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Extracellular polymeric substances (EPS) are a critical influencing factor in sludge dewatering. Disrupting such EPS contributes to the release of bound water in sludge, enhancing the sludge dewatering performance. In This study, quaternized straw fibers that are destructive to the EPS structure and components in active sludge were prepared useing heterogeneous free radical graft polymerization. Straw fibers, dimethyl diallyl ammonium chloride (DMDAAC), ammonium persulfate (APS), and acrylamide (AM) were taken as the substrate, grafting monomer, catalyst, and cross-linking agent, respectively.The optimal processing conditions determined for the DMDAAC-based quaternization and graft modification of straw fibers were as follows: reaction temperature of 60 °C, reaction time of 5 h, 0.100 g of catalyst APS dosage per gram of straw, and 3.000 ml of DMDAAC dosage per gram of straw. The optimal processing conditions yielded 1.335 g of modified straw fibers per gram of straw, 33.67% grafting rate, and 31.70% substitution of the quaternary ammonium groups. The capillary suction time (CST) was conditioned from 243.3 ± 22.6 s in the original sludge to 134.5 ± 34.45 s. The specific resistance to filtration (SRF) was reduced from 8.82 ± 0.51 × 1012 m/kg in the original sludge to 4.59 ± 0.23 × 1012 m/kg. HIGHLIGHTS Modification of straw fiber by quaternary amination grafting can improve sludge dewatering performance.; Modified straw fiber improves sludge dewatering capacity by absorbing EPS.; Modified straw fiber can damage the stability of sludge floc.; Modified straw fiber provides a skeleton structure in the sludge for water removal from the sludge.;

Three polymeric materials; polystyrene (amorphous), low-density polyethylene (semi-crystalline), and poly(methyl methacrylate) (amorphous) were used to explore their behavior and properties during processing using a co-rotating twin-screw extruder. Injection molding and compression molding were used for preparing the test specimens. Screw speed and barrel set temperatures were considered as the main processing variables while observing the process energy consumption of the extruder. The tensile, thermal, and rheological properties of the extruded materials under different processing conditions were evaluated. Test results confirmed that the motor power of the extruder for processing polystyrene and low-density polyethylene increased with increasing screw speed and decreased with increasing barrel set temperatures. Motor power for processing poly(methyl methacrylate) increased significantly with increasing screw speed. The total power consumption of the barrel heaters for processing polystyrene and low-density polyethylene slightly increased with the barrel set temperatures. The tensile modulus of polystyrene decreased with increasing screw speed at higher barrel set temperatures, while low-density polyethylene showed no significant variation. The tensile modulus of poly(methyl methacrylate) did not exhibit a clear trend with the extruder process settings. The effect of process settings on the glass transition temperature and melting temperature of the polymers was not significant, and no evidence was found of any molecular degradation during processing. Rheological properties of poly(methyl methacrylate) showed a significant variation with increasing screw speed and barrel set temperatures, while those of polystyrene and low-density polyethylene did not exhibit a consistent variation.

With the expansion of the scale of electric power, high-quality electrical energy remains a crucial aspect of power system management and operation. The generation of reactive power is the primary cause of the decline in electrical energy quality. Therefore, optimization of reactive power in the power system becomes particularly important. The primary objective of this article is to create a multi-objective reactive power optimization (MORPO) model for distribution networks. The model aims to minimize reactive power loss, reduce the overall compensation required for reactive power devices, and minimize the total sum of node voltage deviations. To tackle the MORPO problems for distribution networks, the improved sparrow search algorithm–particle swarm optimization (ISSA-PSO) algorithm is proposed. Specifically, two improvements are proposed in this paper. The first is to introduce a chaotic mapping mechanism to enhance the diversity of the population during initialization. The second is to introduce a three-stage differential evolution mechanism to improve the global exploration capability of the algorithm. The proposed algorithm is tested on the IEEE 33-node system and the practical 22-node system. The results indicate a reduction of 32.71% in network losses for the IEEE 33-node system after optimization, and the average voltage of the circuit increases from 0.9485 p.u. to 0.9748 p.u. At the same time, optimization results in a reduction of 44.07% in network losses for the practical 22-node system, and the average voltage of the circuit increases from 0.9838 p.u. to 0.9921 p.u. Therefore, the proposed method exhibits better performance for reducing network losses and enhancing voltage levels.

Yield prediction for tomatoes in greenhouses is an important basis for making production plans, and yield prediction accuracy directly affects economic benefits. To improve the prediction accuracy of tomato yield in Chinese-style solar greenhouses (CSGs), a wavelet neural network (WNN) model optimized by a genetic algorithm (GA-WNN) is applied. Eight variables are selected as input parameters and the tomato yield is the prediction output. The GA is adopted to optimize the initial weights, thresholds, and translation factors of the WNN. The experiment results show that the mean relative errors (MREs) of the GA-WNN model, WNN model, and backpropagation (BP) neural network model are 0.0067, 0.0104, and 0.0242, respectively. The results root mean square errors (RMSEs) are 1.725, 2.520, and 5.548, respectively. The EC values are 0.9960, 0.9935, and 0.9868, respectively. Therefore, the GA-WNN model has a higher prediction precision and a better fitting ability compared with the BP and the WNN prediction models. The research of this paper is useful from both theoretical and technical perspectives for quantitative tomato yield prediction in the CSGs.

Three polymeric materials; polystyrene (amorphous), low-density polyethylene (semi-crystalline), and poly(methyl methacrylate) (amorphous) were used to explore their behavior and properties during processing using a co-rotating twin-screw extruder. Injection molding and compression molding were used for preparing the test specimens. Screw speed and barrel set temperatures were considered as the main processing variables while observing the process energy consumption of the extruder. The tensile, thermal, and rheological properties of the extruded materials under different processing conditions were evaluated. Test results confirmed that the motor power of the extruder for processing polystyrene and low-density polyethylene increased with increasing screw speed and decreased with increasing barrel set temperatures. Motor power for processing poly(methyl methacrylate) increased significantly with increasing screw speed. The total power consumption of the barrel heaters for processing polystyrene and low-density polyethylene slightly increased with the barrel set temperatures. The tensile modulus of polystyrene decreased with increasing screw speed at higher barrel set temperatures, while low-density polyethylene showed no significant variation. The tensile modulus of poly(methyl methacrylate) did not exhibit a clear trend with the extruder process settings. The effect of process settings on the glass transition temperature and melting temperature of the polymers was not significant, and no evidence was found of any molecular degradation during processing. Rheological properties of poly(methyl methacrylate) showed a significant variation with increasing screw speed and barrel set temperatures, while those of polystyrene and low-density polyethylene did not exhibit a consistent variation. [ABSTRACT FROM AUTHOR]