Augmented Reality Glasses Interactions

Objective.Visual-Brain Machine Interface(V-BMI) has provide a novel interaction technique for Augmented Reality (AR) industries. Several state-of-arts work has demonstates its high accuracy and real-time interaction capbilities. However, most of the studies employ EEGs devices that are rigid and difficult to apply in real-life AR glasseses application sceniraros. Here we develop a consumer-tier Visual-Brain Machine Inteface(V-BMI) system specialized for Augmented Reality(AR) glasses interactions. Approach. The developed system consists of a wearable hardware which takes advantages of fast set-up, reliable recording and comfortable wearable experience that specificized for AR glasses applications. Complementing this hardware, we have devised a software framework that facilitates real-time interactions within the system while accommodating a modular configuration to enhance scalability. Main results. The developed hardware is only 110g and 120x85x23 mm, which with 1 Tohm and peak to peak voltage is less than 1.5 uV, and a V-BMI based angry bird game and an Internet of Thing (IoT) AR applications are deisgned, we demonstrated such technology merits of intuitive experience and efficiency interaction. The real-time interaction accuracy is between 85 and 96 percentages in a commercial AR glasses (DTI is 2.24s and ITR 65 bits-min ). Significance. Our study indicates the developed system can provide an essential hardware-software framework for consumer based V-BMI AR glasses. Also, we derive several pivotal design factors for a consumer-grade V-BMI-based AR system: 1) Dynamic adaptation of stimulation patterns-classification methods via computer vision algorithms is necessary for AR glasses applications; and 2) Algorithmic localization to foster system stability and latency reduction.Comment: 15 pages,10 figure

Optimization of Ganoderma leucocontextum Fermented Tea Medium Formula Based on High-yield Extracellular Crude

To investigate the optimal nutritional conditions and their contributing factors for the secretion of extracellular crude polysaccharides with Ganoderma leucocontextum on a liquid tea substrate, this study optimized the nutritional conditions of its extracellular crude polysaccharides formation by orthogonal experiment and analysis of variance on the basis of the single-factor test, and explored the relevance between its liquid culture characteristics and the secretion of extracellular crude polysaccharides using correlation and path analyses. The results of study revealed that the greatest output of extracellular crude polysaccharide (1.49±0.33 g/L) was achieved on a tea culture medium of 50 g/L potato, 40 g/L glucose, 3 g/L laterite, 20 g/L Pu'er tea and 0.075 mm tea powder particle size, and was affected by each nutritional condition in the descending order of glucose>tea variety>laterite>potato>tea powder particle size. Moreover, the secretion of extracellular crude polysaccharides in G. leucocontextum was significantly impacted by the soluble solids of the fermentation broth and the number of mycelium balls, with the former having the greatest indirect effect while the latter, the greatest direct and combined effect on it. In conclusion, the nutritional conditions (variety, concentration, particle size, etc.) of the tea culture medium and the liquid culture characteristics of G. leucocontextum exerted a significant and interactive effect on the secretion of extracellular crude polysaccharides, and the aforesaid results may provide a theoretical reference for extraction of polysaccharides from this mushroom and development of it as functional foods

Nanosecond-resolution photothermal dynamic imaging via MHZ digitization and match filtering

Photothermal microscopy has enabled highly sensitive label-free imaging of absorbers, from metallic nanoparticles to chemical bonds. Photothermal signals are conventionally detected via modulation of excitation beam and demodulation of probe beam using lock-in amplifier. While convenient, the wealth of thermal dynamics is not revealed. Here, we present a lock-in free, mid-infrared photothermal dynamic imaging (PDI) system by MHz digitization and match filtering at harmonics of modulation frequency. Thermal-dynamic information is acquired at nanosecond resolution within single pulse excitation. Our method not only increases the imaging speed by two orders of magnitude but also obtains four-fold enhancement of signal-to-noise ratio over lock-in counterpart, enabling high-throughput metabolism analysis at single-cell level. Moreover, by harnessing the thermal decay difference between water and biomolecules, water background is effectively separated in mid-infrared PDI of living cells. This ability to nondestructively probe chemically specific photothermal dynamics offers a valuable tool to characterize biological and material specimens.R01 AI141439 - NIAID NIH HHS; R01 CA224275 - NCI NIH HHS; R35 GM136223 - NIGMS NIH HHS; R42 CA224844 - NCI NIH HHSPublished versio

Development of ε-poly(L-lysine) carbon dots-modified magnetic nanoparticles and their applications as novel antibacterial agents

Magnetic nanoparticles (MNPs) are widely applied in antibacterial therapy owing to their distinct nanoscale structure, intrinsic peroxidase-like activities, and magnetic behavior. However, some deficiencies, such as the tendency to aggregate in water, unsatisfactory biocompatibility, and limited antibacterial effect, hindered their further clinical applications. Surface modification of MNPs is one of the main strategies to improve their (bio)physicochemical properties and enhance biological functions. Herein, antibacterial ε-poly (L-lysine) carbon dots (PL-CDs) modified MNPs (CMNPs) were synthesized to investigate their performance in eliminating pathogenic bacteria. It was found that the PL-CDs were successfully loaded on the surface of MNPs by detecting their morphology, surface charges, functional groups, and other physicochemical properties. The positively charged CMNPs show superparamagnetic properties and are well dispersed in water. Furthermore, bacterial experiments indicate that the CMNPs exhibited highly effective antimicrobial properties against Staphylococcus aureus. Notably, the in vitro cellular assays show that CMNPs have favorable cytocompatibility. Thus, CMNPs acting as novel smart nanomaterials could offer great potential for the clinical treatment of bacterial infections

Diagnosis and functional prediction of microbial markers in tumor tissues of sporadic colorectal cancer patients associated with the MLH1 protein phenotype

ObjectiveMost patients with sporadic colorectal cancer (SCRC) develop microsatellite instability because of defects in mismatch repair (MMR). Moreover, the gut microbiome plays a vital role in the pathogenesis of SCRC. In this study, we assessed the microbial composition and diversity of SCRC tumors with varying MutL protein homolog 1 (MLH1) status, and the effects of functional genes related to bacterial markers and clinical diagnostic prediction.MethodsThe tumor microbial diversity and composition were profiled using high-throughput sequencing of the 16S ribosomal RNA (rRNA) gene V4 region. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt2) software and BugBase tool were used to predict the functional roles of the microbiome. We aimed to construct a high-accuracy model to detect and evaluate the area under the receiver operating characteristic curve with candidate biomarkers.ResultsThe study included 23 patients with negative/defective MLH1 (DM group) and 22 patients with positive/intact MLH1 (IM group). Estimation of alpha diversity indices showed that the Shannon index (p = 0.049) was significantly higher in the DM group than in the controls, while the Simpson index (p = 0.025) was significantly lower. At the genus level, we observed a significant difference in beta diversity in the DM group versus the IM group. Moreover, the abundance of Lachnoclostridium spp. and Coprococcus spp. was significantly more enriched in the DM group than in the IM group (q < 0.01 vs. q < 0.001). When predicting metagenomes, there were 18 Kyoto Encyclopedia of Genes and Genomes pathways and one BugBase function difference in both groups (all q < 0.05). On the basis of the model of diagnostic prediction, we built a simplified optimal model through stepwise selection, consisting of the top two bacterial candidate markers (area under the curve = 0.93).ConclusionIn conclusion, the genera Lachnoclostridium and Coprococcus as key species may be crucial biomarkers for non-invasive diagnostic prediction of DM in patients with SCRC in the future