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•DNN was verified and assessed for shallow landslide susceptibility mapping.•Three optimization algorithms, Adam, SGD, and RMSProp, were used.•Two loss functions, MSE and CE, were ...investigated.•DNN with Adam and MSE is the best and outperformed other models.•DNN-Adam-MSE is a new tool for shallow landslide susceptibility modeling.
This research aims at investigating the capability of Keras’s deep learning models with three robust optimization algorithms (stochastic gradient descent, root mean square propagation, and adaptive moment optimization) and two-loss functions for spatial modeling of landslide hazard at a regional scale. Shallow landslides at the Ha Long area (Vietnam) were selected as a case study. For this regard, set of ten influencing factors (slope, aspect, curvature, topographic wetness index, landuse, distance to road, distance to river, soil type, distance to fault, and lithology) and 193 landslide polygons were prepared to construct a Geographic Information System (GIS) database for the study area. Using the collected database, the DNN with its potential of realizing complex functional mapping hidden in the data is used to generalize a decision boundary that separates the learning space into two distinct categories: landslide (a positive class) and non-landslide (a negative class). Experimental results point out that the utilized the Keras’s deep learning model with the Adam optimization and the mean squared error lost function is the best with the prediction performance of 84.0%. The performance is better than those of the employed benchmark approaches of random forest, J48 decision tree, classification tree, and logistic model tree. We conclude that the Keras’s deep learning model is a new tool for shallow susceptibility mapping at landslide-prone areas.
This research aims at proposing a new artificial intelligence approach (namely RVM-ICA) which is based on the Relevance Vector Machine (RVM) and the Imperialist Competitive Algorithm (ICA) ...optimization for landslide susceptibility modeling. A Geographic Information System (GIS) spatial database was generated from Lang Son city in Lang Son province (Vietnam). This GIS database includes a landslide inventory map and fourteen landslide conditioning factors. The suitability of these factors for landslide susceptibility modeling in the study area was verified by the Information Gain Ratio (IGR) technique. A landslide susceptibility prediction model based on RVM-ICA and the GIS database was established by training and prediction phases. The predictive capability of the new approach was evaluated by calculations of sensitivity, specificity, accuracy, and the area under the Receiver Operating Characteristic curve (AUC). In addition, to assess the applicability of the proposed model, two state-of-the-art soft computing techniques including the support vector machine (SVM) and logistic regression (LR) were used as benchmark methods. The results of this study show that RVM-ICA with AUC = 0.92 achieved a high goodness-of-fit based on both the training and testing datasets. The predictive capability of RVM-ICA outperformed those of SVM with AUC = 0.91 and LR with AUC = 0.87. The experimental results confirm that the newly proposed model is a very promising alternative to assist planners and decision makers in the task of managing landslide prone areas.
Nitrogen removal is crucial in wastewater treatment process as excessive nitrogen content could result in eutrophication and degradation of aquatic ecosystems. Moreover, to satisfy the fast-growing ...need of fertilizers due to an increase in human population, recovering nitrogen from wastewater is of the most sustainable approach. Currently, the membrane technique integrated with biological processes namely bio-membrane based integrated system (BMIS) is a promising technology for recovering nitrogen from wastewater, including osmotic membrane bioreactors, bioelectrochemical systems and membrane photobioreactors. In this review study, the nitrogen recovery in different BMHSs, the role of operational parameters and the nitrogen recovery mechanism were discussed. Apart from this, the implementation of nitrogen recovery at pilot- and full-scale was summarized. Perspectives on the major challenges and recommendations of the BMIS for the nitrogen recovery in wastewater treatment were proposed, in which the integrated technologies and more scale-up studies regarding nitrogen recovery by the BMISs were also highlighted and recommended.
•The N recovery by bio-membrane based integrated systems (BMISs) was discussed.•Various configurations of BMISs for N recovery were reviewed.•Current implementation of N recovery at pilot/full-scale was summarized.•Perspective on BMISs for N recovery was given.•Integrated bio-membrane hybrid systems are promising for N recovery.
Photobioreactor technology, especially bubble column configuration, employing microalgae cultivation (e.g., Chlorella sp.), is an ideal man-made environment to achieve sufficient microalgae biomass ...through its strictly operational control. Nutrients, typically N and P, are necessary elements in the cultivation process, which determine biomass yield and productivity. Specifically, N:P ratios have certain effects on microalgae's biomass growth. It is also attractive that microalgae can sequester CO2 by using that carbon source for photosynthesis and, subsequently, reducing CO2 emission. Therefore, this study aims to investigate the effect of N:P ratios on Chlorella sp.’s growth, and to study the dynamic of CO2 fixation in the bubble column photobioreactor. According to our results, N:P ratio of 15:1 could produce the highest biomass yield (3568 ± 158 mg L−1). The maximum algae concentration was 105 × 106 cells mL−1, receiving after 92 h. Chlorella sp. was also able to sequester CO2 at 28 ± 1.2%, while the specific growth rate and carbon fixation rate were observed at 0.064 h−1 and 68.9 ± 1.91 mg L−1 h−1, respectively. The types of carbon sources (e.g., organic and inorganic carbon) possessed potential impact on microalgae's cultivation.
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•Optimal N:P ratio for culturing Chlorella sp. was 15:1.•Highest biomass concentration achieved in photobioreactor was 3568 mg L−1.•Maximum specific growth rate of Chlorella sp. at optimal N:P ratio was 0.064 h−1.•Carbon sequestration efficiency and rate were 28% and 68.9 mg L−1 h−1.
This study aims to offer insights into how ciprofloxacin (CIP) impact bacterial community structures in the Sponge-MBR process when CIP is spiked into hospital wastewater. We found that the CIP ...toxicity decreased richness critical phylotypes such as phylum class ẟ-, β-, ɣ-proteobacteria, and Flavobacteria that co-respond to suppress denitrification and cake fouling to 37% and 28% respectively. Cluster analysis shows that the different community structures were formed under the influence of CIP toxicity. CIP decreased attached growth biomass by 2.3 times while increasing the concentration of permeate nitrate by 3.8 times, greatly affecting TN removal by up to 26%. Ammonia removal was kept stable by inflating the ammonia removal rate (p < 0.003), with the wealthy Nitrospira genus guaranteeing the nitrification activity. In addition, we observed an increasing richness of Chloroflexi and Planctomycetes, which may play a role in fouling reduction in the Sponge-MBR. Therefore, if the amount of antibiotics in hospital wastewater continues to increase, it is so important to extend biomass retention for denitrification recovery.
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•Alpha diversity rebound from added ciprofloxacin in Sponge membrane bioreactor•Flavobacteria, ẟ, β, and ɣ-proteobacteria co-enhanced fouling and denitrification.•Improved nitrification thanks to the increasingly richness Nitrospira genus•Ciprofloxacin expanded genetic relationship between suspended and attached growth.•The richness of Chloroflexi, Planctomycetes played a vital role in fouling reduction.
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•Freshwater C. vulgaris is comparable to marine microalgae in pollutants removal.•Unsaturated salt forms layer on microalgae cells’ surface.•Microalgae accumulate salt ions in cells ...proportionally to salinities in culture.•Statistic well-confirms the positive effect of salinities on pollutant assimilation.•Organic loading levels might alleviate salinities effect but not yet proved.
This study investigated the growth dynamics of a freshwater and marine microalgae with supported biochemical performance in saline wastewater, the pollutants assimilation by a developed method, and the mechanism of salinity’s effect to pollutants assimilation. Maximal biomass yield was 400–500 mg/L at 0.1–1% salinity while the TOC, NO3−-N, PO43−-P were eliminated 39.5–92.1%, 23–97.4% and 7–30.6%, respectively. The biomass yield and pollutants removal efficiencies reduced significantly when salinity rose from 0.1 to 5%. The freshwater Chlorella vulgaris performed its best with a focus on TOC removal at 0.1% salinity. The marine Chlorella sp. was prominent for removing NO3−-N at 0.1–1% salinity. Through the developed method, the freshwater C. vulgaris competed to the marine microalgae referring to pollutants assimilation up to 5% salinity. This study unveiled the mechanism of salinity’s effect with evidence of salt layer formation and salt accumulation in microalgae.
A modified capacitive-coupled contactless conductivity sensor is proposed and developed for microfluidic flow detection based on the passive wireless inductor-capacitor (LC) technique. The device ...utilizes rapid prototyping including PolyJet 3D printing and PCB technologies to fabricate the microchannel and the readout inductor through which the conductivity of the fluidic flow is analyzed and foreign objects identified. The system employs an LC resonance circuit to monitor the shift in frequency and the change in the reflection coefficient, thereby estimating the conductivity of the fluidic flow and the appearance of objects. The operating principles were characterized by numerical calculations. The performance was validated by experimental measurements. The results show that the higher the electrical conductivity (i.e. the higher concentration) of the NaCl solution passing through the sensing area, the lower the resonance frequency. The resonance frequency due to the passage of NaCl solution with concentrations of 0.1, 0.5, and 1 M were 225.24, 218.93, and 215.67 MHz, respectively. The influence of the distance between the inductors on the resonance frequency of different solution conductivities has also been studied. The sensor system has high potential in various biomedical and chemical applications, particularly in point-of-care applications where sensor chips can be easily incorporated.
The failure of the centralized water supply system forced XY community to become more dependent on uncertain and unstable water sources. The results of surveying 50 households showed that 89.18% of ...total households depended on water collected from rivers, which contributed 58.3% of the total water volume used for the domestic demands. The average water volume consumed was 19.5 liters/person/day (l/p/d), and 86.5% of households used more than one source; 13.5% of households collected water only from rivers, and 45.94% of families had rainwater harvesting (RWH) for their activities (domestic water demand); however, RWH only provided 9.9% of total water consumption. In this study, basic methods were applied to calculate the storage tanks necessary to balance the water deficit created by drought months. Three levels of water demand (14, 20, and 30 l/p/d) can be the best choices for RWH; for a higher demand (40 and 60 l/p/d), small roof area (30–40 m
2
), and many people (six to seven) per family, RWH might be impractical because of unsuitable rainfall or excessively large storage tanks.
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