Explore the vast range of titles available.

PurposeThe purpose of this paper is to investigate the impact of leadership styles on different organizational outcomes and value structure such as: overall business performance, working style, motivation and trust of employees, management efficiency and corporate culture in the context of Vietnamese small and medium enterprises (SMEs).Design/methodology/approachThe authors perform a qualitative analysis and gather data by conducting conversational semi-structured interviews with 51 SME managers from different industries. Data were analyzed using a step-by-step approach following Creswell.FindingsThe study explores the effects of leadership styles on various organizational outcomes. Given the features of SMEs, it sheds light on the significance of leadership styles in changing work environment, increasing staff retention, and promoting the viability of SMEs. It also discusses the selection of leadership styles in accordance with Vietnamese culture.Practical implicationsThis study has practical implications on human resource management in the context of SMEs. SME managers, training providers and support agencies may utilize the research outcomes to raise the awareness of SMEs leaders. Based on the research findings, appropriate training programs should be developed to assist managers in tackling major problems.Originality/valueAlthough several previous studies have tried to investigate the influence of leadership styles on organizational outcomes, this is the first research to explore the topic in the context of SMEs and in conjunction with the Vietnamese culture.

Soil phosphorus is heavily restricted by soil acidification and salinization. There is a need to determine a biological solution for this issue to replace the overuse of chemical phosphorus fertilizer that aggravates adverse conditions, such as salinity, acidity, and metallic toxicity. Therefore, this study aimed at determining the phosphorus dynamics in terms of the soil, growth, and yield of rice under the supplementation of phosphate (P)-solubilizing purple nonsulfur bacteria (PNSB), Cereibacter sphaeroides ST16 and ST26, in salinized soil collected from An Bien district, Kien Giang province, Vietnam, under greenhouse conditions. The experiment followed a completely randomized block design with two factors and four replications. In particular, the reduced percentages of P fertilizer (A) were 0%, 25%, 50%, 75%, and 100% P. The supplementations of C. sphaeroides strains (B) were the negative control, ST16, ST26, and a mixture of both ST16 and ST26. The results showed that supplying the C. sphaeroides ST16 and ST26 reduced the insoluble P content by 10.1–10.6% Fe-P, 10.3–12.2% Ca-P, and 12.7–43.1% Al-P and increased available P by 8.33–27.8%, leading to total P uptake in plants increasing by 29.4–56.1%. The C. sphaeroides strains also reduced soil Na+. Therefore, supplying the C. sphaeroides strains increased the rice growth and yield components of rice, leading to a greater yield of 26.5–51.0%. Supplying each strain of ST16 and ST26 reduced 50–100% P fertilizer as recommended. Ultimately, inoculation of the bacterial mixture allowed a reduction by 100% P fertilizer percentage as recommended but the yield remained the still.

An integrated energy system (IES) can alleviate energy crises, promote multi‐energy complementarity, and enhance finer‐grained energy development. Nuclear power is clean and efficient, mainly when using small modular reactors (SMRs), which increase power generation, improve system flexibility, and promote a low‐carbon economy. This paper proposes a bi‐layer scheduling framework for a SMR‐connected integrated energy system (SMR‐IES) to optimize operating cost, carbon emissions, and average demand‐side flexibility during the peak period index. The first layer optimizes the multi‐objective operation of SMR‐IES using a hybrid of the improved augmented ε ‐constraint method and the modified technique for order preference by similarity to the ideal solution approach. This framework incorporates a ladder‐type carbon trading mechanism alongside a multi‐energy demand response program with a comprehensive user satisfaction index to account for carbon emissions throughout the entire process while enhancing demand‐side flexibility for the SMR‐IES. The second layer handles uncertainties using the information gap decision theory approach. The proposed method can determine a scheduling operation with predicted renewable energy sources, load, and energy price errors while keeping optimal objective values within acceptable bounds not higher than 35% of the nominal optimal values ( β = 0.35). Moreover, the proposed method offers a more efficient approach to managing uncertainty than stochastic and robust optimization methods.

In this paper, the results of making a reduced graphene oxide cathode electrode with Cu2S nanoparticles are shown so that it can be used as a counter electrode in quantum dot solar cells to replace other counter electrodes. An rGO-Cu2S paste obtained by hydrolysis was scanned onto the surface of the fluorine-doped tin oxide (FTO) conductive substrate when bound to Cu2S nano by a screen-printing process, then calcined at 350 °C to crystallize the film. Following calcination, the film was examined for structure using energy-dispersive X-ray (EDX) and X-ray diffraction (XRD) spectroscopy, as well as for type and particle size using scanning and transmission electron microscopy and transmission electron microscopy, respectively. Mott-schottky measurement is used to determine the semiconductor and carrier concentrations in the film, and an electrochemical device is used to assess the electrodes redox capacity in a polysulfide electrolyte solution. The operability of the rGO-Cu2S cathode at the peak of the current density in the C-V curve was 24 mA/cm2, a 30-fold increase compared to that of the Cu2S electrode. This result shows that the efficiency, Voc, FF, Jsc are 4.92%, 0.525 V, 0.418, and 22.4 mA/cm2, respectively.

This study was conducted to evaluate the effectiveness of phosphorus P-solubilizing purple nonsulfur bacteria, Cereibacter sphaeroides ST16 and ST26, on improving soil quality, nutrient uptake, growth, and yield of rice farmed in salinized soil in the rice-shrimp system. A two-factor experiment was arranged in completely randomized blocks with four replications. Factor (A) represented P fertilizing rates, including 0%, 25%, 50%, 75%, and 100% P as the recommendation. Factor (B) consisted of the negative control (NC), a strain of C. sphaeroides ST16, C. sphaeroides ST26, and the mixture of ST16 and ST26. The results indicated that using the ST16-ST26 mixture decreased Na+ concentration by 15.2–21.1%, improved soluble P content by 11.5–21.0%, and reduced contents of Fe-P by 14.8–15.1%, Ca-P by 6.18–22.5%, and Al-P by 4.55–8.58%. Additionally, a single or the mixture application increased the total P uptake by 16.7–37.0% and decreased the total Na uptake by 6.12–17.2%, as compared with NC. In addition, fertilizing 100% P developed rice grain yield by 26.1–34.7% as compared with the 0% P applied. Simultaneously, using the ST16-ST26 mixture elevated the rice grain yield by 10.7–25.0%, chlorophyll content, and lowered proline content as compared with NC.

Background Hepatocellular carcinoma (HCC) is a common cancer, especially in the Association of Southeast Asian Nations (ASEAN) region, where the prevalence of hepatitis virus infection is high. Liver resection is a potentially curative and popular therapy for HCC. Laparoscopic surgery using minimally invasive techniques potentially brings benefits to patients who need liver resection for HCC. This study aimed to evaluate the effectiveness, safety, and benefits of laparoscopic liver resection for HCC with long-term follow-up evaluation. Methods This cohort study with 5-year results of total laparoscopic hepatectomy for HCC was conducted in one center. Patients with HCC were selected for laparoscopic liver resection by the same team. The operation also was performed by one team of surgeons. The follow-up protocol was similar to that for open surgery. The patients were scheduled to return for examination every 2 months after the operation. The data for the patients were collected and analyzed using SPSS software. Results From January 2008 to December 2012, 173 enrolled patients with HCC underwent laparoscopic liver resection. The male-to-female ratio was 3:1. The mean age of the patients was 56 years (range 16–83 years). The follow-up period for 130 patients was 21.6 ± 16.0 months (range 0–60 months). The mean tumor size was 3.73 cm (range 2–10 cm). The stages of HCC according to the Barcelona Clinic Liver Cancer (BCLC) categorization were as follows: 0 (6 %), A1 (59.5 %), A2 (6.9 %), A4 (2.9 %), and B (27.2 %). Four patients required conversion to other techniques (2.3 %) because of the potential for major bleeding and tumor perforation. The types of resection were resection of one segment (segments 2, 3, 4, 5, 6, 7, and 8; 43.8 %), resection of two segments (posterior sector, anterior sector, segments 5 and 6, and left lateral sector; 47.9 %), resection of three segments (left and central liver; 4.7 %), and four segments (right liver; 3.6 %). The mean operation time was 112 ± 56 min (range 30–345 min), and the median blood loss was 100 ml (range 20–1,200 ml). The mean hospital stay was 6.5 ± 2.0 days (range, 3 – 19 days). No perioperative mortality occurred. The overall survival rates were 94.2 % at 1 year, 87 % at 2 years, 72.9 % at 3 years, 72.9 % at 4 years, and 72.9 % at 5 years. The mean overall survival time was 49.7 ± 2.1 months (range 45.5–53.9 months). The disease-free survival rates were 79.1 % at 1 year, 60 % at 2 years, 57 % at 3 years, 52 % at 4 years, and 26.3 % at 5 years. The mean disease-free survival time was 38.9 ± 2.6 months (range 33.9–44.0 months). Conclusion Laparoscopic liver resection for HCC is feasible, safe, and effective, with good oncologic results. Major and anatomic hepatectomy are possible with improved skill and experience. Laparoscopic liver resection is a promising treatment option with minimally invasive benefits for HCC patients.

Data transmission is crucial in the digital age, making robust legal frameworks for data protection and the free flow of information essential. Distinguishing between personal and non-personal data is critical for ensuring regulatory compliance. Roles like controllers and processors define obligations and remedies, ensuring secure and lawful data handling. Based on the analysis of the European Union perspective on the aforementioned aspects, the paper provides implications for Vietnam in addressing the regulatory gaps regarding data-related laws in general and data transmission in particular.

As Convolutional Neural Networks (CNN) have become essential to modern applications such as image classification on social networks or self-driving vehicles, evasion attacks targeting CNNs can lead to damage for users. Therefore, there has been a rising amount of research focusing on defending against evasion attacks. Image denoisers have been used to mitigate the impact of evasion attacks; however, there is not a sufficiently broad view of the use of image denoisers as adversarial defenses in image classification due to a lack of trade-off analysis. Thus, image denoisers' costs, including training time, image reconstruction time, and loss of benign F1 scores of CNN classifiers, are explored in this thesis. Additionally, Emulated Autoencoder (EAE), which is the proposed method of this thesis to optimize trade-offs for high volume classification tasks, is evaluated alongside state-of-the-art image denoisers in the gray-box and white-box threat models. EAE outperforms most image denoisers in both the gray-box and white-box threat models while drastically reducing training and image reconstruction time compared to the state-of-the-art denoisers. As a result, EAE is more appropriate for securing high-volume classification applications of images.

Leadership and leadership styles are considered as decisive factors to the success and failure of small and medium enterprises (SMEs). The objectives of the paper are to identify benefits and drawbacks of applying three major leadership styles, namely autocratic, democratic and laissez-faire styles of Vietnamese SMEs leaders, who are working in various business fields. The qualitative approach was used to explore the perceptions of 51 Vietnamese SME managers, and the N-vivo software was useful in data analysis. The theoretical contribution, therefore, can be seen by the in-depth investigating on the leadership styles from the multi-dimensional viewpoints of SMEs leaders in the culture context of one Asian emerging nation such as Vietnam. The paper is also expected to be useful for SME managers to better understanding leadership styles, in order to adjust and perfect their leadership behaviors for more effective managerial and organizational performance.

Soil salinity caused by climate change associated with rising sea level is considered as one of the most severe natural hazards that has a negative effect on agricultural activities in the coastal areas in most tropical climates. This issue has become more severe and increasingly occurred in the Mekong River Delta of Vietnam. The main objective of this work is to map soil salinity intrusion in Ben Tre province located on the Mekong River Delta of Vietnam using the Sentinel-1 Synthetic Aperture Radar (SAR) C-band data combined with five state-of-the-art machine learning models, Multilayer Perceptron Neural Networks (MLP-NN), Radial Basis Function Neural Networks (RBF-NN), Gaussian Processes (GP), Support Vector Regression (SVR), and Random Forests (RF). For this purpose, 63 soil samples were collected during the field survey conducted from 4–6 April 2018 corresponding to the Sentinel-1 SAR imagery. The performance of the five models was assessed and compared using the root-mean-square error (RMSE), the mean absolute error (MAE), and the correlation coefficient (r). The results revealed that the GP model yielded the highest prediction performance (RMSE = 2.885, MAE = 1.897, and r = 0.808) and outperformed the other machine learning models. We conclude that the advanced machine learning models can be used for mapping soil salinity in the Delta areas; thus, providing a useful tool for assisting farmers and the policy maker in choosing better crop types in the context of climate change.