Antimicrobial resistance (AMR) is a growing threat to human and animal health. Progress in molecular biology has revealed new and significant challenges for AMR mitigation given the immense diversity ...of antibiotic resistance genes (ARGs), the complexity of ARG transfer, and the broad range of omnipresent factors contributing to AMR. Municipal, hospital and abattoir wastewater are collected and treated in wastewater treatment plants (WWTPs), where the presence of diverse selection pressures together with a highly concentrated consortium of pathogenic/commensal microbes create favourable conditions for the transfer of ARGs and proliferation of antibiotic resistant bacteria (ARB). The rapid emergence of antibiotic resistant pathogens of clinical and veterinary significance over the past 80 years has re-defined the role of WWTPs as a focal point in the fight against AMR. By reviewing the occurrence of ARGs in wastewater and sludge and the current technologies used to quantify ARGs and identify ARB, this paper provides a research roadmap to address existing challenges in AMR control via wastewater treatment. Wastewater treatment is a double-edged sword that can act as either a pathway for AMR spread or as a barrier to reduce the environmental release of anthropogenic AMR. State of the art ARB identification technologies, such as metagenomic sequencing and fluorescence-activated cell sorting, have enriched ARG/ARB databases, unveiled keystone species in AMR networks, and improved the resolution of AMR dissemination models. Data and information provided in this review highlight significant knowledge gaps. These include inconsistencies in ARG reporting units, lack of ARG/ARB monitoring surrogates, lack of a standardised protocol for determining ARG removal via wastewater treatments, and the inability to support appropriate risk assessment. This is due to a lack of standard monitoring targets and agreed threshold values, and paucity of information on the ARG-pathogen host relationship and risk management. These research gaps need to be addressed and research findings need to be transformed into practical guidance for WWTP operators to enable effective progress towards mitigating the evolution and spread of AMR.
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•Wastewater treatment plays a crucial role in controlling AMR.•Molecular biology techniques can quantify ARG and identify ARB in wastewater system.•Keystone species of the AMR network and contributing factors can be mapped.•Revealing ARG-pathogen host relationships is essential to assess and monitor risk.•Future work to focus on ARG/ARB surrogates, thresholds and reporting units
Vu Gia-Thu Bon (VGTB) river basin is an area where flash flood and heavy flood events occur frequently, negatively impacting the local community and socio-economic development of Quang Nam Province. ...In recent years, structural and non-structural solutions have been implemented to mitigate damages due to floods. However, under the impact of climate change, natural disasters continue to happen unpredictably day by day. It is, therefore, necessary to develop a spatial decision support system for real-time flood warnings in the VGTB river basin, which will support in ensuring the area's socio-economic development. The main purpose of this study is to develop an online flood warning system in real-time based on Internet-of-Things (IoT) technologies, GIS, telecommunications, and modeling (Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center's River Analysis System (HEC-RAS)) in order to support the local community in the vulnerable downstream areas in the event of heavy rainfall upstream. The structure of the designed system consists of these following components: (1) real-time hydro-meteorological monitoring network, (2) IoT communication infrastructure (Global System for Mobile Communications (GSM), General Packet Radio Service (GPRS), wireless networks), (3) database management system (bio-physical, socio-economic, hydro-meteorological, and inundation), (4) simulating and predicting model (SWAT, HEC-RAS), (5) automated simulating and predicting module, (6) flood warning module via short message service (SMS), (7) WebGIS, application for providing and managing hydro-meteorological and inundation data, and (8) users (citizens and government officers). The entire operating processes of the flood warning system (i.e., hydro-meteorological data collecting, transferring, updating, processing, running SWAT and HEC-RAS, visualizing) are automated. A complete flood warning system for the VGTB river basin has been developed as an outcome of this study, which enables the prediction of flood events 5 h in advance and with high accuracy of 80%.
This study investigated the production of biogas, volatile fatty acids (VFAs), and other soluble organic from lignocellulosic biomass by two microbial communities (i.e. rumen fluid and anaerobic ...sludge). Four types of abundant lignocellulosic biomass (i.e. wheat straw, oaten hay, lurence hay and corn silage) found in Australia were used. The results show that rumen microbes produced four-time higher VFAs level than that of anaerobic sludge reactors, indicating the possible application of rumen microorganism for VFAs generation from lignocellulosic biomass. VFA production in the rumen fluid reactors was probably due to the presence of specific hydrolytic and acidogenic bacteria (e.g. Fibrobacter and Prevotella). VFA production corroborated from the observation of pH drop in the rumen fluid reactors indicated hydrolytic and acidogenic inhibition, suggesting the continuous extraction of VFAs from the reactor. Anaerobic sludge reactors on the other hand, produced more biogas than that of rumen fluid reactors. This observation was consistent with the abundance of methanogens in anaerobic sludge inoculum (3.98% of total microbes) compared to rumen fluid (0.11%). VFA production from lignocellulosic biomass is the building block chemical for bioplastic, biohydrogen and biofuel. The results from this study provide important foundation for the development of engineered systems to generate VFAs from lignocellulosic biomass.
•Rumen fluid produced 4 times more VFAs from biomass than anaerobic sludge microbes.•Lignocellulolytic bacteria (Fibrobacter, Prevotella) were abundant in rumen fluid.•Methanogenic abundance was high in anaerobic sludge inoculum.•Continuous extraction of VFAs from rumen fluid reactor is required for efficiency.
In this paper, we investigate the secrecy performance of a massive MIMO NOMA network. Specifically, we demonstrate a detailed training process in the network and derive downlink ergodic secrecy rates ...of legitimate users. In order to gain system’s insights, discussions on secrecy performance of the network in two special cases, i.e., large number of antennas and high transmit power at the BS, are provided. Furthermore, from the analysis, an optimization to maximize the users’ minimum secrecy rate in each NOMA cluster is proposed to aid the weak users’ secrecy performance. The correctness of our analysis and the efficiency of the proposed are confirmed through computer simulations.
In this work, we consider a joint optimisation of real-time deployment and resource allocation scheme for UAV-aided relay systems in emergency scenarios such as disaster relief and public safety ...missions. In particular, to recover the network within a disaster area, we propose a fast K-means-based user clustering model and jointly optimal power and time transferring allocation which can be applied in the real system by using UAVs as flying base stations for real-time recovering and maintaining network connectivity during and after disasters. Under the stringent QoS constraints, we then provide centralised and distributed models to maximise the energy efficiency of the considered network. Numerical results are provided to illustrate the effectiveness of the proposed computational approaches in terms of network energy efficiency and execution time for solving the resource allocation problem in real-time scenarios. We demonstrate that our proposed algorithm outperforms other benchmark schemes.
Device-to-device (D2D) communications is the integral part of public safety (PS) communications. However, the most important requirement is the users’ rapid discovery to timely communicate the ...emergency information. The existing half-duplex (HD) results in large time delays because it cannot transceive during same time slot. In-band full duplex (IB-FD) communications is an enabler to quickly discover the user because of simultaneous transmission and reception during same time-frequency block. In this paper, we proposed the frame structure for IB-FD system with prioritized PS users in resource allocation. Moreover, to improve spectral efficiency, time-efficient device discovery resource allocation (TE-DDRA) scheme has been proposed as well, where a user can switch the transmission mode from HD to IB-FD when the demand exceeds the available resources in HD mode. The proposal is validated by system-level simulations in terms of discovery time with conventional random access mode. The simulation results shows that with PS priority mode around 37
%
discovery time as compared with random access mode.
Nha Trang Coast is located in the South Central Vietnam and the coastal erosion has occurred rapidly in recent years. Hence it is crucial to accurately monitor the shoreline changes for better ...coastal management and reduction of risks for communities. In this paper, we explored a statistical forecasting model, Seasonal Auto-regressive Integrated Moving Average (SARIMA), and two Machine Learning (ML) models, Neural Network Auto-Regression (NNAR) and Long Short-Term Memory (LSTM), to predict the shoreline variations from surveillance camera images. Compared to the Empirical Orthogonal Function (EOF), the most common method used for predicting shoreline changes from cameras, we demonstrate that the SARIMA, NNAR and LSTM models outperform the EOF model significantly in terms of prediction accuracy. The forecasting performance of the SARIMA model, NNAR model and LSTM model is comparable in both long and short-term predictions. The results suggest that these models are highly effective in detecting shoreline changes from video cameras under extreme weather conditions.
Anaerobic co-digestion (AcoD) can utilise spare digestion capacity at existing wastewater treatment plants (WWTP) to generate surplus biogas beyond the plant's internal energy requirement. Data from ...industry reports and the peer-reviewed literature show that through AcoD, numerous examples of WWTPs have become net energy producers, necessitating other high-value applications for surplus biogas. A globally emerging trend is to upgrade biogas to biomethane, which can then be used as town gas or transport fuel. Water, organic solvent and chemical scrubbing, pressure swing adsorption, membrane separation, and cryogenic technology are commercially available CO2 removal technologies for biogas upgrade. Although water scrubbing is currently the most widely applied technology due to low capital and operation cost, significant market growth in membrane separation has been seen over the 2015–2019 period. Further progress in materials engineering and sciences is expected and will further enhance the membrane separation competitiveness for biogas upgrading. Several emerging biotechnologies to i) improve biogas quality from AcoD; ii) accelerate the absorption rate, and iii) captures CO2 in microalgal culture have also been examined and discussed in this review. Through a combination of AcoD and biogas upgrade, more WWTPs are expected to become net energy producers.
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•Anaerobic co-digestion has allowed many WWTPs to become net energy producers•Biogas upgrade is essential for utilising excess gas as domestic & transport fuel•Commercial scale biogas upgrading technologies are available•Membrane separation has emerged the most preferred technology•New bioprocesses have also emerged as potential alternative for biogas upgrade
We consider device-to-device (D2D) wireless information and power transfer systems using an unmanned aerial vehicle (UAV) as a relay-assisted node. As the energy capacity and flight time of UAVs is ...limited, a significant issue in deploying UAV is to manage energy consumption in real-time application, which is proportional to the UAV transmit power. To tackle this important issue, we develop a real-time resource allocation algorithm for maximizing the energy efficiency by jointly optimizing the energy-harvesting time and power control for the considered (D2D) communication embedded with UAV. We demonstrate the effectiveness of the proposed algorithms as running time for solving them can be conducted in milliseconds.
In this study, we consider the combination of clustering and resource allocation based on game theory in ultra-dense networks that consist of multiple macrocells using massive multiple-input ...multiple-output and a vast number of randomly distributed drones serving as small-cell base stations. In particular, to mitigate the intercell interference, we propose a coalition game for clustering small cells, with the utility function being the ratio of signal to interference. Then, the optimization problem of resource allocation is divided into two subproblems: subchannel allocation and power allocation. We use the Hungarian method, which is efficient for solving binary optimization problems, to assign the subchannels to users in each cluster of small cells. Additionally, a centralized algorithm with low computational complexity and a distributed algorithm based on the Stackelberg game are provided to maximize the network energy efficiency (EE). The numerical results demonstrate that the game-based method outperforms the centralized method in terms of execution time in small cells and is better than traditional clustering in terms of EE.
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