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The current study fractionated pollution sources and investigated the impacts of seasonal and tidal variations on Saigon River's surface water quality. Ninety-six water samples were collected across dry and rainy seasons, covering ebb and flood tides, and analysed for 19 parameters. During the dry season, ebb tide showed higher levels of electrical conductivity, sulfate, chloride, sodium, and potassium. During the rainy season, ebb tide exhibited greater concentrations of ammonium, total nitrogen, and phosphorus. The water quality index was significantly lower during the dry season's ebb tide compared to the flood tide but remained similar in both tidal phases during the rainy season. Four primary pollution sources were quantified, with seawater intrusion and agricultural activities contributing 62.68% and 28.54%, respectively, to water quality degradation. Briefly, the river's surface water quality was inferior during the dry season compared to the rainy season, primarily due to seawater intrusion and agricultural activities, requiring remediation. [ABSTRACT FROM AUTHOR]

Three new species of Polycarpaea from Vietnam, Polycarpaea vanphongensis V.T. Tran, H.T. Truong & N.V. Binh, Polycarpaea chungana V.T. Tran, H.T. Truong & N.V. Binh, Polycarpaea phuquocensis V.T. Tran, H.T. Truong & N.V. Binh are described and illustrated based on evidence of molecular sequence data from two markers (ITS1-5.8S-ITS2 and rps16) and combined morphological characteristics. Polycarpaea vanphongensis is closely related to Polycarpaea gaudichaudi Gagnep., Polycarpaea arenaria (Lour.) Gagnep., Polycarpaea phuquocensis V.T. Tran, H.T. Truong & N.V. Binh but differs by its stem glabrous, leaf ovate to elliptic, glabrous, ovary oblong ovoid, base obtuse, apex attenuate, capsule oblong void, 3.8 mm long. Polycarpaea phuquocensis V.T. Tran, H.T. Truong & N.V. Binh differs from the three species mentioned above by its stem being densely villous, leaf spathulate, ciliate, ovary ovoid, base acute, apex obtuse, capsule ovoid, 1.2 mm long. Polycarpaea chungana V.T. Tran, H.T. Truong & N.V. Binh is most similar to Polycarpaea lignosa Gagnep., but differs in having leaf oblong or linear, sparse ciliate, sepal and petal apex deeply concaved or slightly bifid, ovary ovoid, ovoid, 0.8–1.0 mm long. Furthermore, the achievements of analysis using molecular data on the systematic positions of 7 other species are results that have not been in previous molecular analyses. [ABSTRACT FROM AUTHOR]

Issues Addressed: Promoting public health messages in adolescence may influence future health outcomes. A better understanding of what influences adolescent engagement with public health issues is needed. Methods: Adolescents aged 13–19 years from New South Wales, Australia, were recruited via study advertisements to participate in an online focus group. All provided informed consent and completed a short survey including demographics and selection of leading public health issues of concern. Participants attended a 75–90 min focus group conducted through Zoom teleconference that explored top public health issues of concern to participants, and barriers/enablers to engage with these issues. Qualitative data was thematically analysed using NVivo. A working group reached consensus on final themes. Results: Out of 18 participants (mean 15.4 [SD: 2.2] years; 50% female), most attended high school (83%), spoke predominantly English at home (89%), and resided in metropolitan areas (94%). The top public health issues of concern selected were mental health (56%) and the environment/climate change (56%). From the thematic analysis, underlying drivers of adolescent engagement with public health issues included: personal connection to these issues, broader societal impact, and exposure to public health issues on digital media. Barriers included feeling unempowered, and a lack of support and opportunities. Conclusions: This study provides insights on the barriers and enablers of adolescents engaging with public health issues of concern to them. So What?: Understanding this may help health professionals and researchers to design more influential public health campaigns and interventions, including through co‐design processes, which may improve future health outcomes. [ABSTRACT FROM AUTHOR]

This study investigates the impact of climate change on hydrological dynamics in the Ruzizi River Basin (RRB) by leveraging a combination of observational historical data and downscaled climate model outputs. The primary objective is to evaluate changes in precipitation, temperature, and water balance components under different climate scenarios. We employed a multi-modal ensemble (MME) approach to enhance the accuracy of climate projections, integrating historical climate data spanning from 1950 to 2014 with downscaled projections for the SSP2-4.5 and SSP5-8.5 scenarios, covering future periods from 2040 to 2100. Our methodology involved calibrating and validating the SWAT model against observed hydrological data to ensure reliable simulations of future climate scenarios. The model's performance was assessed using metrics such as R2, NSE, KGE, and PBIAS, which closely aligned with recommended standards. Results reveal a significant decline in mean annual precipitation, with reductions of up to 37.86% by mid-century under the SSP5-8.5 scenario. This decline is projected to lead to substantial reductions in surface runoff, evapotranspiration, and water yield, alongside a marked decrease in mean monthly stream flow, critically impacting agricultural, domestic, and ecological water needs. The study underscores the necessity of adaptive water resource management strategies to address these anticipated changes. Key recommendations include implementing a dynamic reservoir operation system, enhancing forecasting tools, and incorporating green infrastructure to maintain water quality, support ecosystem resilience, and ensure sustainable water use in the RRB. This research emphasizes the need for localized strategies to address climate-driven hydrological changes and protect future water resources. [ABSTRACT FROM AUTHOR]

Missing values are a common issue in many high-dimensional datasets, but a majority of classification algorithms require complete data. Therefore, imputation methods are usually used to estimate and fill missing values with plausible values before using the classification algorithms to learn classifiers or using the learnt classifiers to classify unseen incomplete samples. However, good imputation methods are usually computationally intensive on high-dimensional datasets because these datasets not only have a large number of features, but also often suffer from a large number of missing values. Another approach is to use decision tree algorithms which do not need imputation, and can work directly with incomplete data. However, using decision trees to classify high-dimensional data often leads to large classification accuracy because of the curse of dimensionality. Ensemble techniques which build multiple classifiers instead of a single classifier have been widely used to improve accuracy for decision trees. This paper aims to investigate different ensemble methods to find effective and efficient ensembles of decision trees for classification with high-dimensional incomplete data. Experimental results show that the random subspace method is the most accurate ensemble. The random subspace method is also more accurate than other classification algorithms which needs to combine with imputation when working with incomplete data. Moreover, the random subspace method is much faster than the other algorithms because it can directly work on incomplete data, so does not have to spend time estimating missing values. [ABSTRACT FROM AUTHOR]

Research on solutions to improve the regulation capacity of power systems is essential and urgent in the context of renewable energy sources being highly variable and constituting a significant proportion of Vietnam's power system by 2030. Pumped storage hydropower plants serve as an excellent energy reserve and are widely used to provide peak energy demands for daily and nightly loads. In Vietnam, the Bac Ai hydropower storage project, currently under construction, is the first of its kind and is expected to play a significant role as a large-scale energy storage system. This comes at a time when renewable energy sources are growing rapidly, with many large-scale solar and wind power plants being invested and commissioned. This project will be crucial to addressing surplus and shortage issues in power system load, stabilizing the system, regulating frequency, and ensuring stable, safe, and reliable operation of the national power grid. However, to assess the necessity of this project within the Vietnamese power system, scientific evaluations are required regarding the impact of capacity scale, timing, and operational position of this project within the development scenarios of Vietnam's power system. This study investigates an optimization problem for the operation of the Vietnamese power system, considering the characteristics of generation sources and transmission lines using the PyPSA software. The aim is to calculate and identify the role of the Bac Ai pumped storage hydropower plant in Ninh Thuan province in the 2030 scenario of Vietnam's power system, which includes a high proportion of renewable energy sources. [ABSTRACT FROM AUTHOR]

An effective approach to addressing the speech separation problem is utilizing a time–frequency (T-F) mask. The ideal binary mask (IBM) and ideal ratio mask (IRM) have long been widely used to separate speech signals. However, the IBM is better at improving speech intelligibility, while the IRM is better at improving speech quality. To leverage their respective strengths and overcome weaknesses, we propose an ideal threshold-based mask (ITM) to combine these two masks. By adjusting two thresholds, these two masks are combined to jointly act on speech separation. We list the impact of using different threshold combinations on speech separation performance under ideal conditions and discuss a reasonable range for fine tuning the thresholds. By using masks as a training target, to evaluate the effectiveness of the proposed method, we conducted supervised speech separation experiments applying a deep neural network (DNN) and long short-term memory (LSTM), the results of which were measured by three objective indicators: the signal-to-distortion ratio (SDR), signal-to-interference ratio (SIR), and signal-to-artifact ratio improvement (SAR). Experimental results show that the proposed mask combines the strengths of the IBM and IRM and implies that the accuracy of speech separation can potentially be further improved by effectively leveraging the advantages of different masks. [ABSTRACT FROM AUTHOR]

With rising environmental concerns, accurate air quality predictions have become paramount as they help in planning preventive measures and policies for potential health hazards and environmental problems caused by poor air quality. Most of the time, air quality data are time series data. However, due to various reasons, we often encounter missing values in datasets collected during data preparation and aggregation steps. The inability to analyze and handle missing data will significantly hinder the data analysis process. To address this issue, this paper offers an extensive review of air quality prediction and missing data imputation techniques for time series, particularly in relation to environmental challenges. In addition, we empirically assess eight imputation methods, including mean, median, kNNI, MICE, SAITS, BRITS, MRNN, and Transformer, to scrutinize their impact on air quality data. The evaluation is conducted using diverse air quality datasets gathered from numerous cities globally. Based on these evaluations, we offer practical recommendations for practitioners dealing with missing data in time series scenarios for environmental data. [ABSTRACT FROM AUTHOR]

This paper presents a disturbance observer‐based controller for a class of multi‐actuator systems that possess passivity properties. By distributing the input and aggregating the output using the same vectors, the original plant is transformed into an aggregation‐and‐distribution plant (ADP), which is also passive. Based on the ADP, this paper derives the conditions for the controller to sufficiently ensure that the overall system has a finite L2‐gain. The conditions can be checked via the passivity notation of several transfer functions. It is not required to establish the overall system's dynamical equation, thereby alleviating the design burden. The additional objective can be attained by performing an optimization on the aggregation/distribution vectors. Several practical applications are introduced as motivating examples, and the effectiveness of the proposed method is demonstrated by the integration of motion control and energy management for electric vehicles. [ABSTRACT FROM AUTHOR]

Antibiotic resistance (AR) rates in Vietnam are among the highest in Asia, and recent infections due to multi-drug resistance in the country have caused thousands of deaths each year. This study investigated a Vietnamese community's preferences for antibiotic treatment and its knowledge and attitudes regarding antibiotics. A discrete choice experiment-based survey was developed and administered to the population of interest. The respondents were given sociodemographic-, knowledge- and attitude-related items and 17 pairs of choice tasks. Two hypothetical options were included in each choice task. Latent class analysis was conducted to determine the differences among the respondents' preferences. Among 1,014 respondents, 805 (79.4%) gave valid questionnaires. A three-latent-class model with four covariates (age, healthcare-related education or career, occupation, and attitude classifications) was used in the analysis. All five attributes significantly influenced the respondents' decisions. The majority, including young employed respondents with non-healthcare-related work or education, found treatment failure more important. Older respondents who had healthcare-related education/careers and/or appropriate antibiotic use- and antibiotics resistance-related attitudes, regarded contribution to antibiotic resistance as an important attribute in selecting antibiotic treatments. Unemployed individuals with correct knowledge identified the cost of antibiotic treatment as the most essential decision-making factor. Findings suggest minimal antibiotic impact on resistance; only 7.83% view it as amajor concern. The respondents exhibited substantial preference heterogeneity, and the general Vietnamese public had poor knowledge of and attitudes toward antibiotic use and antibiotic resistance. This study emphasizes the need for individual responsibility for antibiotic resistance and appropriate antibiotic use. [ABSTRACT FROM AUTHOR]

To respond to the ever-increasing requirements of automotive electronics, universities need to adapt and play an active role in creating a new research environment and provide proper education to the young generation, which will face challenging tasks in this rapidly developed field. Vehicular technology education is crucial for the next generation of automotive electronics developers and engineers. Several education models, such as problem- and project-based learning (PPBL), academia–academia collaboration, and academia–industry collaboration, are highlighted as successful examples. [ABSTRACT FROM AUTHOR]

Molecular property prediction is an important step in the drug discovery pipeline. Numerous computational methods have been developed to predict a wide range of molecular properties. While recent approaches have shown promising results, no single architecture can comprehensively address all tasks, making this area persistently challenging and requiring substantial time and effort. Beyond traditional machine learning and deep learning architectures for regular data, several deep learning architectures have been designed for graph-structured data to overcome the limitations of conventional methods. Utilizing graph-structured data in quantitative structure–activity relationship (QSAR) modeling allows models to effectively extract unique features, especially where connectivity information is crucial. In our study, we developed residual graph attention networks (ResGAT), a deep learning architecture for molecular graph-structured data. This architecture is a combination of graph attention networks and shortcut connections to address both regression and classification problems. It is also customizable to adapt to various dataset sizes, enhancing the learning process based on molecular patterns. When tested multiple times with both random and scaffold sampling strategies on nine benchmark molecular datasets, QSAR models developed using ResGAT demonstrated stability and competitive performance compared to state-of-the-art methods. [ABSTRACT FROM AUTHOR]

Molecular representations have essential roles in bio-cheminformatics as they facilitate the growth of machine learning applications in numerous sub-domains of biology and chemistry, especially drug discovery. These representations transform the structural and chemical information of molecules into machine-readable formats that can be efficiently processed by computer programs. In this paper, we present a comprehensive review, providing readers with diverse perspectives on the strengths and weaknesses of well-known molecular representations, along with their respective categories and implementation sources. Moreover, we provide a summary of the applicability of these representations in de novo molecular design, molecular property prediction, and chemical reactions. Besides, representations for macromolecules are discussed with highlighted pros and cons. By addressing these aspects, we aim to offer a valuable resource on the significant role of molecular representations in advancing bio-cheminformatics and its related domains. [ABSTRACT FROM AUTHOR]

As reported by the FAO, in 2022, approximately 735 million people experienced undernourishment, underscoring the critical need for effective strategies to address micronutrient deficiencies. Among these strategies, the mass fortification of staple foods, particularly rice—a dietary staple for half of the global population—has emerged as one of the most effective approaches. Conventional milling processes diminish the nutritional content of rice, necessitating the development of fortification methods to enhance its nutrient profile. This study investigates advanced fortification techniques to improve the nutritional value of rice, focusing on vitamins B1, B2, and B6, with guidelines from the US Institute of Medicine's Dietary Reference Intakes. The results indicate that implementing ultrasonic treatments and optimal soaking conditions (60 °C for 60 min) significantly enhances the absorption of these vitamins. Effective parameters included a concentration of 1500 ppm for vitamin B1 and higher levels for vitamins B2 and B6, with a rice-to-vitamin solution ratio of 1:4. These conditions yielded an absorbed vitamin B1 content of 1050 mg/kg, bringing the fortified rice closer to meeting recommended intake levels. Given the global average daily consumption of 100 g of rice per person, this research demonstrates the feasibility of fortifying rice to address nutrient deficiencies effectively and contribute to improved dietary health worldwide. Further enhancement of vitamin B2 and B6 levels remains essential for optimal fortification, highlighting the potential of fortified rice as a sustainable solution for improving global nutrition. [ABSTRACT FROM AUTHOR]

Technology is increasingly disruptive, and economic transformation according to technology development is inevitable. Especially the field of E-commerce is constantly catching up with that development. We can easily see the development and importance of e-commerce in Vietnam and worldwide after the Covid-19 pandemic. Therefore, to attract and get customers online, businesses need to come up with solutions to increase the customer experience when shopping for their products. And the solution to this problem is the application of blockchain technology (blockchain) to e-commerce. Customer experience when shopping on e-commerce platforms with blockchain application is influenced by factors such as perceived risk, security, transparency, information synchronization, cost savings. To carry out this research, the research team conducted a survey and analysis based on 402 most suitable survey questionnaires, then conducted an assessment of factors affecting the shopping experience of customers when applying blockchain to e-commerce using Smart PLS 4.0 software and SPSS software. The survey was conducted with customers who have experience buying on e-commerce. The results of this research paper are a premise for many other future studies related to blockchain technology and draw out the governance implications for Vietnamese businesses in improving the shopping experience of customers when applying blockchain technology to e-commerce. In addition, the research results also help shoppers access the benefits of blockchain technology, helping customers feel more secure and confident when buying on e-commerce. [ABSTRACT FROM AUTHOR]

Background and Aim: The measurement of esophageal acid exposure time (AET) using combined multichannel intraluminal impedance–pH (MII‐pH) tests is the gold standard for diagnosing gastroesophageal reflux disease (GERD). However, this catheter‐based 24‐h test can cause considerable patient discomfort. Our aim is to identify factors affecting AET and to develop a scoring model for predicting AET abnormalities before conducting the MII‐pH test. Methods: Of the 366 patients who underwent MII‐pH test at two facilities in Japan and Vietnam, 255 patients who also had esophagogastroduodenoscopy and high‐resolution manometry were included in this study. Logistic regression analysis was conducted using risk factors for AET > 6% identified from a derivation cohort (n = 109). A scoring system predicting AET > 6% was then constructed and externally validated with a separate cohort (n = 146). Results: Three variables were derived from the prediction model: male gender, Hill grades III–IV, and weak mean distal contractile integrals. Based on these scores, patients were classified into low (0 point), intermediate (1–3 points), and high (4 points) risk groups. The probabilities of having an AET > 6% were 6%, 34%, and 100% for these groups, respectively. A score of < 1 excluded patients with abnormal AET, with a negative predictive value of 93.8% in the derivation cohort and 80.0% in the validation cohort. Conclusions: We derived and externally validated a prediction model for abnormal AET. This system could assist in guiding the appropriate treatment strategies for GERD. [ABSTRACT FROM AUTHOR]

Background: The increasing needs of people living with dementia (PLWD) in Vietnam present an enormous public health challenge. Vietnam is an understudied country, and little is known regarding the overall unmet needs of caregivers or the demographic risk factors associated with unmet caregiving needs. This study aimed to determine the burden of unmet care needs of community‐dwelling PLWD and identify sociodemographic risks associated with unmet care needs. Methods: A cross‐sectional study in a rural area facing urbanisation in Hanoi, Vietnam recruited PWLD‐caregiver dyads with multistage sampling. We utilised the Camberwell Assessment of Need for the Elderly (CANE) instrument to evaluate care needs across four domains. Caregivers rated PLWD needs, with higher scores indicating greater unmet needs. The Mann–Whitney test was employed for comparing two groups, while the Kruskal–Wallis test was used for comparisons involving more than two groups in the analysis, and a P‐value of less than 0.05 was considered statistically significant. Results: Among 90 PLWD participating in the study, the overall mean care needs score was 11.6 ± 4.3, with only 16.2% of PLWD having their care needs met. Environmental and physical needs were more frequently met than psychological or social needs. Only 48.0% and 43.9% of environmental and physical needs were met respectively, and a meagre 20.9% and 23.6% for psychological and social needs. Unmet care needs were more frequent for PWLD who were female, single or divorced, had lower monthly household income, or who were in more advanced stages of dementia, as indicated by Clinical Dementia Rating scores ≥1. Conclusions: Unmet needs for PWLD are common. Increased caregiver education, resources, and services in Vietnam are urgently required to improve the quality of life for this population. [ABSTRACT FROM AUTHOR]

This study assessed the performance of domesticated tiger shrimp Penaeus monodon postlarvae and mud crab Scylla paramamosain co‐cultured in 90 extensive rice‐shrimp ponds in the Mekong River Delta of Vietnam from 2022 to Sep 2023. Limited supplementary feeding was applied for only 20% of the studied ponds. Results show that ponds stocked with domesticated postlarvae produced significantly larger shrimps at harvest and had better postlarvae usage efficiency (P < 0.05) compared with those stocked with older postlarvae produced by wild‐caught broodstock. Furthermore, a combination of stocking domesticated postlarvae and using organic fertilizer for pond preparation and during the crop was found to significantly improve productivity by 28% and final harvest size by 67% (P < 0.05). Larger shrimps fetched 54% higher farm‐gate prices, thus significantly increasing gross revenue for farmers. Co‐culture of mud crab in rice‐shrimp ponds at low densities (0.2–0.7 pcs/m2) was popular and profitable. Productivity was 116–187 kg/ha/crop with a profit margin up to 92.8%. Income from mud crab was very similar to that from shrimp. The results of this study suggest that domesticated postlarvae of P. monodon should be used for stocking extensive systems, preferably in combination of using organic fertilizer to enhance natural foods. Further improvement of income and profit can be achieved if more attention is paid on crablet quality and quality improvement. [ABSTRACT FROM AUTHOR]

Detecting and analyzing various defect types in semiconductor materials is an important prerequisite for understanding the underlying mechanisms and tailoring the production processes. Analysis of microscopy images that reveal defects typically requires image analysis tasks such as segmentation and object detection. With the permanently increasing amount of data from experiments, handling these tasks manually becomes more and more impossible. In this work, we combine various image analysis and data mining techniques to create a robust and accurate, automated image analysis pipeline for extracting the type and position of all defects in a microscopy image of a KOH-etched 4H-SiC wafer. [ABSTRACT FROM AUTHOR]

The wind power market is expanding quickly and the cost of wind power equipment is decreasing, making wind power technology a key player in the world's energy transition. Assessing wind potential and selecting the right wind turbine site are crucial parameters for developing a wind farm. Vietnam focuses on onshore and nearshore wind power projects due to its promising wind power potential and supportive policies. However, Vietnam has diverse climate characteristics and wind patterns. Therefore, initial basic research is necessary to evaluate the feasibility of investing in wind power projects. This study examines the technical feasibility of a typical wind power project in the Southeast region of Vietnam using Wind Atlas Analysis and Application Program (WAsP) software. The results indicate that the wind turbine's type and installation location significantly affect wind power plants' efficiency. The total power output of the wind power project after factoring with losses at a rate of 17%, is 304,149 MWh. [ABSTRACT FROM AUTHOR]

Nowadays, the wind power market is growing rapidly, while the cost of wind power equipment is decreasing, so Vietnam is currently building many wind power projects to ensure green energy development in its power system. However, some barriers in price mechanisms, and economic and technical conditions have also caused disadvantages in the process of developing wind power projects. This paper studies the SWOT-TOWS analysis to evaluate in greater detail the strengths, weaknesses, opportunities, and threat factors linked to it. Then the former compares the internal and external factors influencing the wind power industry on the way it exploits potential strategies. In general, Vietnam has satisfactory wind power development potential, and the wind power sector has been supported by a number of strong but unstable policies in the past. The rapid development of wind power capacity in recent times has also led to great challenges for investors and managers in actual operating conditions. Currently, investment costs for wind power plants are still quite high, Feed in Tariff (FIT) prices are not stable, transmission grid capacity is limited, and environmental treatment issues during construction and operation have not been fully considered. [ABSTRACT FROM AUTHOR]

Traditional energy sources are gradually being exhausted, which causes many negative effects on the environment and contributes to the climate change. Countries around the world, including Vietnam, are focusing on developing renewable energy sources, such as solar power, to combat climate change and create a foundation for sustainable development. The development of solar power, particularly rooftop solar power, is being encouraged in various provinces and cities in Vietnam. The Northwest is a mountainous region in the Northern part of Vietnam with considerable solar energy potential. However, developing rooftop solar power projects requires balancing economic, technical, and environmental goals. Currently, there is no comprehensive research in Vietnam that fully evaluates the sustainable development goals for rooftop solar power in the Northwest region. This paper focuses on identifying the factors that influence the decision to install and use rooftop solar power in the Northwest region of Vietnam with the support of the Analytic Hierarchy Process (AHP) method and Expert Choice software. This impact ranges to varying degrees. The most significant influencing factor is the solar energy development policy, with a priority of 36.1%, while the social factor has the lowest priority value of 7.7%. The primary factor affecting people's decisions is the future solar power development policy, with a weight value of 24.2. [ABSTRACT FROM AUTHOR]

Remotely sensed evapotranspiration (ETRS) shows promise for enhancing hydrological models, especially in regions lacking in situ streamflow observations. However, model calibration studies showed conflicting results regarding the ability of ETRS products to improve streamflow simulation. Rather than relying on model calibration, here we produce the first randomized experiment that explores the full streamflow–ET skill distribution, and also the first probabilistic assessment of the value of different global ETRS products for streamflow simulation. Using 280,000 randomized SWAT (Soil and Water Assessment Tool) model runs across seven catchments and four ETRS products, we show that the relationship between ET and streamflow skills is complex, and simultaneous improvement in both skills is only possible in a limited range. Parameter sensitivity analysis indicates that the most sensitive parameters can have opposite contributions to ET and streamflow skills, leading to skill trade-offs. Conditional probability assessment reveals that models with good ET skills are likely to produce good streamflow skills, but not vice versa. We suggest that randomized experiments such as ours should be performed before model calibration to determine whether using ETRS is worthwhile, and to help in interpreting the calibration results. [ABSTRACT FROM AUTHOR]

Future changes in streamflow and sediment, influenced by anthropogenic activities and climate change, have a crucial role in watershed management. This study aimed to quantify the effects of anthropogenic and natural drivers on future streamflow and sediment changes in the tropical Sai Gon Dong Nai River basin using the Soil and Water Assessment Tool (SWAT) model. Specifically, the model incorporated thirty-six reservoirs and analyzed twenty future climate projected scenarios from four Coupled Model Intercomparison Project Phase 6 (CMIP6) General Circulation Models (GCMs) for 2023–2100. These models include BCC-CSM2-MR (China), CanESM5 (Canada), MIROC6 (Japan), and MRI-ESM2-0 (Japan). Our findings indicate that (1) dam operation and diversion lead to a 0.5% decrease in streamflow during the dry season and a 4.1% increase during the rainy season compared to those in scenarios without dams; (2) there is a 37.4% decrease in annual sediment across the entire basin under same climate conditions; and (3) rainfall is projected to decrease (24.6% – 6.2%), resulting in a decrease in streamflow (0.2 – 32.2%) and sediment (39.3 – 56.0%) compared to historical records. Streamflow is expected to decrease during the rainy season (16.7 – 23.1%) and increase during the dry season (14.5 – 25.4%). Further potential degradation of the environmental conditions and water mismanagement are caused by the synergies between too much and too little rainfall conditions. The anticipated reductions in future streamflow and sediment could adversely affect ecological streamflow, water security, and sediment dynamics in the Sai Gon Dong Nai River basin. Our approach effectively identifies future changes in streamflow and sediment due to the combined effects of climate change and reservoir operations, providing valuable insights for integrated water resource management in tropical regions. [ABSTRACT FROM AUTHOR]

ATTR amyloidosis results from the conversion of transthyretin into amyloid fibrils that deposit in tissues causing organ failure and death. This conversion is facilitated by mutations in ATTRv amyloidosis, or aging in ATTRwt amyloidosis. ATTRv amyloidosis exhibits extreme phenotypic variability, whereas ATTRwt amyloidosis presentation is consistent and predictable. Previously, we found unique structural variabilities in cardiac amyloid fibrils from polyneuropathic ATTRv-I84S patients. In contrast, cardiac fibrils from five genotypically different patients with cardiomyopathy or mixed phenotypes are structurally homogeneous. To understand fibril structure's impact on phenotype, it is necessary to study the fibrils from multiple patients sharing genotype and phenotype. Here we show the cryo-electron microscopy structures of fibrils extracted from four cardiomyopathic ATTRwt amyloidosis patients. Our study confirms that they share identical conformations with minimal structural variability, consistent with their homogenous clinical presentation. Our study contributes to the understanding of ATTR amyloidosis biopathology and calls for further studies. Cryo-EM analysis of fibrils from four cardiomyopathic ATTRwt amyloidosis patients reveals identical structures with minimal variability. This finding contributes to the understanding of ATTR amyloidosis biopathology. [ABSTRACT FROM AUTHOR]

This study investigates the effectiveness of internal controls governing green credit operations in Vietnamese commercial banks. We employ regression analysis to identify key factors influencing control effectiveness. Six key areas emerge: Risk Management, Macroeconomic Factors, Monitoring Activities, Group Benefits, Work Motivation, and Information and Communication. Independent sample T-tests and one-way ANOVA tests reveal significant variations in control effectiveness based on employee age groups and positions within the banks. Further analysis categorizes these factors into strong and weak impact groups based on their Beta coefficients. Risk Management and Macroeconomic Factors emerge as strong influencers, highlighting the critical role of robust risk management practices and favorable economic conditions. Conversely, Monitoring Activities, Group Benefits, Information and Communication, and Work Motivation have weaker but still notable impacts, suggesting areas for improvement in internal supervisory practices, communication systems, and employee motivation strategies. The findings underscore the critical role of risk management and macroeconomic factors while highlighting opportunities for enhancing supervisory practices, internal communication, and employee motivation within Vietnamese commercial banks. [ABSTRACT FROM AUTHOR]

The Trusted Execution Environment (TEE) is designed to establish a safe environment that prevents the execution of unauthenticated programs. The nature of TEE is a continuous verification process with hashing, signing, and verifying. Such a process is called the Chain-of-Trust, derived from the Root-of-Trust (RoT). Typically, the RoT is pre-programmed, hard-coded, or embedded in hardware, which is locally produced and checked before booting. The TEE employs various cryptographic processes throughout the boot process to verify the authenticity of the bootloader. It also validates other sensitive data and applications, such as software connected to the operating system. TEE is a self-contained environment and should not serve as the RoT or handle secure boot operations. Therefore, the issue of implementing hardware for RoT has become a challenge that requires further investigation and advancement. The main objective of this proposal is to introduce a secured RISC-V-based System-on-Chip (SoC) architecture capable of securely booting a TEE using a versatile boot program while maintaining complete isolation from the TEE processors. The suggested design has many cryptographic accelerators essential for the secure boot procedure. Furthermore, a separate 32-bit MicroController Unit (MCU) is concealed from the TEE side. This MCU manages sensitive information, such as the root key, and critical operations like the Zero Stage BootLoader (ZSBL) and key generation program. Once the RoT is integrated into the isolated sub-system, it becomes completely unavailable from the TEE side, even after booting, using any method. Besides providing a secured boot flow, the system is integrated with essential crypto-cores supporting Transport Layer Security (TLS) 1.3. The chip is finally fabricated using the Complementary Metal–Oxide–Semiconductor (CMOS) 180 nm process. [ABSTRACT FROM AUTHOR]

Recently, antiferroelectric and antiferroelectric‐like materials have regained interest in electronic devices, such as field‐effect transistors, memory, and transducers. Particularly in micro/nano‐electromechanical coupling systems such as actuators, these innovative materials, with their peculiar phase transition between antiferroelectric and ferroelectric phases, show promise in offering large electro‐strain, fast response, and low power consumption devices. However, compared to numerous computational models of ferroelectric actuators, numerical modeling of antiferroelectric and antiferroelectric‐like actuators remains relatively unexplored. In this paper, we propose a phenomenological model of uniaxial antiferroelectric and antiferroelectric‐like actuators based on their switching polarization behavior. Specifically, both the double hysteresis loop of antiferroelectric materials and the pinched hysteresis loop of antiferroelectric‐like materials can be captured by two hyperbolic tangent functions. This allows us to cast a polarization‐dependent strain and piezoelectric tensor into the constitutive laws. The proposed model is then implemented into a finite element framework, in which the voltage‐induced deformation can be solved using the Newton–Raphson procedure. Numerical examples of both antiferroelectric and antiferroelectric‐like actuators are illustrated and compared with experimental data, showing our proposed model can serve as a useful tool for the design and development of antiferroelectric and antiferroelectric‐like actuators. [ABSTRACT FROM AUTHOR]

Live coccidiosis vaccines have mainly been used to reduce Eimeria species infection, which is considered the most economically important disease in the poultry industry. Evaluation data on vaccine effectiveness through large-scale field experiments are lacking, especially in broilers. Thus, the effectiveness of a commercial coccidiosis vaccine was evaluated in approximately 900,000 chicks reared on three open-broiler farms where coccidiosis is prevalent. The vaccine's effectiveness after vaccination of 1-day-old chicks was monitored using three parameters (lesion score, fecal oocyst shedding, and production index, PI) in nine trials performed three times on each farm. Lesion scores were confirmed in three different areas of the intestine because the vaccine contained four Eimeria species. The average lesion scores were 0.36 to 0.64 in the duodenal region, 0.30 to 0.39 in the jejuno-ileal region, and 0.18 to 0.39 in the cecal region. The average fecal oocyst shedding rate ranged from 19,766 to 100,100 oocysts per gram, showing large variations depending on farms and buildings within the farm. Compared with the PI of the previous 9–10 trials on each farm, the PI increased by 2.45 to 23.55. Because of the potential for perturbation of the fecal microbiota by live coccidiosis vaccines, the fecal microbiota was investigated using 16S rRNA microbial profiling. Although the β-diversity was significantly different in distribution and relative abundance among farms (PERMANOVA, pseudo-F = 4.863, p = 0.009), a Kyoto Encyclopedia of Genes and Genomes pathway analysis found no significant bacterial invasion of the epithelial cell pathway across farms. This large-scale field trial of a live Eimeria vaccine indicates that coccidiosis vaccines can have meaningful effects on the poultry industry and could be used as an alternative to the prophylactic use of anticoccidial drugs under field conditions. [ABSTRACT FROM AUTHOR]

Saline acid sulphate soils are commonly ameliorated using traditional amendments like lime and cow manure. Biochar, derived from crop residues, is another potential remedy for this type of soil. Their combined use may create synergistic effects, necessitating further investigation. This study aims to assess the combined impacts of biochar with traditional amendments on soil quality, properties and rice yield. A field experiment was established with six treatments: no‐amendment (control), lime, cow manure, biochar, combined lime and biochar, and combined cow manure and biochar with rice (Oryza sativa) planted in four replicates. The study revealed that the effects of these amendments on soil properties were driven by their inherent characteristics and secondary processes, such as neutralization. Combining biochar with lime significantly increased soil pH (6.2), and exchangeable calcium (648.6 cmol(+) kg−1), while reducing exchangeable aluminium (11.83 cmol(+) kg−1) and iron (37.5 cmol(+) kg−1), compared to the control. Meanwhile, combining biochar with cow manure notably enhanced Mehlich‐1 phosphorous (3.4 mg kg−1), organic carbon (4.99%), ammonium (27.0 mg kg−1) and cation exchange capacity (17.2 cmol(+) kg−1). Biochar combined with cow manure exhibited greater synergetic effects on soil quality than when combined with lime. Consequently, these combinations improved the soil quality index, which exhibited a strong correlation with rice yield and biomass when its value was below 0.4. This finding indicates that these combinations exhibit insignificant synergistic effects on rice yield and growth. Further research is needed to elucidate these findings and explore the optimal application rates concerning soil properties for improved management practices. [ABSTRACT FROM AUTHOR]

In the modern era of the Internet of Things (IoT), especially with the rapid development of quantum computers, the implementation of postquantum cryptography algorithms in numerous terminals allows them to defend against potential future quantum attack threats. Lattice-based cryptography can withstand quantum computing attacks, making it a viable substitute for the currently prevalent classical public-key cryptography technique. However, the algorithm's significant time complexity places a substantial computational burden on the already resource-limited chip in the IoT terminal. In lattice-based cryptography algorithms, the polynomial multiplication on the finite field is well known as the most time-consuming process. Therefore, investigations into efficient methods for calculating polynomial multiplication are essential for adopting these quantum-resistant lattice-based algorithms on a low-profile IoT terminal. Number theoretic transform (NTT), a variant of fast Fourier transform (FFT), is a technique widely employed to accelerate polynomial multiplication on the finite field to achieve a subquadratic time complexity. This study presents an efficient FPGA-based implementation of number theoretic transform for the CRYSTAL Kyber, a lattice-based public-key cryptography algorithm. Our hybrid design, which supports both forward and inverse NTT, is able run at high frequencies up to 417 MHz on a low-profile Artix7-XC7A100T and achieve a low latency of 1.10 μ s while achieving state-of-the-art hardware efficiency, consuming only 541-LUTs, 680 FFs, and four 18 Kb BRAMs. This is made possible thanks to the newly proposed multilevel pipeline butterfly unit architecture in combination with employing an effective coefficient accessing pattern. [ABSTRACT FROM AUTHOR]

Antimicrobial resistance (AMR) is a growing public health crisis that requires innovative solutions. Current susceptibility testing approaches limit our ability to rapidly distinguish between antimicrobial-susceptible and -resistant organisms. Salmonella Typhimurium (S. Typhimurium) is an enteric pathogen responsible for severe gastrointestinal illness and invasive disease. Despite widespread resistance, ciprofloxacin remains a common treatment for Salmonella infections, particularly in lower-resource settings, where the drug is given empirically. Here, we exploit high-content imaging to generate deep phenotyping of S. Typhimurium isolates longitudinally exposed to increasing concentrations of ciprofloxacin. We apply machine learning algorithms to the imaging data and demonstrate that individual isolates display distinct growth and morphological characteristics that cluster by time point and susceptibility to ciprofloxacin, which occur independently of ciprofloxacin exposure. Using a further set of S. Typhimurium clinical isolates, we find that machine learning classifiers can accurately predict ciprofloxacin susceptibility without exposure to it or any prior knowledge of resistance phenotype. These results demonstrate the principle of using high-content imaging with machine learning algorithms to predict drug susceptibility of clinical bacterial isolates. This technique may be an important tool in understanding the morphological impact of antimicrobials on the bacterial cell to identify drugs with new modes of action. In this work, authors combine high resolution imaging and machine learning to infer drug susceptibility in the absence of antimicrobial exposure, with the goal of their method to be transposed to diagnostics and study of the impact of any perturbation on bacterial cells. [ABSTRACT FROM AUTHOR]

This systematic review synthesises the evidence for the effectiveness of a single session of yoga or its components including meditation and breathing techniques in reducing acute stress reactivity in healthy adults. Following the PRISMA guidelines, we searched Medline, EMBASE, Cochrane, CINAHL, and PsycINFO on 30th July 2023 for randomised controlled or crossover trials of yoga components and reporting physiological and/or psychological outcome measure(s) related to stress reactivity. Risk of bias (ROB) was assessed using the Cochrane ROB 2 tool. Data were synthesised narratively. Twenty‐one out of 28 eligible studies (n = 2574) relating to 31 interventions (meditation [n = 22], breathing [n = 4] and yoga [n = 5]) reported outcomes in favour of the intervention. Stress reactivity was reported to be reduced by 71% of studies measuring physiological outcomes and 65% of studies measuring psychological outcomes. These studies show that a single session of yoga components is effective in reducing acute stress reactivity in adults and could be recommended for stress management. Future studies with larger populations and a more equal representation of genders and age groups are warranted. [ABSTRACT FROM AUTHOR]

In a complex network application, a set of nodes might be partitioned into multiple local clusters with different functions, properties, or communication protocols, and the communication is restricted between nodes of the same cluster to maximize efficiency and other security concern. Thus, there has been a rise in network design problems with additional constraints regarding the clustering of vertices, one of them being Clustered Steiner Tree Problem—a variant of the Steiner Tree Problem. Recently, a heuristic-based algorithm was proposed to solve the problem. However, its obtained result is limited in terms of solution quality when applied to the problem in the Euclidean case. This paper proposes a Genetic Algorithm called Shortest-Path Genetic Algorithm for solving the CluSteiner. In the proposal, a permutation-based individual representation that reduces the dimensionality of chromosomes to the number of clusters is devised. The proposed algorithm can solve the problem in both Euclidean and non-Euclidean cases. Experiment results compared to existing works in the literature are analyzed in detail to prove the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Full-text search has a wide range of applications, including tracking systems, computer vision, and natural language processing. Standard methods usually implement a two-phase procedure: indexing and retrieving, with the retrieval performance entirely dependent on the index efficiency. In most cases, the more powerful the index algorithm, the more memory and processing time are required. The amount of time and memory required to index a collection of documents is proportional to its overall size. In this paper, we propose a full-text search hardware implementation without the indexing phase, thus removing the time and memory requirements for indexing. Additionally, we propose an efficient design to leverage the parallel architecture of High Bandwidth Memory (HBM). To our knowledge, few (if not zero) researchers have integrated their full-text search system with an effective data access control on HBM. The functionality of the proposed system is verified on the Xilinx Alveo U50 Field-Programmable Gate Array (FPGA). The experimental results show that our system achieved a throughput of 8 Gigabytes per second, about 6697× speed-up compared to other software-based approaches. [ABSTRACT FROM AUTHOR]

Desertification is a specific land-degrading process, reducing soil productivity and potentially threatening global food security. Therefore, spatially and temporally identifying and mapping desertification-sensitive areas is essential for better management. The current study aimed to (1) assess spatial areas sensitive to desertification and (2) examine the changing tendency of the desertification-sensitive areas over the past 25 years in the provincial Ninh Thuan. The desertification sensitivity index (DSI) was computed based on the Medalus model using 10 quantitative parameters, grouped into the soil, climate, and vegetation quality indexes, computed for the years 1996, 2005, 2010, and 2016. GIS was used to map desertification-sensitive areas associated with five DSI classes. Results showed that classes II and III had the highest area percentage, followed by classes IV and V, and class I. The classes most sensitive to desertification (classes IV and V) covered around 13 to 17%, and classes II and III were 25 to 32% of the total study area, respectively. The coastal areas located in the southeastern parts were more sensitive to desertification than the other parts. Over the four examined periods, the areas of classes IV and V increased while those of classes II and I decreased. These indicated that the study province tended to increase in its desertification sensitivity with a severe increase in the coastal areas over the past 25 years. The key factors involved in these changes could be related the human activities and climate variation, which could be more serious in southeastern areas than in the other areas. [ABSTRACT FROM AUTHOR]

Sarcopenia, a condition characterized by muscle mass decline, is one of the leading health problems in the elderly. This study determined the rate of sarcopenia according to criteria by Asian Working Group for Sarcopenia (AWGS) and related factors in elderly people. A community-based cross-sectional study was conducted in 632 people aged 60 years or over in Ho Chi Minh City. Data were collected through a predefined questionnaire and direct measurement. Sarcopenia was identified based on the Inbody 770 machine and AWGS criteria. The prevalence of sarcopenia was 32.0%. Participants with advanced age, low education, unemployment, low level of family economics and frailty were more likely to have sarcopenia. Among these, frailty had the highest impact on sarcopenia, with significantly higher odds of having sarcopenia found in participants with pre-frailty (OR = 4.80, 95% CI 2.75–8.38, p < 0.001) and frailty (OR = 21.16, 95% CI 8.96–49.97, p < 0.001). In contrast, BMI was inversely associated with sarcopenia. Sarcopenia is prevalent in the Vietnamese elderly. Apart from social demographic characteristics including age, education, employment and family economic status, frailty appeared to be an important risk factor. Early screening, referral, and treatment of sarcopenia among the elderly having a high risk of sarcopenia are recommended. [ABSTRACT FROM AUTHOR]

Aim: To validate algorithms based on electronic health data to identify composition of lines of therapy (LOT) in multiple myeloma (MM). Materials & methods: This study used available electronic health data for selected adults within Henry Ford Health (Michigan, USA) newly diagnosed with MM in 2006–2017. Algorithm performance in this population was verified via chart review. As with prior oncology studies, good performance was defined as positive predictive value (PPV) ≥75%. Results: Accuracy for identifying LOT1 (N = 133) was 85.0%. For the most frequent regimens, accuracy was 92.5–97.7%, PPV 80.6–93.8%, sensitivity 88.2–89.3% and specificity 94.3–99.1%. Algorithm performance decreased in subsequent LOTs, with decreasing sample sizes. Only 19.5% of patients received maintenance therapy during LOT1. Accuracy for identifying maintenance therapy was 85.7%; PPV for the most common maintenance therapy was 73.3%. Conclusion: Algorithms performed well in identifying LOT1 – especially more commonly used regimens – and slightly less well in identifying maintenance therapy therein. Electronic health data helps us understand treatment in the 'real world'. The data has great value in cancer if we can identify the drugs patients get. Yet this is hard in multiple myeloma (MM), where treatment is complex. Algorithms (set of decision rules) to identify drugs can help here. We tested an existing algorithm for identifying 'lines of therapy' (LOT) given to patients with MM. Each LOT included one or more drugs for MM. We also developed and tested a new algorithm for 'maintenance therapy'. This is a treatment given to help maintain the response to the main MM treatment. We tested how well the algorithms identified MM treatments in electronic health data. This data came from Henry Ford Health, a healthcare system in Michigan, USA. Treatments were confirmed by cancer specialists who reviewed medical charts. The LOT algorithm was good at finding the first LOT patients. The maintenance algorithm did a fair job of identifying the most used therapy. Our algorithms could help researchers study the real-world treatment of MM. [ABSTRACT FROM AUTHOR]

Background: Hepatitis B virus (HBV) vaccination in Vietnamese adults remains low and unequally distributed. We conducted a study on HBV-naïve adults living in Ho Chi Minh City, Viet Nam, to determine barriers associated with HBV vaccination uptake after removing the financial barrier by providing free coupons for HBV vaccination. Methods: After being screened for HBsAg, anti-HBs, and anti-HBc, 284 HBV-naïve study participants aged 18 and over (i.e., negative for HBsAg, anti-HBs, and anti-HBc total) were provided free 3-dose HBV vaccine coupons. Next, study participants' receipt of 1st, 2nd, and 3rd doses of HBV vaccine was documented at a pre-specified study healthcare facility, where HBV vaccines were distributed at no cost to the participants. Upon study entry, participants answered questionnaires on sociodemographics, knowledge of HBV and HBV vaccination, and related social and behavioral factors. The proportions of three doses of HBV vaccine uptake and their confidence intervals were analyzed. Associations of HBV vaccine initiation with exposures at study entry were evaluated using modified Poisson regression. Results: 98.9% (281 of 284) of study participants had complete data and were included in the analysis. The proportion of participants obtaining the 1st, 2nd, and 3rd doses of HBV vaccine was 11.7% (95% Confidence Interval [95% CI] 8.0-15.5%), 10.7% (95%CI 7.1–14.3%), and 8.9% (95%CI 5.6–12.2%), respectively. On the other hand, participants were more likely to initiate the 1st dose if they had adequate knowledge of transmission (adjusted relative risk [aRR] = 2.58, 95% CI 1.12–5.92), adequate knowledge of severity (aRR = 6.75, 95%CI 3.38–13.48), and annual health-checking seeking behavior (aRR = 2.04, 95%CI 1.07–3.87). Conclusion: We documented a low HBV vaccination uptake despite incentivization. However, increased vaccine initiation was associated with better HBV knowledge and annual health check-up adherence. When considering expanding HBV vaccination to the general adult population, we should appreciate that HBV knowledge is an independent predictor of vaccine uptake. [ABSTRACT FROM AUTHOR]

Despite their popularity, the construction and operation of hydropower reservoirs pose challenges to water resources. This study investigated the impacts of cascading dams on streamflow in Tanzania's Rufiji River Basin. The SWAT model was developed to represent the entire Rufiji River Basin. The model simulated the streamflow for 41 years, from 1982 to 2022, and developed two main scenarios: with-dam and without-dam. To capture the influence of all dams, the results were emphasized from 2000 to 2022, when all three dams were operating. Calibration and validation were applied at the Rufiji-Stiegler and Kilombero-Swero stations with good performance. The results show that cascading dams annually decrease the streamflow by 1% at Rufiji-Stiegler station. In contrast, individually, the Mtera Dam displayed a 5% decrease while the Kidatu and Kihansi Dams exerted a 1% increase on the annual streamflow downstream at Rufiji-Stiegler. During 2000–2022, the Rufiji River Basin showed an annual reduction in streamflow contribution of 104.97 m3/s. Therefore, the reservoir's operation significantly impacts the downstream streamflow. The findings are expected to guide policymakers, water resource managers, and environmentalists in mitigating potential adverse effects while optimizing the benefits of hydropower generation and water regulation within the region. [ABSTRACT FROM AUTHOR]

In 2008, Vietnam's Prime Minister approved the construction of the 'Hanoi Urban Railway System', a major infrastructure project for the country's capital city. The construction of Line 2A, the first line of this 8‐line railway, took ten years to complete, and was finally inaugurated in November 2021. Spanning 13 km across the city centre, Line 2A encountered more than just construction setbacks, with its reputation tarnished by contractor choice, accidents, and public scepticism over safety and accessibility. Sowing further seeds of doubt in the minds of many Hanoi residents is the fact that two‐thirds of the original financing came from preferential loans from Vietnam's large northern neighbour, conditional on the contractor and key materials being sourced from Vietnam's large, northern neighbour. Moreover, the project is informally categorized as part of Vietnam's large northern neighbour's Belt and Road Initiative. Drawing from conceptual literature regarding infrastructural politics and mobility (in)justice, we analyse how Hanoi residents have experienced and negotiated the construction of this Chinese‐Vietnamese infrastructure project. In particular, we consider how the livelihoods of those directly affected by the railway's operations, namely motorbike taxi‐drivers, have been impacted to date. [ABSTRACT FROM AUTHOR]

Internet-of-things networks consist of multiple sensor devices spread over a wide area. In order to protect the data from unauthorized access and tampering, it is essential to ensure secure communication between the sensor devices and the central server. This security measure aims to guarantee authenticity, confidentiality, and data integrity. Unlike traditional computing systems, sensor node devices are often limited regarding memory and computing power. Lightweight communication protocols, such as LoRaWAN, were introduced to overcome these limitations. However, despite the lightweight feature, the protocol is vulnerable to different types of attacks. This proposal presents a highly secure key establishment protocol that combines two cryptography schemes: Elliptic Curve Qu–Vanstone and signcryption key encapsulation. The protocol provides a method to establish a secure channel that inherits the security properties of the two schemes. Also, it allows for fast rekeying with only one exchange message, significantly reducing the handshake complexity in low-bandwidth communication. In addition, the selected schemes complement each other and share the same mathematical operations in elliptic curve cryptography. Moreover, with the rise of a community-friendly platform like RISC-V, we implemented the protocol on a RISC-V system to evaluate its overheads regarding the cycle count and execution time. [ABSTRACT FROM AUTHOR]