Passivation of lead and cadmium and increase of the nutrient content during sewage sludge composting by phosphate amendments.

As an efficient and cost-effective biological treatment method for sewage sludge, composting has been widely used worldwide. To passivate heavy metals and enhance the nutrient content in compost, in the present study, phosphate rock, calcium magnesium phosphate, and monopotassium phosphate were added to the composting substrate. According to the Community Bureau of Reference sequential extraction procedure, phosphate rock and monopotassium phosphate amendments exhibit a good passivation effect on Cd and Pb. The X-ray diffraction patterns proved the formation of Pb3(PO4)2 and Cd5(PO4)2SiO4 crystals, and X-ray absorption near-edge structure spectroscopy illustrated the change in P speciation after phosphate amendment. Furthermore, phosphate amendment increased the contents of total P and available P, and it reduced the loss of N during sewage sludge composting. The germination index showed that the target phosphate amendments in sewage sludge compost had no negative effects on seed germination, and this method has great potential to be used as a soil amendment.

Effect of phosphate amendments on improving the fertilizer efficiency and reducing the mobility of heavy metals during sewage sludge composting.

Composting has been globally applied as an effective and cost-efficient process to manage and reuse sewage sludge. In the present study, four different phosphates as well as a mixture of ferrous sulfate and monopotassium phosphate were used in sewage sludge composting. The results showed that these phosphate amendments promoted an increase in temperature and the degradation of organic matter as well as reduction on nitrogen loss during 18 days of composting. In addition, ferrous sulfate and phosphate had a synergistic effect on reducing nitrogen loss. The contents of total phosphorus and available phosphorus in the compost with addition of 1% phosphate were 40.9% and 66.1% higher than the compost with control treatment. Using the BCR (Community Bureau of Reference) sequential extraction procedure, the addition of calcium magnesium phosphate significantly reduced the mobility factor of Cd, Zn and Cu by 24.2%, 1.7% and 18.8%, respectively. The mobility factors of Pb were increased in all samples, but the monopotassium phosphate treated sample exhibited the greatest Pb passivation ability with the lowest mobility factor increase (1.8%) among all treatments. The X-ray diffraction patterns of compost samples indicated that the passivation mechanism of Cu and Zn may be the forming CuFeS2 and ZnCu(P2O7) crystals during sewage sludge composting. The germination index showed that the compost of all treatments was safe for agricultural application; the germination index of the calcium magnesium phosphate treatment was 99.9 ±â€¯11.8%, which was the highest among all treatments.

Quantifying the impact of strong ties in international scientific research collaboration.

Tie strength has been examined as an antecedent of creativity. Although it has been discovered that international collaboration affects scientific performance, the effect of tie strength in the international collaboration network has been largely neglected. Based on international publications of 72 countries/regions published from 1993 to 2013, we combine descriptive and panel regression methods to examine how the bonding of strong collaboration ties contributes to countries' international scientific performance. Strong ties occur at an average rate of 1 in 4 collaborators, whereas countries/regions share on average 84% of articles with their strong-tie collaborators. Our quantitative results provide an explanation for this phenomenon in international collaboration: the establishment of a strong tie relationship contributes to above-average productivity and citation frequency for countries/regions. To further explore which types of strong ties tend to have stronger citation impact, we analyse the relationship between persistent and stable collaboration and publication citation impact. Experimental results show that international collaborations with greater persistence and moderate stability tend to produce high impact publications. It is noteworthy that when the collaboration period is divided into different time intervals, similar findings can be found after the same analysis procedure is carried out. This indicates that our conclusions are robust. Overall, this study provides quantitative insights into the added value of long-term commitment and social trust associated with strong collaborative partnerships in international collaboration.

Multi-objective dynamic population shuffled frog-leaping biclustering of microarray data.

BACKGROUND: Multi-objective optimization (MOO) involves optimization problems with multiple objectives. Generally, theose objectives is used to estimate very different aspects of the solutions, and these aspects are often in conflict with each other. MOO first gets a Pareto set, and then looks for both commonality and systematic variations across the set. For the large-scale data sets, heuristic search algorithms such as EA combined with MOO techniques are ideal. Newly DNA microarray technology may study the transcriptional response of a complete genome to different experimental conditions and yield a lot of large-scale datasets. Biclustering technique can simultaneously cluster rows and columns of a dataset, and hlep to extract more accurate information from those datasets. Biclustering need optimize several conflicting objectives, and can be solved with MOO methods. As a heuristics-based optimization approach, the particle swarm optimization (PSO) simulate the movements of a bird flock finding food. The shuffled frog-leaping algorithm (SFL) is a population-based cooperative search metaphor combining the benefits of the local search of PSO and the global shuffled of information of the complex evolution technique. SFL is used to solve the optimization problems of the large-scale datasets. RESULTS: This paper integrates dynamic population strategy and shuffled frog-leaping algorithm into biclustering of microarray data, and proposes a novel multi-objective dynamic population shuffled frog-leaping biclustering (MODPSFLB) algorithm to mine maximum bicluesters from microarray data. Experimental results show that the proposed MODPSFLB algorithm can effectively find significant biological structures in terms of related biological processes, components and molecular functions. CONCLUSIONS: The proposed MODPSFLB algorithm has good diversity and fast convergence of Pareto solutions and will become a powerful systematic functional analysis in genome research.

Inhibitory Effects of the Addition of KNO3 on Volatile Sulfur Compound Emissions during Sewage Sludge Composting.

Odor released from the sewage sludge composting process often has a negative impact on the sewage sludge treatment facility and becomes a hindrance to promoting compost technology. This study investigated the effect of adding KNO3 on the emissions of volatile sulfur compounds, such as hydrogen sulfide (H2S), dimethyl sulfide (DMS), and carbon disulfide (CS2), during sewage sludge composting and on the physicochemical properties of compost products, such as arylsulfatase activity, available sulfur, total sulfur, moisture content, and germination index. The results showed that the addition of KNO3 could inhibit the emissions of volatile sulfur compounds during composting. KNO3 can also increase the heating rate and peak temperature of the compost pile and reduce the available sulfur loss. The addition of 4% and 8% KNO3 had the best effect on H2S emissions, and it reduced the emissions of H2S during composting by 19.5% and 20.0%, respectively. The addition of 4% KNO3 had the best effect on DMS and CS2 emissions, and it reduced the emissions of DMS and CS2 by 75.8% and 63.0%, respectively. Furthermore, adding 4% KNO3 had the best effect from the perspective of improving the germination index of the compost.

Dynamic biclustering of microarray data by multi-objective immune optimization.

BACKGROUND: Newly microarray technologies yield large-scale datasets. The microarray datasets are usually presented in 2D matrices, where rows represent genes and columns represent experimental conditions. Systematic analysis of those datasets provides the increasing amount of information, which is urgently needed in the post-genomic era. Biclustering, which is a technique developed to allow simultaneous clustering of rows and columns of a dataset, might be useful to extract more accurate information from those datasets. Biclustering requires the optimization of two conflicting objectives (residue and volume), and a multi-objective artificial immune system capable of performing a multi-population search. As a heuristic search technique, artificial immune systems (AISs) can be considered a new computational paradigm inspired by the immunological system of vertebrates and designed to solve a wide range of optimization problems. During biclustering several objectives in conflict with each other have to be optimized simultaneously, so multi-objective optimization model is suitable for solving biclustering problem. RESULTS: Based on dynamic population, this paper proposes a novel dynamic multi-objective immune optimization biclustering (DMOIOB) algorithm to mine coherent patterns from microarray data. Experimental results on two common and public datasets of gene expression profiles show that our approach can effectively find significant localized structures related to sets of genes that show consistent expression patterns across subsets of experimental conditions. The mined patterns present a significant biological relevance in terms of related biological processes, components and molecular functions in a species-independent manner. CONCLUSIONS: The proposed DMOIOB algorithm is an efficient tool to analyze large microarray datasets. It achieves a good diversity and rapid convergence.

Emission of volatile organic compounds from a small-scale municipal solid waste transfer station: Ozone-formation potential and health risk assessment.

Volatile organic compounds (VOCs) are the main precursors of tropospheric ozone and secondary aerosol generation, posing a threat to human health and affecting the environmental climate. A large quantity of VOCs can be produced in the initial decomposition stage of municipal solid waste (MSW). In this study, the atmosphere in an MSW transfer station was monitored for one year. The emission characteristics of VOCs in different seasons and working hours were analyzed, and the ozone-formation potential of VOCs was calculated through the maximum incremental reaction method, and health risks posed by the VOCs in the MSW transfer station were assessed. The results showed that the highest concentration of VOCs appeared in spring and summer, accounting for 70.6% and 26.6% of total VOCs (TVOCs) in peak working periods, respectively. Oxygenated compounds and terpenes contributed most to ozone formation, accounting for 41.0% and 50.6% of total ozone formation, respectively. The carcinogenic risks were above the safe threshold, labeled "probable risks". Tetrachloroethylene and 1,2-dichloroethane were the main contributors to carcinogenic risks. The mean non-carcinogenic risks were within the safe threshold in the MSW transfer station. From the perspective of protecting human health and ecological environmental safety, VOC control needs to be further strengthened in the transfer station.

Emission characteristics and health risk assessment of VOCs from a food waste anaerobic digestion plant: A case study of Suzhou, China.

The process of anaerobic digestion in food waste treatment plants generates a large amount of volatile organic compounds (VOCs). Long-term exposure to this exhaust gas can pose a threat to the health of workers and people living nearby. In this study, VOCs emitted from different working units in a food waste anaerobic digestion plant were monitored for a year. Variations in VOCs emitted from each unit were analyzed and a health risk assessment was conducted for each working unit. The results show that the concentration of VOCs in different units varied greatly. The highest cumulative concentration of VOCs appeared in the hydrothermal hydrolysis unit (3.49 × 104 µg/m3), followed by the sorting/crushing room (8.97 × 103 µg/m3), anaerobic digestion unit (6.21 × 102 µg/m3), and biogas production unit (2.01 × 102 µg/m3). Oxygenated compounds and terpenes were the major components of the emitted VOCs, accounting for more than 98% of total VOC emissions. The carcinogenic risk in the plant exceeded the safety threshold (ILCR<1 × 10-6), while the non-carcinogenic risk was within the acceptable range (HI < 1). The carcinogenic risk from the hydrothermal hydrolysis unit was the highest, reaching 4.4 × 10-5, and was labeled as "probable risk." The carcinogenic risk at the plant boundary was 1.2 × 10-5, indicating exhaust gases can cause a health threat to neighbors. Therefore, management VOCs in anaerobic digestion plants should receive more attention, and employees should minimize the time they spend in the hydrothermal hydrolysis unit.

Biclustering of microarray data with MOSPO based on crowding distance.

BACKGROUND: High-throughput microarray technologies have generated and accumulated massive amounts of gene expression datasets that contain expression levels of thousands of genes under hundreds of different experimental conditions. The microarray datasets are usually presented in 2D matrices, where rows represent genes and columns represent experimental conditions. The analysis of such datasets can discover local structures composed by sets of genes that show coherent expression patterns under subsets of experimental conditions. It leads to the development of sophisticated algorithms capable of extracting novel and useful knowledge from a biomedical point of view. In the medical domain, these patterns are useful for understanding various diseases, and aid in more accurate diagnosis, prognosis, treatment planning, as well as drug discovery. RESULTS: In this work we present the CMOPSOB (Crowding distance based Multi-objective Particle Swarm Optimization Biclustering), a novel clustering approach for microarray datasets to cluster genes and conditions highly related in sub-portions of the microarray data. The objective of biclustering is to find sub-matrices, i.e. maximal subgroups of genes and subgroups of conditions where the genes exhibit highly correlated activities over a subset of conditions. Since these objectives are mutually conflicting, they become suitable candidates for multi-objective modelling. Our approach CMOPSOB is based on a heuristic search technique, multi-objective particle swarm optimization, which simulates the movements of a flock of birds which aim to find food. In the meantime, the nearest neighbour search strategies based on crowding distance and -dominance can rapidly converge to the Pareto front and guarantee diversity of solutions. We compare the potential of this methodology with other biclustering algorithms by analyzing two common and public datasets of gene expression profiles. In all cases our method can find localized structures related to sets of genes that show consistent expression patterns across subsets of experimental conditions. The mined patterns present a significant biological relevance in terms of related biological processes, components and molecular functions in a species-independent manner. CONCLUSION: The proposed CMOPSOB algorithm is successfully applied to biclustering of microarray dataset. It achieves a good diversity in the obtained Pareto front, and rapid convergence. Therefore, it is a useful tool to analyze large microarray datasets.

Application of ceramsite and activated alumina balls as recyclable bulking agents for sludge composting.

Composting is a major sludge-treatment method and bulking agents are very important in sludge composting. In this study, ceramsite and activated alumina balls were chosen as recyclable bulking agents for sludge composting. Variations in the temperature, pH, electrical conductivity, organic matter, dissolved organic carbon, moisture content, and heavy metals were detected during composting with different bulking-agent treatments as well as differences in the germination index values. The results showed that both bulking agents could ensure the maturity of the compost; further, ceramsite treatment resulted in the best water removal efficiency. According to the sequential extraction procedure, both ceramsite and activated alumina balls could stabilize Cd but they also increased the mobility of Zn. After comparing the effects of different particle sizes of ceramsite on composting, 20 mm was determined to be the most optimal value. Additionally, the recovery rates of ceramsite and activated alumina balls were 96.9% and 99.9%, respectively.