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Information about labor migration plays an important role in planning and implementing socio-economic development policies in each region and for the whole country. This study used data from Vietnam Household Living Standards Survey 2018, 2016 and 2014 conducted by the General Statistics Office of Vietnam to analyze labor migration trends based on demographic characteristics and regional features. Statistical results show that the percentage of labor migrants tended to increase in the period 2014-2018. The results show that demographic factors such as ethnicity, age, gender, marital status, and education had a strong relationship with labor migration flows. In addition, there was a positive correlation between regional characteristics such as unemployment and underemployment and labor migration. By understanding the demographic and regional characteristics that influence specific groups of migrant workers, policymakers can establish target policies to effectively control labor migration flows

Three types of biomass of invasive plants and agrowastes, namely, the wattle bark of Acacia auriculiformis (BA), mimosa (BM), and coffee husks (BC), were converted into biochars through slow pyrolysis and investigated for their ability to remove dyes in water. The properties of the materials were characterized using Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), and Brunauer–Emmett–Teller (BET) analysis. The BET surface area (total pore volume) of BC was 2.62 m2/g (0.007 cm3/g), far below those of BA and BM with 393.15 cm2/g (0.195 m3/g) and 285.53 cm2/g (0.153 m3/g), respectively. The optimal adsorption doses for the removal of methylene blue (MB) were found to be 2, 5, and 5 g/L for BC, BA, and BM, respectively. The suitable pH ranges for MB removal were 6–12 for BA, 7–12 for BC, and 2–10 for BM. The majority of MB (over 83%) was removed in the initial 30 min, followed by a more quasisteady state condition after the removal rate exceeded 90%. The experimental data were fitted with the kinetic models (PFO, PSO, Bangham, IDP), indicating that physicochemical adsorption, pore diffusion process, and multiple stages are the dominant mechanisms for the MB adsorption onto biochars. Finally, BA and BM showed similar adsorption efficiencies, while BC may not be favorable for use as an adsorbent due to its low surface area and low pore volume.

The failure of the centralized water supply system forced XY community to become more dependent on uncertain and unstable water sources. The results of surveying 50 households showed that 89.18% of total households depended on water collected from rivers, which contributed 58.3% of the total water volume used for the domestic demands. The average water volume consumed was 19.5 liters/person/day (l/p/d), and 86.5% of households used more than one source; 13.5% of households collected water only from rivers, and 45.94% of families had rainwater harvesting (RWH) for their activities (domestic water demand); however, RWH only provided 9.9% of total water consumption. In this study, basic methods were applied to calculate the storage tanks necessary to balance the water deficit created by drought months. Three levels of water demand (14, 20, and 30 l/p/d) can be the best choices for RWH; for a higher demand (40 and 60 l/p/d), small roof area (30-40 m2), and many people (six to seven) per family, RWH might be impractical because of unsuitable rainfall or excessively large storage tanks.

This paper deals with H∞ control problem for nonlinear conformable fractional order systems. The authors first derive new sufficient condition for exponential stability of nonlinear conformable fractional order systems based on Lyapunov-like function method for conformable fractional order systems and linear matrix inequalities (LMIs) approach. Then, by introducing a new concepts of H∞ control problem for nonlinear conformable fractional order systems, the authors study H∞ performance analysis and H∞ state feedback controller design problems for the considered systems. In terms of LMIs, a sufficient condition is proposed to ensure the nonlinear conformable fractional order systems are not only exponentially stable, but also satisfy H∞ performance γ. An explicit expression for state feedback controllers is also designed to make the closed-loop system is exponentially stable with H∞ performance γ. Finally, numerical examples are given to illustrate the validity and effectiveness of the proposed results.

Formulation of heterojunction with remarkable high efficiency by utilizing solar light is promising to synchronously overcome energy and environmental crises. In this concern, hexagonal-borocarbonitride (h-BCN) based Z-schemes have proved potential candidates due to their spatially separated oxidation and reduction sites, robust light-harvesting ability, high charge pair migration and separation, and strong redox ability. H-BCN has emerged as a hotspot in the research field as a metal-free photocatalyst with a tunable bandgap range of 0-5.5 eV. The BCN photocatalyst displayed synergistic benefits of both graphene and boron nitride. Herein, the review demonstrates the current state-of-the-art in the Z-scheme photocatalytic application with a special emphasis on the predominant features of their photoactivity. Initially, fundamental aspects and various synthesis techniques are discussed, including thermal polymerization, template-assisted, and template-free methods. Afterward, the reaction mechanism of direct Z-scheme photocatalysts and indirect Z-scheme (all-solid-state) are highlighted. Moreover, the emerging Step-scheme (S-scheme) systems are briefly deliberated to understand the charge transfer pathway mechanism with an induced internal electric field. This review critically aims to comprehensively summarize the photo-redox applications of various h-BCN-based heterojunction photocatalysts including CO

Knowing the effluent quality of treatment systems in advance to enable the design of treatment systems that comply with environmental standards is a realistic strategy. This study aims to develop machine learning - based predictive models for designing the subsurface constructed wetlands (SCW). Data from the SCW literature during the period of 2009–2020 included 618 sets and 10 features. Five algorithms namely, Random forest, Classification and Regression trees, Support vector machines, K-nearest neighbors, and Cubist were compared to determine an optimal algorithm. All nine input features including the influent concentrations, C:N ratio, hydraulic loading rate, height, aeration, flow type, feeding, and filter type were confirmed as relevant features for the predictive algorithms. The comparative result revealed that Cubist is the best algorithm with the lowest RMSE (7.77 and 21.77 mg.L−1 for NH4–N and COD, respectively) corresponding to 84% of the variance in the effluents explained. The coefficient of determination of the Cubist algorithm obtained for NH4–N and COD prediction from the test data were 0.92 and 0.93, respectively. Five case studies of the application of SCW design were also exercised and verified by the prediction model. Finally, a fully developed Cubist algorithm-based design tool for SCW was proposed.

This study evaluated and compared the performance of two vertical flow constructed wetlands (VF) using expanded clay (VF1) and biochar (VF2), of which both are low-cost, eco-friendly, and exhibit potentially high adsorption as compared to conventional filter layers. Both VFs achieved relatively high removal for organic matters (i.e. Biological oxygen demand during 5 days, BOD5) and nitrogen, accounting for 9.5 - 10.5 g.BOD5.m-2.d-1 and 3.5 - 3.6 g.NH4-N.m-2.d-1, respectively. The different filter materials did not exert any significant discrepancy to effluent quality in terms of suspended solids, organic matters and NO3-N (P > 0.05), but they did influence NH4-N effluent as evidenced by the removal rate of that by VF1 and VF2 being of 82.4 ± 5.7 and 84.6 ± 6.4%, respectively (P 2) and the root mean square error (RMSE) of whole fitting data achieved 74.0% and 5.0 mg.L-1, 80.0% and 0.3 mg.L-1, 90.1% and 2.9 mg.L-1, and 48.5% and 0.5 mg.L-1 for BOD5_VF1, NH4-N_VF1, BOD5_VF2, and NH4-N_VF2, respectively.

Experiential learning is a process that begins with practice, experimentation, and then the learner analyzes and reflects on the experience and the results of that experience. This process helps students consolidate knowledge, form and develop new competencies, skills, behaviors, and even new ways of thinking. This approach is considered to have many advantages compared to the traditional educational method. This research is completed based on analysis and assessment from survey activities and understanding the study habits of students, and the teaching methods of elementary, middle and high school teachers in Ho Chi Minh City. Through research, some schools in the city are still teaching and learning by traditional methods, the experiential activities alternating with classroom lessons are still rather new. Most of the students feel quite boring and monotonous when every day when they come to class, they listen to lectures, copy lessons, return lessons without any experiential activities. The inclusion of practical activities in the above lessons is very necessary to change the atmosphere in the classroom as well as help students to absorb knowledge in an intuitive and vivid way. And this research shows the benefits of practical experiences for learning and teaching in schools today. Methods of face-to-face interviews and questionnaires were used and then analyzed using a fivepoint Likert scale. The research results confirm the role of experiential teaching and clarify the question of how to help improve the quality of teaching in today's smart and modern society.

The failure of the centralized water supply system forced XY community to become more dependent on uncertain and unstable water sources. The results of surveying 50 households showed that 89.18% of total households depended on water collected from rivers, which contributed 58.3% of the total water volume used for the domestic demands. The average water volume consumed was 19.5 liters/person/day (l/p/d), and 86.5% of households used more than one source; 13.5% of households collected water only from rivers, and 45.94% of families had rainwater harvesting (RWH) for their activities (domestic water demand); however, RWH only provided 9.9% of total water consumption. In this study, basic methods were applied to calculate the storage tanks necessary to balance the water deficit created by drought months. Three levels of water demand (14, 20, and 30 l/p/d) can be the best choices for RWH; for a higher demand (40 and 60 l/p/d), small roof area (30-40 m

The increasing accumulation of pharmaceuticals in aquatic ecosystems could impair freshwater quality and threaten human health. Despite the adsorption of pharmaceuticals on biochars is one of the most cost-effective and eco-friendly removal methods, the wide variation of experimental designs and research aims among previous studies pose significant challenge in selecting biochar for optimal removal. In this work, literature data of 1033 sets with 21 variables collected from 267 papers over ten years (2010–2020) covering 19 pharmaceuticals onto 88 biochars were assessed by different machine learning (ML) algorithms i.e., Linear regression model (LM), Feed-forward neural networks (NNET), Deep neutral networks (DNN), Cubist, K-nearest neighbor (KNN), and Random forest (RF), to predict equilibrium adsorption capacity (Qe) and explore adsorption mechanisms. LM showed the best performance on ranking importance of input variables. Except for initial concentration of pharmaceuticals, Qe was strongly governed by biochars' properties including specific surface area (BET), pore volume (PV), and pore structure (PS) rather than pharmaceuticals’ properties and experimental conditions. The most accurate model for estimating Qe was achieved by Cubist, followed by KNN, RF, KNN, NNET and LM. The generalization ability was observed by the tuned Cubist with 26 rules for the prediction of the unseen data. This study not only provides an insightful evidence for data-based adsorption mechanisms of pharmaceuticals on biochars, but also offers a potential method to accurately predict the biochar adsorption performance without conducting any experiments, which will be of high interests in practice in terms of water/wastewater treatment using biochars.

Anionic Congo red dye (CR) is not effectively removed by conventional adsorbents. Three novel biochars derived from agro-waste (Acacia auriculiformis), modified with metal salts of FeCl3, AlCl3, and CaCl2 at 500 °C pyrolysis have been developed to enhance CR treatment. These biochars revealed significant differences in effluents compared to BC, which satisfied initial research expectations (P

Subsurface constructed wetland (SCW) appears to be an economical and environmental-friendly practice to treat nitrogen-enriched (waste) water. Nevertheless, the removal mechanisms in SCW are complicated and rather time-consuming to conduct and assessment the efficiency of new experiments. This work mined data from literature and developed the machine learning models to elucidate the effect of influent inputs and predict ammonium removal rate (ARR) in SCW treatment. 755 sets and 11 attributes were applied in four modeled algorithms, including Random forest, Cubist, Support vector machines, and K-nearest neighbors. Six out of ten input features including ammonium (NH4), total nitrogen (TN), hydraulic loading rate (HLR), the filter height (i.e., Height), aeration mode (i.e., Aeration), and types of inlet feeding (i.e., Feeding) have posed pronounced influences on the ARR. The Cubist algorithm appears the most optimal model showing the lowest RMSE i.e., 0.974 and the highest R 2 i.e., 0.957. The contribution of variables followed the order of NH4, HLR, TN, Aeration, Height and Feeding corresponding to 97, 93, 71, 49, 34, and 34%, respectively. The generalization ability to forecast ARR using testing data achieved the R 2 of 0.970 and the RMSE of 1.140 g/m 2 d, indicating that Cubist is a reliable tool for ARR prediction. User interface and web tool of final predictive model are provided to facilitate the application for designing and developing SCW system in real practice.

Pham, Thai-Hong, Nguyen, Thi Huyen, Constant, Jerome (2019): First record of the cicadas genus Orientopsaltria Kato, 1944 (Hemiptera: Cicadidae) from Vietnam, with description of one new species. Zootaxa 4603 (3): 575-582, DOI: https://doi.org/10.11646/zootaxa.4603.3.10

This study investigates the effect of cultural distance on global bank linkages using country-pair data for the period 1990–2013. We followed Schwartz (2006) to measure cultural distance, and employed the number of bank pairs involved in cross-border syndicated lending from the source to target countries as a measure of bank linkages. We found that cultural distance has a negative association with bank linkages. This effect is stronger in countries featuring higher informational asymmetries, as represented by weaker institutions, higher uncertainty, or revolution shocks. Our results hold even when employing alternative measures of bank linkages and cultural distance, and when considering the potential endogeneity of cultural distance.

International audience; The primary purpose of this study is to measure the technical efficiency of 30 doctorategranting universities, the universities or the higher education institutes with PhD training programs, in Vietnam, applying the sensitivity analysis of data envelopment analysis (DEA). The study uses eight sets of input-output specifications using the replacement as well as aggregation/disaggregation of variables. The measurement results allow us to examine the sensitivity of the efficiency of these universities with the sets of variables. The findings also show the impact of variables on their efficiency and its “sustainability”.

Recently, thanks to the advancement in SiC process technology, the deep trench termination (DT2) technique becomes an appropriate choice for future high voltage SiC power device. This technique termination is based on the use of a wide and deep trench, which is filled by a dielectric and associated with a field plate. DT2 technique increases the breakdown voltage (VBR) to a value near to the ideal one that can be obtained in a plan case; and at the same time, reduces drastically the chip area comparing to the previous conventional techniques. In this work, the DT2 used for a 3 kV 4H-SiC bipolar vertical diode is presented. Simulations using TCAD SENTAURUS software show that a maximum breakdown voltage of 3286 V at room temperature can be achieved with a deep trench of 20μm corresponding to 98 % of a parallel plane breakdown voltage for the drift layer of 18 μm. Those simulations also point out the important impact of the structure of the trench; the dielectric critical electric filled (Ec), the permittivity (εr) of the dielectric filled, etching defects as microtrench, fixed charges at the interfaces...on the VBR of power device.

The mechanism of lactamization of corresponding lactones was investigated by means of gas chromatography and synthesis of possible intermediates as references. Lactones react with amines via the amino acid with subsequent elimination of water to the corresponding lactams. In the first step, also hydroxyamides are in equilibrium with the lactones and amines, respectively, which are not able to form the amide though. This mechanism opens a new approach for the synthesis of Nβ-disubstituted tryptamines.

Nd 10.5 Fe 83.5−x Ga x B 6 (x=1.5, 3 and 4.5) ribbons were prepared by melt-spinning method with various wheel speeds from 5 to 40 m s −1. Strong crystallographic texture with c-axis of Nd 2 Fe 14 B crystallites along normal of the ribbon surface was observed. The texture degree can be enhanced by decreasing the quenching rate during solidification of the melt and by increasing the concentration of Ga. Preferred orientation of the nanocrystallites with their size of 10–30 nm is obtained not only by controlling the quenching rate of the melt during solidification but also by appropriately annealing the over-quenched ribbons. The texture of microstructure clearly affects magnetic anisotropy of the ribbons. With increasing concentration of Ga, the magnetic anisotropy of the ribbons is considerably increased. The coercivity above 6.5 kOe and maximum energy products larger than 15 MGOe can be achieved on the ribbons with Ga-concentration of 1.5%.

In this paper, we present the results of an investigation of the influence of fabrication conditions on the structure and magnetic properties of Nd 10.5−x Fe 83.5−y Co x Nb y B 6 (x=0–6; y=1.5–3) nanocomposites prepared by melt-spinning combined with annealing. By changing the quenching rate (by varying the tangential velocity of the copper wheel from 10 m s −1 to 40 m s −1), one can select a suitable velocity to obtain an alloy that has good, hard magnetic behavior without annealing. However, the hard magnetic behavior of the alloy is better and more stable when the alloy is quenched at a high rate to create an amorphous state and subsequently annealed in the range of 650–800 °C for 10 min. The results also show that the Co concentration has an important effect on the structure and magnetic properties of the alloys.