Royal Commission for Jubail and Yanbu

Abstract The Education and Training Evaluation Commission in Saudi Arabia reports that many students entering university preparatory year programs face difficulties with basic English skills, particularly receptive skills in reading and listening, which are key to academic study. These difficulties are commonly associated with low learner motivation and limited exposure to relevant English practice. Although Mobile-Assisted Language Learning has gained international attention for its gamified and adaptive features, empirical evidence from Saudi preparatory year contexts remains limited. This mixed-methods pilot study considers the use of Duolingo and ReadTheory in relation to learner motivation and receptive skill development. Sixty male students at A1–A2 levels of the Common European Framework of Reference for Languages were purposively selected from a Saudi public university. The intervention was structured using the PF-4M framework, with a focus on authenticity, personalization, autonomy, and contextualization. Quantitative data were collected using a CEFR-aligned receptive skills test administered before and after the intervention and a post-intervention adapted Language Learning Motivation Scale. Qualitative data were drawn from reflective journals and weekly classroom observations documenting learner engagement. Results showed increases in receptive test scores, with mean scores rising from 8.12 to 15.17, alongside higher reported motivation levels. While both applications were well received, some learners reported challenges with comprehension and independent learning. The findings show that Mobile-Assisted Language Learning is associated with receptive skill development among beginner learners.

In assessment-driven educational systems, particularly within Saudi EFL contexts, instructors face increasing pressure to align their teaching with high-stakes testing frameworks. While individual teacher attributes such as language aptitude, metalinguistic awareness, self-efficacy, and anxiety have been studied in isolation, their interactive effects on Teaching for Assessment (TFA) practices remain underexplored. This study aimed to investigate how these cognitive and affective factors predict and mediate TFA engagement among university EFL instructors in Saudi Arabia. A quantitative, cross-sectional design was employed using five validated instruments to measure language aptitude, metalinguistic awareness, language anxiety, teacher self-efficacy, and TFA practices. A purposive sample of 247 Saudi university EFL instructors participated. Hierarchical regression, mediation (PROCESS Model 4), and moderated mediation (Models 14 and 58) analyses were conducted using SPSS and Hayes' PROCESS Macro. Self-efficacy was the strongest positive predictor of TFA practices, followed by metalinguistic awareness. Language anxiety negatively influenced TFA, while language aptitude showed only an indirect effect via metalinguistic awareness. Moderation analysis revealed that anxiety weakened the relationship between metalinguistic awareness and TFA, while self-efficacy enhanced the entire indirect pathway from aptitude to TFA. These findings validate a moderated mediation model and highlight complex cognitive-affective dynamics influencing assessment behavior. The study confirms that cognitive ability alone is insufficient to foster assessment-aligned teaching. Rather, the interplay of self-efficacy, metalinguistic awareness, and anxiety significantly shapes TFA practices. These insights underscore the need for professional development programs that enhance both cognitive skills and emotional readiness among EFL instructors.

Accurate calibration of instrumentation transmitters is critical for ensuring operational safety, process efficiency, and regulatory compliance in the oil and gas industry. Traditional calibration methods and existing machine learning approaches treat calibration as a purely data-driven regression problem, ignoring the underlying sensor physics and failing to adapt to evolving drift patterns. This paper proposes a novel Physics-Informed Adaptive Drift Compensation (PI-ADC) framework that integrates first-principles sensor models with data-driven machine learning for automated calibration of pressure, temperature, flow, and level transmitters. The PI-ADC framework incorporates three key innovations: (1) a physics-constrained loss function that enforces thermodynamic consistency, (2) an adaptive drift detection mechanism using statistical process control, and (3) a selective retraining strategy that updates models only when significant drift is detected. We conduct comprehensive experiments comparing nine machine learning algorithms—SVR, RF, XGBoost, KNN, ANN, LSTM, 1D-CNN, GPR, and LSTM-SVM hybrid—enhanced with the proposed PI-ADC framework using industrial datasets from 45 instrumentation transmitters across three petroleum facilities over 18 months. Results demonstrate that the PI-ADC-enhanced XGBoost achieves 52.3% RMSE reduction compared to traditional polynomial fitting (p < 0.001), with 34.7% improvement in long-term stability over standalone ML approaches. The framework reduces required retraining frequency by 67% while maintaining calibration accuracy within ±0.1% of full scale. A pilot deployment at an offshore platform validates the practical applicability of the proposed approach.

Abstract The efficiency, quality, and reliability of shell and tube heat exchangers are significantly influenced by the design and execution of tube-to-tubesheet (TTS) welding. The key factor includes the selection of materials, welding process, and accuracy of dimensional specifications. There are three commonly used TTS joint designs such as the expanded joint (no welding), seal-welded joint (single pass welding with or without expansion), and strength-welded joint (two pass welding followed by expansion) as per the American Society of Mechanical Engineers (ASME) Section VIII Div. 1 UW-20. An extensive literature review revealed a strong reliance on various welding processes but the designs were limited to traditional joint configurations. In the proposed study, an attempt was made to investigate TTS welding using the gas tungsten arc welding (GTAW) process with a three pass or three layer technique following the inspection standard (ASME Section IX QW 193). Experimental investigations were conducted on a 50 mm thickness carbon steel tubesheet (SA 516 Gr. 70 N) and 19.05 mm outside diameter (OD) with 2.11 mm thickness of carbon steel tubes (SA 179) using a GTAW welding machine for ten samples. The quality of the TTS joint was assessed through various inspection techniques in accordance with ASME Section IX QW 193.1-191.3, encompassing visual inspection, liquid penetrant testing, and macroscopic examination to identify the minimum leak path (MLP). The experimental findings demonstrated that the three pass GTAW technique significantly enhances the quality and reliability and also extends the life of TTS welds in heat exchangers due to better MLP.

UHPC has been found to have excellent freeze–thaw durability in cold regions. Previous UHPC testing performed has mostly focused on concrete with compressive strength above 21 ksi (145 MPa). In this study, testing was conducted to determine at what strength level concrete transitions to provide excellent freeze–thaw (F–T) performance. Non-proprietary concrete samples were made for freeze–thaw durability from four different concrete mixture designs: 12–15 ksi, 15–18 ksi, 18–21 ksi, and 21+ ksi (83–145+ MPa), and these were tested according to ASTM C666, using 1.5% steel fibers. The samples were made for three different curing regimens: limewater curing in a fog room, simulated precast curing, and steam curing. Low-temperature differential scanning calorimetry (DSC) and mercury intrusion porosimetry (MIP) tests were carried out to reveal the freeze–thaw mechanism of the concrete samples. All mixtures with compressive strength above 15 ksi (103 MPa) performed excellent in freeze–thaw testing with no damage seen. Steam curing was found to negatively affect the freeze–thaw performance at the lowest strength level tested.