Nowadays, the world is moving towards green energy vehicles and electric vehicles (EVs) are one of the chosen solutions. Vehicle-to-grid (V2G) technology is gradually gaining attention to support issues of performance optimization, energy fluctuations, reducing grid operating costs and bringing optimal efficiency to owners. Along with the rapid increase in the number of EVs, the deployment of effective electric vehicle charging station (EVCS) infrastructure is desirable. However, improper installation can cause many negative impacts on the grid and vice versa, especially EVCS applying V2G charging and discharging techniques. In this study, we propose a computational model to determine the optimal location and size of EVCS applying V2G technique in a distribution network integrating distributed generation sources (DG) with the goal of minimizing active power loss, using an improved method combining the firefly algorithm with the quantum-inspired evolutionary algorithm (QBFA) to find solutions for the problem. The solution results are simulated on a 33-node IEEE standard distribution network using Matlab software and compared with the original FA algorithm to evaluate and propose computational solutions to develop the EVCS system infrastructure in practice.

Subgrade improvement applications have extensively investigated the economic and environmental advantages of utilizing recycled concrete aggregate (RCA) waste. This solution has been widely studied in recent decades. Previous studies focus on the effect of  RCA content while RCA particle size impact on the strength of Soil-Recycle Concrete Aggregates (SRCA) mixture is less investigated. This study presents the findings of the relationship between different sizes of recycled concrete aggregate (RCA) particles and certain characteristics of soil-cement recycled concrete aggregate (SRCA) mixtures. The test results showed that adding RCA with cement to unstabilized soil significantly improved its stress-strain behavior. Incorporating larger RCA particle sizes into unstabilized soil reduced the optimum moisture content (OMC) and increased the maximum dry density (MDD). Conversely, using finer RCA particle sizes in soil mixtures increased the compressive strength compared to larger RCA particles. This blend of RCA-stabilized expansive soil is suitable for subgrade improvement applications, such as building low-traffic volume roads and ensuring embankment stability.

A bimetallic FeCo-ZIFs was successfully synthesized by solvothermal method and determined by various techniques such as powder X-ray diffraction (PXRD), energy – dispersive X-ray spectroscopy (EDX), scanning electron microscope (SEM), Fourier – transform infrared spectroscopy (FT – IR), thermo – gravimetric analysis (TGA) and nitrogen absorption ability. The obtained FeCo-ZIFs was used as an efficient catalyst for removing Ciprofloxacin in water. It showed that the decomposition efficiency of Ciprofloxacin reached 92.1% with a weight of 0.4 g/L of FeCo-ZIFs, combined with 0.3 g/L of potassium peroxydisulfate for 30 min at room temperature. According to research, this is the first time FeCo-ZIFs was applied to treat Ciprofloxacin.

This study investigated the effectiveness of Trichoderma spp. in decomposing watermelon rind and producing bio-organic fertilizer. Response Surface Methodology (RSM) in conjunction with Central Composite Design (CCD) was employed to optimize the cultivation conditions for Brassica juncea using the bio-organic fertilizer made from watermelon rind composted with Trichoderma spp. The results indicate that Trichoderma spp. significantly accelerates the decomposition of watermelon rind and enhances the quality of the resulting bio-organic fertilizer. Composting duration and fertilization rate notably impact the growth parameters, specifically the length and width of Brassica juncea leaves, while the concentration of microbial inoculants does not have a significant effect. Microbial analysis showed that the levels of Coliform, E. coli, and Salmonella in the bio-organic fertilizers were below the regulatory limits specified by ND 108/2017/ND-CP, with none detected in fertilizers produced with Trichoderma spp. RSM optimization identified the most effective composting conditions as 18 days, a 4 wt.% Trichoderma spp. content, and a 50 v/v% fertilizer volume fraction. A high-accuracy mathematical model was developed to predict plant growth based on these variables, effectively forecasting the impact of composting parameters on crop development.

Peperomia pellucida (L.) Kunth is a valuable herbal plant with numerous medicinal properties, offering potential for the development of herbal products with antioxidant benefits. Extraction is a critical step in the recovery and analysis of bioactive compounds in botanical materials. The judicious selection of extraction methodologies and solvents is important in ensuring the recovery and protection of the biological efficacy of these compounds, thereby facilitating the standardization of herbal products. This study investigates the influence of solvent on the yield, chemical composition, and antioxidative activity of P. Pellucida seed extract. The results underscore a propensity towards maximal yield with ethanol employment. Furthermore, all extracts manifest a moderate antioxidative capacity, with the ethyl acetate extract particularly demonstrating heightened activity. Dill apiol is identified as the predominant constituent in all extracts, constituting up to 83% of the composition. The study's findings suggest the promising potential of P. Pellucida seed extract as a valuable source of antioxidants, paving the way for the creation of beneficial herbal products

These days, wind energy plays an increasingly crucial role in the energy sector, posing challenges in its management and operation. Given the current upgrade of Vietnam's 500kV grid infrastructure, wind farms are concentrated in specific regions. This concentration can lead to significant power influxes into the grid at certain times, causing grid overload. Hence, the National Load Dispatch Center is currently regulating power generation based on forecasted data from generating units. Therefore, short-term power forecasting for wind farms is crucial to mitigate grid overload. This article proposes a short-term forecast of active power in wind farm using model based on Artificial Neural Network on Matlab platform, considering the impact of power regulation on the grid. The model was tested using real data from the Ia Pết Đăk Đoa 1 wind farm in Gia Lai province. Time forecast with 15-minute intervals for the next 4 hours. The collected results show the superiority of the method in forecasting with low errors and save calculation time.

This study was conducted to find a facile method for preparing dicalcium phosphate anhydrous (DCPA) from the bones of Nile Tilapia, recovered from a by-product of the fillet process. The by-product containing bones of the Nile Tilapia collected from a local factory was stewed in boiling water and treated with NaOH solution to remove organic impurities to obtained bones of Tilapia. The pre-treated bones were then calcined and ground to a fine powder before converting to dicalcium phosphate anhydrous. The factors affecting the yield of DCPA such as precipitation pH, reaction temperature, and reaction time were investigated. Modern analytical methods such as XRD, SEM, XRF, and TGA were employed to characterize the DCPA. The DCPA product with high crystallinity (> 98.5%) with particle sizes ranging from 1 to 3 μm was obtained at pH 5, 90 min reaction, and 80°C. This study showed a facile and viable method for producing dicalcium phosphate anhydrous from the bones of Nile Tilapia.

Purple passion fruit has been popularly planted in Vietnam and its peels are considered by-products or agricultural wastes after processing, which could cause environmental issues. Noticeably, these peels contain some valuable components with high bioactivities and applicability like anthocyanins (natural colorants) and pectin. Therefore, this work proposed a process for sequential recycling of anthocyanins and pectin from purple passion fruit waste, in which anthocyanin extraction conditions and their bioactivity by ultrasound-assisted solvent extraction were studied and the characteristics of the obtained pectin were analyzed. The studied results showed that approximately 95% anthocyanins (125.4 mg/100g dried peels) were extracted under the best conditions like 80% ethanol (v/v), 1:25 (g/mL) solid/liquid ratio, 40oC incubation temperature, and 10 min sonication time. The findings demonstrated the antioxidant and cytotoxic activity of KB epithelial cells of the anthocyanin extract. Besides, 7.47% of pectin from the residues after extraction anthocyanins were extracted by citric acid with pH 2 at 87oC for 90 min. The pectin has 68.34 % purity, and 57.14% of DE, and FT-IR spectra confirmed its structure. This study can be utilized to recover useful components from purple passion fruit peel waste, improving the fruit’s worth and reducing the environmental impacts of its peels.

The current study investigates the influences of cutting parameters (cutting speed, feed rate, and depth of cut) on the surface roughness during turning C45 steel using CNC QUICK TURN 150 SG  (Mazak, Japan) with carbide inserts WNMG431PP CA525 (Kyocera Precision Tools TAC08616). The experiment design was based on the Taguchi method. The results show that the feed rate significantly influences surface roughness; the cutting velocity is second in order, and the depth of cut is the weakest influence parameter on the surface roughness. The regression equation was proposed to predict the surface roughness and its determination coefficient ( ) of 0.9985. The prediction given by the proposed models is compared to the experiment. The mean absolute error and the mean square error values are 6.73% and 0.85%. Hence, the model is reliable in estimating surface roughness.

The digital soil EC map has been widely applied in agriculture globally due to its ability to explain various soil characteristics. However, the Mekong Delta region lacks comprehensive data on soil EC. This study aims to address this gap by using commonly employed algorithms—K-Nearest Neighbors (KNN), Inverse Distance Weighting (IDW), Kriging interpolation, and Convolutional Neural Networks (CNN)—to map soil EC over an area of approximately 0.14 hectares. Using 228 data samples, the study found that the Gaussian model within Kriging was the most effective for interpolating soil EC, achieving the highest R-squared values (0.792682 with test data and 0.962258 with full data) and the lowest RMSE values (0.048951 with test data and 0.021987 with full data). Additionally, GPS data collection using the U-blox ZED-F9P-01B GPS module and U-blox ANN-MB-00 antenna yielded accurate and reliable results under rice field conditions (Q=1). This research provides valuable insights into soil management and agricultural practices in the Mekong Delta.

Coffee is one of the most consumed drinks, which releases large amounts of used coffee grounds (UCG), causing environmental problems. Thus, UCG was re-used in combination with bottom ash (BA) as fine aggregates in making alkali-activated non-load-bearing lightweight composites (ANLC) in this study. To evaluate the effect of UCG on the properties of ANLC, seven ANLC mixtures with UCG/BA ratios of 0/100, 5/95, 10/90, 15/85, 20/80, 25/75, and 30/70 were prepared. The experimental results showed that the properties of ANLC were influenced significantly with UCG contents. Indeed, an increase in UCG content led to a decrease in dry density, strength, and drying shrinkage while increasing the water absorption of the ANLC. Correlations among properties of ANLC were established and the potential applications of ANLC in real practice were also suggested, proving that the ANLC produced in this study could be applied for non-load-bearing elements. Among the mixtures, the 28-day ANLC specimen containing 5% UCG exhibited the highest flexural and compressive strengths of 7.12 MPa and 39.4 MPa, respectively, and the lowest water absorption of 10.29% with the relatively low dry density of 1671 kg/m3­, indicating the feasibility of using UCG as fine aggregate in the production and application of ANLC.

The three-dimensional hydraulic model Flow-3D was used to simulate the flow velocity in the Cai Khe channel when operating the gates of the Cai Khe barrier. Primary and secondary data were collected to build, calibrate, and validate the model. The NSE coefficient for calibration and validation cases were 0.74 and 0.61, respectively, indicating the reliability of the model. The case of operating the gate to discharge pollutants and create a unidirectional flow with a water level difference between the field and the river of 1,94 meters was chosen to check for potential erosion. The simulation results showed that at profiles 1 and 2 (located 10 meters and 60 meters from the center of the sluice towards the river, respectively), the average flow velocities were 2,97 m/s and 4,99 m/s, respectively, which are greater than the allowable non-erosive velocity (vx = 0,19 – 0,26 m/s). Therefore, the riverbed needs to be reinforced to prevent erosion when operating the sluice gates.

The purpose of this study was to investigate the effects of different particle sizes and contents of limestone powder (LSP) on the compressive strength and workability of ordinary Portland cement (OPC) paste. Three types of limestone with different specific surface areas (SSA) were used to replace OPC in proportions ranging from 0 to 40%. Both compressive strength and flow experiments were conducted, and the results were analyzed using regression analysis. The findings were further corroborated by X-ray diffraction analysis. The experimental results show that the higher the SSA and the smaller the particle size, the worse the workability. Notably, when the content of LSP is less than 20%, the influence of LSP particle size on compressive strength and workability is not significant. However, when it exceeds 20%, the greater the SSA of LSP, the smaller the particle size, and the smaller the reduction in compressive strength.

This study aims to investigate the cutting quality of a thin laminated core using a non-oriented electrical steel sheet by a pulsed Nd: YAG laser. The influences of three process parameters, laser power (P), scanning speed (v), and pulse repetition rate (f), on the three cutting qualities, cutting time (TC), height of recast layer (H), and kerf surface roughness (Sa), are examined. Each process parameter is elected with three levels and total of 27 experimental datasets are achieved. The preference selection index method is based on the experimental results to determine the best cutting quality through multi-qualities. The best quality is found at No.23 with process parameters of P = 18 W, v = 600 mm/s, and f = 30 kHz for qualities of TC = 20.6 s, H = 20.2 µm, and Sa = 2.4 µm.