The socio-economic development of each country requires the contribution of businesses to social goals and the state budget. Improving tax compliance behavior is consistent with improving the ability of businesses to contribute to the budget. The objective of the study is to evaluate factors affecting tax compliance behavior for businesses. The study is conducted on 202 enterprises in Thai Nguyen, a locality located in the key economic region of Vietnam and with a high level of economic development. Through quantitative analysis of the research results, it found that: the system legislation and socio-economic conditions have the strongest influence on businesses' tax compliance behavior. However, the influence of business characteristics and tax authority characteristics on tax compliance behavior is lower.

The effect of pH value at three levels (5, 7, and 9) and temperature at two levels (25 and 50ºC) on the sorption properties of chlorantraniliprole-CAP, dinotefuran-DNF, bispyribac-sodium-BPS, and metribuzin-MBZ were studied in calcareous soil. The sorption of CAP at pH 5 (38.2%) was significantly higher than that at pH 7 (32.4%) and 9 (28.4%), whereas the sorption of DNF at pH 5 was lower than that at pH 7. The adsorption of BPS at pH 9 was statistically significantly higher than that at pH 5 and pH 7. Regarding the herbicide MBZ adsorption percentages were 47.0, 61.1 and 57.1 % at pH 5, 7 and 9. The number of tested pesticides adsorbed by the soil was significantly influenced by the temperature. The adsorbed amount of CAP was decreased from 37% to 33% as the temperature was increased from 25˚C to 50 ˚C, while no significant differences of adsorbed DNF. Data showed that the adsorption of BPS and MBZ statistically decreases with temperature. The data from the adsorption behaviour of CAP, DNF, BPS, and MBZ in tested soil at different temperatures correspond well with the Freundlich isotherm. The negative ΔG˚ indicated that the adsorption of CAP, DNF, BPS, and MBZ were spontaneous at different temperatures. There was an increase in the entropy of the pesticide-soil systems as shown by the positive values of ΔS˚.

There were still contradictory results from earlier research on the relationship between organizational innovation, performance, and management control systems (MCS). In order to account for these contradictory results, future studies ought to concentrate on the empirical analysis of Simon's MCS theory. The purpose of the study was to assess the mediation and moderation model in relation to performance, innovation, and MCS. The study intends to broaden the scope by employing a more thorough definition and measurement of research variables. Because the Partial Least Square (PLS) can concurrently assess the existence of a dual dependency relationship of a latent variable, the study used PLS to test the hypothesis. The mediated hypothesis which holds that MCS indirectly affects performance through innovation seems to be supported by these data. All things considered, this study contributes to the understanding of the ambiguous and contradictory conclusions of earlier studies that examined the connection between MCS, innovation, and performance.

A crucial direction in the progress of modern medical chemistry is the development and improvement of theoretical investigation methods of drugs mechanisms of action, predicting their activity, and virtual design of new drugs. This review describes the history of targeted search for biologically active compounds, current in silico approaches and tools used in the rational design of potential drugs, in particular the main computational strategies used in modern drug design are presented and outlines the main methodologies for implementing these strategies.

Financial reports provide information about a company's assets, liabilities, equity, income, expenses and cash flow. This information can be used by various parties such as investors, creditors, government and management to make business decisions and assess company performance. Companies in obtaining good financial reports need to detect fraudulent financial statements first. Financial statement fraud can be detrimental to investors and creditors because it gives a wrong picture of a company's financial performance. This study aims to examine the effect of big data competence and the tone of the top internal auditors on the detection of financial statement fraud, as well as to mediate the effect of big data competence on the detection of financial statement fraud through self-efficacy. This research uses a sample of 183 respondents who are internal auditors in companies in Indonesia. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results of the study show that big data competence has no significant effect on the detection of financial statement fraud, but has a positive and significant effect on self-efficacy. In addition, the internal auditor's tone of the top also has a positive and significant effect on the detection of financial statement fraud. Finally, self-efficacy partially mediates the relationship between big data competence and fraud detection of financial statements. This research provides important implications for practitioners and decision makers in developing internal auditor competence in the field of big data and paying attention to tone of the top as an important factor in detecting fraudulent financial statements. In addition, this research also contributes to strengthening the understanding of the relationship between big data competence, tone of the top, self-efficacy, and fraud detection of financial statements in the Indonesian context.

While decent work has emerged as the central theme of the psychology of work theory and a global concept and directive for promoting social, political, and economic justice, it has garnered increasing scientific and political attention in the past two decades. However, until now, no defined measurement scale for the pharmaceutical supply chain exists. The present study aims to design and validate key performance indicators (KPIs) for 'decent work' in the pharmaceutical industry supply chain of Iran, using the Decent Work Daffi Scale (2017) as a reliable framework with five sub-scales and 15 items, tested and validated. For the validation of the Decent Work Scale, a quantitative survey study was conducted among selected pharmaceutical industry experts with a sample size of 228 individuals in the year 2023. The current study adopted an exploratory factor analysis approach using SPSS software and a confirmatory factor analysis through AMOS version 24 software. In this context, the factor structure, convergent validity, discriminant validity, and Cronbach's alpha coefficients were examined. The results showed that the five-factor structure outperforms the one-factor model with evidence supporting the convergent, discriminant, and predictive validity of the five-factor scale. Thus, the measurement of decent work in the pharmaceutical industry of Iran comprises five sub-scales: occupational safety conditions, access to healthcare, adequate remuneration, Free time and rest, and alignment of organizational values with family and societal values. This scale can serve as a useful tool for industrial and organizational psychology research, as well as for studies on the sustainability of social supply chains.

On the base of 3-formylpicolinic acid by two successive heterocyclizations (the formation of a pyrone fragment by the cyclization of chloroacetone with the carboxyl and formyl groups; and the construction of the thiazole cycle through the bromination of the acetyl fragment and following interaction with thioamides), 6-(2-(phenyl/thiophen-2-yl)thiazole-4-yl)-8H-pyrano[3,4-b]pyridin-8-ones were obtained; and then the pyrone fragment was converted to pyridone by the action of ammonia under high pressure. When such 6-(2-R-thiazol-4-yl)-1,7-naphthyridin-8(7H)-ones reacted with triflic anhydride, O-sulfonylation of the pyridone fragment occurred, after that triflate group was easily substituted by secondary cyclic aliphatic amines. Thus, a number of new 8-amino-6-(2-R-thiazol-4-yl)-1,7-naphthyridines – previously inaccessible heterocyclic derivatives with promising biological activity – were obtained.

This paper examines how generational cohorts influence households’ choices regarding housing tenure and considers the diverse preferences and socio-economic factors that shape decisions—using survey data on 425 families in Ho Chi Minh City, Vietnam. The data is analyzed using a multinomial logit model. The results indicate that generation significantly positively affects housing tenure choice, such that, unlike older cohorts, younger generations are more inclined to rent houses as their preferred housing option. Furthermore, permanent income plays a significant role in shaping housing tenure choices. On the other hand, social-economic variables, namely education, gender of references, family structures, and area of residence, were significant in influencing housing tenure decisions. This finding highlights the importance of housing policies prioritizing affordable and accessible rental options in large cities.

The white mango scale insect Aulacaspis tubercularis (Newstead) (Hemiptera: Diaspididae), which causes defoliation, drying out of young twigs, dieback, poor flowering, and decreased fruit output, causes serious damage to mango trees in Egypt. Attacks on mango fruits result in pink imperfections that lower their value as a commercial and export item. The current report aims to support the development of integrated management plans to combat A. tuberculosis and to identify more effective, eco-friendly insecticides. The bug may cause a considerable decrease in mango production and jeopardize the sustainability of mango plantation production if no management measures are taken. Currently, the application of a small number of insecticides—the majority of which have poor performance and are disruptive is the primary method used to manage A. tubercularis. In order to suppress this insect, we created novel pesticides called insect growth regulators (N, N′-substituted benzamide derivatives). By using both traditional and elemental spectroscopic investigations (IR, 1HNMR, and 13CNMR), these synthesized compounds which are linked to the most well-known insect growth regulator insecticides had their structures validated. The findings showed that A. tubercularis nymphs were more responsive to the evaluated treatments than adult females. After one day of application, all tested treatments resulted in a sizable proportion of mortality; the percentage of mortality increased with time for both A. tubercularis nymphs and adult females. Furthermore, the treatment with compound 3b was more effective than other synthesized compounds, with a LC50 of 0.318 ppm against nymphs and a LC50 of 0.993 ppm against adult females of A. tubercularis. While the treatment with compound 5 was the least toxic for controlling this pest, many assessments are essential to studying the efficacy of these treatments on advantageous insects.

Several models have been developed to predict financial difficulties and corporate bankruptcy. In this research various models were employed, including the Altman model (referred to as the Z-Score), the Springate model (known as the S-Score), the Zmijewski model (designated as the X-Score), and the Grover model (referred to as the G-Score). These techniques serve the purpose of evaluating the likelihood of encountering financial difficulties, which in turn determines the probability of PT Garuda Indonesia (Persero) Tbk going bankrupt. The study utilized secondary data sourced from financial statements spanning the years from 2020 to 2022. The application of the Altman model for bankruptcy prediction revealed that PT Garuda Indonesia (Persero), Tbk experienced financial distress throughout the period from 2020 to 2022. According to the Springate model, the company was in a state of distress and declared bankruptcy in 2020 and 2022, while 2021 fell into a grey area. The Zmijewski model indicated that the company was on the brink of bankruptcy, with financial difficulties and a potential risk of bankruptcy within the next three years. Grover's model predicted bankruptcy for the company in 2020 and 2022, but indicated safety in 2021. Notably, the Taffler model emerged as the most accurate in forecasting bankruptcy, boasting a 100% accuracy rate with no errors. Meanwhile, the Zmijewski model achieved an 81.25% accuracy rate with an error rate of 18.75%, and the Springate model exhibited the lowest accuracy in bankruptcy prediction, scoring only 12.50% accuracy with an error rate of 87.50%.