Objective: This research analyzed the psychometric properties of the Ambivalent Classism Inventory (ICA) in Peru. Methodology: A critical review of literature related to poverty, inequality, and structural gaps was conducted, involving 882 participants aged 14 to 89 years (M = 24.61, SD = 9.07). Results: Exploratory-confirmatory factor analyses were satisfactory, finding a similar factorial structure to the original scale and the adaptation (hostile classism, protective paternalism, and complementary class differentiation). Regarding items, there was a reduction, leaving only 12; however, comparing alternative models, the three-factor structure with 12 reagents showed adequate fit (χ² = 214.588, df = 51, p < 0.001; CFI = 0.996; RMSEA = 0.060; SRMR = 0.033), allowing for invariance testing. Practical Implications: The scale allows for investigating attitude profiles of individuals with privileged social class. Contribution: The instrument is a valuable contribution, considering that the nation has a high poverty rate, leading to economic, political, and social inequality among the population.

This study conducts a comparative analysis of various machine learning and deep learning models for predicting order quantities in supply chain tiers. The models employed include XGBoost, Random Forest, CNN-BiLSTM, Linear Regression, Support Vector Regression (SVR), K-Nearest Neighbors (KNN), Multi-Layer Perceptron (MLP), Recurrent Neural Network (RNN), Bidirectional LSTM (BiLSTM), Bidirectional GRU (BiGRU), Conv1D-BiLSTM, Attention-LSTM, Transformer, and LSTM-CNN hybrid models. Experimental results show that the XGBoost, Random Forest, CNN-BiLSTM, and MLP models exhibit superior predictive performance. In particular, the XGBoost model demonstrates the best results across all performance metrics, attributed to its effective learning of complex data patterns and variable interactions. Although the KNN model also shows perfect predictions with zero error values, this indicates a need for further review of data processing procedures or model validation methods. Conversely, the BiLSTM, BiGRU, and Transformer models exhibit relatively lower performance. Models with moderate performance include Linear Regression, RNN, Conv1D-BiLSTM, Attention-LSTM, and the LSTM-CNN hybrid model, all displaying relatively higher errors and lower coefficients of determination (R²). As a result, tree-based models (XGBoost, Random Forest) and certain deep learning models like CNN-BiLSTM are found to be effective for predicting order quantities in supply chain tiers. In contrast, RNN-based models (BiLSTM, BiGRU) and the Transformer show relatively lower predictive power. Based on these results, we suggest that tree-based models and CNN-based deep learning models should be prioritized when selecting predictive models in practical applications.

In the process of seeking sustainable development, enterprises have chosen international business strategy. The purpose of this study is to examine the relationship between the degree of internationalization of Chinese listed firms and financial reporting quality, as well as whether audit committees can moderate the impact of enterprise internationalization on financial reporting quality. The empirical analysis results of Chinese listed manufacturing firms from 2014 to 2018 show that: the degree of corporate internationalization has a significant U-shaped relationship with earnings management. This new finding solves the problem that scholars have inconsistent views on the internationalization of enterprises and the quality of financial reporting. The study also found that audit committees with experience working in accounting firms can inhibit firm earnings management behavior in the early stage of internationalization; audit committees with experience working overseas can inhibit firm earnings management behavior in the later stage of internationalization; the higher the remuneration of audit committee experts, the more it can inhibit firm earnings management behavior in the early stage of internationalization. In the later stage of internationalization, the higher the remuneration of audit committee experts, it helps the earnings management behavior of firms. This provides new evidence on the functioning of the audit committee’s role; however, the independence of the audit committee and the proportion of financial experts do not have a significant effect on the inhibition of earnings management.

A three-factor experiment was set at the Horticulture Laboratory, Hajee Mohammad Danesh Science and Technology University, Dinajpur, to study the effects of the controlled deterioration (CD) on the pea seeds at the constant temperature of 35 ℃. The 3 factors considered were: 3 pea seed sources (Rangpur Local/RL, Dinajpur Local/DL and Thakurgaon Local/TL); 3 ageing periods (0, 8 and 16 days); and 3 seed moisture contents (12, 16 and 20% MC). The 27 treatment combinations compared in the CRD with the 3 repetitions for the 8 arenas were: % germination, % abnormal seedlings, % dead seeds, % soil emergence and seedling evaluation test for the root and shoot lengths as well as their dry matter contents. Identical prototypes of notable (5–1% level) degradations were recorded everywhere. But the disparities were lucid under the extreme stresses. Moreover, highly noteworthy (1% level) relations were traced amid all the traits ranging from -0.9847 (soil emergence × abnormal seedling) to 0.9623 (soil emergence × normal seedling). So, the CD technique was very effectual in judging the physiological statuses of the seed sources studied. Thus, the germination test might be add-on by a vigor test, the latter of which could be assessed by quantifying the seedlings’ root and shoot lengths and/or their dry matter accumulations. Moreover, in the seed quality certification, the suitable limits of vigor for the chosen traits could also be got by this technique. But the seeds of several pea varieties should be exploited to fix-up the agreeable limits of the traits. Furthermore, to save time, the ageing period could be squeezed by raising the seed MC.

This research focuses on patients’ perceptions regarding the accessibility of dental services in Slovenia across four dimensions: financial accessibility, time accessibility, geographical accessibility, and service quality. We observed how specific factors impact accessibility dimensions of dental services in Slovenia, that patients perceive important. A cross-sectional quantitative survey was conducted using proportionate stratified sampling. Data was collected through an online questionnaire, and 599 completed responses were received from patients regarding their experiences and perceptions of accessibility to dental care. A SEM (structural equation model) approach was used to examine the data. The analysis revealed that patients perceive all four dimensions of accessibility: financial, time, geographical, and service quality important and they all constitute the perception of dental accessibility. The findings of this study can assist policymakers in developing a more accessible dental health system by considering the results proposed in our model.

The process management variable and the service quality variable date most prominently from the beginning of the last century, and therefore, in organizations from different parts of the world, whose search was to contribute effectively to administrative tasks, facing the challenges of constant changes and evaluations. In Peru, both variables were implemented since 2018, by technical standards, in order to contribute and improve public institutional work. Thus, the objective was to know the most outstanding characteristics of process management and service quality, using studies from different entities at the ecumenical level and revealing their main benefits of application and contribution. Furthermore, based on the systematic and methodical review of scientific articles from databases indexed to multiple journals, which are registered and organized in databases such as WOS and SCOPUS, thus theorizing their authors and perspectives. For this study, the documentary analysis technique and the data collection guide were considered as an instrument; in accordance with the PRISMA method. Finally, it is concluded that process management are methods available in an organization to provide effective results using resources efficiently, with dimensions of analysis, monitoring, and process improvements, contributing to organizational and strategic productivity; Likewise, the quality of the service is user satisfaction when judging the value of some service, dimensioning, analyzing needs, as well as evaluating, supervising and improving the service, fulfilling needs with knowledge of their expectations.