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Compound floods due to intense rainfall and storm surges in coastal areas have shown an increasing trend in some parts of the world, and many studies suggested a strong link with climate change. Yet, such link has not been fully explored and quantitively assessed. In this paper, we demonstrate the development and application of a nonstationary framework to determining different compound scenarios, where individual drivers and their interactions have altered under climate change. The framework has been applied to one of the most flood-prone areas: the Ho Chi Minh City of Vietnam, to help analyze the present and future compound flood risks in both the dry and wet seasons driven by the joint effect from heavy inland rainfall and high skew surge. Over the period of 1980–2017, the two drivers are found to be significantly correlated in March and April, corresponding to the transition from dry-to-wet seasons. We also find that the commonly-used traditional multivariate statistical models underestimate the flood magnitudes for both the current (represented by 2020) and future (represented by 2050) scenarios, when compared with the results produced by the nonstationary methods. In addition, the results reveal that the dry season is expected to receive more floods triggered by the increased intensity and frequency of rainfall extremes, with the magnitude reaching a similar level to that of the wet season. This is in line with the climate projections under RCP4.5 and 8.5 scenarios although the duration of dry spells is expected to increase and the total annual rainfall to decrease in Vietnam. The simulated flood inundations indicate remarkable increases in flood magnitude and extension, especially at the locations identified as low risk by the stationary models.

Hand-raising gesture is one of the most popular signs of communication, whose frequency is related to the classroom’s atmosphere, the attractiveness of the subject, and the level of interactions between students and teachers. However, automatic hand-raising gesture detection and recognition remains still a challenging problem mainly due to low hand resolution, hand occlusion, various backgrounds, and viewpoint changes. While majority of the existing methods focus on static hand-raising posture detection, in this paper, we propose a framework for dynamic hand gesture recognition from classroom videos consisting of two main stages: hand posture detection and dynamic hand gesture recognition. In hand posture detection stage, we extend the previous work by adding relative position-aware in non-local network. After detecting the hand-raising posture on static pixels, which in turn accelerates the performance images, at the dynamic hand gesture recognition stage, we incorporate object detection and tracking to associate the hand-raising detection results at consecutive frames to supplement the missing detection due to the occlusion issue and obtain hand-raising gesture recognition at the event level. The experimental results show that the proposed method outperforms three benchmark models for static hand posture detection that are Faster-RCNN, Libra-RCNN, and Libra-RCNN+RDA on our dataset with the gains obtained for mAP being 7.68%, 5.76%, and 0.35% higher, respectively. In terms of event-level recognition results, the proposed method achieves the value of frame-wise accuracy, temporal_IoU, F1-score@0.3, and Levenshtein-score are 90.0%, 84.4%, 83.2%, and 84.3%, respectively. The code and dataset used in the paper will be made publicity available for research community.

Electronic word of mouth (e-WOM) studies have been popular as a result of the rise of social networks and e-commerce. Nonetheless, there has been very little research on CSR communication associated with e-WOM. The purpose of this study is to see how e-WOM, as a means of sharing information about CSR activities, affects Vietnamese B2C e-commerce customers’ trust. With the help of 349 online consumers in Hanoi, data was gathered through online and direct survey methods. As a result of the findings, we can conclude that the relationship between e-WOM and customer’s trust is moderated by CSR messages. The authors provide a variety of solutions based on the research findings to assist B2C organizations in improving their communicating information about CSR activities to achieve the optimum marketing effectiveness

Urban flooding is a major challenge for many megacities in low-elevation coastal zones (LECZs), especially in Southeast Asia. In these regions, the effects of environmental stressors overlap with rapid urbanization, which significantly aggravates the hazard potential. Ho Chi Minh City (HCMC) in southern Vietnam is a prime example of this set of problems and therefore a suitable case study to apply the concept of low-regret disaster risk adaptation as defined by the Intergovernmental Panel on Climate Change (IPCC). In order to explore and evaluate potential options of hazard mitigation, a hydro-numerical model was employed to scrutinize the effectiveness of two adaptation strategies: (1) a classic flood protection scheme including a large-scale ring dike as currently constructed in HCMC and (2) the widespread installation of small-scale rainwater detention as envisioned in the framework of the Chinese Sponge City Program (SCP). A third adaptation scenario (3) assesses the combination of both approaches (1) and (2). From a hydrological point of view, the reduction in various flood intensity proxies that were computed within this study suggests that large-scale flood protection is comparable but slightly more effective than small-scale rainwater storage: for instance, the two adaptation options could reduce the normalized flood severity index (INFS), which is a measure combining flood depth and duration, by 17.9 % and 17.7 %, respectively. The number of flood-prone manufacturing firms that would be protected after adaptation, in turn, is nearly 2 times higher for the ring dike than for the Sponge City approach. However, the numerical results also reveal that both response options can be implemented in parallel, not only without reducing their individual effectiveness but also complementarily with considerable added value. Additionally, from a governance perspective, decentralized rainwater storage conforms ideally to the low-regret paradigm: while the existing large-scale ring dike depends on a binary commitment (to build or not to build), decentralized small- and micro-scale solutions can be implemented gradually (for example through targeted subsidies) and add technical redundancy to the overall system. In the end, both strategies are highly complementary in their spatial and temporal reduction in flood intensity. Local decision-makers may hence specifically seek combined strategies, adding to singular approaches, and design multi-faceted adaptation pathways in order to successfully prepare for a deeply uncertain future.

Fusion techniques with the aim to leverage the discriminative power of different appearance features for person representation have been widely applied in person re-identification. They are performed by concatenating all feature vectors (known as early fusion) or by combining matching scores of different classifiers (known as late fusion). Previous studies have proved that late fusion techniques achieve better results than early fusion ones. However, majority of the studies focus on determining the suitable weighting schemes that can reflect the role of each feature. The determined weights are then integrated in conventional similarity functions, such as Cosine [L. Zheng, S. Wang, L. Tian, F. He, Z. Liu and Q. Tian, Queryadaptive late fusion for image search and person reidentification, in Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2015, pp. 1741–1750]. The contribution of this paper is two-fold. First, a robust person re-identification method by combining the metric learning with late fusion techniques is proposed. The metric learning method Cross-view Quadratic Discriminant Analysis (XQDA) is employed to learn a discriminant low dimensional subspace to minimize the intra-person distance while maximize the inter-person distance. Moreover, product rule-based and sum rule-based late fusion techniques are applied on these distances. Second, concerning feature engineering, the ResNet extraction process has been modified in order to extract local features of different stripes in person images. To show the effectiveness of the proposed method, both single-shot and multi-shot scenarios are considered. Three state-of-the-art features that are Gaussians of Gaussians (GOG), Local Maximal Occurrence (LOMO) and deep-learned features extracted through a Residual network (ResNet) are extracted from person images. The experimental results on three benchmark datasets that are iLIDS-VID, PRID-2011 and VIPeR show that the proposed method [Formula: see text]% [Formula: see text]% of improvement over the best results obtained with the single feature. The proposed method that achieves the accuracy of 85.73%, 93.82% and 50.85% at rank-1 for iLIDS-VID, PRID-2011 and VIPeR, respectively, outperforms different SOTA methods including deep learning ones. Source code is publicly available to facilitate the development of person re-ID system.

Hydro-numerical models offer an increasingly important tool to determine the adequacy and evaluate the effectiveness of potential flood protection measures. However, a significant obstacle in setting up hydro-numerical and associated flood damage models is the tedious and oftentimes prohibitively costly process of acquiring reliable input data, which particularly applies to coastal megacities in developing countries and emerging economies. To address this problem, this paper takes the example of Ho Chi Minh City, Vietnam, and proposes a new and comprehensive methodology for acquiring, processing, and applying the necessary open-access data (topography, bathymetry, tidal, river flow, and precipitation time series) to set up an urban surface run-off model. As a key novelty of the paper, a normalized flood severity index (NFSI) that combines flood depth and duration is proposed. The index serves as an indicator that helps uncover urban inundation hotspots with severe damage potential, drawing attention to specific districts or boroughs with special adaptation needs or emergency response measures. The approach is validated by comparison with more than 300 locally reported flood samples, which correspond to NFSI-processed inundation hotspots in over 73 % of all cases. These findings corroborate the robustness of the proposed index, which may significantly enhance the interpretation and trustworthiness of hydro-numerical assessments in the future. The proposed approach and developed indicators are generic and may be replicated and adopted in other coastal megacities.

This article presents the design and characterization of a direct current (dc) sensor utilizing the Hall effect in AlGaN/GaN 2-D electron gas (2DEG) four-terminal devices and a flux concentrator. The sensor was fabricated from an AlGaN/GaN/Si wafer grown by metal-organic chemical vapor deposition. The sensor exhibited excellent linearity and repeatability with a high Hall voltage under the primary current ranging from −5 to 5 A. The sensitivity of the sensor was measured to be 0.26 (V/A)/A at 20 °C and independent of ambient temperature up to 200 °C. The obtained result is greater than that of other reported Hall effect-based current sensors. The high sensitivity and thermal stability at varying temperatures are attributed to the high electron mobility, wide bandgap, and stability of carrier density in 2DEG. Combining these factors with the excellent mechanical strength, electrical conductivity, and chemical inertness of GaN, the proposed sensor is promising for current monitoring in a wide range of operation temperatures.

Human action recognition (HAR) under different camera viewpoints is the most critical requirement for practical deployment. In this paper, we propose a novel method that leverages successful deep learning-based features for action representation and multi-view analysis to accomplish robust HAR under viewpoint changes. Specifically, we investigate various deep learning techniques, from 2D CNNs to 3D CNNs to capture spatial and temporal characteristics of actions at each separated camera view. A common feature space is then constructed to keep view-invariant features among extracted streams. This is carried out by learning a set of linear transformations that project private features into the common space in which the classes are well distinguished from each other. To this end, we first adopt Multi-view Discriminant Analysis (MvDA). The original MvDA suffers from odd situations in which the most class-discrepant common space could not be found because its objective is overly concentrated on pushing classes from the global mean but unaware of the distance between specific pairs of adjoining classes. We then introduce a pairwise-covariance maximizing extension that takes pairwise distances between classes into account, namely pc-MvDA. The novel method also differs in the way that could be more favorably applied for large high-dimensional multi-view datasets. Extensive experimental results on four datasets (IXMAS, MuHAVi, MICAGes, NTU RGB+D) show that pc-MvDA achieves consistent performance gain, especially for harder classes. The code is publicly available for research purpose at https://github.com/inspiros/pcmvda.

Marine litter is a significant threat to the marine environment, human health, and the economy. In this study, beach litter surveys along Vietnamese coasts were conducted in a local context to quantify and characterize marine litter using the modified GESAMP marine litter monitoring guideline. A total of 21,754 items weighing 136,820.2 g was recorded across 14 surveys from September 2020 to January 2021. Plastic was the most abundant type of litter by both quantity (20,744 items) and weight (100,371.2 g). Fishing gear 1 (fishing plastic rope, net pieces, fishing lures and lines, hard plastic floats) and soft plastic fragments were the most frequently observed items (17.65% and 17.24%, respectively). This study not only demonstrates the abundance and composition of marine litter in Vietnam, it also provides valuable information for the implementation of appropriate preventive measures, such as the redesign of collection, reuse, and recycling programs, and informs policy and priorities, with a focus on action and investment in Vietnam. Moreover, insights from this study indicate that citizen science is a useful approach for collecting data on marine litter in Vietnam.

Deforestation due to agricultural land expansion occurred greatly during 1994 to 2005 with a high proportion of forests being converted into agriculture in the upstream Dong Nai river basin in Vietnam. Most of these conversions included expansions of coffee plantations in Dak Lak and Lam Dong provinces, which are in the world’s Robusta coffee production area. The aim of this study is to quantify the impact on the water cycle due to the conversion of forest to coffee plantations in a tropical humid climate region by the application of a hydrological model: soil and water assessment tool (SWAT). The model was calibrated with climate data from 1980–1994, validated with climate data from 1995–2010, and verified with statistical indicators such as Nash–Sutcliffe efficiency (NSE), percent bias (PBIAS), and ratio of the root mean square error (RSR). The simulations indicated that forest conversions into agriculture (expansion of coffee plantations) had significantly increased surface runoff (SUR) while actual evapotranspiration (ET), soil water content (SW), and groundwater discharge (GW) decreased. These changes are mainly related to the decrease in infiltration and leaf area index (LAI) post land cover changes. However, the soil was not thoroughly destroyed after deforestation due to the replacement of the lost forest with crops and vegetation. Therefore, changes in infiltration were marginal and not sufficient to bring large changes in the annual flow. Higher reductions in ET and SW were proposed, resulting in reduced streamflow in the dry season at the basin where the proportion of agricultural land was higher than the forest cover. Besides the plantation expansion, which resulted in streamflow reductions in the dry season, an existing problem was over-irrigation of coffee plantations that could likely deplete groundwater resources. Hence, balancing economic benefits by coffee production and mitigating groundwater depletion issues should be prioritized for land use management in the study area.

Based on a qualitative case study in An Giang province, Vietnam, we mapped the understanding of the ‘Living with Floods’ (LWF) concept and the implementation of three projects to explain the effectiveness of water governance in Vietnam. We have demonstrated how perceptions on the LWF concept differ per government level and the limits of water governance effectiveness. Diverging perceptions undermine the effectiveness of water governance. A framework and a list of indicators are proposed to measure the effectiveness of floodwater governance. Integrating local and social aspects in LWF policies and vertical coordination may help align short-term benefits with long-term adaptation.

Risk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing3. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk management governance and high investment in integrated management. The observed difficulty of managing unprecedented events is alarming, given that more extreme hydrological events are projected owing to climate change3.

Exploring whether society is sufficiently equipped and motivated to adopt planned interventions is vital for modern plan development trajectories. The Motivation and Ability (MOTA) framework offers a tool to assess the societal adoptability of plans by exploring stakeholders' motivations and abilities. It was originally developed to assess plan implementation feasibility for structural measures of flood management in the Mekong Delta. Further development is necessary before applying the tool in other contexts and for other types of planning interventions. Institutional measures like participatory water management (PWM) have long been recognized as essential elements for water management, but have so far also remained out of the reach of conventional planning assessment tools such as cost–benefit or cost-effectiveness analyses. This research, therefore, aims at extending the MOTA tool in the context of PWM reforms in Bangladesh. It does this by, first, further detailing the MOTA components and identifying indicators for quantification and, second, an expert validation and application of this framework for coastal communities in Bangladesh. Our results suggest that the MOTA framework is capable of informing policymakers and implementing agencies about how to enhance the stakeholders' motivation and ability to ensure an enduring implementation of PWM reforms. HIGHLIGHTS The Motivation and Ability (MOTA) framework appeared recently to capture the societal and institutional dimensions in assessing the implementation feasibility of structural measures. This research further extends the MOTA framework and tests whether this can be applicable in case of assessing the implementation feasibility of soft measures like participatory water management.

The Vietnamese Mekong Delta (VMD) is an example of a complex dynamic socio-hydrological system in which societies and hydrology interact and co-evolve. The dominant engineering approach in the VMD has enhanced the dynamics of society and hydrology. This study looks at the implications of socio-hydrological dynamics in the coastal VMD where saline water is controlled by various infrastructures. In the first phase, key informant interviews and focus group discussions were used to explore socio-hydrological dynamics in the study area. The results show divergence in livelihood strategies inside the freshwater-projected area, shaping a heterogeneous agricultural landscape of fresh- and brackish-water livelihoods manifested by four socio-hydrological groups. Next, the Motivation and Ability (MOTA) framework and household surveys were used to assess the adaptability in the agricultural development pathway advocated by the freshwater policy. The result revealed differentiations among these socio-hydrological groups. The findings suggest other practices may be required to help the area navigate towards future adaptations to socio-hydrological changes.

Socio-hydrological approaches are gaining momentum due to the importance of understanding the dynamics and co-evolution of water and human systems. Various socio-hydrological approaches have been developed to improve the adaptive capacity of local people to deal with water-related issues. In this study, a social-hydrological approach was developed to enhance the water supply resilience in Con Dao Island, Vietnam. We used a water-balance model, involving the Water Evaluation and Planning (WEAP) tool, to conduct a scenario-based evaluation of water demands. In doing so, we assessed the impacts of socio-economic development, such as population growth and climate change, on increasing water demand. The modelling results showed that the existing reservoirs—the main sources to recharge the groundwater (accounting for 56.92% in 2018 and 65.59% in 2030)—play a critical role in enhancing water supply resilience in the island, particularly during the dry season. In addition, future water shortages can be solved by investment in water supply infrastructures in combination with the use of alternative water sources, such as rainwater and desalinated seawater. The findings further indicate that while the local actors have a high awareness of the role of natural resources, they seem to neglect climate change. To meet the future water demands, we argue that upgrading and constructing new reservoirs, mobilizing resources for freshwater alternatives and investing in water supply facilities are among the most suitable roadmaps for the island. In addition, strengthening adaptive capacity, raising awareness and building professional capacity for both local people and officials are strongly recommended. The research concludes with a roadmap that envisages the integration of social capacity to address the complex interaction and co-evolution of the human–water system to foster water-supply resilience in the study area.

Coastal environments include several different habitat typologies, from shorelines to estuaries, and rocky and muddy environments. All these ecosystems are very vulnerable to anthropogenic pressures, climate fluctuations, stressing the need to monitor their quality status and suggest possible measures for the remediation and recovery of their natural equilibria. In the light of these considerations, this Special Issue (SI) collects a number of multi-faceted scientific contributions on the quality of aquatic ecosystems, with a particular focus on the transitional environments where marine and terrestrial habitats are in close relationship. Fil: Bergamasco, Alessandro. Consiglio Nazionale delle Ricerche; Italia Fil: Nguyen, Hong Quan. Vietnam National University; Vietnam Fil: Caruso, Gabriella. Consiglio Nazionale delle Ricerche; Italia Fil: Xing, Qianguo. Chinese Academy of Sciences; República de China Fil: Carol, Eleonora Silvina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Investigaciones Geológicas. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo. Centro de Investigaciones Geológicas; Argentina

For many decades in Vietnam, rainwater harvesting has been widely used as a nature-based solution in rural areas, aiming at good-quality drinking water with low cost and little energy. Recently, rainwater for drinking has attracted much attention from the Vietnam government. Furthermore, despite its efforts, the outcomes are not as expected due to local barriers. This paper reviewed rainwater for drinking demonstration projects in some specific areas of Vietnam, with identification of the technical, economic, and social barriers, further suggesting possible overcome strategies. A lesson learnt from this study would be the principle of promoting rainwater for drinking in developing countries, looking forward to sustainability.

Sustainable livelihood development is an ongoing challenge worldwide, and has regained importance due to threats of water shortages and climate change. To cope with changing climatic, demographic and market conditions in Vietnam’s Mekong Delta (VMD) an agricultural transformation process has been suggested in the recent Mekong Delta Plan. This agricultural transformation process requires the implementation of alternative livelihood models. The majority of current agricultural livelihood models in the VMD have been introduced by the government in a top-down manner. In this study, we applied a bottom-up approach to understand the motivations and abilities of local farmers to adopt alternative livelihood models. It is based on the MOTA methodological framework, which is further tested with the use of multivariate analyses. The study was conducted in Ben Tre coastal province. Results showed that farmers’ motivations and abilities to apply alternative models vary substantially among different groups, driven by their perceptions on triggers and opportunities. Acknowledging this diversity is essential to the development of agricultural transformation plans. Furthermore, based on the analysis, a projection of the precise support that communities need to supplement their knowledge, skills and financial capacities, as well as interventions to reduce the risks of new livelihood models, is given.

In the present study, in silico predictions and molecular docking were performed on five clerodane diterpenes (1–5) from Polyalthia longifolia seeds to evaluate their potential as xanthine oxidase (XO) inhibitors. The initial screening was conducted by target prediction using TargetNet web server application and only compounds 3 and 4 showed a potential interaction with XO. Compounds 3 and 4 were subsequently subjected to in silico analyses on XO protein structure (PDB: 1N5X) using Schrödinger Release 2020–3 followed by structural modeling & molecular simulation studies to confirm the initial prediction result and identify the binding mode of these compounds to the XO. Molecular docking results revealed that compounds 3 (-37.3 kcal/mol) and 4 (-32.0 kcal/mol) binds more stably to XO than the reference drug allopurinol (-27.0 kcal/mol). Interestingly, two residues Glu 802 and Thr 1010 were observed as the two main H-bond binding sites for both tested compounds and the allopurinol. The center scaffold of allopurinol was positioned by some π-π stacking with Phe 914 and Phe 1009, while that of compounds 3 and 4 were supported by many hydrophobic interactions mainly with Leu 648, Phe 649, Phe 1013, and Leu 1014. Additionally, the docking simulation predicted that the inhibitory effect of compounds 3 and 4 was mediated by creating H-bond with particularly Glu 802, which is a key amino acid for XO enzyme inhibition. Altogether, in vitro studies showed that compounds 3 and 4 had better inhibitory capacity against XO enzyme with IC50 values significantly (p < 0.001) lower than that of allopurinol. In short, the present study identified cleroda-4(18),13-dien-15,16-olide as novel potential XO inhibitors, which can be potentially used for the treatment of gout.

This paper investigates the contamination of floodwaters in the urban center of Can Tho city, Vietnam. We sampled water from sewers, surface water bodies, and flood, before, during, and after specific flooding events. Total nucleic acid was extracted from the samples and subjected to a quantitative polymerase chain reaction (qPCR) to detect specific enteric pathogens. The difference between pathogen concentrations in floodwater and sewer water was compared by using the Mann Whitney U test. Correlations between the different pathogens were determined using the non-parametric Spearman test. E. coli and Rotavirus-A were the most prevalent pathogens in floodwater. We observed a weak association between E. coli and Rotavirus in flood-related waters (r E. coli and Rotavirus A concentrations (p > 0.05). Our results indicate that floodwater poses a significant urban public health risk due to the presence of enteric pathogens.

Marine debris is a significant threat to the marine environment, human health and the economy in Can Gio island, Vietnam. In this study, we conducted beach litter surveys to quantify and characterize marine litter from six beach transects in this region for the first time using the OSPAR beach litter monitoring guideline. A total of 29,456 items weighting 529,432 g was recorded from 12 surveys in two monitoring campaigns in December 2019 (dry season) and in June 2020 (rainy season). Plastic was the most abundant type of litter in terms of quantity (a total of 26,662 items) and weight (325,606 g), followed by paper and cardboard, cloth, wood, metal, glass and ceramics, rubber and other items. Meanwhile, ropes (less than 1 cm in diameter) and plastic bags accounted for the major parts of sampled plastic items, i.e., 20.18% and 14.46%, respectively. In general, a higher percentage of marine litter, particularly the fishing related items, was found in the rainy season than in the dry season, possibly due to increased fishing and aquaculture activities. In contrast, a reduction pattern of the single use plastics in the rainy season might be due to the decreased tourism activities during the Covid pandemic period. This study not only showed the magnitude of litter pollution, but also provided valuable information that could help decision making to better control and reduce marine litter in the region. In addition, insights from this study indicate that there is an urgent need to design collection, reuse and recycling programs in the area. The collected recyclables, specially plastics, will be a great source of materials for recyclers in a circular economy achieving sustainable development goals.

Groundwater serves as the major source for drinking water and the only fresh water source in the dry season in Ca Mau province, the Vietnamese Mekong Delta. The study is performed to assess groundwater quality in the area. Groundwater Quality Index (GWQI), magnesium hazard (MH), sodium percentage (Na%), sodium adsorption ratio (SAR), permeability index (PI) combined with geostatistical tools were conducted by using groundwater quality data from 400 samples collected from private wells. GWQI values suggest that 7%, 63%, 28%, 2%, 1% of total samples are classified into excellent, good, poor, very poor and unsuitable for drinking water. High Cl and TDS are the main cause of high GWQI values suggesting that saltwater intrusion deteriorates groundwater quality. For irrigation purposes, 4%, 17%, 36%, 43% of total samples classify into Good, Permissible, Doubtful, Unsuitable respectively by Na% indicator; 55.0%, 30.9%, 11.9%, 2.2% of total samples is Excellent, Good, Doubtful and Unsuitable according to SAR, 54% samples are unsuitable by MH index, and all samples are good by PI. This study provides useful information on groundwater quality for various purposes in Ca Mau province, that could help water management and water users to identify the necessary approach for groundwater protection and water-treatment methods before utilising the groundwater source for specific purposes in the study area.

This paper compares three shaft-sensorless control schemes for wound-field flux-switching machines based on a high frequency (HF) square-wave voltage injection technique. An HF model for the machine, with inclusion of the field winding, is first presented. Because the machine had armature and field windings, HF voltage is injected into and processed in the armature winding as with conventional permanent magnet synchronous machines (PMSMs) or injected into one winding and processed in the induced current signal in the other winding. Both the analytical and experimental results reveal that the scheme with $d$ -axis voltage injection and a $q$ -axis induced current process is generally similar to that used for PMSMs. Polarity identification is required to prevent phase errors in the estimated position. The schemes with separate windings for voltage injection and current processing demonstrate superior performance compared with the scheme without, and both schemes do not require polarity identification. Moreover, voltage injection at the field winding has an additional advantage for high-speed operations.

The use of electrolyte-based nanofluid is a new approach for enhancing the performance of Vanadium Redox Flow Batteries (VRFBs). This paper, for the first time in the literature, presents an experimental study to comprehensively investigate the rheological behaviour, electrical conductivity, and thermal conductivity of a newly prepared electrochemical graphene oxide (EGO)/ vanadium (IV) electrolyte-based nanofluid in different weight concentration and bulk temperatures. SEM, FT-IR and X-ray Diffraction (XRD) characterizations were performed and different functional groups, smooth 2D layered structures, and low crystallinity were detected in our tailored oxidation EGO which are amongst the enhancing features for VRFBs electrode materials. It was observed that the optimum weight concentration of nanoparticles in the electrolyte-based nanofluid is 0.05 wt% with strong colloidal stability, enhanced electrical and thermal conductivities, and an optimal viscosity. The maximum feasible enhancements in electrical and thermal conductivities that were achieved were 12%, and 4%, respectively, which can positively affect the performance of flow battery in terms of electrochemical activity on the electrode surface and thermal management of the flow battery system. In addition, the rheological evaluation showed that the behaviour of the electrolyte-based nanofluid tends to change from Newtonian to non-Newtonian for weight concentrations higher than 0.05%. The results obtained from rheological behaviour can provide useful insights in choosing an optimum pumping system of the flow batteries working with electrolyte-based nanofluid.

The delta of the Mekong River in Vietnam has been heavily impacted by anthropogenic stresses in recent years, such as upstream dam construction and sand mining within the main and distributary channels, leading to riverbank and coastal erosion. Intensive bathymetric surveys, conducted within the Tien River branch during the dry and wet season 2018, reveal a high magnitude of sand mining activities. For the year 2018, an analysis of bathymetric maps and the local refilling processes leads to an estimated sand extraction volume of 4.64 $$\pm $$± 0.31 Mm$${}^{3}$$3/yr in the study area, which covered around 20 km. Reported statistics of sand mining for all of the Mekong’s channels within the delta, which have a cumulative length of several hundred kilometres, are 17.77 Mm$${}^{3}$$3/yr for this period. Results from this study highlight that these statistics are likely too conservative. It is also shown that natural sediment supplies from upper reaches of the Mekong are insufficient to compensate for the loss of extracted bed aggregates, illustrating the non-sustainable nature of the local sand mining practices.

This research work is a part of a research project funded by Defense Science Organisation (DSO) to develop a vertical takeoff and landing (VTOL) micro air vehicle (MAV). Previous work has focused on conceptual design and numerical investigation of the aerodynamic properties of the MAV. This work focuses on the dynamic analysis and control system design of the current MAV design during non-hover flight. Both numerical simulation and analytical approaches were employed to obtain the results. For the simulation approach, a full 6 degree-of-freedom model was built using MATLAB Simulink and Aerospace Blockset. The design of the flight control system was based on the linearised mathematical model of the MAV. Based on this linear model, appropriate control strategies were developed for various flight conditions such as cruise, climb, and turning flight. Finally, the controllers developed based on the linear approximation were applied to the non-linear system to examine their validity. It was proven that the designed controllers worked well for the non-linear aircraft model, even in the presence of disturbances. Finally, preliminary implementation of the embedded control system, which consists of an Inertial Measurement Unit (IMU) and a servo control board, to the MAV prototype was developed. MASTER OF ENGINEERING (MAE)

This paper describes an event-based water quality model for sparsely gauged catchments. The model was cultivated in a robust way to cope with practical issues, such as limited available data and error propagation. A simplified model structure and fewer input parameters are the most appealing features of this model. All model components are coupled and controlled within an Excel Spreadsheet Macro as an operational tool. Herein, the geomorphological instantaneous unit hydrograph (GIUH), the simplified process erosion and sedimentation component, the loading function, and the river routing from different existing modeling systems are adopted and linked together. Furthermore, an add-on Monte Carlo simulation tool is provided to deliver an uncertainty analysis for calibration of the output obtained from the model results. The model was successfully applied to simulate nutrient dynamics for small catchment scales during flood events in Vietnam. The success of the model application shows the ability of our model, which can adapt the model complexity to the data availability, i.e., the dominant processes in the system should be captured, whereas the minor processes may be neglected or treated in a less complex manner.

We report the effect of stress or strain on the electronic characteristics of a normally off AlGaN/GaN high electron mobility transistor (HEMT) and demonstrate its role as a highly sensitive pressure sensor. We observe that the HEMT drain current exhibits a linear change of 2.5%/bar upon the application of pressure, which is translated to a strain sensitivity of 1250 ppm−1. This is the highest strain sensitivity ever reported on HEMTs and many other conventional strain sensing configurations. The relative change of drain current is largest when the gate bias is near-threshold and drain bias is slightly larger than the saturation bias. The electron sheet density and mobility changes in the AlGaN/GaN heterointerface under the applied pressure or mechanical strain are explained qualitatively. The spontaneous and piezoelectric-polarization-induced surface and interface charges in the AlGaN/GaN heterojunction can be used to develop very sensitive and robust pressure sensors. The results demonstrate a considerable potential of normally off AlGaN/GaN HEMTs for highly sensitive and reliable mechanical sensing applications with low energy consumption.

Strain-relieved GaSb quantum dots on GaAs can be achieved by either periodic interfacial misfit (IMF) or the conventional Stranski–Krastanov (SK) growth modes by changing the growth parameters. In this study, the Sb interfacial treatment was employed to improve the GaSb crystal quality including low defect density, smooth surface morphology, and high hole mobility. This technique yields two-dimensional (2D) islands with a height as low as 1.7 nm and width up to 190 nm in the IMF growth mode. In contrast to the interfacial treatments conventionally employed in the initial strain relaxation of GaSb/GaAs hererostructure, the Sb treatment promotes the formation of strong Ga-Sb bonds on the surface of the grown island, which effectively reduces the interfacial free energy and thus promotes the formation of 2D islands. With the Sb interfacial treatment, a high-relaxation 100-nm GaSb epilayer was grown on the GaAs substrate, the epilayers was strain relaxed and exhibited enhanced electrical properties with a high hole mobility of ~667 cm2 V−1 s−1 and with superior optical properties as evidenced by the photoluminescence B-line peak. The results of this study demonstrate an effective interfacial-treatment growth technique to relax the initial strain for the highly mismatched GaSb layers grown on a GaAs substrate.

Rapid global changes (population growth, urbanization and frequent extreme weather conditions) have cumulatively affected local water bodies and resulted in unfavorable hydrological, ecological, and environmental changes in the major river systems. Particularly, communities in isolated riverine islands are heavily affected due to their poor adaptive capacities, which is well documented in the contemporary literature. The focal point for the vulnerability of these people lies in the water resources (drinking water availability, agricultural water quality, salt-water intrusion, flooding etc.) and the future interaction between human and water systems. This paper advocates the importance of socio-hydrological research in the context of enhancing social adaptive capacity as well as for developing a resilient water environment in three very large riverine islands in Asia: Fraserganj (India), Dakshin Bedkashi (Bangladesh) (both from the Ganges-Brahaputra-Meghna Delta) and Con Dao Island (Mekong River, Vietnam). It also explores how the nexus of human–water relations could be applied to improve adaptive measures to manage local water needs while mitigating undesirable changes to the hydrological cycle. Socio-hydrological models as an integrated tool can be used to quantify the feedbacks between water resources and society at multiple scales, with the aim of expediting stakeholder participation for sustainable water resource management. The proposed idea in this study will be helpful to sketch projections of alternatives that explicitly account for plausible and co-evolving trajectories of the socio-hydrological system, which will yield both insights into cause–effect relationships and help stakeholders to identify safe functioning space.

Flood is a devastating natural hazard that may cause damage to the environment infrastructure, and society. Hence, identifying the susceptible areas to flood is an important task for every country to prevent such dangerous consequences. The present study developed a framework for identifying flood-prone areas of the Topľa river basin, Slovakia using geographic information system (GIS), multi-criteria decision making approach (MCDMA), bivariate statistics (Frequency Ratio (FR), Statistical Index (SI)) and machine learning (Naive Bayes Tree (NBT), Logistic Regression (LR)). To reach such a goal, different physical-geographical factors (criteria) were integrated and mapped. To access the relationship and interdependences among the criteria, decision-making trial and evaluation laboratory (DEMATEL) and analytic network process (ANP) were used. Based on the experts’ decisions, the DEMATEL-ANP model was used to compute the relative weights of different criteria and a GIS-based linear combination was performed to derive the susceptibility index. Separately, the flood susceptibility index computation through NBT-FR and NBT-SI hybrid models assumed, in the first stage, the estimation of the weight of each class/category of conditioning factor through SI and FR and the integration of these values in NBT algorithm. The application of LR stand-alone required the calculation of the weights of conditioning factors by analysing their spatial relation with the location of the historical flood events. The study revealed that very high and high flood susceptibility classes covered between 20% and 47% of the study area, respectively. The validation of results, using the past flood points, highlighted that the hybrid DEMATEL-ANP model was the most performant with an Area Under ROC curve higher than 0.97, an accuracy of 0.922 and a value of HSS of 0.844. The presented methodological approach used for the identification of flood susceptible areas can serve as an alternative for the updating of preliminary flood risk assessment based on the EU Floods Directive.

The upstream Dong Nai River Basin is located in the country&rsquo, s key economic development region and its water resources are a key component of sustainable regional development. The objective of this study was to assess the impact of land use and land cover changes (LULCC) on the flow regime in this tropical forest basin using a flow&ndash, duration curve analysis that has been widely used in Japan. This study combined two different temporal and spatial scales of satellite data, Landsat and Global Inventory Modeling, and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) to analyze LUCC. Results from the land cover classification of five Landsat images between 1973 and 2014 indicated that the forest area decreased significantly in the period of 1994 to 2005 due to population growth, leading to land conversion for agriculture. Furthermore, secular changes in the annual GIMMS-NDVI data revealed that land cover changes occurred from 1996 and a large amount of forest was lost in 1999, however, due to the rapid regrowth of secondary forest of tropical forests and the development of the crop, the vegetation recovered shortly afterwards in 2000 before decreasing again after 2004. Following large-scale deforestation, the total discharge, maximum flow, and the plentiful, ordinary, low, and small-scale runoff increased sharply and decreased thereafter because of vegetation regrowth.

The effects of plasma enhanced atomic layer deposition (PEALD)-AlN interfacial passivation layer (IPL) on the Al 2 O 3 /In 0.53 Ga 0.47 As interfaces qualities are studied with different plasma powers. The improvement in electrical properties, including capacitance-voltage (C-V) hysteresis, frequency dispersion, and interface state densities (Dit) are demonstrated on the Al 2 O 3 /n, p-In 0.53 Ga 0.47 As MOS capacitors. The excellent C-V behaviors are observed on both type of In 0.53 Ga 0.47 As-based MOS devices by performing a thin AlN-IPL at the plasma power of 150 W. To explore the interaction between PEALD-AlN layer and In 0.53 Ga 0.47 As surface, X-ray photoelectron spectroscopy and high-resolution transmission electron microscopy analyses have also been characterized.

The electrical properties of Al2O3/n-InGaAs metal–oxide–semiconductor capacitors (MOSCAPs) with In content of 0.53, 0.7, and 1 (InAs) have been investigated. Results show small capacitance–voltage (C–V) frequency dispersion in accumulation (1.70% to 1.85% per decade) for these MOSCAPs, mostly being assigned to border traps in Al2O3. With higher In content, shorter minority-carrier response time and smaller C–V hysteresis are observed. The reduction of C–V hysteresis might be related to the reduction of Ga-bearing oxides in Al2O3/InGaAs interfaces as indicated by x-ray photoelectron spectroscopy.

The characteristics of Al2O3/InSb MOSCAPs processed with different postdeposition annealing (PDA) temperatures are investigated. X-ray photoelectron spectroscopy analysis shows a significant reduction of InSb-oxides after HCl plus trimethyl aluminum treatment and oxide deposition. Multifrequency capacitance-voltage (C-V) characteristics exhibit low-frequency and asymmetrical C-V behaviors, in which capacitance in the InSb conduction band side is lower than in the valence band side. The electrical properties of the MOSCAPs are sensitive to PDA temperature and degraded significantly at PDA temperature >300 °C. This degradation is closely related to the diffusion of In, Sb into Al2O3 as indicated by transmission electron microscopy analyses.

We demonstrate the good-performance In0.5Ga0.5As-based metal-oxide-semiconductor capacitor (MOSCAP) on GaAs substrate using metal-organic chemical vapor deposition technique. In0.5Ga0.5As film grown on GaAs substrate is proved to be high quality with threading dislocation density as low as 106 cm-2. The performance of the MOSCAPs is comparable to that of In0.53Ga0.47As/InP-based devices grown by molecular beam epitaxy technique. The devices show a nice capacitance-voltage response, with small frequency dispersion. The parallel conductance contours show the free movement of Fermi level with the gate bias. Acceptable interface trap density Dit values of 5 × 1011-2 × 1012 eV-1 · cm-2 in the energy range of 0.64-0.52 eV above the InGaAs valence band maximum in In0.5Ga0.5As/GaAs MOSCAPs obtained by conductance methods were shown.