Tạp chí Khoa học Tài nguyên và Môi trường
Tạp chí của Trường Đại học Tài nguyên và Môi trường Hà Nội
Legal risks for land recovery enterprises with delayed project implementation: reform requirements in the context of capital market development
Land recovery for delayed projects is posing significant legal risks in the context of an increasingly developed capital market. In practice, many enterprises use land use rights as collateral to mobilize capital from banks and investors; therefore, land recovery not only affects enterprises but also creates spillover impacts on credit institutions and the financial market as a whole. This article analyzes legal shortcomings in land recovery where enterprises fail to put land into use in accordance with the approved schedule, with particular emphasis on conflicts between the Land Law, the Investment Law, and regulations on credit and secured transactions. It also provides a comparative perspective with international experiences to highlight the need for legal reforms aimed at protecting legitimate rights of investors and preventing systemic risks to the capital market, especially in the context where land use rights are increasingly “financialized” as a primary form of collateral in credit and investment transactions. Accordingly, the article contributes an interdisciplinary approach linking Land Law and Financial Law, proposing a legal reform model toward ensuring the stability of the national financial system.
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Impacts of climate change on the living conditions of ethnic minority and mountainous communities in Nghe An province
This study analyzes the impacts of climate change on the living conditions of ethnic minority and mountainous communities in Nghe An province, while examining the relationship between climate-related impacts and local population planning and settlement stabilization practices. The research employed secondary data collection and synthesis, along with sociological surveys conducted with 200 households and 90 local officials in 2024, combined with descriptive statistical and comparative analysis methods. The results indicate that household livelihoods remain unstable (mean score = 2.32), while natural disasters have caused very high levels of damage to living conditions and production activities (mean score = 4.11). Community adaptive capacity is assessed at a moderate level (3.27), and public participation in population arrangement and settlement stabilization processes remains limited (2.41). Differences between community perceptions and managerial assessments also reveal gaps in integrating climate change considerations into settlement planning practices. Based on these findings, the study proposes strengthening the integration of climate change factors into residential spatial planning, promoting climate-resilient livelihoods, and enhancing meaningful community participation to improve the sustainability of livelihood stabilization in ethnic minority and mountainous areas.
Legal framework for the carbon market in Vietnam
Vietnam has committed to reducing greenhouse gas emissions under the Paris Agreement and achieving net-zero emissions by 2050. To realize this goal, establishing a legal framework for the carbon market is an urgent task, as it provides an economic instrument to promote emission reductions and mobilize green finance. Vietnam has already developed an initial legal foundation, including the Law on Environmental protection (2020), Decree No. 06/2022/ND-CP, Decree No. 119/2025/ND-CP, and Decision No. 232/QD-TTg. However, detailed regulations regarding trading mechanisms, carbon pricing, ownership rights, and market monitoring systems remain incomplete. In practice, international experience from China and the European Union Emissions Trading System (EU ETS) demonstrates that national emissions trading systems can be effective when supported by transparent regulations and strong enforcement mechanisms. For sustainable development, Vietnam needs to establish a unified national authority responsible for carbon market management, refine mechanisms for the ownership and benefit-sharing of forest carbon credits, develop a national MRV (Measurement, Reporting, and Verification) system, and apply digital technologies such as blockchain to carbon credit registries. In addition, it is necessary to link the carbon market with green finance instruments, introduce tax incentives, and support enterprises in adopting low-carbon technologies. These measures would help ensure that the carbon market operates transparently, fairly, and in alignment with international standards.
Breast cancer classification and prediction based on Artificial Neural Networks using cellular diagnostic data
Breast cancer is one of the leading causes of cancer - related mortality among women worldwide. Early detection and accurate diagnosis play a crucial role in improving treatment outcomes and reducing mortality rates. In recent years, machine learning and deep learning techniques have been increasingly applied in biomedical domains to assist clinicians in disease diagnosis. This paper presents a breast cancer classification approach based on an Artificial Neural Network (ANN) using the Breast Cancer Wisconsin (Diagnostic) dataset, which contains 569 samples and 30 morphological cell features. The proposed research pipeline includes data preprocessing, Z-score standardization, an 80/20 train - test split, ANN training with ReLU activation and Dropout regularization, model evaluation using Accuracy, Confusion Matrix, and ROC - AUC metrics, and finally inference on new patient data. Experimental results demonstrate that the proposed ANN model achieves approximately 97 - 98 % accuracy on the test set, with an AUC of about 0.99, indicating excellent discriminative performance between benign and malignant tumors. This study contributes both academically by validating the effectiveness of ANN for medical diagnostic data and practically by providing a potential decision-support tool for breast cancer diagnosis.
A study on evaluating the HEC - HMS Model for flood runoff forecasting at Ngoi Hut Hydrological Station
The Ngòi Hút river is a tributary of the Thao river located in Lao Cai province. Its steep topography and highly variable flow regime make the basin prone to frequent flooding during heavy rainfall. This study uses the HEC - HMS hydrological model to simulate flows and to develop a flood forecasting scheme for the Ngoi Hut Hydrometric Station. Calibration and validation against four flood events in 2024 yielded Nash - Sutcliffe efficiency coefficients of 0.76 - 0.85 and Pearson correlation coefficients r of 0.89 - 0.96, indicating good agreement with observed data. Based on these results, a 3-hour lead-time flood forecasting procedure was formulated and evaluated using statistical performance metrics. The forecast reliability P(%) for the four events was 86 %, 84 %, 68 %, and 82 %, respectively. Composite evaluation indicators show that the forecasting results fall within acceptable ranges.
Assessment of land quality to support agricultural production orientation in Van Don Special Zone, Quang Ninh province
This study aims to identify soil properties that influence agricultural production in the Van Don Special Zone. Through field surveys, sample collection, soil profile analysis, and soil classification in accordance with current Vietnamese standards, the agricultural land in the Van Don Special Zone was found to comprise six main soil groups and thirteen soil units. The study analyzed thirteen soil profiles to determine fourteen physical and chemical soil indicators. These results support the assessment of agricultural land degradation levels, thereby providing guidance for land use planning and for selecting suitable crops based on soil characteristics.
Study on the accumulation of heavy metals in coastal sediments in Hai Phong city
This study aims to investigate the spatial distribution and accumulation mechanisms of heavy metals (Cu, Pb, Zn, Cd, and As) in coastal sediments of Hai Phong, Vietnam, based on sediment grain size composition, metal concentrations, and correlation analysis. The results reveal a clear spatial heterogeneity in sediment characteristics, with fine - grained sediments (silt - clay) dominating estuarine and tidal flat areas, while coarser sediments (sand) prevail in offshore zones. Among the studied metals, Zn exhibits the highest relative abundance, followed by Pb and As, whereas Cu and Cd are present at lower levels. The concentrations of heavy metals are generally higher in estuarine regions and decrease seaward, indicating significant influence from land - based sources. Pearson correlation demonstrates strong positive relationships among Pb, Zn, and As, suggesting a common anthropogenic origin and similar accumulation behavior associated with fine particles and organic matter. Overall, the accumulation of heavy metals in the study area is governed by a combination of sediment grain size, terrestrial inputs, and hydrodynamic conditions. Estuarine and tidal flat zones act as effective sinks for heavy metals and should be prioritized in environmental monitoring and management strategies.
Assessment of the current situation and factors influencing the development of smart cities in Hanoi under a polycentric spatial orientation
This study aims to assess the current situation and analyze the factors influencing the development of a smart city model in Hanoi, with a focus on the system of five satellite urban areas. Data were collected from 350 respondents. Both qualitative and quantitative research methods were employed, with data processed using SPSS 22 software. Reliability was tested using Cronbach’s Alpha, and Exploratory Factor Analysis (EFA) was conducted to validate the measurement scales. Correlation analysis and multiple linear regression were also applied. The results indicate that all factors have an impact, among which smart governance has the strongest influence, followed by smart economy and smart citizens, while environmental, living, and mobility factors show lower impacts. The study confirms the role of satellite urban areas in expanding development space and reducing pressure on Hanoi’s inner city.
Assessment of water quality of the Ma River section from Ban Lat bridge to the convergence of the Do and Ma Rivers, Thanh Hoa province in 2025 and proposal of management solutions
This study assesses the current status and trends of surface water quality in the Ma River section flowing from Ban Lat bridge to the confluence of the Do and Ma Rivers in Thanh Hoa province in 2025. Research data was collected through six monitoring periods at key locations such as Ban Lat bridge, Kieu Bridge, Bong Junction, and the Gong River area. Analysis parameters included physical parameters (temperature, pH, TSS) and organic and nutrient pollution parameters (BOD5, COD, NH4+, NO2-, PO43-). The assessment results, based on the National Technical Standard QCVN 08:2023/BTNMT and the Water Quality Index (WQI), show that: The water quality of the Ma River generally remains at a moderate to good level, however, there is a clear differentiation depending on location and time. Regarding the Water Quality Index (WQI), the upstream area (Ban Lat Bridge) achieved the best quality, while downstream points and the confluence area of ​​the Do River recorded a decrease in water quality to “Poor” during the 4th monitoring period; Regarding physicochemical parameters, BOD5 values ​​fluctuated widely from 3.2 to 15.2 mg/L, reflecting local organic pollution pressure in some sections of the river flowing through residential areas. The main causes of water quality degradation have been identified as untreated domestic wastewater, agricultural practices using chemical fertilizers, and wastewater from cage aquaculture on the river. Based on this, the study proposes a group of management solutions focusing on improving the centralized wastewater collection system, strictly controlling agricultural wastewater sources, and strengthening the automated monitoring network to sustainably protect the Ma River's water resources.
Application of large language models in identifying and analyzing Facebook scam pages
This study addresses the escalating challenge of sophisticated online scams on the Facebook social media platform in Vietnam. The research aims to develop a scam detection and analysis system that prioritizes not only technical accuracy but also transparency and explainability (Explainable AI). The research subjects are public Facebook profiles and Fanpages involving common scam scenarios such as gambling and fake recruitment. The proposed methodology is a layered architecture integrating a hybrid PhoBERT-v2 and XGBoost model to simultaneously process Vietnamese semantic features and behavioral metadata. The system utilizes Retrieval-Augmented Generation (RAG) and the Model Context Protocol (MCP) to build AI agents capable of real-time blacklist lookups and providing legal-based explanations. Experimental results on real-world datasets show that the model achieves 92.58 % accuracy, 92,76 % F1-Score, and a 0.9509 ROC-AUC. The study contributes a comprehensive solution to enhance community information security awareness by combining detection technology with user education.
Analysis of environmental management regulations on hospital waste in Vietnam
Medical waste management is a critical component of environmental and public health protection. This article analyzes the legal framework governing hospital waste management in Vietnam for the 2021 - 2025 period, focusing on the 2020 Law on Environmental Protection. Using documentary and comparative legal analysis, the study evaluates the paradigm shift from “end-of-pipe” control to an integrated permitting system and circular economy orientation. Results indicate significant legal synchronization between sectors. However, implementation faces practical challenges: heavy compliance costs for financially autonomous medical facilities, complex licensing procedures, and a lack of standardized treatment infrastructure. The research contributes a policy impact analysis framework and proposes three core solutions: establishing a financial subsidy mechanism for medical waste treatment, developing clustered regional treatment models, and standardizing environmental training for hospital personnel.
Carbon credits from mangrove ecosystems and the potential for developing sustainable livelihoods of Vietnam's coastal communities
In the context of climate change and the development of global carbon markets, carbon credits from mangrove ecosystems are considered a potential nature - based solution for greenhouse gas mitigation and sustainable coastal development. This paper aims to review the scientific basis of mangrove carbon credits, analyze their development potential in Vietnam, and assess their contribution to the sustainable livelihoods of coastal communities. The results indicate that Vietnam’s mangrove forests have significant potential for carbon credit development. However, the development of mangrove carbon credits still faces several challenges, including the lack of a comprehensive Measurement - Reporting - Verification (MRV) system, high implementation costs, and unclear benefit-sharing mechanisms. The study also highlights that carbon credits could provide an additional financial source for forest conservation and support sustainable livelihood development for coastal communities. Based on these findings, the paper recommends improving the legal framework, strengthening technical capacity, and promoting pilot projects to effectively utilize the carbon potential of mangrove ecosystems in Vietnam.
Preliminary assessment of the current status of domestic solid waste management in Rach Cheo commune, Ca Mau province
This study focuses on assessing the current status of generation, composition, and management practices of household solid waste in Rach Cheo commune, a rural area in Ca Mau province, to propose management solutions. The research methodology combined quantitative interviews with 30 households and direct waste sampling and analysis from 15 households over one week. Descriptive statistical analysis revealed a household solid waste generation rate of around 0.2 kg/capita/day in the study area, with food waste constituting the predominant component at 83.86 %. Other components included recyclable waste (8.77 %), residual waste (5.70 %), and hazardous waste (1.67 %). Despite local authorities' awareness-raising efforts, the rate of at-source waste separation among households remained limited at 43 %, and open burning was the most common disposal method (50 %) due to the absence of centralized collection services. This study provides scientific evidence to support measures to improve local household solid waste management. Key recommendations include enhancing community education, developing effective at-source separation models, and developing collection and treatment infrastructure tailored to rural conditions.
Closing agricultural loops through the conversion of rice straw into cellulose-based soil amendment materials
Closing material loops is central to sustainable agriculture, where agricultural residues should be revalorized as functional resources rather than treated as waste. In Vietnam, rice straw represents an abundant lignocellulosic biomass with strong potential for developing soil amendment materials in the context of soil degradation and increasing drought stress. This review examines the potential for converting rice straw into cellulose-based hydrogels through the lenses of green chemistry and the circular economy. Cellulose can be recovered using a range of approaches, including high-pressure steam treatment, hydrogen peroxide oxidation, enzymatic processes, and deep eutectic solvents. Building on these pathways, cellulose-based hydrogels emerge as promising materials because their three-dimensional polymer networks enable water uptake and gradual release, thereby improving soil moisture regulation and supporting nutrient retention. When designed from biobased feedstocks and environmentally benign crosslinking agents, these materials also offer the prospect of biodegradation after use.
Research on the selection of low-carbon technologies criteria for the energy sector in Vinh Yen ward, Phu Tho province
In Viet Nam, the energy sector is the largest source of emissions, accounting for approximately 65 % of total greenhouse gas emissions, primarily from the combustion of fossil fuels for electricity generation, transportation, and industrial activities [3]. Therefore, promoting the selection and deployment of low-carbon technologies in the energy sector represents a key solution for gradually reducing emission intensity, improving energy efficiency, and directly contributing to the achievement of net-zero emission targets. The research results propose a set of criteria for selecting low-carbon technology in the energy sector (energy efficiency, transportation, and energy production) and establish priority levels based on percentile ranking. The criteria set was piloted in Vinh Yen ward, Phu Tho province, with high priority given to low-carbon technology options listed in Viet Nam’s NDC (2022) [3], specifically E3, E4 (energy efficiency); E21, E23, E25 (transportation); and E30 (energy production).
Study on the applicability of the CH4Net model and Sentinel-2 imagery in identifying the spatial distribution related to CH4 emissions in the Red River delta
Methane (CH4) is one of the important greenhouse gases, playing a significant role in global climate change due to its high heat-trapping capacity in the atmosphere [1]. Monitoring and predicting the spatial distribution of CH4 remains challenging, stemming from the complex interaction between surface factors and atmospheric dynamics. In this study, a multi-source data integration methodology framework is proposed, combining Sentinel-2 optical imagery, CH4 data from Sentinel-5P, and ERA5-Land meteorological data to classify CH4 levels according to a spatial grid at the monthly scale. To ensure that the model evaluation accurately reflects the generalization capability, the study applies a spatially independent data partitioning strategy, in which the grid cells in the training and test sets do not overlap. The CH4Net-RRD deep learning model was constructed and used to extract spatial features from Sentinel-2 images, while meteorological variables were processed using a multilayer perceptron network. The two feature sources were combined to perform methane binary classification. Experimental results showed that the model using only Sentinel-2 achieved a Macro F1-score of 0.8100, reflecting average surface information extraction capabilities. When meteorological data were integrated, the model performance increased to 0.9128, indicating a significant supporting role of atmospheric variables. Notably, the model using only ERA5 achieved perfect performance (Macro F1 = 1.0000), suggesting that at the monthly grid scale, CH4 distribution is primarily governed by meteorological conditions. Spatial analysis revealed that prediction deviations are not randomly distributed but concentrated in transitional regions. The research results clarify the dominant role of atmospheric factors in CH4 distribution, while also emphasizing the importance of spatially independent assessment methods in environmental modeling problems using remote sensing.
Estimating above ground forest biomass using multi-source remote sensing data and machine learning in Thai Nguyen
This study aims to estimate above ground biomass (AGB) of forests in Thai Nguyen province by integrating multi-source remote sensing data with advanced machine learning techniques. The dataset includes Sentinel-2 optical imagery, Sentinel-1 radar data, the SRTM digital elevation model (DEM), and spaceborne GEDI LiDAR data. This integration enables the simultaneous exploitation of spectral characteristics, vertical vegetation structure, and topographic factors, thereby improving the accuracy of forest biomass modeling in the study area. Training samples were derived directly from GEDI data, which provide reliable reference AGB values for model training and validation. The Gradient Tree Boosting algorithm was employed to develop a regression model for AGB estimation, effectively capturing complex nonlinear relationships among input variables. Model performance was evaluated using cross-validation, yielding a coefficient of determination (R²) of 0.78, a root mean square error (RMSE) of 38.32 Mg/ha, and a bias of 0.09, indicating good agreement between predicted and reference values. The results demonstrate that integrating multi-source remote sensing data with machine learning techniques can effectively estimate forest AGB in Thai Nguyen province. Additionally, the study highlights the potential of GEDI data as a reliable reference for AGB, offering promising opportunities for forest monitoring, management, and policy planning at local and regional scales.
Characteristics of the phytoplankton community and its relationship with water quality in Trieu Khuc lake, Hanoi
Trieu Khuc lake is an important residential water body located in a traditional craft village area in Thanh Liet, Hanoi, currently under significant pressure from untreated domestic and production wastewater. This study aimed to assess the phytoplankton community structure and water quality using biological indices and physicochemical parameters. Sampling was conducted over nine surveys from May 2022 to January 2023 at four sites. A total of 74 species and subspecies belonging to six divisions were identified, with Chlorophyta dominating in species composition (50 %). However, Cyanobacteria dominated in cell density and determined the overall biomass of the lake. Phytoplankton density showed strong temporal variation, peaking in October 2022 (average 2.671 × 10⁶ cells/mL). Environmental parameters indicated severe degradation, with dissolved oxygen consistently below 1 mg/L, high turbidity, and signs of acidification. Biological indices, including Shannon - Wiener (H’ < 1), Palmer (14 - 16), and Bio-index, consistently indicated organic pollution and eutrophic conditions. The strong agreement between biological and physicochemical assessments suggests that the lake is heavily polluted and strongly affected by nutrient-rich wastewater inputs.
Assessment of arabica coffee silverskin: nutritional value and biological effects as a potential food ingredient
Coffee silverskin is a major by-product of the coffee roasting process, accounting for approximately 4.2 % (w/w) of coffee beans. It is a rich source of proteins, dietary fibers, lipids, and bioactive secondary metabolites. Therefore, they are considered a promising raw material for applications in the food, cosmetics, biofuel, and fertilizer industries. This study evaluated the nutritional composition, extraction yield, and biological activities of the Arabica coffee silverskin extracts. The results showed that the contents of protein, carbohydrate, and lipid were 8.72 <!-- [if gte msEquation 12]><m:oMath><m:r>±</m:r></m:oMath><![endif]--> 0.10 %, 40.44 <!-- [if gte msEquation 12]><m:oMath><m:r>±</m:r></m:oMath><![endif]--> 0.27 %, 2.73 <!-- [if gte msEquation 12]><m:oMath><m:r>±</m:r></m:oMath><![endif]--> 0.10 % (calculated on a dry weight basis - DW). The extraction yield using methanol reached 8.44 <!-- [if gte msEquation 12]><m:oMath><m:r>±</m:r></m:oMath><![endif]--> 0.42 %. The extract exhibited strong antioxidant activity with an IC50 value of 191.18 <!-- [if gte msEquation 12]><m:oMath><m:r>±</m:r></m:oMath><![endif]--> 1.62 µg/mL and showed notable UV - absorbing capacity with an in vitro Sun Protection Factor (SPF) value of 6.46<!-- [if gte msEquation 12]><m:oMath><m:r> ± </m:r></m:oMath><![endif]--> 0.12 at a concentration of 1.000 µg/mL. These results indicate that Arabica coffee silverskin is a nutrient - rich material with potent antioxidant and UV - protective properties, demonstrating high potential for applications in functional foods and cosmetics while promoting a circular economy by valorizing agricultural by-products.
Using the PRISMA framework to conduct a comprehensive study of source stream occurrence in mountain areas
Headwater stream blockages present a significant hydrogeomorphic challenge, often linked to landslides, flash floods, and debris flows in mountainous regions. Blockage caused by landslides, debris flows, or human activities can create temporary reservoirs, heightening the risk of sudden dam failure and severe downstream impacts. As climate change intensifies the frequency and severity of extreme rainfall, the threat of stream blockages is rising in Vietnam's mountainous river basins. This study systematically reviews recent advances in the mechanisms, detection methods, and predictive modelling of stream blockage using a structured evidence synthesis approach consistent with PRISMA 2020 guidelines. The review reveals that current research is predominantly fragmented, focusing either on slope instability thresholds or post-failure dam-break hydraulics, with limited efforts to model the full event chain linking extreme rainfall, landslides, headwater stream blockages, temporary impoundment, and dam failure. Based on the synthesis, this study proposes a conceptual integrated framework for early warning that combines dynamic rainfall thresholds, probabilistic slope instability modelling, satellite-based blockage detection, and two-dimensional flood routing simulation. The framework emphasises the need for physics-informed machine learning and multi-source data integration to reduce uncertainty and enhance interpretability. In the context of intensifying extreme precipitation under climate change and increasing anthropogenic disturbance in mountainous catchments, the findings provide a strategic direction for advancing probabilistic, process-based hazard assessment of landslide-induced upstream flow blockage. The proposed framework offers a scientific foundation for developing operational early warning systems in data-scarce, tectonically active monsoon regions such as Northwestern Vietnam.
20. Assessment of the current status and proposed solutions for medical solid waste management at Duc Giang General Hospital, Hanoi city
Medical solid waste management is a key component in protecting the environment and public health in healthcare service delivery. This study was conducted to assess the status of medical solid waste management at Duc Giang General Hospital, Hanoi city, and to propose appropriate management solutions. The results show that the classification, collection, storage, and transfer of medical solid waste at Duc Giang general hospital have been implemented in a relatively systematic manner and in compliance with current regulations. However, several limitations remain, including limited awareness among some patients and their relatives, as well as shortcomings in supervision and guidance on source waste segregation. Based on these findings, the study proposes several solutions to enhance the effectiveness of medical solid waste management at the hospital in the coming period.
19. Research and development of an information system to support real estate transactions in Hanoi city
The real estate market in Hanoi is developing rapidly but faces significant challenges regarding transparency and information asymmetry. Participants in transactions often encounter difficulties in verifying legal status, true value, and planning information, leading to numerous disputes. This paper focuses on researching and proposing an integrated information system (IS) model to support stakeholders (buyers, sellers, brokers, and regulatory agencies) in safely and efficiently searching, verifying, and conducting real estate transactions. The research utilizes system analysis and database design methods. GIS (Geographic Information System) technology is applied to visualize planning map data, and Web/Mobile technology is used to build an interactive interface. Data is collected from reliable sources such as the Department of Agriculture and Environment, major real estate exchanges, and field surveys. The proposed information system not only contributes to the transparency of the capital's real estate market but also serves as a powerful tool to reduce transaction time and costs. The research results are an important foundation for developing e-government applications in land management in Hanoi.
18. Evaluation of domestic solid waste collection fee mechanism in Xuan Dinh ward, Hanoi city from an environmental economics perspective and proposals for improvement towards the circular economy
In the context of rapid urbanization, domestic solid waste management in major cities like Hanoi faces numerous challenges, particularly regarding financial sustainability and environmental efficiency. Xuan Dinh Ward, with its high urbanization rate and population density, is experiencing increasing pressure from waste generation. This study evaluates the current domestic solid waste collection fee mechanism in Xuan Dinh Ward from an environmental economics perspective by conducting field surveys of 50 households, combined with Cost-Benefit Analysis (CBA) and multi-criteria decision matrix methods. The results indicate that the current flat-rate fee mechanism, at approximately 24,000 VND/person/month, covers only about 49.7 % of actual costs and eliminates incentives for waste reduction and source separation. Based on these findings, the study proposes a roadmap to transition to a Pay-As-You-Throw (PAYT) mechanism integrated with the circular economy, including implementing a two-part fee structure and formalizing the informal collection sector to improve management efficiency and ensure social equity.
17. Research on building a pharmaceutical and cosmeceutical website using the Laravel framework combined with AI for customer care and Blockchain technology for data security
The research focuses on developing an e-commerce website for the dermo-cosmetics industry using the Laravel framework to address two major challenges: personalizing the customer experience and ensuring product origin transparency. The system integrates Artificial Intelligence via a Chatbot (Cosmebot) using the Gemini API, enabling natural-language product consultation based on user needs and budgets. Notably, the Skin Test feature analyzes skin conditions (acne, oiliness, redness) from images to recommend personalized skincare routines. In terms of security, Blockchain and IPFS technologies are used to store immutable product data, enabling anti-counterfeit authentication via QR codes. The website not only completes core business operations such as sales management, logistics, and loyalty systems but also enhances consumer trust through transparency and modernization. Experimental results demonstrate that the system operates stably and effectively meets practical demands in the era of digital transformation.
16. Scientific basis and application potential of surface velocity measurement technology for hydrological stations in tidal river regions of Viet Nam
This study evaluates the scientific basis and applicability of surface point velocity measurement technologies, including surface Doppler radar, fixed acoustic sensors, and the Large-Scale Particle Image Velocimetry (LSPIV) system, for discharge estimation in tidal rivers in Vietnam. Velocity data were collected from 17 hydrological stations within the national monitoring network in 2025. Cross-sectional mean velocities were measured and calibrated using Acoustic Doppler Current Profiler (ADCP) instruments in accordance with the recommendations of WMO [1] and USGS [3]. Based on these data, regression relationships between surface point velocity (Vs) and mean velocity (Vtb) were established. The results indicate a strong correlation between Vs and Vtb, with correlation coefficients (R) mostly exceeding 0.9. This confirms that surface point velocity can serve as a proxy for representative vertical mean velocity in discharge estimation for tidal river stations, both for currently applied stations and for potential extension to other tidal river stations in Vietnam. Furthermore, the findings highlight the potential of non-contact measurement technologies in improving automation and the reliability of hydrological observations.
15. Assessment of surface water quality changes in Ong Chuong canal, An Giang province 2020 - 2022
The research objective was to assess the changes in surface water quality in the Ong Chuong canal, An Giang province, during the period 2020 - 2022. Analysis of surface water samples taken at three points (beginning, middle, and end the Ong Chuong canal) showed pH values ranging from 6.85 - 7.32, DO from 4.01 - 5.02 mg/l, TSS from 44 - 103 mg/l, COD from 12 - 390 mg/l, BOD5 from 8 - 254 mg/l, total Nitrogen (TN) from 0.018 - 0.336 mg/l, total Phosphorus (TP) from KPH -0.064 mg/l, Ammonium (NH4+) from KPH -1.46 mg/l, and total Coliform from 1500 - >240000 MPN/100 ml. Overall, the surface water quality of Ong Chuong canal has pH, total nitrogen, and total phosphorus values that are still within the permissible limits. However, parameters such as DO, TSS, COD, BOD5, and total Coliform have increased beyond the permissible limits. The pollution is caused by the impact of organic matter and microbial decomposition, especially Ammonia, which exceeded the permissible limit in 2021 - 2022, and the remaining parameters also exceeded the standards (QCVN 08:2023/BTNMT, level A), negatively affecting aquatic life and human health if Ong Chuong canal water is used directly without treatment.
14. Application of Geographic Information Systems (GIS) to the development of land unit maps supporting agricultural production in Van Don Special Economic Zone, Quang Ninh province
Van Don Special Economic Zone has great potential and advantages for developing agricultural production, especially fruit cultivation. The area covers a total of 58,477.9 hectares, including 42,392.5 hectares of agricultural land, which makes up 72.49 % of the total. To create a land unit map that supports the assessment of agricultural land potential, the study surveyed 41,147.2 hectares using six classification criteria: soil type, slope, soil texture, soil depth, irrigation, and drainage conditions. Using GIS technology, six individual thematic maps were produced. By overlaying these maps with ArcView 10.3 software, the study identified 38 distinct land units. These results, combined with detailed descriptions of each unit, provide an important foundation for evaluating the agricultural land potential of Van Don Special Economic Zone in Quang Ninh province.
13. Integrating a SARIMAX model and climate scenarios to project dengue incidence in An Giang province by the late 21st century
Climate change is a critical driver of dengue transmission in tropical regions, yet long-term local-scale projections in Vietnam remain scarce. This study applies a Seasonal Autoregressive Integrated Moving Average with Exogenous Variables (SARIMAX) model (2,0,1)(0,0,1,12) to quantify the relationship between climate variables and dengue incidence and to project future incidence in An Giang province throughout the 21st century. Monthly dengue case counts (2001 - 2021) were integrated with outputs from 20 global climate models under Shared Socioeconomic Pathway (SSP) scenarios. Climatic predictors were reduced using Principal Component Analysis (PCA) to address multicollinearity, with lagged associations incorporated to improve model performance. Temperature exhibited the strongest association with dengue incidence at a lag of 2 - 3 months, whereas precipitation showed significant effects at lags of 0 - 2 months. Projections indicate a consistent upward trend, with dengue incidence increasing by approximately 25 - 30 % under high emission SSP scenarios by the late 21st century. These findings highlight the importance of integrating climate information into local dengue early warning and forecasting systems.
12. Communication management at Vietnam Airlines: Current situation and solutions for improvement
This study examines the current state of communication management at Vietnam Airlines from 2019 - 2025 and proposes solutions to enhance communication effectiveness amid digital transformation and intensifying competition in the aviation industry. The research employs a mixed-method approach combining qualitative and quantitative methods. Qualitative data were collected through in-depth interviews with communication managers, industry experts, and journalists, while quantitative data were obtained from a survey of 100 customers and 149 employees of the corporation. The results indicate that Vietnam Airlines has established a relatively clear brand image as the national flag carrier and maintained an effective internal communication system that contributes to employee engagement. However, several challenges remain, including the gap between brand communication and service experience in certain operational situations, as well as limitations in the current system for measuring communication performance. Based on these findings, the study suggests strengthening the integration between communication management and operational performance indicators, while applying digital tools such as e-CRM, social listening, and customer data platforms to improve communication effectiveness and customer experience.
11. Legal framework and practice of municipal solid waste management
This paper analyzes the legal framework for municipal solid waste management in Vietnam during the 2020 - 2025 period, focusing on the Law on Environmental Protection 2020 and newly issued national technical regulations. The study indicates that the current system of legal documents has established a solid foundation for transitioning from a landfill-based model to a circular economy through mandatory source separation regulations and the standardization of modern treatment technologies, such as waste-to-energy and co-processing. However, empirical analysis reveals a persistent gap between policy requirements and local technical infrastructure capacity, particularly regarding the lack of synchronization in collection and transportation, as well as limitations in emission monitoring. Based on these identified issues, the study proposes key solutions for infrastructure synchronization, the application of digital technology in environmental data management, and the enhancement of multi-dimensional monitoring mechanisms to bridge the implementation gap towards sustainable waste management goals.