Freshwater Algal Bloom Prediction by Support Vector Machine in Macau Storage Reservoirs

Understanding and predicting dynamic change of algae population in freshwater reservoirs is particularly important, as algae-releasing cyanotoxins are carcinogens that would affect the health of public. However, the high complex nonlinearity of water variables and their interactions makes it difficult to model the growth of algae species. Recently, support vector machine (SVM) was reported to have advantages of only requiring a small amount of samples, high degree of prediction accuracy, and long prediction period to solve the nonlinear problems. In this study, the SVM-based prediction and forecast models for phytoplankton abundance in Macau Storage Reservoir (MSR) are proposed, in which the water parameters of pH, SiO2, alkalinity, bicarbonate (HCO3 -), dissolved oxygen (DO), total nitrogen (TN), UV254, turbidity, conductivity, nitrate, total nitrogen (TN), orthophosphate (PO4 3−), total phosphorus (TP), suspended solid (SS) and total organic carbon (TOC) selected from the correlation analysis of the 23 monthly water variables were included, with 8-year (2001–2008) data for training and the most recent 3 years (2009–2011) for testing. The modeling results showed that the prediction and forecast powers were estimated as approximately 0.76 and 0.86, respectively, showing that the SVM is an effective new way that can be used for monitoring algal bloom in drinking water storage reservoir

Development of a statistical forecasting model for PM

A daily PM2.5 forecasting model based on multiple linear regression (MLR) and backward trajectory clustering of HYSPLIT was designed for its application to small cities where PM2.5 level is easily affected by regional transport. The objective of this study is to investigate the regions that affect the fine particulate concentration of Macau and to develop an effective forecasting system to enhance the capture of PM2.5 episodes. By clustering the HYSPLIT 24-hr backward trajectories originated at Macau from 2015 to 2017, five potential transportation paths of PM2.5 were found. A cluster based statistical model was developed and trained with air quality and meteorological data of2015 and 2016. Then, the trained model was evaluated with data of 2017. Comparing to an ordinary model without backward trajectory clustering, the cluster based PM2.5 forecasting model yielded similar general forecast performance in 2017. However, the critical success index of the cluster based model was 11% higher than that of the ordinary model. This means the cluster based model has better model performance in PM2.5 concentration prediction and it is more important for the health of the public

Association of Human Mortality with Air Pollution of Hong Kong

In this study, we attempted to investigate the general statistical association of air pollution with the cardiovascular and respiratory mortality of the elderly in Hong Kong. Based on six years of measurements including the major air pollutant concentrations (PM10, SO2, NO, NO2, O3, CO), ambient temperature, and mortality (respiratory, cardiovascular) between 2005 and 2010, correlation analysis was carried out in annual, monthly and weekly time scales. From an annual perspective, it was found that the air pollution species may pose a constant effect on the respiratory and the cardiovascular mortality during the studied period since the elderly mortality rates and the air pollution annual concentrations show obvious constant trends. From a monthly time scale, it was found that NO2 and CO have high positive cross correlation with the respiratory mortality of the following 1 to 2 months. In addition, PM10 and CO also have similar delayed influence on the cardiovascular mortality. Among these four pollutants, only CO was found to exhibit high statistical association in the weekly time scale and it is most related to the cardiovascular mortality of the week after next. Therefore, it was concluded that the effect of air pollution on the elderly mortality of Hong Kong should be cumulative. This study implies that the establishment of weekly or monthly air quality indices is necessary for health implications

Temporal Patterns of Bacterial and Viral Communities during Algae Blooms of a Reservoir in Macau

Compositions of microbial communities associated with blooms of algae in a storage reservoir in Macau, China were investigated between 2013 and 2016. Algae were enumerated by visible light microscopy. Profiles of organisms in water were examined by 16S rRNA sequences and viral metagenomics, based on next generation sequencing. Results of 16S rRNA sequencing indicated that majority of the identified organisms were bacteria closely related to Proteobacteria, Cyanobacteria, Verrucomicrobia, Bacteroidetes, and Actinobacteria. Metagenomics sequences demonstrated that the dominant virus was Phycodnavirus, accounting for 70% of the total population. Patterns of relative numbers of bacteria in the microbial community and their temporal changes were determined through alpha diversity indices, principal coordinates analysis (PCoA), relative abundance, and visualized by Venn diagrams. Ways in which the bacterial and viral communities are influenced by various water-related variables were elucidated based on redundancy analysis (RDA). Relationships of the relative numbers of bacteria with trophic status in a reservoir used for drinking water in Macau, provided insight into associations of Phycodnavirus and Proteobacteria with changes in blooms of algae

On the Structure of a New Superhard Hexagonal Carbon Phase

Molecular dynamics simulations show that graphite will transform into a superhard phase under cold compression. Recent experiments show that there is a sp(3)-rich hexagonal carbon polymorph (a(0)=2.496 angstrom, c(0)=4.123 angstrom) with a bulk modulus of 447 GPa and average density about 3.6 g/cm(3), restricted to the space group of P-62c (No. 190), but the detailed atomic structure was not obtained [Wang et al, P. Natl. Acad. Sci. 101(38), 13699]. Here we set carbon atoms occupying P-62c 4f Wyckoff positions of P-62c, and calculate the total energy of the different structures changing the internal parameter z by first-principles calculations using geometry optimisation algorithm in CASTEP code, which shows that the stable structures in energy (at local minimum points) are hexagonal carbon (z =1/4) and hexagonal diamond (z = 1/16). The calculated mechanical properties and lattice parameters of the structure P-62c 4f(z = 1/4) are in good agreement with those of the new hexagonal carbon proposed by Wang et al, which indicates that the atomic structure is a possible candidate

Comparative safety and effectiveness of cholinesterase inhibitors and memantine for Alzheimer’s disease: a network meta-analysis of 41 randomized controlled trials

Abstract Background Cholinesterase inhibitors and memantine have been approved for management of Alzheimer’s disease (AD), but there has been no consensus about the choice of various types and doses of drugs at different stages. Hence, we compared and ranked the efficacy and tolerability of these available drugs. Methods We searched PubMed, the Cochrane Central Register of Controlled Trials, and Embase for randomized controlled trials (RCTs) published from database inception to July 21, 2017. The primary outcomes were the mean overall changes in cognitive function and responders who had any adverse events. We conducted a random-effects network meta-analysis. Results Forty-one RCTs were included in this study. Compared with placebo, galantamine 32 mg daily (standardized mean difference – 0.51, 95% credible interval – 0.67 to − 0.35), galantamine 24 mg daily (− 0.50, − 0.61 to − 0.40), and donepezil 10 mg daily (− 0.40, − 0.51 to − 0.29) were probably the most effective agents on cognition for mild to moderate AD, and memantine 20 mg combined with donepezil 10 mg (0.76, 0.39 to 1.11) was recommended for moderate to severe patients. Memantine showed the best profile of acceptability. Rivastigmine transdermal 15-cm2 patch was the best optional treatment both in function and global changes. None of the medicines was likely to improve neuropsychiatric symptoms through this analysis. Conclusions Pharmacological interventions have beneficial effects on cognition, function, and global changes, but not on neuropsychiatric symptoms, through current network meta-analysis. The choice of drugs may mainly depend on the disease severity and clinical symptoms

Enhanced Nitrite Production from the Aqueous Photolysis of Nitrate in the Presence of Vanillic Acid and Implications for the Roles of Light-Absorbing Organics

A prominent source of hydroxyl radicals ((OH)-O-center dot), nitrous acid (HONO) plays a key role in tropospheric chemistry. Apart from direct emission, HONO (or its conjugate base nitrite, NO2-) can be formed secondarily in the atmosphere. Yet, how secondary HONO forms requires elucidation, especially for heterogeneous processes involving numerous organic compounds in atmospheric aerosols. We investigated nitrite production from aqueous photolysis of nitrate for a range of conditions (pH, organic compound, nitrate concentration, and cation). Upon adding small oxygenates such as ethanol, n-butanol, or formate as (OH)-O-center dot scavengers, the average intrinsic quantum yield of nitrite [Phi-(NO2-)] was 0.75 +/- 0.15%. With near-UV-light-absorbing vanillic acid (VA), however, the effective Phi(NO2-) was strongly pHdependent, reaching 8.0 +/- 2.1% at a pH of 8 and 1.5 +/- 0.39% at a more atmospherically relevant pH of 5. Our results suggest that brown carbon (BrC) may greatly enhance the nitrite production from the aqueous nitrate photolysis through photosensitizing reactions, where the triplet excited state of BrC may generate solvated electrons, which reduce nitrate to NO2 for further conversion to nitrite. This photosensitization process by BrC chromophores during nitrate photolysis under mildly acidic conditions may partly explain the missing HONO in urban environments