ABSTRACT
The box-covering method plays a fundamental role in the fractal property recognition and renormalization analysis of complex networks. This study proposes the hub-collision avoidance and leaf-node options (HALO) algorithm. In the box sampling process, a forward sampling rule (for avoiding hub collisions) and a reverse sampling rule (for preferentially selecting leaf nodes) are determined for bidirectional network traversal to reduce the randomness of sampling. In the box selection process, the larger necessary boxes are preferentially selected to join the solution by continuously removing small boxes. The compact-box-burning (CBB) algorithm, the maximum-excluded-mass-burning (MEMB) algorithm, the overlapping-box-covering (OBCA) algorithm, and the algorithm for combining small-box-removal strategy and maximum box sampling with a sampling density of 30 (SM30) are compared with HALO in experiments. Results on nine real networks show that HALO achieves the highest performance score and obtains 11.40%, 7.67%, 2.18%, and 8.19% fewer boxes than the compared algorithms, respectively. The algorithm determinism is significantly improved. The fractal dimensions estimated by covering four standard networks are more accurate. Moreover, different from MEMB or OBCA, HALO is not affected by the tightness of the hubs and exhibits a stable performance in different networks. Finally, the time complexities of HALO and the compared algorithms are all O(N2), which is reasonable and acceptable.
Subject(s)
Algorithms , FractalsABSTRACT
This study is aim to illustrate Phyllostachys edulis' role in affecting air quality under hazy day and solar day. P. edulis is a crucial plants growing well at suburban area at China Southern. In this manuscript, on 2 weather conditions (hazy day; solar day), changes in atmospheric particulate matter (PM), polycyclic aromatic hydrocarbons (PAHs), associated volatile organic compounds (VOCs), and PAHs in leaves and soils were measured, with PM-detection equipment and the GC-MC method, in a typical bamboo forest at suburban areas. The results showed that: (1) Bamboo forest decreased atmospheric PM2.5 and PM10 concentrations significantly by 20% and 15%, respectively, on the hazy day nightfall time, when they were times higher than that on any other time. Also, similar effects on atmospheric PAHs and VOCs were found. (2) Significant increases in PAHs of leaves and soil were found inside the forest on the hazy day. (3) Bamboo forest also reduced the atmospheric VOC concentrations, and changed the compounds of 10 VOCs present in the highest concentration list. Thus, bamboo forests strongly regulate atmospheric PM2.5 through capture or retention, for the changes in atmospheric VOCs and increase in PAHs of leaves and soil.
Subject(s)
Environmental Monitoring/methods , Particulate Matter/analysis , Sasa/metabolism , Air Pollutants/analysis , Air Pollution/analysis , China , Forests , Particulate Matter/adverse effects , Particulate Matter/metabolism , Polycyclic Aromatic Hydrocarbons/analysis , Soil/chemistry , Volatile Organic Compounds/analysis , WeatherABSTRACT
Two new phenylpropanoid glycosides, named ß-D-(1-O-acetyl-3,6-O-diferuloyl) fructofuranosyl ß-D-6'-O-acetylglucopyranoside (1) and ß-D-(1-O-acetyl-3,6-O-diferuloyl) fructofuranosyl α-D-glucopyranoside (2), along with two known analogues (3-4) and four glycerides (5-8), were isolated from the EtOAc extract of the leaves of Ananas comosus. Their structures were elucidated on the basis of 1D- and 2D-NMR analyses, as well as HR-ESI-MS experiments. Compounds 1-4 showed significant antibacterial activities against Staphylococcus aureus and Escherichia coli.
Subject(s)
Ananas/chemistry , Glycosides/chemistry , Plant Leaves/chemistry , Anti-Bacterial Agents/chemistry , Anti-Bacterial Agents/pharmacology , Bacteria/drug effects , Molecular StructureABSTRACT
OBJECTIVE: To study the optimum preparation process of the volatile oil of Dalbergia odorifera-beta-cyclodextrin. METHODS: The saturated water solution mixing method was compared with microwave method and ultrasonic method by determining the ultilization ratio of the volatile oil in Dalbergia odorifera. The optimum preparation conditions were investigated by the orthogonal design. The quality of the volatile oil before and after included were analyzed by TLC. RESULTS: The optimum preparation conditions for inclusion were as follows: m(volatile oil of Dalbergia odorifera): m (beta-CD) = 1:10 (g/g), ultrasonic time was 1h, the temperature was 70 degrees C. The ultilization ratio of the volatile oil was 82.02%. CONCLUSION: Ultrasonic method is the best method.
