Revealing the effect of sea buckthorn oil, fish oil and structured lipid on intestinal microbiota, colonic short chain fatty acid composition and serum lipid profiles in vivo.

In this study, the effects of sea buckthorn oil (SBO), fish oil (FO) and an enzymatically synthesized structured lipid (SL) on serum, short-chain fatty acids (SCFAs) and intestinal microbiota in Sprague-Dawley (SD) rats were investigated. The results demonstrated that FO, SBO, and SL effectively reduced the levels of high-density lipoprotein cholesterol and low-density lipoprotein cholesterol in the serum of SD rats. SBO increased serum triglyceride levels, while FO elevated total cholesterol levels. Furthermore, all three dietary lipids decreased short-chain fatty acid production and enhanced intestinal microbiota diversity. FO increased the abundance of intestinal microbiota including Romboutsia, Lactobacillus, Escherichia-Shigella, and Lachnospiraceae_NK4A136_group. Conversely, all three dietary lipids reduced the abundance of Klebsiella and Blautia. These findings provide a foundation for understanding the functionality of SBO and FO as well as their potential application in synthesizing novel SLs to regulate intestinal microbiota.

Which is the optimal choice for neonates' formula or breast milk?

The incidence of prematurity has been increasing since the twenty-first century. Premature neonates are extremely vulnerable and require a rich supply of nutrients, including carbohydrates, proteins, docosahexaenoic acid (DHA), arachidonic acid (ARA) and others. Typical breast milk serves as the primary source for infants under six months old to provide these nutrients. However, depending on the individual needs of preterm infants, a more diverse and intricate range of nutrients may be necessary. This paper provides a comprehensive review of the current research progress on the physical and chemical properties, biological activity, function, and structure of breast milk, as well as explores the relationship between the main components of milk globular membrane and infant growth. Additionally, compare the nutritional composition of milk from different mammals and newborn milk powder, providing a comprehensive understanding of the differences in milk composition and detailed reference for meeting daily nutritional needs during lactation.

[Characteristics of Atmospheric Dust Fall Pollution and Its Chemical Composition and Mass Reconstruction in Mentougou District of Beijing].

To study the characteristics of atmospheric dust fall pollution in Mentougou District of Beijing, the monthly average monitoring results of 57 atmospheric dust fall samples from two state-controlled ambient air stations in Mentougou District from 2018 to 2022 were collected, and the atmospheric dust fall pollution status and its time variation characteristics in Mentougou District were analyzed. In order to explore the characteristics of chemical components of atmospheric dust fall and the results of quality mass reconstruction and their sources, 57 dust fall samples were collected using the active suction method at the Sanjiadian State-controlled Ambient Air Station. The mass concentration of dust fall and its chemical components were measured, the characteristics of chemical components in atmospheric dust fall were studied, and the mass reconstruction of the main components of atmospheric dust fall was performed using particle mass reconstruction technology. The reliability of the mass reconstruction results and the reasons for its undetermined components were also discussed. The results showed that from 2018 to 2022, the monthly dust fall in Mentougou District of Beijing changed periodically, being the maximum in April or May in spring and the minimum in October or November in autumn, and the maximum monthly dust fall was 3.2 to 8.4 times the minimum monthly dust fall. The order of the quarterly average monthly dust fall was as follows:spring>summer>autumn>winter, and the dust fall mainly came from spring and summer, accounting for 40.1%-43.0% and 23.8%-37.5% of the total annual dust fall, respectively. The annual average monthly dust fall in Mentougou District of Beijing showed a significant downward trend. The dust fall in 2022 had decreased by 52.8% compared with that in 2018, with an average annual decline of 13.2%, which was related to the improvement in the fine management level of urban environmental protection in Beijing in recent years. In 2021, soil dust had a significant impact on dust fall in Mentougou District, with an actual contribution of 44.2%. The chemical components in the atmospheric dust fall in Mentougou District were mainly water-soluble ions, crustal elements, organic carbon(OC), and elemental carbon(EC). The total mass of the measured chemical components accounted for 65.0% of the mass fraction of the dust fall. The secondary organic carbon(SOC) was also an important component of the atmospheric dust fall, and its mass concentration was 13.5 µg·m-3, accounting for 96.4% of the mass fraction of OC. The main components of atmospheric dust fall mass reconstruction were crust element fugitive dust, organic matter(OM), SO42-, NO3-, NH4+, trace elements, EC, and Cl-, with mass concentrations of 34.8, 28.0, 20.6, 15.0, 5.6, 4.3, 3.2, and 2.2 µg·m-3, accounting for 25.5%, 20.6%, 15.1%, 11.1%, 4.1%, 3.2%, 2.3%, and 1.6% of the dust fall quality, respectively. The atmospheric dust fall mainly came from the soil dust, construction cement dust, biomass combustion, waste incineration, and secondary transformation process. The measured mass concentration of atmospheric dust fall had a good correlation with the reconstructed mass concentration of chemical components, and the determination coefficient R2 was 0.8173. The undetermined components in the mass reconstruction results accounted for 16.5% of the dust fall mass, of which the particle bound water(PBW) in the dust fall accounted for 6.2% of the dust fall mass, and the remaining undetermined components might have been related to the unmeasured components, the selected estimation coefficient of OM and crustal elemental dust, the particle size composition, the selected chemical component analysis method, and its measurement error.

Untargeted Metabolomic Analysis Combined with Chemometrics Revealed the Effects of Different Cooking Methods on Lentinus edodes.

Cooking methods affect the compositions of Lentinus edodes metabolites. Nevertheless, little information is available on the specific impact of different cooking methods on Lentinus edodes via metabolomic analysis. This study determined the influence of boiling, steaming, air-frying, and roasting on the metabolomic profiles of Lentinus edodes based on UHPLC-Q-Exactive Orbitrap MS/MS in combination with chemometrics. A total of 990 metabolites were detected and classified into 11 super-classes. Subsequently, the metabolites of the four cooking methods were distinguished using multivariate statistical analysis. The results showed that boiling caused a massive loss of metabolites while roasting and air-frying led to an evident upregulation. The upregulation of metabolites in the steaming groups was not as significant as in roasting and air-frying. This study provided reference data for a comprehensive understanding of the metabolites associated with domestic cooking methods and valuable guidance for the development of Lentinus edodes and its products in the future.

Combining Untargeted Lipidomics Analysis and Chemometrics to Identify the Edible and Poisonous Mushrooms (Pleurotus cornucopiae vs Omphalotus japonicus).

The global phenomenon of eating poisonous mushrooms by mistake occurs every year. Untargeted lipidomics analysis combined with chemometrics was used to identify mushroom varieties. Two kinds of mushrooms with similar appearance, namely, Pleurotus cornucopiae (P. cornucopiae) and Omphalotus japonicus (O. japonicus) were selected as models, where O. japonicus was a poisonous mushroom and P. cornucopiae was an edible mushroom. First, the lipid extraction efficiency of eight solvents was compared. The methyl tert-butyl ether/methanol (2:1, v/v) had higher lipid extraction efficiency of extracting mushroom lipids than other solvents, in terms of the lipid coverage, response intensity, and solvent safety. Afterward, the comprehensive lipidomics analysis of the two mushrooms was conducted. A total of 21 lipid classes and 267 molecular species were identified in O. japonicus, whereas 22 lipid classes and 266 molecular species in P. cornucopiae. The principal component analysis demonstrated that 37 characteristic metabolites, including TAG 18:1_18:2_18:0;1O, TAG 18:1_18:1_18:2, TAG 16:2_18:2_18:2, etc., could be used to distinguish the two mushrooms. These differential lipids were able to identify P. cornucopiae blended with 5% (w/w) O. japonicus. This study explored a novel method for identifying poisonous mushrooms from edible mushrooms and provided a reference for food safety of consumers.

Protective effect and mechanism insight of purified Antarctic kill phospholipids against mice ulcerative colitis combined with bioinformatics.

Antarctic krill oil is functional oil and has a complex phospholipids composition that poses difficulties in elucidating its effect mechanism on ulcerative colitis (UC). The mechanism of UC action was studied by bioinformatics, and the therapeutic effect of Antarctic krill phospholipids (APL) on dextran sulfate sodium (DSS)-induced colitis mice was verified. GO functional enrichment analysis uncovered an enrichment of these genes in the regulation of cell-cell adhesion, membrane region, signaling receptor activator activity, and cytokine activity. Meanwhile, the KEGG results revealed the genes were enriched in the TNF signaling pathway, pathogenic Escherichia coli infection, inflammatory bowel disease and tight junction. Animal experiments showed that APL treatment alleviated the UC symptoms and reduced inflammatory damage. Meanwhile, the expressions of the tight junction (TJ) proteins, ZO-1 and occludin, were restored, and the levels of IL-6 and TNF-α were reduced. Moreover, Firmicutes/Bacteroidetes ratio in the intestinal microbiota was regulated, and the contents of short-chain fatty acids metabolites were raised. These findings would provide an insight for the beneficial effects of APL and dietary therapy strategies for UC.

Exfoliated 2D Layered and Nonlayered Metal Phosphorous Trichalcogenides Nanosheets as Promising Electrocatalysts for CO2 Reduction.

Two-dimensional (2D) materials catalysts provide an atomic-scale view on a fascinating arena for understanding the mechanism of electrocatalytic carbon dioxide reduction (CO2 ECR). Here, we successfully exfoliated both layered and nonlayered ultra-thin metal phosphorous trichalcogenides (MPCh3 ) nanosheets via wet grinding exfoliation (WGE), and systematically investigated the mechanism of MPCh3 as catalysts for CO2 ECR. Unlike the layered CoPS3 and NiPS3 nanosheets, the active Sn atoms tend to be exposed on the surfaces of nonlayered SnPS3 nanosheets. Correspondingly, the nonlayered SnPS3 nanosheets exhibit clearly improved catalytic activity, showing formic acid selectivity up to 31.6 % with -7.51 mA cm-2 at -0.65 V vs. RHE. The enhanced catalytic performance can be attributed to the formation of HCOO* via the first proton-electron pair addition on the SnPS3 surface. These results provide a new avenue to understand the novel CO2 ECR mechanism of Sn-based and MPCh3 -based catalysts.

Local Path Planning of Autonomous Vehicle Based on an Improved Heuristic Bi-RRT Algorithm in Dynamic Obstacle Avoidance Environment.

The existing variants of the rapidly exploring random tree (RRT) cannot be effectively applied in local path planning of the autonomous vehicle and solve the coherence problem of paths between the front and back frames. Thus, an improved heuristic Bi-RRT algorithm is proposed, which is suitable for obstacle avoidance of the vehicle in an unknown dynamic environment. The vehicle constraint considering the driver's driving habit and the obstacle-free direct connection mode of two random trees are introduced. Multi-sampling biased towards the target state reduces invalid searches, and parent node selection with the comprehensive measurement index accelerates the algorithm's execution while making the initial path gentle. The adaptive greedy step size, introducing the target direction, expands the node more effectively. Moreover, path reorganization minimizes redundant path points and makes the path's curvature continuous, and path coherence makes paths between the frames connect smoothly. Simulation analysis clarifies the efficient performance of the proposed algorithm, which can generate the smoothest path within the shortest time compared with the other four algorithms. Furthermore, the experiments on dynamic environments further show that the proposed algorithm can generate a differentiable coherence path, ensuring the ride comfort and stability of the vehicle.

[Emission Concentration and Characteristics of Particulate Matter and Water-Soluble Ions in Exhaust Gas of Typical Combustion Sources with Ultra-Low Emission].

A self-developed direct condensation sampling system and monitoring method for total particulate matter (TPM) in ultra-low-emission and high-humidity exhaust gas were applied to the emission monitoring of particulate matter in flue gas from three typical combustion sources with ultra-low emissions in Beijing. The emission levels and composition characteristics of particulate matter and water-soluble ions in the exhaust gas of typical combustion sources with ultra-low emissions were analyzed and evaluated. The interaction and influencing factors of filterable particulate matter (FPM) and condensable particulate matter (CPM) and their water-soluble ions were explored. The results showed that the emission concentration of FPM in the exhaust gas of the coal-fired boiler with ultra-low emissions was between 1.04 mg·m-3 and 1.11 mg·m-3 in standard smoke oxygen content, and that of TPM was between 3.82 mg·m-3 and 8.69 mg·m-3, which all met the national ultra-low emission limit (10 mg·m-3). However, the TPM emission concentration of the coal-fired power plant exceeded the emission limit of Beijing (5 mg·m-3). The emission concentrations of CPM and its total water-soluble ions from the coal-fired heating boiler were 3.05 mg·m-3 and 1.30 mg·m-3, respectively, which were significantly lower than those of the coal-fired power plant, and were related to the higher load and flue gas temperature of the coal-fired power plant. Furthermore, the emission concentrations of CPM and its total water-soluble ions from the coal-fired power plant boiler were 2.2 to 2.4 times and 1.7 to 2.2 times greater than those of the coal-fired heating boiler, respectively. The emission concentrations of TPM and its total water-soluble ions from the gas power plant were 1.99 mg·m-3 and 1.44 mg·m-3, respectively, which were significantly lower than those from the coal-fired boiler. CPM was the main form of particulate matter in the exhaust gas of the combustion source. The contribution of CPM to TPM in the ultra-low-emission boiler flue gas increased significantly, and increased with the increase in the flue gas temperature, ranging from 72.6% to 88.1% for the coal-fired boiler and 93.1% for the gas power plant. Total water-soluble ions made up 66.1% to 94.2% of the CPM. The flue gas temperature had a significant impact on the existing forms, removal efficiencies, and emission concentrations of particulate matter and water-soluble ions. SO42- was the main characteristic water-soluble ion of particulate matter in the coal-fired boiler, and its emission concentration ranged from 0.98 mg·m-3 to 1.18 mg·m-3, accounting for 27.7% to 49.6% of the total water-soluble ion emissions, which originated from flue gas desulfurization. F- was another characteristic water-soluble ion of particulate matter in the coal-fired power plant, and its emission concentration ranged from 1.91 mg·m-3 to 2.32 mg·m-3, accounting for 54.4% to 56.1% of the total water-soluble ion emissions, which might have been related to the high F content of fuel coal. NH4+ was the main characteristic water-soluble ion of particulate matter in the gas power plant, and its emission concentration was 0.92 mg·m-3, accounting for 64.2% of the total water-soluble ion emissions, which originated from the escape of NH3 in the process of selective catalytic reduction. The emission concentration of NH4+ was significantly higher than that of the coal-fired boiler; this might have been related to the synergistic removal effect of the gas-fired power plant, which lacked other purification facilities.

[Monitoring Method of Total Particulate Matter in Ultra-low-emission and High-humidity Exhaust Gas from Stationary Sources and an Actual Test in a Gas Power Plant].

With the implementation of ultra-low-emission transformation in coal-fired power plants and other related industries in China, the concentrations of filterable particulate matter (FPM) and gaseous pollutants in exhaust gas from stationary sources have reduced significantly, while the emission of condensable particulate matter (CPM) remains a concern. In this study, the monitoring methods of FPM and CPM at a relatively low FPM concentration in exhaust gas from stationary sources in China and abroad were comprehensively analyzed. On the basis of existing research and experimental exploration, the monitoring methods of FPM and CPM were further studied. A direct condensation sampling and monitoring method for total particulate matter (TPM) in ultra-low-emission and high-humidity exhaust gas from stationary sources, which is suitable for the actual situation in China, was developed and established before being used to measure TPM in exhaust gas from a gas power plant in Beijing. The results showed that the emission concentration of TPM in the exhaust gas from the gas power plant was between 1.98 mg·m-3 and 3.77 mg·m-3 (average of 2.81 mg·m-3), whereas the average emission concentration of FPM was only 0.10 mg·m-3. The emission type of particulate matter in exhaust gas from the gas power plant was mainly CPM, which accounted for 93.8% to 99.2% of the TPM (average of 97.0%). The proportion of FPM to TPM ranged from 0.7% to 6.2% (average of 3.0%). The emission concentration of filterable CPM was slightly higher than that of FPM.

[Pollution Characteristics and Potential Ecological Risks of Heavy Metals in Road Dust in Beijing].

Based on the concentrations of 21 inorganic elements in particulate matter with diameters less than 10 µm (PM10) in 2004, and PM2.5 in 2004 and 2013 of representative road dust in Beijing, the pollution characteristics and potential ecological risks of heavy metals in this dust were analyzed and discussed. The results showed that the six main elements in road dust in Beijing were Si, Ca, Al, Fe, Mg, and K, and the proportions of the total content of the six elements in PM10 in 2004, PM2.5 in 2004, and PM2.5 in 2013 accounted for 96.51%, 96.42%, and 96.53% of the total content of all elements tested, respectively. The elemental enrichment level and the pollution degree and the potential ecological risk of heavy metal in road dust in Beijing in 2004 were PM2.5>PM10. Se, a characteristic element of coal dust, was highly enriched in PM2.5 in 2004, and Cd was high in PM10 and PM2.5 in 2004 with enrichment factors of 1024.03, 68.15, and 871.55, respectively. Co, Zn, Ca, and Cu were significantly enriched in PM10 and PM2.5 in 2004 with enrichment factors of 12.93, 12.33, 8.30, and 8.07 in PM10 and 17.41, 21.80, 12.83, and 19.73 in PM2.5, respectively; Na and Si were not enriched in the road dust. The pollution load index (PLI) of heavy metals was 3.95 in PM10 and 7.71 in PM2.5 in 2004. Owing to the implementation of dust, motor vehicles, and combustion source control measures in Beijing and the relocation of the Shougang corporation, the elemental enrichment level, pollution degree, and potential ecological risk of heavy metals in road dust PM2.5 in 2013 were significantly lower than those in 2004. The enrichment factors of Cd and Se in PM2.5 in 2013 decreased to 98.47 and 0.95, respectively; those of Cu, Ca, and Zn decreased to 11.90, 8.84, and 8.20, respectively; and PLI decreased to 2.56. The results showed that the total potential ecological risk of heavy metals in road dust in Beijing was extremely strong. Heavy metal Cd was the most significant pollution factor and the main potential ecological risk source; its potential ecological risk index (RI) contribution to the total RI of heavy metals was more than 85%. In 2004, the pollution degree of heavy metals in road dust of main roads was significantly higher than that for other road types. The pollution degree of heavy metals in PM10 was main road > expressway entrance to Beijing > secondary main road > ring road; that for PM2.5 was main road > ring road > expressway entrance to Beijing > secondary main road. For PM2.5 in 2013, however, the order was expressway entrance to Beijing > main road > ring road > secondary main road. The pollution degree of heavy metals in road dust of secondary main roads was significantly lower than that for other road types. In 2013, for road dust PM2.5 in Beijing, the correlation of heavy metals Ti, Zn, V, Cr, Cu, Pb, and Ni was significant owing mainly to traffic-related emissions.

[Characteristics and Interannual Variation of Chemical Components in Typical Road Dust in Beijing].

Samples of road dust were collected from selected representative roads in Beijing in September 2004 and May 2013, and then re-suspended on filters using a NK-ZXF sampler to prepare road dust PM10 and PM2.5 samples. The concentrations of the chemical components in the road dust PM10 and PM2.5 were analyzed, and source profiles of the road dust in Beijing in 2004 and 2013 were established. The characteristics and interannual variation of the chemical components in the road dust in Beijing were analyzed and discussed. The results showed that the chemical components in the road dust PM10 and PM2.5 in Beijing were Ca, Si, organic carbon (OC), Al, Fe, K, Mg, SO42-, and elemental carbon (EC). The total content of these chemical components in the PM10 in 2004, PM2.5 in 2004, and PM2.5 in 2013 were 46.7303%, 56.9198%, and 38.7478%, respectively, and the total content of these chemical components accounted for 95.9%, 94.3% and 94.7% of the total content of all components tested, respectively. In 2004, the contents of Si and Al in the road dust of ring road were significantly lower than those of other road types, and the influence of soil dust on the ring road was the smallest. The content of Ca, a characteristic element of construction dust, was the highest in main road, and was the lowest in the expressway entrance to Beijing. The content of EC in the road dust from the expressway entrance to Beijing was significantly higher than that in other road types. However, in 2013, the total content of all components tested and the contents of Si, Al, and Ca in the road dust PM2.5 of secondary main roads were significantly lower than those for other road types. Due to the implementation of dust, motor vehicles, and combustion source control measures in Beijing and the relocation of the Shougang corporation, only the content of SO42- in the road dust PM2.5 in Beijing increased slightly by 2.0% in 2013 compared with in 2004; the contents of the other components decreased significantly. The contents of Ca, Si, OC, Al, Fe, K, EC, and NO3- decreased by 45.1%, 31.5%, 17.5%, 20.3%, 55.6%, 33.3%, 30.0%, and 50.3%, respectively. The results showed that the ratio of[NO3-]/[SO42-] did not accurately reflect the changes in the relative contributions of fixed sources and moving sources. The[OC]/[EC] ratios of PM10 in 2004, PM2.5 in 2004, and PM2.5 in 2013 were 9.77±3.88, 9.36±3.25, and 14.41±10.41, respectively. Secondary organic carbon (SOC) pollution was present in road dust in Beijing, and the SOC was an important component in the road dust PM10 and PM2.5. The source profiles of different urban road dust samples and the source profiles of road dust of different sizes in the same city were not very similar, so the corresponding source profiles should be established and updated in a timely manner.

Serendipity-A Machine-Learning Application for Mining Serendipitous Drug Usage From Social Media.

Serendipitous drug usage refers to the unexpected relief of comorbid diseases or symptoms when taking medication for a different known indication. Historically, serendipity has contributed significantly to identifying many new drug indications. If patient-reported serendipitous drug usage in social media could be computationally identified, it could help generate and validate drug-repositioning hypotheses. We investigated deep neural network models for mining serendipitous drug usage from social media. We used the word2vec algorithm to construct word-embedding features from drug reviews posted in a WebMD patient forum. We adapted and redesigned the convolutional neural network, long short-term memory network, and convolutional long short-term memory network by adding contextual information extracted from drug-review posts, information-filtering tools, medical ontology, and medical knowledge. We trained, tuned, and evaluated our models with a gold-standard dataset of 15714 sentences (447 [2.8%] describing serendipitous drug usage). Additionally, we compared our deep neural networks to support vector machine, random forest, and AdaBoost.M1 algorithms. Context information helped to reduce the false-positive rate of deep neural network models. If we used an extremely imbalanced dataset with limited instances of serendipitous drug usage, deep neural network models did not outperform other machine-learning models with n-gram and context features. However, deep neural network models could more effectively use word embedding in feature construction, an advantage that makes them worthy of further investigation. Finally, we implemented natural-language processing and machine-learning methods in a web-based application to help scientists and software developers mine social media for serendipitous drug usage.

[Testing of Concentration and Characteristics of Particulate Matters Emitted from Stationary Combustion Sources in Beijing].

A self-built monitoring sampling system on particulate matters and water soluble ions emitted from stationary combustion sources and a size separated sampling system on particulate matters based on FPS4000 and ELPI + were applied to test particulate matters in fumes of typical stationary combustion sources in Beijing. The results showed that the maximum concentration of total particulate matters in fumes of stationary combustion sources in Beijing was 83.68 mg · m⁻³ in standard smoke oxygen content and the minimum was 0.12 mg · m⁻³. And particle number concentration was in the 104-106 cm⁻³ number of grade. Both mass and number concentration ranking order of particulate matters emitted from stationary combustion sources in Beijing was: heating gas fired boilers < power plant coal fired boilers < heating coal fired boilers. And two or three peaks existed under 1 µm of particulate size for both number size distribution and mass size distribution. The number concentration for PM2.5 accounted for over 99.8% of that for PM10 and that for PM0.1 accounted for over 83% of that for PM2.5. But the proportions of PM0.1, and PM2.5 in PM10 were significantly lower in quality analysis,the proportion of PM2.5 in PM10 was about 82%, and that of PM0.1 in PM2.5 was about 27%-33%.

[Emission Characteristics of Water-Soluble Ions in Fumes of Coal Fired Boilers in Beijing].

Selecting coal fired boilers with typical flue gas desulfurization and dust extraction systems in Beijing as the study objects, the issues and characteristics of the water-soluble ions in fumes of coal fired boilers and theirs influence factors were analyzed and evaluated. The maximum mass concentration of total water-soluble ions in fumes of coal fired boilers in Beijing was 51.240 mg x m(-3) in the benchmark fume oxygen content, the minimum was 7.186 mg x m(-3), and the issues of the water-soluble ions were uncorrelated with the fume moisture content. SO4(2-) was the primary characteristic water-soluble ion for desulfurization reaction, and the rate of contribution of SO4(2-) in total water-soluble ions ranged from 63.8% to 81.0%. F- was another characteristic water-soluble ion in fumes of thermal power plant, and the rate of contribution of F- in total water-soluble ions ranged from 22.2% to 32.5%. The fume purification technologies significantly influenced the issues and the emission characteristics of water-soluble ions in fumes of coal fired boilers. Na+ was a characteristic water-soluble ion for the desulfurizer NaOH, NH4+ and NO3+ were characteristic for the desulfurizer NH4HCO3, and Mg2+ was characteristic for the desulfurizer MgO, but the Ca2+ emission was not increased by addition of the desulfurizer CaO or CaCO3 The concentrations of NH4+ and NO3- in fumes of thermal power plant were lower than those in fumes of industrial or heating coal fired boilers. The form of water-soluble ions was significantly correlated with fume temperature. The most water-soluble ions were in superfine state at higher fume temperature and were not easily captured by the filter membrane.

VAET: A Visual Analytics Approach for E-Transactions Time-Series.

Previous studies on E-transaction time-series have mainly focused on finding temporal trends of transaction behavior. Interesting transactions that are time-stamped and situation-relevant may easily be obscured in a large amount of information. This paper proposes a visual analytics system, Visual Analysis of E-transaction Time-Series (VAET), that allows the analysts to interactively explore large transaction datasets for insights about time-varying transactions. With a set of analyst-determined training samples, VAET automatically estimates the saliency of each transaction in a large time-series using a probabilistic decision tree learner. It provides an effective time-of-saliency (TOS) map where the analysts can explore a large number of transactions at different time granularities. Interesting transactions are further encoded with KnotLines, a compact visual representation that captures both the temporal variations and the contextual connection of transactions. The analysts can thus explore, select, and investigate knotlines of interest. A case study and user study with a real E-transactions dataset (26 million records) demonstrate the effectiveness of VAET.

TenniVis: Visualization for Tennis Match Analysis.

Existing research efforts into tennis visualization have primarily focused on using ball and player tracking data to enhance professional tennis broadcasts and to aid coaches in helping their students. Gathering and analyzing this data typically requires the use of an array of synchronized cameras, which are expensive for non-professional tennis matches. In this paper, we propose TenniVis, a novel tennis match visualization system that relies entirely on data that can be easily collected, such as score, point outcomes, point lengths, service information, and match videos that can be captured by one consumer-level camera. It provides two new visualizations to allow tennis coaches and players to quickly gain insights into match performance. It also provides rich interactions to support ad hoc hypothesis development and testing. We first demonstrate the usefulness of the system by analyzing the 2007 Australian Open men's singles final. We then validate its usability by two pilot user studies where two college tennis coaches analyzed the matches of their own players. The results indicate that useful insights can quickly be discovered and ad hoc hypotheses based on these insights can conveniently be tested through linked match videos.