Search Results (61)

This study investigates the fatigue performance of 3D-printed metal shafts fabricated via Wire Arc Additive Manufacturing (WAAM) with stacked steel ring substrates under rotating bending (ISO 1143:2021). A Taguchi L25 orthogonal array was used to analyze five process parameters: ring diameter, current intensity, torch speed, ring thickness, and contact tip to workpiece distance (CTWD). Analysis of Variance (ANOVA) identified ring diameter as the dominant factor, significantly enhancing fatigue life at 14.0 mm by reducing stress concentrations. Current intensity (125 A) and torch speed (550 mm/min) further improve weld quality and microstructure, while ring thickness (1.0 mm) and CTWD (1.5 mm) have minor effects. A linear regression model (R² = 0.9603) accurately predicts fatigue life, with optimal settings yielding 299,730 cycles. The stacked-ring configuration enables intricate structures like cooling channels, ideal for aerospace and automotive applications. The 3.5% unexplained variance suggests parameter interactions, warranting further investigation into shielding gas effects and multiaxial loading to broaden material and loading applicability. Full article

This study investigates the sustainable livelihoods of households in the coastal forest regions of Quang Tri Province, Vietnam, focusing on identifying the key factors that shape household resilience in the face of socio-economic and environmental challenges. Although the sustainable livelihoods approach is widely established in research, this study differentiates itself by applying a multivariate analysis to explore the relative impacts of various livelihood capitals—human, physical, financial, social, and environmental—specifically within the context of coastal forest ecosystems, a relatively under-researched area in Vietnam. The research identifies both factors affecting livelihood outcomes, emphasizing the role of community resources, seasonal fluctuations, and adaptation strategies. Additionally, the study highlights how environmental changes and natural resource constraints are more detrimental to livelihoods in these regions compared to other rural settings. Through these insights, this paper contributes to the growing body of literature by offering a nuanced understanding of how coastal forest communities can navigate the pressures of climate change, market volatility, and limited resources. The findings underscore the importance of enhancing adaptive capacity and crafting targeted policy interventions to support vulnerable households in the region. This study also highlights the limitations of existing research, emphasizing the need for future studies to integrate the complex interplay of environmental, social, and economic factors in coastal ecosystems. Full article

Quang Tri, located in the central region of Vietnam, regularly experiences prolonged and extreme rainfall that causes severe and widespread flooding. This has resulted in significant losses in terms of both lives and property. Therefore, an integrated flood risk map is an essential tool for supporting disaster response and prevention efforts, utilizing a multi-criteria analysis approach to assess flood risks. This study proposes a method for constructing flood risk maps for the downstream areas of river basins in Quang Tri Province, based on the combination of the unweighted method by Iyengar and Sudarshan with multi-criteria and spatial analysis. The results indicate that during the historic flood in October 2020, the level of flood risk varied significantly among communes in 10 districts in the downstream areas. Specifically, the Hai Phong, Dien Sanh, Hai Hung, and Hai Quy communes in Hai Lang district had the largest proportion of the highest risk area (level 5), accounting for 3.76% of the total area. The area classified as medium risk (level 3) represented approximately 16.54%. The resulting flood risk map enables Quang Tri authorities to focus disaster prevention and response efforts more effectively on the most vulnerable areas identified, particularly the high-risk communes in Hai Lang district. Full article

Coral reefs are well known for their diversity and value, providing habitats for a third of marine species within just 0.2% of the ocean. However, these natural habitats face significant threats and degradation, leading to unresolved issues related to coral loss inventory, coral protection, and the implementation of long-term conservation policies. In this study, we examined two decades of changes in coral spatial distribution within the Nha Trang Bay Marine Protected Area (MPA) using remote sensing and machine learning (ML) approaches. We identified various factors contributing to coral reef loss and analyzed the effectiveness of management policies over the past 20 years. By employing the Light Gradient Boosting Machine (LGBM) and Deep Forest (DF) models on Landsat (2002, κ = 0.83, F₁ = 0.85) and Planet (2016, κ = 0.89, F₁ = 0.82; 2024, κ = 0.92, F₁ = 0.86) images, we achieved high confidence in our inventory of coral changes. Our findings revealed that 191.38 hectares of coral disappeared from Nha Trang Bay MPA between 2002 and 2024. The 8-year period from 2016 to 2024 saw a loss of 66.32 hectares, which is in linear approximation to the 125.06 hectares lost during the 14-year period from 2002 to 2016. It is concluded that the key factors contributing to coral loss include land-use dynamics, global warming, and the impact of starfish. To address these challenges, we propose next a modern community-based management paradigm to enhance the conservation of existing coral reefs and protect potential habitats within Nha Trang Bay MPA. Full article

Turing’s instability has been widely introduced to explain the formation of several biological and ecological patterns, such as the skin patterning of fish or animals, wings of butterflies, pigmentation, and labyrinth patterns of the cerebral cortex of mammals. Such a mechanism may occur in the ecosystem due to the differential diffusion dispersal that happen if one of the constituent species results in the activator or the prey, showing a tendency to undergo autocatalytic growth. The diffusion of the constituent species activator is a random mobility function called passive diffusion. If the other species in the system (the predator/inhibitor) disperses sufficiently faster than the activator, then the spatially uniform distribution of species becomes unstable, and the system will settle into a stationary state. This paper introduced Turing’s mechanism in our reaction–taxis–diffusion model to simulate the harmful algal bloom (HAB) pattern. A numerical approach, the Runge–Kutta method, was used to deal with this system of reaction–taxis–diffusion equations, and the findings were qualitatively compared to the aerial patterns obtained by a drone flying over Torment Lake in Nova Scotia (Canada) during the bloom season of September 2023. Full article

Electric vehicle (EV) battery technology is at the forefront of the shift towards sustainable transportation. However, maximising the environmental and economic benefits of electric vehicles depends on advances in battery life cycle management. This comprehensive review analyses trends, techniques, and challenges across EV battery development, capacity prediction, and recycling, drawing on a dataset of over 22,000 articles from four major databases. Using Dynamic Topic Modelling (DTM), this study identifies key innovations and evolving research themes in battery-related technologies, capacity degradation factors, and recycling methods. The literature is structured into two primary themes: (1) “Electric Vehicle Battery Technologies, Development & Trends” and (2) “Capacity Prediction and Influencing Factors”. DTM revealed pivotal findings: advancements in lithium-ion and solid-state batteries for higher energy density, improvements in recycling technologies to reduce environmental impact, and the efficacy of machine learning-based models for real-time capacity prediction. Gaps persist in scaling sustainable recycling methods, developing cost-effective manufacturing processes, and creating standards for life cycle impact assessment. Future directions emphasise multidisciplinary research on new battery chemistries, efficient end-of-life management, and policy frameworks that support circular economy practices. This review serves as a resource for stakeholders to address the critical technological and regulatory challenges that will shape the sustainable future of electric vehicles. Full article

Precision agriculture (PA) technologies combined with remote sensors, GPS, and GIS are transforming the agricultural industry while promoting sustainable farming practices with the ability to optimize resource utilization and minimize environmental impact. However, their implementation faces challenges such as high computational costs, complexity, low image resolution, and limited GPS accuracy. These issues hinder timely delivery of prescription maps and impede farmers’ ability to make effective, on-the-spot decisions regarding farm management, especially in stress-sensitive crops. Therefore, this study proposes field programmable gate array (FPGA)-based hardware solutions and real-time kinematic GPS (RTK-GPS) to develop a real-time crop-monitoring system that can address the limitations of current PA technologies. Our proposed system uses high-accuracy RTK and real-time FPGA-based image-processing (RFIP) devices for data collection, geotagging real-time field data via Python and a camera. The acquired images are processed to extract metadata then visualized as a heat map on Google Maps, indicating green area intensity based on romaine lettuce leafage. The RFIP system showed a strong correlation (R² = 0.9566) with a reference system and performed well in field tests, providing a Lin’s concordance correlation coefficient (CCC) of 0.8292. This study demonstrates the potential of the developed system to address current PA limitations by providing real-time, accurate data for immediate decision making. In the future, this proposed system will be integrated with autonomous farm equipment to further enhance sustainable farming practices, including real-time crop health monitoring, yield assessment, and crop disease detection. Full article

The grey-shanked douc langur (Pygathrix cinerea) is a recently described, critically endangered primate, endemic to Vietnam. In this study, we describe the Central Highland species’ complete mitochondrial genome (mitogenome—mtDNA). It is a circular molecule with a length of 16,541 base pairs (bp). The genome consists of 37 genes, consistent with those found in most other vertebrates, including 13 protein coding genes, 22 transfer RNAs, and two ribosomal RNAs. A comparison with the mitogenomes of more than 50 primates showed that the mitogenome of Vietnamese Central Highland Pygathrix cinerea has a conservative gene order. We identified 43 nucleotide differences when comparing this genome with a previously published mitogenome of Pygathrix cinerea. It is evident that there are distinct differences between the Pygathrix cinerea we are currently studying and other Pygathrix cinerea specimens. These differences are unlikely to be solely the result of sequencing errors, as the mitogenomes were generated using high-quality methods. The genetic divergence observed between the two Pygathrix cinerea mitogenomes implies the potential existence of at least two distinct lineages or forms of this primate species within its native range in Vietnam. Full article

The Tam Giang-Cau Hai lagoon (TGCH) in Thua Thien Hue province (Vietnam) is a marsh/lagoon system and ranks among the largest waterbodies in Southeast Asia. It plays a significant role in terms of both socio-economic and environmental resources. However, anthropogenic stress, as well as the discharge of untreated domestic and industrial sewage with agricultural runoff from its three major tributaries, dramatically damages the water quality of the lagoon. Especially after heavy rain and flash floods, the continuous degradation of its water quality, followed by harmful algal and cyanobacterial bloom patterns (HABs), is more perceptible. In this study, several physicochemical factors, cyanotoxins (anatoxins (ATXs), saxitoxins (STXs), microcystins (MCs)), phycotoxins (STXs, okadaic acid (OA), and dinophysistoxins (DTXs)) were analyzed in water and shellfish samples from 13 stations in June 2023 from 13 stations, using enzyme-linked immunosorbent assay (ELISA) kits for the ATXs and STXs, and the serine/threonine phosphatase type 2A (PP2A) inhibition assay kit for the MCs, OA, and DTXs. The results showed for the first time the co-occurrence of freshwater cyanotoxins and marine phycotoxins in water and shellfish samples in this lagoon. Traces of ATXs and STXs were detected in the shellfish and the orders of magnitude were below the seafood safety action levels. However, toxins inhibiting the PP2A enzyme, such as MCs and nodularin (NODs), as well as OA and DTXs, were detected at higher concentrations (maximum: 130.4 μg equiv. MC-LR/kg shellfish meat wet weight), approaching the actionable level proposed for this class of toxin in shellfish (160 μg of OA equivalent per kg of edible bivalve mollusk meat). It is very important to note that due to the possible false positives produced by the ELISA test in complex matrices such as a crude shellfish extract, this preliminary and pilot research will be repeated with a more sophisticated method, such as liquid chromatography coupled with mass spectroscopy (LC-MS), in the upcoming research plan. Full article

Acacia hybrid (Acacia mangium Willd. × A. auriculiformis A. Cunn. Ex Benth.) dominates plantation wood production in central Vietnam. Dependence on a single species may increase biological risks. The potential of eucalypt as an alternative was examined by comparing the growth and survival of acacia hybrid and eucalypt hybrid (Eucalyptus urophylla S.T. Blake × E. pellita F. Muell.) clones in Quang Tri province at three planting densities (1333, 1667 and 2222 trees ha⁻¹). The experiment was planted on an eroded shallow soil common in the region. At age 5 years, survival of acacia (74%) was higher than that of eucalypt (67%), a consequence of high mortality from wind damage for one eucalypt clone. Eucalypt was taller by about 2 m, but stem diameters of acacia and eucalypt were very similar. For both taxa, diameter decreased significantly as planting density increased. Across planting densities, mean standing volume was 107 and 108 m³ ha⁻¹ for acacia and eucalyptus, respectively. Linear regressions of stocking at 5 years on volume accounted for over half of the variance in acacia and eucalypt plot volumes, demonstrating the strong effect of stocking on yield. There were similarly strong effects of stocking on stem diameter. Acacia hybrid plantations of nearby small growers had stockings at age 5 years that averaged over 2500 stems ha⁻¹. Growers planted at higher densities and allowed their trees to multi-stem. Their standing volumes at age 5 years ranged from 83 to 102 m³ ha⁻¹. Understanding how to reduce tree mortality would assist growers to choose planting densities and stand management that optimise growth, log diameter classes and net returns. Full article

Using radar to estimate and forecast precipitation as input for hydrological models has become increasingly popular in recent years because of its superior spatial and temporal simulation compared with using rain gauge data. This study used radar-based quantitative precipitation estimation (QPE) to select the optimal parameter set for the MIKE URBAN hydrological model and radar-based quantitative precipitation forecasting (QPF) to simulate inundation in Nam Dinh city, Vietnam. The results show the following: (1) radar has the potential to improve the modeling and provide the data needed for real-time smart control if proper bias adjustment is obtained and the risk of underestimated flows after heavy rain is minimized, and (2) the MIKE URBAN model used to calculate two simulation scenarios with rain gauge data and QPE data showed effectiveness in combining the application of radar-based precipitation for the forecasting and warning of urban floods in Nam Dinh city. The results in Scenario 2 with rainfall forecast data from radar provide better simulation results. The average relative error in Scenario 2 is 9%, while the average relative error in Scenario 1 is 15%. Using the grid radar-based precipitation forecasting as input data for the MIKE URBAN model significantly reduces the error between the observed water depth and the simulated results compared with the case using an input rain gauge measured at Nam Dinh station (the difference in inundation level of Scenario 2 using radar-based precipitation is 0.005 m, and it is 0.03 m in Scenario 1). The results obtained using the QPE and QPF radar as input for the MIKE URBAN model will be the basis for establishing an operational forecasting system for the Northern Delta and Midland Regional Hydro-Meteorological Center, Viet Nam Meteorological and Hydrological Administration. Full article

The increase in extreme weather events causes secondary hazards that can influence people and the environment enormously. The Ca Mau Peninsula is known as one of the areas most severely affected by drought, and excessive groundwater exploitation is one of the reasons leading to a higher risk of land subsidence. This study uses the Delphi method and the KAMET rule table to analyze and select indicators that affect subsidence. The study uses the analytic hierarchy process (AHP) analytical hierarchy method to evaluate the weights of influencing factors, combined with geographic information system (GIS) technology to overlay the map layers of the main influencing factors and build a subsidence risk warning zoning map of the study area. The influencing factors selected to evaluate the impact on land subsidence in the study area during the drought period included geological structure, soil characteristics, groundwater flow exploitation, water flow in the dry season, current land use status, and evaporation in the dry season. The weights of these factors were evaluated based on the synthesis of relevant documents as well as consultation with experts. The results indicate that nearly two-thirds of the Ca Mau Peninsula area is currently at very low or low risk of subsidence. Meanwhile, 23% of the area is at medium risk, nearly 9% is at high risk, and 0.1% of the study area is at very high risk. Subsidence risk warning zoning maps can provide a visual and general overview of areas with high subsidence risk, supporting managers in making reference plans for socio-economic development in the Ca Mau Peninsula. Full article

Managing uncertainties and risks is always a difficult but fascinating task in fresh fruit supply chains, especially when dealing with the strategy for the production and conveyance of fresh fruit in Vietnam. Following the COVID-19 outbreak, the confluence of economic recession and persistent adverse weather conditions has exacerbated challenges faced by dragon fruit cultivators. This research investigates a two-stage stochastic programming (TSSP) approach which is developed and served as a valuable tool for analyzing uncertainties, optimizing operations, and managing risks in the fresh fruit industry, ultimately contributing to the sustainability and resilience of supply chains in the agricultural sector. A prototype is provided to illustrate the complex and dynamic nature of dragon fruit cultivation and consumption in Vietnam. Data on the selling prices of dragon fruit were collected from several sources between 2013 and 2022 in Binh Thuan Province, Vietnam. The results were obtained from the model by using three different approaches in order of their versatility and efficacy: (1) Scenario tree generation; (2) Sample average approximation; (3) Chance-constrained programming. Full article

This study examines the hydrodynamic regimes in Shediac Bay, located in New Brunswick, Canada, with a focus on the breach in the Grande-Digue sand spit. The breach, which was developed in the mid-1980s, has raised concerns about its potential impacts on water renewal time and water quality in the inner bay. The aims of this study, using mathematical modeling approaches, were to evaluate the flow regimes passing through the breach and influences on the distribution of dissolved matter, providing insights into whether the breach should be allowed to naturally evolve or be artificially infilled to prevent contaminant stagnancy in the bay. The study considered three simulation scenarios to comprehend the water renewal time and the role of the breach in the environmental management of Shediac Bay. Results indicated that completely closing the breach would significantly increase the water renewal time in the inner bay, although the spatial extent of this increase is limited. However, the study identified some limitations, including the need to better define the concentration limit for considering water as renewed and the lack of consideration of dynamic factors such as wind and wave effects. Full article

Rehydration of dairy powders is a complex and essential process. A relatively new quantitative mechanism for monitoring powders’ rehydration process uses the effective diffusion coefficient. This research focused on modifying a previously used labor-intensive method that will be able to automatically measure the real-time water diffusion coefficient in dairy powders based on confocal microscopy techniques. Furthermore, morphological characteristics and local hydration of individual particles were identified using an imaging analysis procedure written in Matlab©—R2023b and image analysis through machine learning algorithms written in Python™-3.11. The first model includes segmentation into binary images and labeling particles during water diffusion. The second model includes the expansion of data set selection, neural network training and particle markup. For both models, the effective diffusion follows Fick’s second law for spherical geometry. The effective diffusion coefficient on each particle was computed from the dye intensity during the rehydration process. The results showed that effective diffusion coefficients for water increased linearly with increasing powder particle size and are in agreement with previously used methods. In summary, the models provide two independent machine measurements of effective diffusion coefficient based on the same set of micrographs and may be useful in a wide variety of high-protein powders. Full article