Spatiotemporal multi-graph convolutional network-based provincial-day-level terrorism risk prediction.

Predicting terrorism risk is crucial for formulating detailed counter-strategies. However, this task is challenging mainly because the risk of the concerned potential victim is not isolated. Terrorism risk has a spatiotemporal interprovincial contagious characteristic. The risk diffusion mechanism comes from three possibilities: cross-provincial terrorist attacks, internal and external echoes, and internal self-excitation. This study proposed a novel spatiotemporal graph convolutional network (STGCN)-based extension method to capture the complex and multidimensional non-Euclidean relationships between different provinces and forecast the daily risks. Specifically, three graph structures were constructed to represent the contagious process between provinces: the distance graph, the province-level root cause similarity graph, and the self-excited graph. The long short-term memory and self-attention layers were extended to STGCN for capturing context-dependent temporal characters. At the same time, the one-dimensional convolutional neural network kernel with the gated linear unit inside the classical STGCN can model single-node-dependent temporal features, and the spectral graph convolution modules can capture spatial features. The experimental results on Afghanistan terrorist attack data from 2005 to 2020 demonstrate the effectiveness of the proposed extended STGCN method compared to other machine learning prediction models. Furthermore, the results illustrate the crucial of capturing comprehensive spatiotemporal correlation characters among provinces. Based on this, this article provides counter-terrorism management insights on addressing the long-term root causes of terrorism risk and performing short-term situational prevention.

Interpretable spatial identity neural network-based epidemic prediction.

Epidemic spatial-temporal risk analysis, e.g., infectious number forecasting, is a mainstream task in the multivariate time series research field, which plays a crucial role in the public health management process. With the rise of deep learning methods, many studies have focused on the epidemic prediction problem. However, recent primary prediction techniques face two challenges: the overcomplicated model and unsatisfactory interpretability. Therefore, this paper proposes an Interpretable Spatial IDentity (ISID) neural network to predict infectious numbers at the regional weekly level, which employs a light model structure and provides post-hoc explanations. First, this paper streamlines the classical spatio-temporal identity model (STID) and retains the optional spatial identity matrix for learning the contagion relationship between regions. Second, the well-known SHapley Additive explanations (SHAP) method was adopted to interpret how the ISID model predicts with multivariate sliding-window time series input data. The prediction accuracy of ISID is compared with several models in the experimental study, and the results show that the proposed ISID model achieves satisfactory epidemic prediction performance. Furthermore, the SHAP result demonstrates that the ISID pays particular attention to the most proximate and remote data in the input sequence (typically 20 steps long) while paying little attention to the intermediate steps. This study contributes to reliable and interpretable epidemic prediction through a more coherent approach for public health experts.

Stretchable One-Dimensional Conductors for Wearable Applications.

Continuous, one-dimensional (1D) stretchable conductors have attracted significant attention for the development of wearables and soft-matter electronics. Through the use of advanced spinning, printing, and textile technologies, 1D stretchable conductors in the forms of fibers, wires, and yarns can be designed and engineered to meet the demanding requirements for different wearable applications. Several crucial parameters, such as microarchitecture, conductivity, stretchability, and scalability, play essential roles in designing and developing wearable devices and intelligent textiles. Methodologies and fabrication processes have successfully realized 1D conductors that are highly conductive, strong, lightweight, stretchable, and conformable and can be readily integrated with common fabrics and soft matter. This review summarizes the latest advances in continuous, 1D stretchable conductors and emphasizes recent developments in materials, methodologies, fabrication processes, and strategies geared toward applications in electrical interconnects, mechanical sensors, actuators, and heaters. This review classifies 1D conductors into three categories on the basis of their electrical responses: (1) rigid 1D conductors, (2) piezoresistive 1D conductors, and (3) resistance-stable 1D conductors. This review also evaluates the present challenges in these areas and presents perspectives for improving the performance of stretchable 1D conductors for wearable textile and flexible electronic applications.

Influence of nitrite accumulation on "Candidatus Accumulibacter" population structure and enhanced biological phosphorus removal from municipal wastewater.

A modified University of Cape Town (MUCT) process was used to treat real municipal wastewater with low carbon to nitrogen ratio (C/N). To our knowledge, this is the first study where the influence of nitrite accumulation on "Candidatus Accumulibacter" clade-level population structure was investigated during nitritation establishment and destruction. Real time quantitative PCR assays were conducted using the polyphosphate kinase 1 gene (ppk1) as a genetic marker. Abundances of total "Candidatus Accumulibacter", the relative distributions and population structure of the five "Candidatus Accumulibacter" clades were characterized. Under complete nitrification, clade I using nitrate as electron acceptor was below 5% of total "Candidatus Accumulibacter". When the reactor was transformed into nitritation, clade I gradually disappeared. Clade IID using nitrite as electron acceptor for denitrifying phosphorus (P) removal was always the dominant "Candidatus Accumulibacter" throughout the operational period. This clade was above 90% on average in total "Candidatus Accumulibacter", even up to nearly 100%, which was associated with good performance of denitrifying P removal via nitrite pathway. The nitrite concentrations affected the abundance of clade IID. The P removal was mainly completed by anoxic P uptake of about 88%. The P removal efficiency clearly had a positive correlation with the nitrite accumulation ratio. Under nitritation, the P removal efficiency was 30% higher than that under complete nitrification, suggesting that nitrite was appropriate as electron acceptor for denitrifying P removal when treating carbon-limited wastewater.

Integration of denitrifying phosphorus removal via nitrite pathway, simultaneous nitritation-denitritation and anammox treating carbon-limited municipal sewage.

High nutrients removal above 90% from carbon-limited municipal sewage was obtained without adding external carbon source. Achieving nitritation was a prerequisite to improve nutrients removal. Denitrifying phosphorus (P) removal using nitrite as electron acceptor was the key pathway in anoxic zone, where nitrogen removal reached above 60% and average denitrifying P removal was 88%. Simultaneous nitritation/denitritation and anaerobic ammonia oxidation (anammox) possibly contributed to nitrogen removal of 26-36% in aerobic zone. Quantitative PCR assays presented that the abundance of anammox bacteria under nitritation was more than that under complete nitrification. The largest amount of anammox bacteria was 1.32×10(6)copies/gVSS, about 5.6 times increase over a period of 255days. Nitrite concentration of 17mg/L in aerobic zone inhibited anammox bacteria. Quantitative results suggested possible occurrence of anammox. Based on performance of nitritation, combining heterotrophic denitrification with autotrophic nitrogen removal is an effective strategy to improve nutrients removal from carbon-limited wastewater.

Impact of nitrite on aerobic phosphorus uptake by poly-phosphate accumulating organisms in enhanced biological phosphorus removal sludges.

Impact of nitrite on aerobic phosphorus (P) uptake of poly-phosphate accumulating organisms (PAOs) in three different enhanced biological phosphorus removal (EBPR) systems was investigated, i.e., the enriched PAOs culture fed with synthetic wastewater, the two lab-scale sequencing batch reactors (SBRs) treating domestic wastewater for nutrient removal through nitrite-pathway nitritation and nitrate-pathway nitrification, respectively. Fluorescence in situ hybridization results showed that PAOs in the three sludges accounted for 72, 7.6 and 6.5% of bacteria, respectively. In the enriched PAOs culture, at free nitrous acid (FNA) concentration of 0.47 × 10(-3) mg HNO2-N/L, aerobic P-uptake and oxidation of intercellular poly-ß-hydroxyalkanoates were both inhibited. Denitrifying phosphorus removal under the aerobic conditions was observed, indicating the existence of PAOs using nitrite as electron acceptor in this culture. When the FNA concentration reached 2.25 × 10(-3) mg HNO2-N/L, denitrifying phosphorus removal was also inhibited. And the inhibition ceased once nitrite was exhausted. Corresponding to both SBRs treating domestic wastewater with nitritation and nitrification pathway, nitrite inhibition on aerobic P-uptake by PAOs did not occur even though FNA concentration reached 3 × 10(-3) and 2.13 × 10(-3) mg HNO2-N/L, respectively. Therefore, PAOs taken from different EBPR activated sludges had different tolerance to nitrite.

Nitritation and denitrifying phosphorus removal via nitrite pathway from domestic wastewater in a continuous MUCT process.

Nitritation and denitrifying P removal under mode of nitritation and nitrification was investigated in continuous MUCT process treating domestic wastewater. Nitritation was established through short hydraulic retention time to 6 h and low dissolved oxygen concentration of 0.3-0.5 mg/L. Nitritation was stabilized for 95 days with average nitrite accumulation ratio over 90%. Ammonia and total nitrogen removal under nitritation reached 99% and 83%, respectively, much better than complete nitrification. Real-time quantitative PCR assays presented that cell numbers and percentages of ammonia oxidizing bacteria (AOB) population had a clear correlation with nitrite accumulation ratios. The highest percentage of AOB was 13% of total bacterial population. P removal was mainly completed by denitrifying P removal of about 90% occurring in anoxic zone. The P removal efficiency under nitritation was 30% higher than that under complete nitrification. Denitrifying P removal under nitritation was highly beneficial to the treatment of wastewater with limiting carbon source.

[Denitrifying phosphorus removal in a Modified University of Cape Town (MUCT) process treating domestic wastewater under nitrification and nitritation].

The performance of denitrifying phosphorus removal under nitrification and nitritation was investigated in a lab-scale Modified University of Cape Town (MUCT) process treating real domestic wastewater with low C/N ratio. The experimental results of 180 days showed that nitritation was achieved at short hydraulic retention time (HRT) and low dissolved oxygen (DO) of 0.3-0.5 mg x L(-1), and an average nitrite accumulation rate (NAR) of above 70% was achieved during nitritation stage. The MUCT process showed a good performance of denitrifying phosphorus removal. Under nitritation mode, total and denitrifying phosphorus removal efficiencies were 90% and 91%, respectively; under nitrification mode, total and denitrifying phosphorus removal efficiencies were 60% and 88%, respectively. Although phosphorus removal performance under nitritation was better than that under nitrification, the results of fluorescence in situ hybridization (FISH) indicated that the percentage of phosphorus accumulating organisms (PAOs) in biomass was about 37% under two modes. The effluent COD concentration was below 50 mg x L(-1) during the experimental period. Batch tests of different nitrifying sludges showed that the percentage of denitrifying phosphorus removal bacteria (DPBs) in PAOs using NO2(-)-N as an electron acceptor under nitritation mode was almost the same as that using NO3(-)-N as an electron acceptor under nitrification mode, with an average percentage of 38%. Compared with nitrification mode with conventional phosphorus removal, nitritation mode with denitrifying phosphorus removal has a superior performance treating limited carbon source wastewater.