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Salinity intrusion is a pressing issue in the coastal areas worldwide. It affects the natural environment and causes massive economic loss due to its impacts on the agricultural productivity and food safety. Here, we assessed the salinity intrusion in the Tra Vinh Province, in the Mekong Delta of Vietnam. Landsat 8 OLI image was utilized to derive indices for soil salinity estimate including the single bands, Vegetation Soil Salinity Index (VSSI), Soil Adjusted Vegetation Index (SAVI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Salinity Index (NDSI). Statistical analysis between the electrical conductivity (EC1:5, dS/m) and the environmental indices derived from Landsat 8 OLI image was performed. Results indicated that spectral values of near-infrared (NIR) band and VSSI were better correlated with EC1:5 (r2 = 0.8 and r2 = 0.7, respectively) than the other indices. Comparative results show that soil salinity derived from Landsat 8 was consistent with in situ data with coefficient of determination, R2 = 0.89 and RMSE = 0.96 dS/m for NIR band and R2 = 0.77 and RMSE = 1.27 dS/m for VSSI index. Findings of this study demonstrate that Landsat 8 OLI images reveal a high potential for spatiotemporally monitoring the magnitude of soil salinity at the top soil layer. Outcomes of this study are useful for agricultural activities, planners, and farmers by mapping the soil salinity contamination for better selection of accomodating crop types to reduce economical loss in the context of climate change. Our proposed method that estimates soil salinity using satellite-derived variables can be potentially useful as a fast-approach to detect the soil salinity in the other regions with low cost and considerable accuracy.

This paper investigates the flexural bearing behavior of reinforced concrete beams through experimental analysis and advanced machine learning predictive models. The primary problem centers around understanding how varying compositions of construction materials, particularly the inclusion of recycled aggregates and carbon fiber-reinforced polymer (CFRP), affect the structural performance of concrete beams. Eight beams, including those with natural aggregates, recycled aggregates, fly ash, and CFRP, were tested. The study employs state-of-the-art machine learning frameworks, including Random Forest Regressor (RFR), XGBoost (XGB), and LightGBM (LGBM). The formation of these models involved data acquisition from experiments, preprocessing of key input features (such as rebars area, cement portion, recycled and natural aggregate masses, silica fume, fly ash, compressive strength, and CFRP presence), model selection, and hyperparameter tuning using Pareto optimization. The models were then evaluated using performance metrics like Mean Squared Error (MSE), Mean Absolute Error (MAE), and coefficient of determination (R 2 ). Outputs focus on load-induced deflection and mid-span displacement. With a dataset of 4851 samples, the optimized models demonstrated excellent performance. The experimental results revealed substantial enhancements in both compressive strength and load-bearing capacity, notably observed in beams incorporating 70% recycled aggregate and 10% silica fume. These beams exhibited a remarkable increase in compressive strength of up to 53.03% and a 7% boost in load-bearing capacity compared to those without recycled aggregate. By integrating experimental analysis with advanced computational techniques, this study advances the understanding of eco-friendly construction materials and their performance, shedding light on the intricate interactions between sustainable construction materials and the flexural bearing behavior of beams.

Purpose: This study examines the factors influencing Vietnamese employees' intention to participate in the Voluntary Pension Fund (VPF), with the goal of providing insights into enhancing employee engagement with this financial security mechanism. Design/methodology/approach: A survey was conducted with 320 working employees, followed by Exploratory Factor Analysis (EFA) to identify key factors. An empirical model was then applied to examine the impacts of these factors on employees' participation intentions. Findings: The study identified four significant factors influencing participation intention: the risk protection feature of VPF, the financial security provided by VPF, the expectation of benefits from participating in VPF, and risk perception related to the certainty of receiving benefits from VPF. Research limitations/implications: The findings underscore the need to raise awareness about the benefits of VPF participation among employees and develop effective mechanisms to promote the adoption of VPF in Vietnam, thereby ensuring its effectiveness as a financial security solution. Originality/value: The study offers insight into employees' adoption of voluntary pension schemes. It is also a vital source for policymakers and corporate managers to have appropriate action plans and programs to improve the adoption rate of the Voluntary Pension Fund in Vietnam.

Background. Early prediction of severe dengue could significantly assist patient triage and case management. Methods. We prospectively investigated 7563 children with ≤3 days of fever recruited in the outpatient departments of 6 hospitals in southern Vietnam between 2010 and 2013. The primary endpoint of interest was severe dengue (2009 World Health Organization Guidelines), and predefined risk variables were collected at the time of enrollment to enable prognostic model development. Results. The analysis population comprised 7544 patients, of whom 2060 (27.3%) had laboratory-confirmed dengue; nested among these were 117 (1.5%) severe cases. In the multivariate logistic model, a history of vomiting, lower platelet count, elevated aspartate aminotransferase (AST) level, positivity in the nonstructural protein 1 (NS1) rapid test, and viremia magnitude were all independently associated with severe dengue. The final prognostic model (Early Severe Dengue Identifier [ESDI]) included history of vomiting, platelet count, AST level. and NS1 rapid test status. Conclusions. The ESDI had acceptable performance features (area under the curve = 0.95, sensitivity 87% (95% confidence interval [CI], 80%–92%), specificity 88% (95% CI, 87%–89%), positive predictive value 10% (95% CI, 9%–12%), and negative predictive value of 99% (95% CI, 98%–100%) in the population of all 7563 enrolled children. A score chart, for routine clinical use, was derived from the prognostic model and could improve triage and management of children presenting with fever in dengue-endemic areas.

The pathogenesis of dengue in infants is poorly understood. We postulated that dengue severity in infants would be positively associated with markers of viral burden and that maternally derived, neutralizing anti-dengue antibody would have decayed before the age at which infants with dengue presented to the hospital. In 75 Vietnamese infants with primary dengue, we found significant heterogeneity in viremia and NS1 antigenemia at hospital presentation, and these factors were independent of disease grade or continuous measures of disease severity. Neutralizing antibody titers, predicted in each infant at the time of their illness, suggested that the majority of infants (65%) experienced dengue hemorrhagic fever when the maternally derived neutralizing antibody titer had declined to <1:20. Collectively, these data have important implications for dengue vaccine research because they suggest that viral burden may not solely explain severe dengue in infants and that neutralizing antibody is a reasonable but not absolute marker of protective immunity in infants.

We address the problem of modifying vertex weights of a block graph at minimum total cost so that a predetermined set of p connected vertices becomes a connected p-median on the perturbed block graph. This problem is the so-called inverse connected p-median problem on block graphs. We consider the problem on a block graph with uniform edge lengths under various cost functions, say rectilinear norm, Chebyshev norm, and bottleneck Hamming distance. To solve the problem, we first find an optimality criterion for a set that is a connected p-median. Based on this criterion, we can formulate the problem as a convex or quasiconvex univariate optimization problem. Finally, we develop combinatorial algorithms that solve the problems under the three cost functions in O(nlogn) time, where n is the number of vertices in the underlying block graph.

An autonomous robot case study illustrates the use of the behavior, interaction, priority (BIP) component framework as a unifying semantic model to ensure correctness of essential system design properties.

Pediatric diarrheal disease presents a major public health burden in low- to middle-income countries. The clinical benefits of empirical antimicrobial treatment for diarrhea are unclear in settings that lack reliable diagnostics and have high antimicrobial resistance (AMR). We conducted a prospective multicenter cross-sectional study of pediatric patients hospitalized with diarrhea containing blood and/or mucus in Ho Chi Minh City, Vietnam. Clinical parameters, including disease outcome and treatment, were measured. Shigella, nontyphoidal Salmonella (NTS), and Campylobacter were isolated from fecal samples, and their antimicrobial susceptibility profiles were determined. Statistical analyses, comprising log-rank tests and accelerated failure time models, were performed to assess the effect of antimicrobials on disease outcome. Among 3166 recruited participants (median age 10 months; interquartile range, 6.5-16.7 months), one-third (1096 of 3166) had bloody diarrhea, and 25% (793 of 3166) were culture positive for Shigella, NTS, or Campylobacter. More than 85% of patients (2697 of 3166) were treated with antimicrobials; fluoroquinolones were the most commonly administered antimicrobials. AMR was highly prevalent among the isolated bacteria, including resistance against fluoroquinolones and third-generation cephalosporins. Antimicrobial treatment and multidrug resistance status of the infecting pathogens were found to have no significant effect on outcome. Antimicrobial treatment was significantly associated with an increase in the duration of hospitalization with particular groups of diarrheal diseases. In a setting with high antimicrobial usage and high AMR, our results imply a lack of clinical benefit for treating diarrhea with antimicrobials; adequately powered randomized controlled trials are required to assess the role of antimicrobials for diarrhea.

Based on the Hedge Algebras (HA) methodology, this paper presents a method for managing the trajectory of a delta robot. This technique is easily applied to existing devices in the process control domain. In the proposed control method, the semantically quantitative mapping may replace the verbal values of the fundamental rule in an analogous manner (SQM). Consequently, the basic rule may be represented as a three-dimensional numerical grid with linear interpolations. Compared to the Fuzzy Logic controller, it reduces the controller’s complexity. In addition, when the control strategy is applied in reality, the system’s response time is decreased. The simulation results indicate that the proposed technique is more exact than previous approaches. The experimental results reveal that the proposed technique is effective for robot trajectory tracking difficulties.

This paper introduces a novel method for online 3-D bin packing, which is a strongly NP-hard problem, based on a space splitting and merging technique. In this scenario, the incoming box is unknown and must be immediately packed. The problem has many applications in industries that use manipulators to automate the packing process. The main idea of the approach is to divide the bin into spaces. These spaces are then categorized into one of two types of data structures: main and secondary data structures. Each node in the main data structure holds the information of a space that can be used to fit a new box. Each node in the secondary data structure holds the information of a space that cannot be used to place a box. The search algorithm based on these two data structures reduces the required search effort and simplifies the organizing and editing of the data structure. The experimental results demonstrate that the proposed method can achieve a packed volume ratio of up to 83% in the case of multiple bins being used. The position of a placed box can be found within milliseconds.