Factors Affecting Pre-Serviced Teachers’ Satisfaction with Training Quality of the Primary Education Program at Thu Dau Mot University

/0 Comments/in /by

This paper examines the determinants of pre-serviced teachers’ satisfaction concerning the training quality within the Primary Education program at Thu Dau Mot University. Empirical data were gathered from a sample of 303 pre-serviced teachers via questionnaires. SPSS 26 was employed to conduct Cronbach’s Alpha reliability testing, exploratory factor analysis (EFA), Pearson correlation analysis, and multiple linear regression. The findings reveal that alumni satisfaction toward training quality is influenced by four distinct factors: curriculum, teaching staff, physical facilities, and student support activities. Notably, the curriculum emerged as the most critical factor driving overall satisfaction.

A Cross-Linguistic Study of Lexical Compatibility in Germanic Languages

/in /by

Lexical compatibility plays a crucial role in the formation and interpretation of word combinations across languages. It reflects the semantic, syntactic, and collocational constraints that determine the co-occurrence of lexical units in discourse. This study investigates the principle of lexical compatibility in selected Germanic languages, with particular emphasis on English and German. Employing a comparative linguistic approach, the research examines how lexical items combine to form meaningful word combinations and identifies both common and language-specific patterns of lexical selection. The study draws on theoretical perspectives from lexical semantics, collocation studies, and corpus linguistics to analyze compatibility relations among lexical units. The findings suggest that while Germanic languages share a number of compatibility patterns due to their common linguistic heritage, significant differences emerge as a result of language-specific semantic preferences, cultural influences, and structural developments. The research contributes to the understanding of lexical combinability and provides insights into the mechanisms underlying word combination formation in Germanic languages. The results may also have practical implications for foreign language teaching, translation studies, and lexicographic research.

Medication Adherence in Diabetes Mellitus Patients Based on the Health Belief Model Perception

/in /by

Diabetes Mellitus (DM) is a chronic disease that requires long-term treatment. Treatment adherence is an important factor in controlling blood glucose levels and preventing complications. Patient perception based on the Health Belief Model (HBM) is thought to play a role in shaping treatment adherence behavior. This study aims to analyze the influence of HBM perceptions on treatment adherence in DM patients at the Gadingrejo community health center, Pringsewu, Lampung province, Indonesia. This study used an observational analytical design with a case-control approach conducted in April–June 2026. A sample of 206 respondents consisting of 103 case groups and 103 control groups, selected using a stratified random sampling technique. Data were collected using the HBM and MMAS-8 questionnaires, then analyzed using the Chi-Square test with α = 0.05. There was a significant influence between perceived susceptibility (p<0.001; OR=3.051; 95%CI=1.730–5.383), perceived severity (p=0.002; OR=2.482; 95%CI=1.417–4.347), perceived benefit (p<0.001; OR=2.927; 95%CI=1.662–5.156), perceived barriers (p=0.012; OR=2.120; 95%CI=1.213–3.702), self-efficacy (p=0.005; OR=2.290; 95%CI=1.310–4.003), and cues to action (p<0.001; OR=4.531; 95%CI=2.492–8.239) on medication adherence. All constructs of the HBM influence medication adherence in DM patients. Increasing positive perceptions and reducing barriers can support better medication adherence.

Pillars of European chemicals legislation

/in /by

This article examines key European regulations concerning hazardous substances. To this end, the relevant provisions were analyzed and their requirements identified.

The REACH and CLP regulations form the basis for the registration, classification, labeling, and handling of chemicals and chemical products within European Union member states. They are supplemented by other EU regulations addressing particularly hazardous chemicals, covering areas such as import and export (PIC Regulation) as well as manufacture and storage (Seveso III Directive). Furthermore, regulations concerning specific product groups—such as biocides, pesticides, persistent organic pollutants, and detergents—are discussed. The regulations clearly indicate that both individual chemicals and mixtures may be subject to registration and/or notification obligations.

Budgetary Control Systems and Accountability in Kenya’s Public Sector Organizations: A Management Accounting Perspective

/in /by

Budget control and accountability are key aspects of public sector financial management. Both in developed and developing economy, public institutions exist to manage public resources in an efficient, transparent, and accountable manner. Concerns about transparency and accountability in Kenya’s public sector institutions are a result of corruption, mismanagement of funds, weak internal control, and inefficient management of public resources. From a management accounting viewpoint, budgetary control systems aid in the planning, coordination, and evaluation of activities. This research explores the contribution of budget control systems to accountability in public sector institutions in Kenya. Specifically, it examines the contribution of management accounting techniques to transparency, governance, operational and financial accountability. The study also examines the key challenges in public sector budgeting relating to politics, behavior, inadequate technology and corruption, and recent trends such as digital budgeting, and performance-based budgeting. A Structured Literature Review was utilized, accessing publications from 2020 to 2026, including peer reviewed journals, government publications, authoritative policy papers, and other relevant and scholarly works. The research concludes that efficient budget control systems enhance governance and operational effectiveness, and facilitate transparency in public sector institutions. It also posits that the enhancement of budget control systems is essential for improving public financial management and accountability in Kenya.

Predictive Pontryagin Optimal Control of Nonlinear Fully Distributed DCS and CPS under Reliability and Uncertainty Constraints

/in /by

The article provides an overview of the optimal control prediction framework for non-linear CPS and DCS in automation. The core issue is the fact that the present architecture of modern automation systems does not behave like a closed loop control system anymore. The design of these systems combines sensors, actuators, edge controllers, communication channels, digital twin, software-as-a-service, human involvement, and states of cyber-security. Thus, control design must not only address accuracy but should be a multicriteria design problem that accounts for reliability, uncertainty, probability mass, delay in communication, and energy costs. Four levels are considered in the proposed framework. The first level refers to forecasting based on hybrid ARIMA-ML model for a short horizon. The second level is concerned with estimating of risk states using Markov model/HMM.  The contribution is a simulation-ready mathematical architecture in which each node solves a local Hamiltonian problem using predicted states, neighbour information and reliability constraints, while the global CPS behavior emerges through networked local decisions. The paper formulates the nonlinear dynamics, cost functional, Hamiltonian conditions, reliability constraints and evaluation protocol for smart factories, smart grids, intelligent buildings and smart campuses. The framework is positioned as a bridge between predictive maintenance and optimal distributed automation control.

Developing Van Hiele-Based Project Learning Tools through Plastic Waste Paving Block Design on Similarity Materials

/in /by

This study aimed to develop Project Based Learning (PjBL) instructional tools through plastic-waste paving block design based on Van Hiele theory that are valid and practical for learning similarity topics. The study employed a Research and Development (R&D) approach using the 4D model developed by Thiagarajan, consisting of the define, design, develop, and disseminate stages. The participants were seventh-grade students of SMP Science Quran Al Irsyad Al Islamiyyah Jember in the 2025/2026 academic year, consisting of an experimental class and a control class. Data were collected using validation sheets, observation sheets, student response questionnaires, and readability instruments. The results indicated that the developed instructional tools met the validity criteria, with validity scores of 3.76 for the teaching module, 3.67 for the student worksheet, and 3.72 for the user guide. The practicality criteria were also achieved, as indicated by a learning implementation score of 3.5 (high category), student activity of 90% (very good category), and student responses of 92% (very positive category). These findings indicate that Project Based Learning instructional tools integrating Van Hiele theory and plastic waste paving block design are valid and practical for supporting geometry learning on similarity topics through authentic project activities involving plastic-waste paving block design.

Implementing the 5S Program to Reduce Waste: A Lean Maintenance Approach

/in /by

This study aims to evaluate the implementation of the 5S program as a strategy to enhance maintenance effectiveness, reduce waste, and improve productivity and operational quality in the workplace. The research uses a case study approach with descriptive analysis to identify activities that contribute to inefficiencies in the maintenance process. Big Picture Mapping is applied to visualize the current value stream and identify potential sources of waste, while a work area audit assesses the initial condition of the operational environment. The study focuses on companies implementing lean principles and requiring continuous improvement in maintenance practices. The findings indicate that the application of the 5S methodology—Seiri (Sort), Seiton (Set in Order), Seiso (Shine), Seiketsu (Standardize), and Shitsuke (Sustain)—creates a more organized and efficient workplace. This structured system improves workflow, enabling tasks to be completed more quickly and accurately. Furthermore, it enhances productivity, stabilizes quality, and supports better alignment with customer expectations. The program also promotes a culture of discipline and continuous improvement, contributing to sustainable operational performance and operational excellence.

The Effect of Digital Payment on MSME Performance: Mediating Role of Transaction Velocity and Security

/in /by

Within an Accounting Information System (AIS) framework, digital payments function as automated data-capture tools integrated into the revenue cycle. By using digital payments or payment gateways, organizations can record transactions accurately and in real time, thereby eliminating manual processes that are susceptible to human error. A robust AIS ensures that all cash inflows are authorized and recorded, which supports reliable financial reporting and objective measurement of micro, small, and medium enterprise (MSME) performance. Digital payments further enhance financial and operational outcomes for MSMEs by increasing transaction velocity and security. The present study investigates and empirically validates (a) the causal relationships among digital payment, transaction velocity, transaction security, and MSME performance, and (b) the mediating roles of transaction velocity and security in the relationship between digital payment and MSME performance. Data were collected through a survey using questionnaires distributed to respondents selected via purposive sampling. The study uses primary data and focuses on four constructs: digital payment, transaction velocity, transaction security, and MSME performance, each measured by 21 reflective indicators. Respondents included MSME entrepreneurs at the managerial level (owners or managers) operating in the wholesale and retail, culinary, fashion, agribusiness, and service sectors. The survey targeted MSMEs on the islands of Java, Bali, and Sumatra, yielding 145 valid data points. Structural equation modeling with partial least squares was employed for data analysis, using SmartPLS version 3.29 for data processing and hypothesis testing. All hypotheses concerning the direct effects of exogenous constructs on endogenous constructs were significantly supported. Furthermore, empirical findings indicate that transaction velocity and security mediate the causal relationship between digital payment and MSME performance.

Cross-Country Transfer Learning for FDI Forecasting in Small Macroeconomic Datasets

/in /by

This study examines whether transfer learning can improve machine learning performance under data-scarce forecasting conditions. The empirical application focuses on forecasting foreign direct investment (FDI) inflows using CatBoostRegressor. The source domain is represented by a broad international panel of countries, while the target domain consists of Central Asian economies.

CatBoost is evaluated in two settings: without transfer learning, where the model is trained only on target-region data, and with transfer learning, where the model is first pretrained on the source domain and then fine-tuned on the target domain. The results are compared with simple baseline models, including a lagged-target naive model and a regional mean benchmark.

The findings show that transfer learning substantially improves predictive accuracy. Compared with the target-only CatBoost model, the transfer learning model reduces RMSE from 4.0421 to 3.0426 and MAE from 3.3504 to 2.3369. also improves from − 5.8205 to − 0.0761. These results suggest that transfer learning can help stabilize machine learning forecasts when target-domain observations are limited.