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The red imported fire ant,Solenopsis invictaBuren is a destructive invasive species that has spread around the world. Early detection ofS. invictanests is critical for effective monitoring and control in invaded regions. This study presents a novel surveillance system forS. invictanests combining artificial intelligence and robotic dogs. The system was designed with intelligent recognition algorithms to accurately identifyS. invictanests. With a precision rate of 95%, the system yielded efficient detection ofS. invictanests with increased sensitivity and low missing and false discovery rates, which can aid or even replace humans in locating and delivering pesticides to fire ant nests in open fields to effective control of this invasive pest.

The rapid dewatering process of wastewater sludge was studied. The effects of two different thickening methods on subsequent conditioning and pressing were compared: gravity thickening and mechanical concentration. The study also investigated the optimal type and the concentration of flocculant added by sludge concentration, which was 0.2%. In terms of mechanical concentration method, under the same formulation of conditioner, the addition of Polyacrylamide(PAM) could significantly promote the dewatering process. Compared with the gravitational sedimentation and the sludge without chemical concentration, the filtration rate and dry-base treatment efficiency of the sludge during pressing were obviously improved, and the moisture content of the sludge cake was reduced.

To solve the highly non-linear problem of sludge conditioning and dewatering model, the Support Vector Machines (SVM), was used to model the sludge conditioning process and the sample data like organic matter content, dosage ratio of reagent A and reagent B was set as input while the filter index was set as out put. The simulation results indicated that the filtering performance was basically consistent with the actual value of dosage and the model prediction result, and the target value could be well predicted. It shown that the model had a certain value for industrial application.

In this study, the sludge of three municipal sewage treatment plants in Foshan City, Guangdong Province, China, was dewatered and recycled. The experimental results shown that after deep dewatering with different chemical conditioning reagents, the moisture content of municipal sewage sludge was decreased greatly, from about 97% to about 55%. After dewatering, the organic matter content of sludge was maintained at a high level which is beneficial to the composting treatment of the sludge. The organic matter content of sludge in Foshan No. 1 Sewage Treatment Plant and No. 2 Sewage Treatment Plant was more than 30%, while it was between 15% and 20% in Foshan No. 3 Sewage Treatment Plant. Sludge from all three sewage treatment plants neeed to add a small amount of nutrients to compost. After 14 days of the aerobic composting, the moisture content of the sewage sludge could be reduced to less than 50%, and all the index met the requirements of the agricultural standard.