The accumulation of phosphorus in activated sludge in wastewater treatment plants (WWTPs) provides potential for phosphorus recovery from sewage. This study delves into the potential for releasing phosphorus from waste activated sludge through two distinct treatment methods—thermal hydrolysis and pH adjustment. The investigation was conducted with activated sludge sourced from four WWTPs, each employing distinct phosphorus removal strategies. The findings underscore the notably superior efficacy of pH adjustment in solubilizing sludge phosphorus compared to the prevailing practice of thermal hydrolysis, widely adopted to enhance sludge digestion. The reversibility of phosphorus release within pH fluctuations spanning 2 to 12 implies that the release of sludge phosphorus can be attributed to the dissolution of phosphate precipitates. Alkaline sludge treatment induced the concurrent liberation of COD, nitrogen, and phosphorus through alkaline hydrolysis of sludge biomass and the dissolution of iron or aluminium phosphates, offering potential gains in resource recovery and energy efficiency.

Hydrothermal carbonization (HTC) liquor of waste activated sludge generated during urban sewage biotreatment contains high concentrations of phosphate and thus is an appropriate resource for phosphorus recovery. The influence of proteins in the HTC liquor on vivianite crystallization, as a promising phosphorus recovery method, was investigated in this study from the perspectives of removal efficiencies and product properties. The proteins in the HTC liquor were observed to remain in unhydrolyzed forms with free amino acids having a negligible concentration. For vivianite crystallization in the synthetic HTC liquor with bovine serum albumin (BSA) mimicking the unhydrolyzed proteins, the efficiencies of phosphorus removal and crystallization at pH 6 decreased by 13.5 % and 18.4 %, respectively, compared with the BSA-free controls. The strong interaction between Fe and the proteins was suggested to be responsible for the reduced efficiency of vivianite formation and the variation of crystal growth mode from spirally expanding to x/z-axis extending.

Due to widespread applications, the multi-virus competing spreading dynamics has recently aroused considerable interests. To our knowledge, all previous competing spreading models assume infection rates that are each linear in the virus occupancy probabilities of the individuals in a population. As linear infection rates are overestimation of real infection rates, in some situations these models cannot accurately predict the spreading process of multiple competing viruses. This work takes the first step toward enhancing the accuracy of multi-virus competing spreading models. A continuous-time bilayer-network-based bi-virus competing spreading model with generic infection rates is proposed. Criteria for the extinction of both viruses and for the survival of only one virus are presented, respectively. Numerical examples show that (1) if the generic bi-virus spreading model with linear infection rates predicts that the fraction of nodes infected with some virus would approach zero, the prediction of the fraction is accurate, and (2) if the scenario-relevant generic infection rates could be estimated accurately, the resulting model would be able to accurately forecast the evolutionary process of a pair of competing viruses.

There are plenty of conflicting messages in online social networks. This paper addresses the competition of two conflicting messages. Based on a novel individual-level competing spreading model (the generic UABU model), three criteria for one or two messages to terminate are presented. These criteria manifest the influence of the two message-spreading networks on the evolution of the two messages. Extensive computer simulations show that when a message terminates, the dynamics of a simplified UABU model (the linear UABU model) fits well with the expected evolutionary process of the message. These findings help in understanding the competing spreading process of two conflicting messages.

As compared to the traditional advertising, word-of-mouth (WOM) communications have striking advantages such as significantly lower cost and much faster propagation, and this is especially the case with the popularity of online social networks. This paper focuses on the modeling and analysis of the WOM marketing. A dynamic model, known as the SIPNS model, capturing the WOM marketing processes with both positive and negative comments is established. On this basis, a measure of the overall profit of a WOM marketing campaign is proposed. The SIPNS model is shown to admit a unique equilibrium, and the equilibrium is determined. The impact of different factors on the equilibrium of the SIPNS model is illuminated through theoretical analysis. Extensive experimental results suggest that the equilibrium is much likely to be globally attracting. Finally, the influence of different factors on the expected overall profit of a WOM marketing campaign is ascertained both theoretically and experimentally. Thereby, some promotion strategies are recommended. To our knowledge, this is the first time the WOM marketing is treated in this way.

Alerting at the early stage of malware invasion turns out to be an important complement to malware detection and elimination. This paper addresses the issue of how to dynamically contain the prevalence of malware at a lower cost, provided alerting is feasible. A controlled epidemic model with alert is established, and an optimal control problem based on the epidemic model is formulated. The optimality system for the optimal control problem is derived. The structure of an optimal control for the proposed optimal control problem is characterized under some conditions. Numerical examples show that the cost-efficiency of an optimal control strategy can be enhanced by adjusting the upper and lower bounds on admissible controls.

Advanced persistent threats (APTs) pose a grave threat to cyberspace, because they deactivate all the conventional cyber defense mechanisms. This paper addresses the issue of evaluating the security of the cyber networks under APTs. For this purpose, a dynamic model capturing the APT-based cyber-attack-defense processes is proposed. Theoretical analysis shows that this model admits a globally stable equilibrium. On this basis, a new security metric known as the equilibrium security is suggested. The impact of several factors on the equilibrium security is revealed through theoretical analysis or computer simulation. These findings contribute to the development of feasible security solutions against APTs.

The node-based epidemic modeling is an effective approach to the understanding of the impact of the structure of the propagation network on the epidemics of electronic virus. In view of the heterogeneity of the propagation network, a heterogeneous node-based SIRS model is proposed. Theoretical analysis shows that the maximum eigenvalue of a matrix related to the model determines whether viruses tend to extinction or persist. When viruses persist, the connectedness of the propagation network implies the existence and uniqueness of a viral equilibrium, and a set of sufficient conditions for the global stability of the viral equilibrium are given. Numerical examples verify the correctness of our results.

Virus patches can be disseminated rapidly through computer networks and take effect as soon as they have been installed, which significantly enhances their virus-containing capability. This paper aims to theoretically assess the impact of patch forwarding on the prevalence of computer virus. For that purpose, a new malware epidemic model, which takes into full account the influence of patch forwarding, is proposed. The dynamics of the model is revealed. Specifically, besides the permanent susceptible equilibrium, this model may admit an infected or a patched or a mixed equilibrium. Criteria for the global stability of the four equilibria are given, respectively, accompanied with numerical examples. The obtained results show that the spectral radii of the patch-forwarding network and the virus-spreading network both have a marked impact on the prevalence of computer virus. The influence of some key factors on the prevalence of virus is also revealed. Based on these findings, some strategies of containing electronic virus are recommended.

There are quite a number of different metrics of network robustness. This paper addresses the rationality of four metrics of network robustness (the algebraic connectivity, the effective resistance, the average edge betweenness, and the efficiency) by investigating the robust growth of generalized meshes (GMs). First, a heuristic growth algorithm (the Proximity- Growth algorithm) is proposed. The resulting proximity-optimal GMs are intuitively robust and hence are adopted as the benchmark. Then, a generalized mesh (GM) is grown up by stepwise optimizing a given measure of network robustness. The following findings are presented: (1) The algebraic connectivity-optimal GMs deviate quickly from the proximity-optimal GMs, yielding a number of less robust GMs. This hints that the rationality of the algebraic connectivity as a measure of network robustness is still in doubt. (2) The effective resistace-optimal GMs and the average edge betweenness-optimal GMs are in line with the proximity-optimal GMs. This partly justifies the two quantities as metrics of network robustness. (3) The efficiency-optimal GMs deviate gradually from the proximity-optimal GMs, yielding some less robust GMs. This suggests the limited utility of the efficiency as a measure of network robustness.