Peanut (Arachis hypogaea L.) yield and its components as affected by lime and rice husk ash in An Phu soils, An Giang, Viet Nam

The study of the effects of lime and rice husk ash in peanuts was carried out in winter-spring 2017 inside the dyke at An Phu district, An Giang province, consisted of following experiments: (i) Effects of lime, rice husk ash to Characters in soil. (ii) Effects of lime, rice husk ash on Arsenic and Cadmium uptake of peanuts, (iii) Effects of lime, rice husk ash to Yield and yield components of peanuts. The experiment was carried out with 4 treatments, 4 replications. The results showed that the treatment with lime and rice husk ash combination increased pH and EC in soil; the arsenic and cadminm contents in stems and seeds were lowest (81.0; 27.0 μg/kg and 1.7; 0.18 mg/kg, respectively) and produced the highest average total yield per hectare (7.59 tons) which significantly differed from all other treatments, the lowest yield (4.63 tons) was in the control treatmen

EFFECTS OF SALT STRESS ON PLANT GROWTH AND BIOMASS ALLOCATION IN SOME WETLAND GRASS SPECIES IN THE MEKONG DELTA

Salt stress causes serious damage to many cellular and physiological processes that leads to yield reduction. The study induced salt stress using Hoagland solution added NaCl to evaluate its effects on plant growth and biomass allocation of some wetland grass species in order to identify salt-tolerant species for replacing and/or supplementing rice/grass in rice-shrimp model and salt-affected area in the Mekong Delta. The study also seeks to evaluate the response of leaf chlorophyll (SPAD unit) and proline content in salt-treated plants to varying application of salinity. Typha orientalis, Lepironia articulata, Eleocharis dulcis and Scirpus littoralis were studied in hydroponics condition with four levels of NaCl of 5, 10, 15, 20‰ and the control treatment (without adding NaCl). The experiment was arranged in a completely randomized design with 3 replications. The salt-treated plants showed visually clear responses of inhibited growth under salt stress condition compared to the control plants. Among the four studied species, T. orientalis produced the highest dry shoot biomass (15.5 g DW/plant), while E. dulcis had the lowest value (2.8 g DW/plant). However, only T. orientalis showed significantly decreased in biomass as salinity increased with 9.3 and 4.6 times lower of fresh and dry biomass in plants grown at the salinity level of 20‰ compared to those grown in the control treatment. The other three plant species did not affect by salinity levels. The results indicated that S. littoralis, L. articulata and E. dulcis could tolerate at high salinity of 20‰ (eq. to the EC value in the nutrient solution of 38.0 dS/m) and could be potential candidate to grow in the rice-shrimp model or in the salt-affected soils. 

Machine Learning Models for Inferring the Axial Strength in Short Concrete-Filled Steel Tube Columns Infilled with Various Strength Concrete

Concrete-filled steel tube (CFST) columns are used in the construction industry because of their high strength, ductility, stiffness, and fire resistance. This paper developed machine learning techniques for inferring the axial strength in short CFST columns infilled with various strength concrete. Additive Random Forests (ARF) and Artificial Neural Networks (ANNs) models were developed and tested using large experimental data. These data-driven models enable us to infer the axial strength in CFST columns based on the diameter, the tube thickness, the steel yield stress, concrete strength, column length, and diameter/tube thickness. The analytical results showed that the ARF obtained high accuracy with the 6.39% in mean absolute percentage error (MAPE) and 211.31 kN in mean absolute error (MAE). The ARF outperformed significantly the ANNs with an improvement rate at 84.1% in MAPE and 65.4% in MAE. In comparison with the design codes such as EC4 and AISC, the ARF improved the predictive accuracy with 36.9% in MAPE and 22.3% in MAE. The comparison results confirmed that the ARF was the most effective machine learning model among the investigated approaches. As a contribution, this study proposed a machine learning model for accurately inferring the axial strength in short CFST columns

Linking Ethical Leadership to Employee Creative Performace: The Role of Leader-Member Exchange and Work Engagement

Purpose: The purpose of this research is to investigate the mediating role of leader-member exchange (LMX) and work engagement in the relationship between ethical leadership and creative performance.   Theoretical framework: The study is based on the theoretical foundation that ethical leadership positively influences creative performance. It further posits that this relationship is mediated by both leader-member exchange (LMX) and work engagement.   Design/Methodology/Approach: Data for this study was collected from a Vietnamese service firm, with a sample comprising 78 leaders and 354 employees. The collected data was analyzed using structural equation modeling (SEM) to examine the proposed relationships.   Findings: The findings of the study indicate a significant and positive correlation between ethical leadership and creative performance. Additionally, the study reveals that ethical leadership exerts an influence on both leader-member exchange (LMX) and work engagement, which subsequently enhance employees' demonstration of creativity in their work.   Research, practical & social implications: This research sheds light on the mediating mechanisms through which ethical leadership impacts creative performance. The findings highlight the importance of fostering positive leader-member relationships and promoting work engagement in order to enhance employees' creative behaviors. Practically, the study suggests that organizations should prioritize the development of ethical leadership qualities to foster a creative work environment. Moreover, the research contributes to the broader social implications by emphasizing the significance of ethical leadership in promoting creativity and innovation within organizations.   Originality/Value: This research contributes to the existing literature by examining the mediating role of leader-member exchange and work engagement in the relationship between ethical leadership and creative performance. The study provides valuable insights into the mechanisms through which ethical leaders can enhance creativity in the workplace. The findings of this research contribute to the understanding of the importance of ethical leadership and its impact on organizational outcomes, thereby adding to the originality and value of the study

Serum Granulysin in Differentiation of Stevens-Johnson Syndrome/toxic Epidermal Necrolysis and Erythema Multiforme

BACKGROUND: Stevens-Johnson syndrome (SJS) and toxic epidermal necrolysis (TEN) are acute, life-threatening drug reactions, which lead to massive epidermal necrolysis. Granulysin plays an important role as a key mediator for keratinocyte apoptosis in these conditions. Erythema multiforme (EM) may have skin manifestation similar to SJS/TEN. AIMS: The aim of the study was to compare serum granulysin levels in patients with SJS/TEN and EM as well as to investigate a possible association between serum granulysin levels and the severity of SJS/TEN. METHODS: In total, 48 patients with SJS/TEN, 43 patients with EM, and 20 health controls (HCs) were enrolled. We measured serum granulysin levels using enzyme-linked immunosorbent assay. RESULTS: The average level of serum granulysin in the SJS/TEN patients was 23.0 ng/ml (range 1.2–144.6 ng/ml), significantly higher than that of EM group (20.1 ng/ml; range 8.5–121 ng/ml, p < 0.05) and HCs group (20.8 ng/ml; range 10.1–46.7 ng/ml, p < 0.05). Of 48 SJS/TEN patients, the 25 samples collected <6 days after onset showed higher level of serum granulysin (27.7 ng/ml; range 2.5–144.6 ng/ml) than those collected ≥6 days after onset (17.9 ng/ml; range 1.2–59 ng/ml; p > 0.05). No significant correlation was found between serum granulysin levels and the body surface area affected and the modified-SCORTEN. At the day of re-epithelialization, serum granulysin levels were not different compared with those at the day of hospitalization. CONCLUSIONS: Serum granulysin levels are significantly higher in SJS/TEN group than in EM group. After the onset, serum granulysin levels in patients with SJS/TEN are not a good biomarker to evaluate the severity of the diseases

Exploring Value Co-Destruction Process in Customer Interactions with AI-Powered Mobile Applications

Background: Mobile applications have emerged as important touchpoints for addressing service requests and optimizing human resources. Within the service industry, the integration of artificial intelligence (AI) into these applications has enabled the inference of product demand, provision of personalized service offers, and enhancement of overall firm value. Customers now engage with these apps to stay informed, seek guidance, and make purchases. It is important to recognize that the interactive and human-like qualities of AI can either foster the co-creation of value with customers or potentially lead to the co-destruction of customer value. Although prior research has examined the process of value co-creation, the present study aims to investigate the underlying factors contributing to the value co-destruction process, specifically within AI-powered mobile applications. Method: Our research employs topic modelling and content analysis to examine the value co-destruction process that occurs when customers engage with AI apps. We analyze 7,608 negative reviews obtained from eleven AI apps available on Google Play and App Store AI apps. Results: Our findings reveal six distinct types of value - utilitarian, hedonic, symbolic, social, epistemic, and economic value - that can be co-destroyed during the process. System failure, self-threat and privacy violation are some contributing factors to this value co-destruction process. These values change over time and vary depending on the type of app. Conclusion: Theoretically, our findings extend the concept of value co-destruction in the context of AI apps. We also offer practical recommendations for designing an AI app in a more service-friendly way

The Effect of Awareness on the Behavior of Advertisement on Social Network Basis for Cosmetic Products Line

The study examines the factors affecting the perception and interaction behavior with advertising cosmetic products. The authors used SPSS and Smart PLS software to conduct statistics and analyze survey results. The results of data analysis show that there are 5 factors that directly affect the perception of avoidance: Health concerns; Doubts about advertising intermediaries; Privacy concerns; Information value; Obstructing cognitive goals. The factor that directly affects Avoidant Behavior is Perception of avoidance, there are 5 factors that indirectly affect Avoidant Behavior: Health concerns; Doubts about advertising intermediaries; Privacy concerns; Information value; Obstructing cognitive goals. At the same time, the research also shows that negative experiences do not affect the impact process from Avoidant Perception to Avoidant Behavior. This study has important practical elements for businesses, managers and even social network users in reducing users' awareness and avoidance of advertising

Assessment of the Effectiveness of Matrix Model Among Methadone Patients Using ATS in Ho Chi Minh City, Vietnam

This study assessed the effectiveness of the application of the Matrix model in patients undergoing methadone treatment for Amphetamine-type substance (ATS) in Ho Chi Minh City. A total of 951 methadone patients were screened; 60 (16%) met the inclusion criteria and of those 51 (85%) completed 16 weeks of study procedures. Most of the participants were ATS users with moderate or higher risk of dependence. Compared to the non-intervention group, the intervention group showed a significant reduction in positive urine tests for methamphetamine (a decrease from 100% to 11% vs. a decrease from 100% to 98% for the non-intervention group, p<0.001) and for opiates (a decrease from 36.7% to 3.7% vs. a decrease from 43.3% to 29.2% for the non-intervention group). In the intervention group, the quality of life increased from 76.74 points to 85.5, the proportion of depression decreased from 43.3% to 18.5%, anxiety decreased from 30% to 11.1%, and stress decreased from 76.7% to 29.6%. In the non-intervention group, quality of life decreased from 75.2 points to 74.5 points, the proportion of depression decreased slightly from 40% to 36%, anxiety decreased from 33.3% to 24%, and stress decreased from 76.7% to 76.0%. The intervention group was significantly more likely to adhere to methadone treatment (p<0.001). The proportions of participants in the intervention group and non-intervention group who discontinued treatment were 10% and 20%, respectively. The study results suggested that the MATRIX model could help reduce ATS and opiate use and improve mental health as well as treatment adherence

Factors Affecting Young Consumers’ Intention to Purchase Upcycled Fashion Products – A Case Study in Vietnam

In this study, the author has given different basis to build hypothesis and research models to find out the factors affecting the Vietnamese young consumer's intention to purchase upcycled fashion products. Firstly, this paper focuses on studying the relationship between attitudes and purchase intentions. Secondly, the author studies the effects of factors on attitudes and purchase intentions. The main research subjects are factors affecting Vietnamese young consumer' intention to to purchase upcycled fashion products. Hence, this research was conducted based on survey results among 400 young people aged 18 to 34 in Hanoi and Ho Chi Minh city which are two big city in Vietnam. The authors used two statistical software, SPSS 26.0 and AMOS 20.0, to analyze the survey results. These tools help the authors analyze Cronbach's Alpha reliability coefficients, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), structural equation model (SEM). The results show that there was a positive relationship between young consumers' attitudes and purchase intention in the Vietnamese context. Attitude mediates the relationship between the influencing factors and purchase intention. Moreover, the study test the impact of five main factors including environmental concern, social value, uniqueness value, perception financial risk, and perceive quality risk. The environmental concern (β = 0.337) is considered as the strongest effect on consumers' attitudes towards products. The factors such as uniqueness value (β = 0.302) as well as social value (β = 0.216) also positively affect consumers' attitudes. On the other hand, perception financial risk (β = -0.168), and perceive quality risk (β = -0.280) negatively affect consumers' attitude

ICON in Climate Limited-area Mode (ICON release version 2.6.1): a new regional climate model

For the first time, the Limited-Area Mode of the new ICON (Icosahedral Nonhydrostatic) weather and climate model has been used for a continuous long-term regional climate simulation over Europe. Built upon the Limited-Area Mode of ICON (ICON-LAM), ICON-CLM (ICON in Climate Limited-area Mode, hereafter ICON-CLM, available in ICON release version 2.6.1) is an adaptation for climate applications. A first version of ICON-CLM is now available and has already been integrated into a starter package (ICON-CLM_SP_betal). The starter package provides users with a technical infrastructure that facilitates long-term simulations as well as model evaluation and test routines. ICON-CLM and ICON-CLM_SP were successfully installed and tested on two different computing systems. Tests with different domain decompositions showed bit-identical results, and no systematic outstanding differences were found in the results with different model time steps. ICON-CLM was also able to reproduce the large-scale atmospheric information from the global driving model. Comparison was done between ICON-CLM and the COnsortium for Small-scale MOdeling (COSMO)-CLM (the recommended model configuration by the CLM-Community) performance. For that, an evaluation run of ICON-CLM with ERA-Interim boundary conditions was carried out with the setup similar to the COSMO-CLM recommended optimal setup. ICON-CLM results showed biases in the same range as those of COSMO-CLM for all evaluated surface variables. While this COSMO-CLM simulation was carried out with the latest model version which has been developed and was carefully tuned for climate simulations on the European domain, ICON-CLM was not tuned yet. Nevertheless, ICON-CLM showed a better performance for air temperature and its daily extremes, and slightly better performance for total cloud cover. For precipitation and mean sea level pressure, COSMO-CLM was closer to observations than ICON-CLM. However, as ICON-CLM is still in the early stage of development, there is still much room for improvement