Volume 38 (01) January 2026

Generative AI tools like ChatGPT are rapidly reshaping how students access and engage with knowledge. While these technologies can support learning, their influence depends heavily on students’ epistemic beliefs—their views about the nature, source, and justification of knowledge. Research has shown that epistemic orientations shape whether learners critically interrogate or passively accept information, yet little is known about how this plays out in AI-mediated contexts, particularly in higher education settings outside the West. This study addresses that gap by examining how undergraduate students in Oman engage with ChatGPT through the lens of Hofer and Pintrich’s (1997) epistemic belief framework. Using a qualitative interpretive approach, semi-structured interviews were conducted with thirteen undergraduate students from diverse disciplines to explore how their epistemic beliefs influenced their interactions with ChatGPT. The thematic analysis revealed four engagement patterns: Naïve Believers, Over-Reliant Users, Strategic Skeptics, and Critical Evaluators. These patterns reflect not only individual beliefs but also cultural norms, educational experiences, and workload pressures. The findings advance AI–epistemic beliefs scholarship by showing how cultural context and academic conditions shape trust, verification, and reasoning with AI outputs. The study argues for embedding AI literacy into curricula through strategies such as argumentation-based learning, claim–evidence coordination, and metacognitive scaffolding to foster critical digital literacy and prepare students for an AImediated knowledge environment.

Epistemic beliefs; ChatGPT; generative artificial intelligence; critical digital literacy; higher education

This mixed-methods study examined how integrating smart technologies into entrepreneurship education influences university students’ learning and career intentions. Quantitative survey data (n = 250) showed that 68% of students had exposure to at least one smart tool in their courses; the most frequently used were AI platforms (54% frequent use) and data analytics tools (48%), with IoT (28%) and VR/AR (22%) emerging. Perceived learning benefits were high: engagement 83%, problem-solving confidence 79%, and ability to grasp real-world scenarios 76%. Entrepreneurial intention (5-point scale) increased with exposure: 4.3 (high exposure, ≥3 tools) vs 3.8 (moderate) vs 3.1 (low), and smart-technology exposure correlated positively with intention (r = 0.52, 95% CI [0.42, 0.61], p < .01). Reliability for all survey constructs was acceptable (α > .70). Multiple regression indicated smart-tool usage remained a significant predictor of entrepreneurial intention after controlling for demographics (details in Results). Qualitative interviews (10 faculty; 15 students) explained the mechanisms—hands-on simulations, data-driven feedback, and AI-supported ideation increased self-efficacy and opportunity recognition—clarifying how smart learning environments translate into heightened entrepreneurial motivation. These findings provide empirical support for theory-driven accounts (e.g., TPB, SCCT) and offer actionable guidance for curriculum designers and policymakers seeking to build digitally fluent, innovation-ready graduates.

Smart technologies; entrepreneurship education; university students; educational innovation; digital literacy

The implementation of Virtual Laboratories (V-Labs) in chemical engineering education provides valuable improvements to learning to work in Physical Laboratories (Ph-Labs). This article discusses the effect of Virtual Laboratories (V-Labs) (https://www.labster.com/, https://www.vlab.co.in/) on 120 second-year undergraduate chemical engineering students studying in the CHEM2000 course at the Sohar University. The students participated in a series of six V-Lab simulations, followed by additional Ph-Lab experiments that focused on elementary engineering chemistry and safety. A structured Likert-scale questionnaire, in addition to qualitative data from open-ended questions, was used, and SPSS were used for its analysis. Results were positive, with 98% of students also indicating that V-Labs were a valuable pre-lab training tool, and training on them contributed to their understanding of safety, procedures, and analytical skills. Additionally, 97% felt more confident and better prepared for physical lab sessions after use of V-Labs. There was a significant change in the students’ attitude after the V-Lab intervention, as evidenced by the statistical analysis (p = 0.009), which reinforces the effectiveness of using V-Labs to bridge the preparedness gap. Students appreciated the possibility of repetition in simulations and the opportunity to safely explore complex matter (though some abilities, such as dealing with operations, are best gained through hands-on experimenting), implying that a blended learning strategy is required. The results of the study are in favour of incorporating V-Labs in traditional lab exercises to promote students’ conceptual understanding, confidence, and engagement in engineering education.

Virtual labs; chemical engineering education; laboratory simulation; student perception; engineering pedagogy

This study highlights Sohar University’s significant contribution to enhancing higher education in Oman, in alignment with Oman Vision 2040, by promoting innovation, sustainability, and knowledge-driven development through its Living Lab model. Located in a strategically important region, the institution tackles urgent sustainability issues locally while also influencing national and worldwide contexts. Its objective is to convert ideas (campus zero waste. Solar energy optimization, grey water recycling etc.)into implementable actions. This effort focuses on redefining engineering education to equip graduates with technical proficiency, analytical reasoning, ethical leadership, and a dedication to global citizenship. The implementation of the International Engineering Alliance (IEA) Graduate Attributes framework fosters a culture of sustainability and ethical practices, enabling the shift from academic understanding to practical application. Sohar University applies the “Living Laboratory” model, an innovative strategy that merges academic curricula with the United Nations’ Sustainable Development Goals (SDGs). This paradigm advocates for experiential learning and community involvement, highlighting interdisciplinary research, industrial collaborations, and outreach initiatives. By incorporating practical learning into its curricula, especially in renewable energy and sustainable infrastructure, the institution improves graduate employability in both local and worldwide markets, distinguishing itself as a leader in sustainability solutions. The primary objectives include aligning graduate attributes with specific SDGs, integrating sustainability competencies into core curricula, and transforming the campus into a Centre for Sustainability. Implementation techniques include engagement, curriculum mapping, workshops, mini-grant awards, and program monitoring, which together enhance the university’s academic standing and strengthen its dedication to sustainable human capital development. Sohar University aims to be a national and regional leader in sustainability education, establishing a benchmark for institutions throughout Oman and the Gulf Cooperation Council (GCC).

Living lab; sustainability; experiential learning; competencies; curriculum integrations

Intense and prolonged rainfall can lead to slope failure by increasing pore water pressure, which reduces effective stress and shear resistance. However, the impact of climate change has caused unpredictable rainfall patterns producing varying behaviour of wetting front and runoff. Thus, this study aimed to investigate the effect of tropical rainfall patterns on wetting front behaviour for soil slopes in Peninsular Malaysia using two-dimensional (2D) slope model with rainfall simulator. The rainfall patterns simulated were established based on 20 years historical rainfall data in Peninsular Malaysia recorded from year 2000 to 2020. The results revealed a positive correlation between rainfall intensity, duration, slope gradient, and wetting front responses. Higher rainfall intensity led to deeper wetting front progression on flat surfaces due to lower runoff and higher infiltration. Conversely, steep slopes experienced shallower wetting front progression due to the increase in surface runoff. In addition, an observed 42% increase in wetting front advancement on a 26° slope, corresponding to a change in rainfall pattern from five days 100 mm/hr to two days 420 mm/hr, illustrates a direct and significant correlation between increased rainfall intensity and the rate of wetting front propagation. 2. Therefore, integrating rainfall patterns into slope stability assessments can significantly improve the prediction of rainfall-induced failures and support the development of more robust and adaptive slope designs under varying hydrological conditions.

Slope failure; wetting front; rainfall pattern; climate change

Green procurement plays a crucial role in fostering sustainability in the construction industry by addressing the lifecycle impacts of goods and services. In Sarawak, where lies the architectural landscape includes numerous heritage structures, building retrofitting works aligns with the Sarawak Post COVID-19 Development Strategy (PCDS) 2030, emphasizing sustainable development through circular economy and cultural preservation. However, the implementation of green procurement in retrofitting works faces challenges due to inadequate guidelines, a fragmented supply chain, and a short-term focus that overlooks long-term benefits. To address these issues, this study has adopted a bibliographic review technique utilizing various literature compiled from leading databases including Scopus, Web of Science and Google Scholar. It aims to identify the criteria as implementation strategies in adopting green procurement for retrofitting projects in Sarawak. The findings indicated that there are ten (10) strategies (independent variables) that can be considered in implementing green procurement for building retrofitting works (dependent variables). The criteria are identified as Carbon Footprint Analysis (CF), Green Purchasing (GP), Lifecycle Considerations (LC), Reduced Operational Costs (RO) and Stakeholder Capability (SC). The discussion summarized its relevance to the building retrofitting context with a final construct of conceptual framework relating both IVs and DVs. The findings suggest that stakeholders, policymakers, and practitioners need to recognize these main factors to achieve better sustainability and efficiency in building retrofitting works.

Green procurement; implementation strategies; building retrofitting; retrofitting projects; bibliographic review

Facilities management (FM) focuses on combining people, spaces, processes, and technology to create a safe and efficient built environment, comfortable, functional, and efficient. As healthcare facilities dedicated to providing medical services are no exception to the need for effective facilities management. Various studies have explored, identified, described, and discussed the Critical Success Factors (CSFs) that contribute to the successful implementation of FM, especially in the healthcare sector. As a result, this study was conducted to examine the CSFs for implementing FM in private healthcare facilities in Malaysia. The eight (8) key Critical Success Factors identified in this study are crucial for the effective performance of facilities management, based on a review of the literature and a questionnaire survey conducted with facilities management experts, which provided valuable insights. The study will utilized the key methodologies of the Cronbach’s Alpha and Descriptive Statistics. The results revealed that “top management commitment and support” ranked highest, followed by “budget and cost effectiveness” and “strategic planning,” as the most critical success factors for facilities management (FM) in Private Malaysia’s healthcare sector. The importance of top management commitment in the successful implementation of FM is showed, as their decisions and support are key to enhancing overall FM performance. This study is expected to benefit healthcare practitioners by raising awareness about the importance of critical success factors in FM implementation.

Facilities management; critical success factors; Malaysia private healthcare

This study explores how physical space and activity programming in common areas impact social adjustment among elderly residents in a non-profit nursing home in Thailand. It evaluates social adjustment levels, residents’ opinions about the importance of common areas, and satisfaction with both spatial and activity aspects to assess how these environments support residents’ adaptation and well-being in the nursing home. This quantitative study surveys 35 residents. Although the sample size is modest, it represents the entire population at the nursing home who are physically able to utilize these spaces, making it both contextually appropriate and representative. The survey assessed four domains: social adjustment; common area functionality (including social interaction, relationship building, activity socialization, and usage frequency); environmental satisfaction (covering spatial design, atmosphere, organized activities, and amenities); and demographic data. Descriptive statistics revealed that approximately half of the participants demonstrated a good level of social adjustment. Residents agreed on the importance of common areas in fostering interpersonal connection and engagement, though usage frequency remained moderate. Satisfaction with environmental elements was consistently high. The findings underscore the essential role of well-designed common areas in promoting social integration and emotional wellbeing. Design features such as layout flexibility, accessible pathways, and adaptable seating arrangements were identified as key contributors. The study offers valuable guidance for policymakers and architects in creating agefriendly environments that enhance the quality of life in the nursing home.

Elderly; social adjustment; common areas; nursing home; social interaction

Polymorphism in crystalline materials significantly influences their physicochemical properties, particularly in pharmaceutical applications. This study examined the impact of crystallisation methods on the formation of three Lisoleucine polymorphs (α, β, and γ) using polythermal and isothermal cooling, slow-solvent evaporation, and electric field-assisted crystallisation. X-ray powder diffraction confirmed their distinct crystalline structures, while differential scanning calorimetry and solubility analysis provided insights into thermal stability and dissolution behaviour. Cooling rates, supersaturation levels, and external factors such as mixing speed and electric fields strongly influenced polymorph formation. Rapid cooling favoured the metastable γ form, while controlled cooling rates led to the thermodynamically stable α form. The application of an electric field selectively promoted the β form, highlighting the role of external stimuli in directing polymorphic transitions. All L-isoleucine polymorphs exhibited identical flat hexagonal plate-like morphology and can only be distinguished by crystal apex angles. The α form, the most stable polymorph, had the highest melting point (288.6 °C) and the highest solubility. In contrast, β and γ forms are metastable, undergoing a solid-solid polymorphic transition (276.7 °C and 216.3 °C, respectively) to the thermodynamically stable α form. In aqueous solution, the β form showed the lowest solubility, indicating strong lattice stability, whereas the γ form displayed moderate solubility, compared to the a form which exhibited the highest solubility. These findings highlighted the critical role of crystallisation methods in controlling polymorphic outcomes, contributing to improved process control and formulation consistency in pharmaceutical and materials science applications.

Polymorphism, Crystallisation Method, L-isoleucine Polymorphs, Thermal Stability, Solubility

The Percut Watershed is vital in supporting the region’s ecological and socio-economic systems. However, the watershed has been increasingly impacted by rapid urbanization, deforestation, pollution, and unregulated land use, leading to environmental degradation and decreased water quality. This study aims to assess the current state of the Percut Watershed and evaluate the effectiveness of ongoing management practices. The research utilizes a combination of water quality analysis, land-use mapping through Geographic Information Systems (GIS), and stakeholder engagement to monitor key environmental indicators. The research results show that the Percut Watershed has a restored classification where the total value of the watershed carrying capacity reaches 101.75 (including the “moderate” criteria). Criteria that need attention are critical land and flood vulnerability. The land parameters in the Percut Watershed are considered quite good, with the erosion index in the Percut Watershed also having a moderate value; this is because, apart from natural topographic factors, there is also a mismatch in land use with existing land capabilities. The condition of the water system in the Percut Watershed is considered quite good because the flow regime coefficient value is low, which indicates the land’s ability to hold and store water is quite good high annual flow coefficient value. The use of regional space in the Percut Watershed is still good. Attention needs to be paid, especially to cultivated areas that are topographically less suitable for agricultural cultivation. Effective monitoring and evaluation are crucial for addressing these challenges and ensuring the sustainable management of the watershed.

Percut Watershed; monitoring and evaluation; sustainable watershed management; environmental conservation; water quality

The integrated of bio-based and sustainable composite materials had advanced the additive manufacturing (AM) industry, particularly for fused deposition modelling (FDM). Natural fibre-reinforced composites are gaining prominence due to their eco-friendly properties and compatibility with thermoplastics. This study investigates the influence of infill density and layer thickness on the mechanical properties of a novel pineapple leaf fibre (PALF)reinforced poly-lactic acid (PLA) composite filament used for 3D printing. The composite filament was fabricated through a structured process involving fibre crushing, sieving, mixing with PLA matrix and extrusion. To study the effects of infill density and layer thickness, a series of tensile and flexural test specimens were fabricated in accordance with ASTM D638 and D790 standards, respectively. A design of experiments (DoE) approach, specifically the Taguchi method, was employed to systematically evaluate the influence of layer thickness (0.1 mm, 0.2 mm, 0.3 mm), printing speed (25 mm/s, 50 mm/s, 100 mm/s) and infill density (25%, 50%, 100%), on the mechanical performance. The results revealed a significant correlation between the chosen FDM parameters and the mechanical properties of the PALF/PLA composite. Higher infill density generally contributed to improved tensile and flexural strength due to increased internal material support and reduced void formation. Conversely, lower infill densities, while reducing material consumption and printing time, exhibited reduced mechanical strength. Layer thickness also demonstrated the least influence on the mechanical properties. However, increased layer thickness reduced build time and material overlap. The interaction between infill density and tensile performance is also confirmed in this study with the score of r꞊0.9799 and r꞊0.9806. Negative effect between the printing speed and all mechanical properties with the range values between r꞊-0.0569 and r꞊-0.3608. The study concludes that optimizing these parameters is essential to balance mechanical strength, material efficiency, and printing time. This research contributes to the growing body of knowledge on sustainable 3D printing materials and provides practical insights for optimizing process parameters when using natural fibre composites. It highlights the potential of pineapple leaf fibre as a valuable reinforcement in biodegradable thermoplastics, promoting a circular economy and sustainable manufacturing practices.

Pineapple leaf fibre; poly-lactic polymer; taguchi method; tensile testing, flexural testing; correlation analysis

This study examines the effects of sugarcane bagasse on the properties of thermoplastic cassava starch (TPCS)/ beeswax (BW) composites. Composites containing sugarcane bagasse at varying ratios (10–30 wt.%) were prepared using dry mixing and hot pressing at 145°C. The environmental performance of TPCS/BW/sugarcane bagasse composites was assessed through key indicators such as water solubility and soil biodegradability. In addition, their water affinity characteristics including moisture content, moisture uptake, water absorption, thickness swelling, and morphological features were systematically evaluated to understand their interaction with humid environments. Results demonstrated that the inclusion of sugarcane bagasse reduced the weight loss of the composites during soil burial and water solubility testing, indicating a reduced degradation rate. Water and moisture absorption tests revealed that increasing the sugarcane bagasse ratio decreased the water and moisture absorption percentages, suggesting enhanced hydrophobicity of the materials. However, the overall moisture content increased with higher fibre loading due to the hydrophilic nature of sugarcane bagasse. Thickness swelling analysis showed that adding fibre from 0 to 30 wt.% increased the swelling percentage from 41.1% to 54.1% following two hours of immersion. Morphological examination supported these findings by revealing the composite’s internal structure and fiber-matrix interaction. This suggests that while sugarcane bagasse enhances moisture retention, it also increases expansion upon water exposure. Overall, sugarcane bagasse reduced the water affinity of thermoplastic starch (TPS) while increasing swelling and moisture content, demonstrating its significant influence on the composite’s structural and environmental performance.

Cassava starch; thermoplastic starch; beeswax; natural fibre; sugarcane bagasse fibre

Growing environmental concerns surrounding synthetic fibres have accelerated the search for sustainable alternatives, with recycled polypropylene (rPP) emerging as a cost-effective thermoplastic for Fused Deposition Modelling (FDM) due to its favourable mechanical performance. Nevertheless, FDM-fabricated thermoplastic composites frequently exhibit brittleness, limiting their structural reliability, while the integration of coconut fibre with rPP remains underexplored. This study aims to develop coconut fibre/rPP composite filaments, evaluate their tensile and flexural properties, and examine their potential for sustainable additive manufacturing. Composites were prepared by blending coconut fibre with rPP via hot pressing, followed by filament extrusion and the 3D printing of Honeycomb Sandwich Structures (HCSS). Mechanical characterisation demonstrated that HCSS containing 1 wt% untreated coconut fibre achieved the highest performance, with tensile strength increasing by approximately 5.4% and flexural strength by 10.2% compared with treated coconut fibre. In contrast, fibre contents above 3 wt% resulted in reduced ductility, confirming an inverse relationship between fibre content and the material’s ability to deform under tensile stress. Composites produced with treated fibres showed marginally improved properties; however, untreated fibres at low concentrations delivered competitive performance. These findings establish coconut fibre/rPP composites as a promising and environmentally responsible material system for FDM, with an optimal fibre content of 1 wt% balancing stiffness and ductility for enhanced mechanical reliability in 3D-printed structures.

Fused deposition modelling, coconut fibre, honeycomb sandwich structure, recycle polypropylene

In the field of hybrid composites, the combination of date palm fiber(natural fiber) with fiberglass (synthetic fiber) provides an alternative approach that emphasises on the advantages of both materials to create a composite with unique properties and applications. In this experimental study, hybrid composites were fabricated using different mixing ratio of the epoxy, fiberglass and date palm fiber. Every sample have different mixing ratio of glass fiber and date palm fiber but same epoxy with weight fraction 70% of matrix ratio while 30% balanced consist of glass fiber and dates palm fiber. The study evaluates the impact of this substitution on the overall performance of the hybrid epoxy composites, including aspects like tensile strength, flexural, impact test and morphological structure. For the tensile strength, sample A1(26% Glass Fiber, 4% Dates Palm Fiber) obtained the highest value 87.7MPa. Sample A4(30% Glass Fiber) is the highest value of flexural strength with 218.0MPa while Sample A2 with 101.4KJ/m2 for highest value of the impact test. Then, different structures such as fiber breakage, elamination and debonding are also observed by using Scaning Electron Microscope (SEM). However, the results offer valuable guidance for optimizing the mechanical performance of these composites in various applications It delves into the otential advantages and limitations of using date palm fiber as an alternative to conventional fiber glass in composite materials, aiming to assess the feasibility and efficiency of this substitution in various applications.

Hybrid composites; date palm fiber; fiber glass; epoxy matrix; mechanical properties; tensile strength, flexural strength; morphological analysis

The integration of reverse engineering (RE) and 3D scanning technologies has enhanced efforts to digitally preserve cultural heritage artifacts. However, ensuring dimensional accuracy during data processing, particularly in STL file generation, remains a critical challenge. This study investigates the digital reproduction of the Sundang Raja Muhamad, a 500-year-old Melaka weapon of significant historical value, by comparing the dimensional accuracy of two 3D scanning systems (Rexscan CS2+ and T-Track/T-Scan) and two STL workflows (Direct and Indirect). Direct STL files were produced with minimal manipulation, whereas Indirect STL files underwent additional refinement through surface reconstruction and mesh editing. Dimensional fidelity was evaluated using CAD-to-CAD and CAD-to-Part analyses at five key diameter points on the hilt. Results show that Direct STL files consistently preserved higher geometric accuracy, while Indirect STL files exhibited larger deviations due to extended mesh reconstruction, particularly in regions with limited scan accessibility. The most notable error occurred at Point E, where deviation exceeded the study’s ±0.30 mm tolerance threshold. In terms of scanning performance, Rexscan CS2 + achieved slightly superior overall dimensional accuracy (85.74%) compared to T-Track/T-Scan (84.84%), especially in areas with fine surface details. However, both systems demonstrated limitations when scanning recessed or obstructed features. The findings highlight the importance of selecting appropriate scanning technology and STL processing methods for heritage preservation. Direct STL workflows and tructured-light scanning provide more reliable geometric fidelity, whereas Indirect workflows are better suited for visual enhancement rather than precision applications.

Reverse Engineering; Digital Heritage Preservation; 3D Scanning; Dimensional Evaluation, STL File Accuracy

Today, the proliferation of smart devices and mobile networks, alongside activities like social networking, online gaming, and video streaming, has led to the generation of vast amounts of data. This surge in data consumption has placed significant pressure on mobile service providers to deliver higher data throughput to meet growing demands. As a result, mobile operators require efficient feature selection strategies to optimize throughput while ensuring the effective use of network resources. Feature selection is critical in improving network performance by identifying and prioritizing key parameters that significantly influence throughput. This paper introduces a hybrid feature selection approach that combines mutual information as a filter-based method with Recursive Feature Elimination using an Extra Tree Regressor as a wrapper-based method. The selected features are evaluated using three machine learning algorithms: Extra Tree Regressor, Random Forest, and Extreme Gradient Boosting. Experimental results indicate that the proposed feature selection method, when paired with the Extra Tree Regressor, outperforms both Random Forest and Extreme Gradient Boosting in terms of Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and the R-squared (R²) metric.

Hybrid feature selection; filter; wrapper; downlink throughput prediction; mobile network

The research aims to address the increasing energy consumption in Malaysia, particularly in academic institutions like UiTM Shah Alam. The excessive energy consumption at universities, exemplified by high electric bills due to the continuous operation of electrical components, poses a significant problem. Existing IoT energy monitoring systems lack scalability and real-time accuracy, hindering effective tracking and cost monitoring. The project focuses on designing and developing a system using NodeMCU Lolin and electrostatic sensors to monitor the energy usage of electrical appliances. The objectives include detecting current flow and evaluating power consumption, with the potential to affect the university’s energy monitoring and reduce expenses. The project’s scope involves hardware and range limitations, with specific target groups. The research methodology involves an experimental design and data analysis to develop and implement the IoT-based energy monitoring system, including sensor deployment and data integration development. This compact and simple integration system providing real-time insights into energy consumption patterns, contributing to energy conservation and sustainability was successfully developed. The system successfully analysed the power consumption of selected appliances, empowering users to have informed decisions and potentially reduce energy expenditures.

Internet of Things (IoT); energy consumption; Energy Monitoring System; NodeMCU Lolin; electrostatic sensors

The oil and gas sector deals with complexly hazardous environments, wherein the efficiency and safety with which operations are performed act as preconditions of success and sustainability. This paper focuses on how virtual reality (VR) technology, in particular the most advanced haptic feedback, applied superb and efficiently integrated VR technology to solve challenges and achieve higher performance at the sector level in the building council. By using authentic touch feedback, VR simulations afford a fully–immersive means through which workers can train, strategize and operate in virtual spaces, significantly reducing the risk of injury in the real world. The paper discusses several VR applications, like education, disaster response, and detailed design, emphasizing that haptic feedback is one of the crucial experiences to provide virtual experience. Integration of real-time data enhances operational decision-making, empowering teams to make informed decisions, while simulations improve emergency preparedness and readiness, enabling workers to be capable of managing critical events. Nonetheless, the case examples provide clear evidence that VR and haptics are part of a variety of key tools that can dramatically increase operational efficiencies and safety standards for a safer and more efficient tomorrow for oil and gas operations. It dives into the evolution of new top-of-the-line haptic techs, such as advanced force feedback gloves and full-body suits that provide extremely realistic tactile sensation, further augmenting VR-focused training programs. By harnessing VR and integrating haptic feedback technologies, the oil and gas industry can revolutionize training methods, emergency response planning, and operational decision-making, paving the way for a safer, more efficient, and technologically advanced future for the sector.

Virtual reality; haptic feedback; immersive training; operational efficiency; tactile sensations

Microplastics are flakes or pieces of plastic that are less than or equal to 5 mm in size. Microplastics can be found in the river due to the degradation process of plastic waste that is dumped into the river. Microplastics can settle in sediments for a long time, and their very small size has the potential to threaten biota through the food chain. If microplastics enter the lumen (channels in the body’s vessels), they can affect the immune system and cause intestinal swelling. Pekanbaru City is one of the areas that has the potential to be polluted by microplastics due to its rapid population growth. The city of Pekanbaru is crossed by the Siak River and several of its tributaries. This study aims to analyze the abundance of microplastics in the sediments of the Sail River, which is a tributary of the Siak River. Human activities around the river continue to increase, such as housing, workshops, kiosks, shops, restaurants, and others. The study was conducted in 3 sections, namely upstream, middle, and downstream, and each section had 3 sampling stations. Sediment samples were taken with an Ekman grab sampler. The results of the study indicated the presence of microplastic contamination in the sediments of the Sail River. The abundance of microplastics ranges from 5,335 - 21,374 particles/kg of dry sediment, where the value gets higher downstream. The types of microplastics found were fragments (39%), fibers (30%), and films (31%). The types of microplastics identified based on the Differential Scanning Calorimetry (DSC) test are nylon, polyester, polypropylene (PP) and polytetrafluoroethylene (PTFE). Statistical analysis was carried out to determine the correlation between microplastic abundance and environmental parameters (temperature, pH, and flow velocity). From the correlation test, it was found that flow velocity and temperature had a significant effect on the value of microplastic abundance (p<0.05). Awareness and collective action are required to address this issue. This study emphasizes the urgency of controlling microplastic pollution in rivers to protect the ecosystem and public health in Pekanbaru.

Abundance; Differential Scanning Calorimetry (DSC); microplastics; sail river; sediments

One of the major components in determining the stability of a model rocket is the rocket fin. In order to define the static stability of the model rocket, the relative positions of the centre of gravity and centre of pressure (CP) needs to be calculated first. The centre of gravity depends on the mass distribution of the rocket meanwhile the centre of pressure analysis requires the pressure distribution over the surface of the rocket body. This induces a much more challenging problem as in order to obtain the pressure distribution, wind tunnel testing is required. This present study aims to analyze the centre of pressure of model rocket using mathematical equations as well as computational fluid dynamics (CFD) with varying fins root chord. Mathematical prediction using theoretical Barrowman’s equation as well as OpenRocket software and CFD are used to obtain the centre of pressure as well as the static stability of the designed model rocket. Wind tunnel testing is not necessary as CFD analysis is able to provide the centre of pressure of the rocket. The data from all approaches was then compared and analyzed. It is found that the centre of pressure results from the theoretical Barrowman’s equation and CFD shows the same trend of linear increase in CP as the root chord increases. The stability obtained from the Barrowman’s equation ranging between 3.0 to 3.4 cal and OpenRocket at 2.91 to 3.27 cal shows percentage error of less than 5%. It is also found that the stability of the rocket using CFD analysis shows unstable rocket with stability range of 0.45 to 0.55 cal.

Rocket stability; Barrowman’s equation; centre of pressure; centre of gravity; CFD analysis.

Fused Deposition Modeling (FDM) as a 3D printing technology using thermoplastic polymer materials, influenced by parameters such as layer thickness. This thickness can be adjusted via the Z-axis during layer-by-layer deposition. However, increasing PLA layer thickness from 0.1mm to 0.3mm results in reduced mechanical properties due to increased heating and cooling cycles leading to residual stress accumulation. The effect of layer thickness was examined by printing PLA samples at different layer heights (0.1mm, 0.2mm, 0.3mm) and assessing them through impact testing. Results showed that a 0.1mm layer thickness recorded the highest average impact strength at 29.48 J/m and exhibited a 13.41% decrease in average impact strength compared to 0.2mm and 0.3mm layer thicknesses. Additionally, increased temperature also decreases the mechanical performance of PLA due to its low heat resistance. Therefore, samples for tensile, flexural, and compression testing were printed with a 0.1mm layer thickness and tested at different temperatures (30ºC, 55ºC, 80ºC). The tensile, flexural, and compression test results indicated that samples at 30ºC demonstrated the highest average strength values of 38.777 MPa, 82.917 MPa, and 69.059 MPa, respectively, compared to samples at 55ºC and 80ºC, showing decreases of 98.63%, 100%, and 98.80% from 30ºC to 80ºC. In conclusion, a 0.1mm layer thickness was identified as the best layer thickness compared to 0.2mm and 0.3mm, while samples at 30ºC exhibited the highest tensile, flexural, and compressive strengths compared to 55ºC and 80ºC.

Fused Deposition Modeling (FDM); Polylactic Acid (PLA); layer thickness

Slope stability issues are a critical aspect of civil engineering, particularly in tropical regions like Malaysia, where extreme weather fluctuations and high rainfall frequently trigger slope failures. The combination of steep terrain and intense precipitation significantly increases the risk of landslides, threatening infrastructure, human settlements, and environmental sustainability. This research investigates the impact of heavy rainfall on slope instability at the Aminuddin Baki Institute, Genting Highlands, Pahang, Malaysia, an area characterized by complex topography and high precipitation. Using advanced geotechnical tools, SEEP/W for simulating rainfall infiltration and SLOPE/W for stability analysis, this study assesses slope performance under saturated conditions and evaluates three stabilization techniques: micro-helical anchors, soil nailing, and geotextiles. The analysis showed that rainfallinduced infiltration reduced the slope’s Factor of Safety (FOS) to 1.257, indicating a failure-prone condition. Upon implementing reinforcement methods, FOS values improved to 1.685 (micro-helical anchors), 1.647 (soil nailing), and 1.605 (geotextiles), corresponding to percentage improvements of 34.0%, 30.9%, and 27.7%, respectively, relative to the unreinforced condition. All methods exceeded the JKR minimum safety threshold of 1.5 for reinforced slopes. Among them, micro-helical anchors demonstrated the best performance due to their deeper engagement and anchoring mechanism. These findings highlight the importance of selecting effective and siteappropriate reinforcement strategies. The study contributes valuable insights into cost-effective and sustainable slope stabilization techniques suitable for landslide-prone, high-rainfall environments.

micro-helical anchor; soil nailing; geotextile; landslide; rainfall infiltration; slope stability; back analysis; seepage analysis

Concrete structures are frequently exposed to aggressive environments, particularly infrastructure applications located in coastal areas, saline clays, and acidic soils. These harsh conditions speed up deterioration, reduce durability, and lead to frequent, costly repairs. Conventional concrete often cannot handle these environments over time, especially when high performance is required. These challenges highlight the growing demand for advanced, durable, and sustainable concrete materials. Therefore, this study investigates the effect of modified Styrene Butadiene Rubber (SBR) on the mechanical and durability properties of high-performance concrete reinforced with hybrid fibers. The concrete mix included steel fibers, polypropylene fibers, high-volume fly ash, and nano silica. SBR was added at 0% to 15% by weight of cement, with 2.5% identified as the optimal dosage based on fresh and hardened performance. Results indicate that SBR significantly improved workability, increasing the slump from 20 mm (control) to 95 mm (15% SBR). At 2.5% SBR, compressive strength increased by 4.2% at 7 days and 3.3% at 28 days. Flexural strength improved by 34.8% at 7 days and 18.4% at 28 days, while tensile strength increased by 21% and 25%, respectively. Durability also improved, with chloride penetration reduced by 15.2%, water penetration by 35.6%, and water absorption by 66.7%. These enhancements confirm that modified SBR, in combination with hybrid fibers and supplementary cementitious materials, improves both mechanical and durability performance. The addition of 2.5% SBR enhances both mechanical and durability properties of concrete, demonstrating optimal performance at this concentration.

Styrene butadiene rubber; high volume fly ash; nano silica; polypropylene fiber

Microwave imaging (MWI) has emerged as a promising non-invasive diagnostic technology in medical applications, offering significant advantages over conventional imaging modalities including reduced radiation exposure, cost-effectiveness, and enhanced patient comfort. This comprehensive survey presents a systematic review of MWI through a novel bifurcated taxonomy addressing both methodological aspects (imaging techniques, deep learning approaches, and antenna design) and application domains (breast imaging, brain imaging, and stroke diagnostics). The methodological analysis reveals substantial progress in reconstruction algorithms, with physics-assisted deep learning frameworks demonstrating superior performance in automated thresholding and bias reduction compared to traditional qualitative imaging methods. Advanced techniques like MDLI-Net and DL-MITAT have shown particular promise in handling sparse data scenarios. In antenna technologies, ultra-wideband antennas and miniaturized millimeter-wave sensors represent significant breakthroughs, with some systems capable of detecting malignancies as small as 1mm. Application-wise, brain imaging applications have achieved remarkable accuracy rates exceeding 94% using YOLOv5 models, while breast imaging systems demonstrate effective tumor detection in dense tissues where conventional mammography faces limitations. Despite these advancements in computational methods, particularly deep learning and sophisticated reconstruction algorithms, several challenges remain in translating MWI technology from experimental settings to widespread clinical adoption. Our contributions include structured analysis of recent advances in MWI techniques, critical insights into challenges across medical applications, and identification of research gaps and future directions. Key findings demonstrate that combining qualitative imaging with deep neural networks achieves reliable real-time reconstruction capabilities. While MWI shows considerable potential as a safe, cost-effective alternative to traditional imaging techniques, particularly for breast and brain imaging, further research in computational efficiency, clinical validation, and standardization protocols is necessary for successful clinical implementation across diverse healthcare settings.

Microwave imaging; medical diagnostics; deep learning; breast cancer detection; brain imaging; stroke diagnostics; antenna design; reconstruction algorithms; non-invasive imaging; biomedical engineering

Urban waterfronts are increasingly recognized for their potential to integrate environmental, social, and cultural values, making them essential for sustainable development. While many studies have focused on technical solutions to improve sustainability, few have addressed the significance of the sense of place in fostering environmental stewardship in waterfront areas. This research aims to explore how the sense of place, encompassing cognitive, affective, and behavioral aspects, contributes to environmental sustainability in urban waterfronts. A mixedmethods approach was adopted. Quantitative data were collected through a convenience sampling questionnaire survey of waterfront users (n = 326) to identify significant indicators of the sense of place. Additionally, qualitative insights were obtained from semi-structured interviews with 12 frequent waterfront users to understand how the meanings associated with a place influence sustainable behaviors. The results highlight eight crucial factors that strengthen the sense of place and promote environmental sustainability: 1) attractive landmarks or focal points, 2) regional characteristics that create narrative landscapes, 3) well-maintained surroundings, 4) community events, 5) welcoming public spaces, 6) conservation of cultural and historical heritage, 7) participatory activities, and 8) informative signboards. This study provides urban designers, waterfront developers, and policymakers with a theoretical framework for developing urban waterfronts that enhance community attachment and encourage sustainable practices. It also delivers valuable insights for promoting sustainability in underdeveloped or rural waterfront regions.

Urban waterfront; sense of place; environmental sustainability; Partial Least Squares Structural Equation Modeling (PLS-SEM)

One of the primary challenges in the advancement of microwave sensor technology lies in achieving an optimal balance between miniaturization and operational performance. Miniaturization often leads to a reduction in sensitivity and measurement accuracy, thereby limiting the practical applicability of compact microwave sensors. To address this issue, this study proposes the development of a high-precision microwave sensor based on a Defected Ground Structure (DGS), fabricated on a 1.6 mm-thick FR-4 substrate. The sensor design incorporates a 2-Ring Square Split Ring Resonator (SSRR) embedded within the DGS configuration to enhance electromagnetic field confinement and improve sensing capabilities. The sensor’s performance was systematically evaluated by examining the effect of dimensional scaling on its sensitivity. In particular, variations in the resonant frequency of the transmission coefficient (𝑆21) were analyzed as a function of sensor size reduction. Through an extensive optimization process, the sensor’s physical footprint was successfully reduced by 58%, without compromising the integrity of the DGS architecture. Prior to miniaturization, the sensor demonstrated an accuracy of approximately 81%. Following the size reduction, accuracy markedly improved to 98%, representing a significant enhancement in detection capabilities. This improvement is primarily attributed to the optimization of the surface current distribution intensity, which resulted in stronger localized electromagnetic fields and heightened responsiveness to minor perturbations in the sensor’s environment. Thus, the optimized miniaturized sensor presents a promising solution for high-precision, compact microwave sensing applications, maintaining high sensitivity and reliability despite a substantial decrease in physical dimensions.

High sensitivity; high accuracy; microwave sensor; Defected Ground Structure; Split Ring Resonator; miniaturization

Torrefaction is a thermochemical process in which oil palm waste is heated to generate high calorific value, energy density, and a storable green fuel. This work aims to generate a computational model that can simulate the torrefaction process for the empty fruit bunch (EFB) and evaluate the model outcomes with and without the reaction kinetics. It is shown that the solid carbon mass fraction reduced steadily against temperature, while other liquids and gases increased as more volatile matter was released due to the decomposition of hemicellulose in the biomass. The heat duty decreased when the reactor’s temperature increased, which is due to the decreased activation energy required for the decomposition reaction, as the increase of extractives, including the condensable and non-condensable products, acted as the catalyst for the decomposition to occur. The kinetic involvement in the model is proven to increase the accuracy of the product distribution as it has a higher similarity of the trend of distribution towards the literature compared to non-kinetics, specifically 86.41%, 76.05% and 89.23% error reduction for solids, liquids and gases, respectively. The heat duty of the kinetic model is more realistic due to the involvement of kinetic parameters in the study. In conclusion, applying computational and kinetic modelling can simulate the torrefaction process and will be further introduced to the industry.

Oil palm waste; torrefaction; process simulation; kinetics; Aspen Plus

This study investigates the influence of rainfall patterns on salinity dynamics in estuarine environments through laboratory experiments and MIKE21/3 numerical modelling. A meandering channel simulated varying freshwater flow rates (2.4 L/s, 3.2 L/s, and 4.8 L/s) representing low, moderate, and heavy rainfall scenarios. The study aims to quantify how rainfall-induced freshwater inflows affect salinity intrusion length and concentration in meandering estuaries, and to validate experimental results with numerical modelling. Salinity measurements were taken across multiple cross-sections and depths, supported by tracer visualization, and further analyzed using MIKE 21/3 simulations calibrated against observed data. Model performance was evaluated using R², NSE, and RMSE statistical indicators. Results show that increased freshwater discharge significantly reduces salinity intrusion length, with heavy rainfall decreasing salinity intrusion by up to 30%. Meander bends generated localized salinity gradients due to secondary circulation. The MIKE 21/3 model strongly validated experimental findings (R² > 0.9; NSE > 0.5), confirming its robustness in replicating estuarine salinity dynamics. Unlike previous studies which emphasized straight channels or large-scale rainfall data from remote sensing, this research integrates controlled flume experiments with three-dimensional modelling in a meandering channel. This combined framework provides new insights into tropical rainfall–salinity interactions, addressing a key research gap and offering practical contributions for estuarine water management under climate change.

Salinity dynamics; rainfall impact; estuarine environments; MIKE 21/3 modelling; laboratory experiments

This study aims to enhance the performance of cadmium telluride (CdTe) thin film solar cells through a comprehensive investigation of various buffer layer materials and their influence on device efficiency. Utilizing the SCAPS-1D simulation tool, initially a baseline model has been established for the CdTe solar cell, characterized by a 5 µm thick CdTe absorber layer, a 25 nm thick CdS buffer layer, and carrier concentrations of 10¹⁷ cm^-3 for CdTe and 10¹⁸ cm^-3 for CdS. This baseline configuration yielded key photovoltaic parameters: open-circuit voltage (Voc) of 1.0686 V, short-circuit current density (Jsc) of 23.8378 mA/cm², fill factor (FF) of 88.13%, and an overall efficiency (η) of 22.45%. Building upon this, various buffer layers, including materials such as MZO (magnesium zinc oxide), were introduced to evaluate their impact on device performance. Results indicated that the incorporation of MZO, particularly when used without the traditional CdS layer, significantly enhanced the photovoltaic parameters, achieving an efficiency of 23.66%. Additionally, the MZO buffer layer contributed to improved device stability under elevated temperature conditions and in the presence of structural defects, indicating superior robustness compared to conventional buffer configurations. These findings suggest that optimizing buffer layer materials, especially using MZO, can lead to notable improvements in the efficiency of CdTe solar cells. In conclusion, this research provides valuable insights into material selection and device architecture, paving the way for the development of more efficient thin film photovoltaic technologies.

CdTe thin film solar cell; buffer layer; thickness; carrier concentration; Scaps 1-D

The construction industry in Malaysia faces increasing pressure to adopt sustainable practices due to its high energy consumption and significant greenhouse gas emissions. Green purchasing (GP), defined as the purchasing of goods and services that minimise environmental impact through low-carbon, low-waste, and energy-efficient principles, is a critical strategy for reducing the sector’s ecological footprint. However, the industry’s limited adoption of green purchasing and the dominance of unsustainable building practices continue to pose challenges. This study investigates the influence of government regulations, corporate factors, and material suppliers on the adoption of green purchasing among Malaysian construction firms. A cross-sectional survey was conducted with 187 (G7) contractor companies registered with the Construction Industry Development Board (CIDB). Data were analysed using partial least squares structural equation modelling (PLS-SEM). The results confirm that government regulation (β = 0.148, p < 0.05), corporate factors (β = 0.265, p < 0.01), and material suppliers (β = 0.405, p < 0.001) each have a positive and significant effect on green purchasing adoption, with supplier influence showing the strongest impact. These findings highlight the importance of establishing supportive regulatory frameworks, fostering internal corporate commitment, and strengthening long-term supplier partnerships to drive sustainability in the construction sector. The study contributes to the understanding of green purchasing adoption in developing countries and offers practical insights for policymakers and industry leaders seeking to align construction procurement with national sustainability goals.

Green purchasing adoption; green purchasing influencing factors; construction companies; sustainability; Malaysia

The oil palm tree (Elaeis guineensis) is a major agricultural commodity in Malaysia, significantly contributing to the production of crude palm oil (CPO). Within the milling process, sedimentation is a critical stage that directly influences the quality of the final CPO product. Among the key parameters affecting sedimentation efficiency, fluid velocity plays a crucial role, particularly in controlling sludge blanket dynamics. This study investigates the optimal fluid velocity to enhance sedimentation performance, ensuring compliance with industry quality standards while minimizing the outflow cycle time of sedimentation tanks. To achieve this, Computational Fluid Dynamics (CFD) simulations were employed using COMSOL Multiphysics v6.3. A two-dimensional (2D) model of a sedimentation tank measuring 12.0 m in width and 4.0 m in height (total area: 48.0 m²) was developed. Inlet velocities ranging from 0.2 to 1.5 m/s were simulated using two turbulence models: k-ε and k-ω to assess their influence on flow behaviour, pressure distribution, and mass flux. Simulation results indicate that inlet velocities between 0.9 and 1.5 m/s yield optimal separation efficiency, minimizing oil losses to the sludge and maximizing oil recovery at the upper outlet. The study demonstrates the capability of CFD as a powerful tool for accurately simulating sedimentation tank performance, enabling real-time analysis and optimization of key operational parameters. This approach presents a cost-effective and practical solution for improving CPO quality and sedimentation efficiency in the palm oil mills, with the added benefits of reducing waste and enhancing overall process sustainability.

Crude Palm Oil (CPO); sedimentation, Computational Fluid Dynamics (CFD); optimization

Ensuring food security in arid and resource-constrained regions requires precise knowledge of landscape capabilities to optimize agricultural planning. In Uzbekistan’s Central Zarafshan Basin, where climatic variability, limited water resources, and diverse geomorphic conditions pose significant challenges, identifying land suitable for sustainable cultivation is critical. However, there remains limited spatially explicit evidence on how natural landscape characteristics can be systematically linked to agricultural suitability. This study addresses this gap by integrating remote sensing, GIS-based spatial modeling and agro-climatic evaluation frameworks to classify piedmont plains and alluvial landscapes according to their agricultural potential. High-resolution Landsat-8 imagery and agro-ecological criteria developed by Kogay and Rodionov were applied to assess biophysical variables including slope, soil composition, vegetation cover, hydrology, and population density. The results delineate four suitability classes, marginally suitable, moderately suitable, suitable and highly suitable, highlighting particularly promising zones in proluvial-alluvial plains and oasis areas, while steep, saline and eroded terrains were less favorable. Microzonal analysis further identified opportunities for sustainable intensification in foothill and alluvial fan systems through improved irrigation and land management. Overall, the study demonstrates the value of geospatial technologies and agro-climatic zoning in guiding climate-resilient agriculture, offering a scientifically informed basis for enhancing productivity, resource efficiency and long-term food security in Uzbekistan and other semi-arid regions.

Food Security, Foothill Plain, Alluvial Fan, Landscape, Assessment, Vegetation Index

This study aims at the development of TrizMinds teaching aids using Thunkable software for the subtopic of Physical Contradictions in Design and Technology (RBT) Form 2. The main problem is divided into three aspects, namely the inappropriateness of “Chalk and Talk” teaching, the focus of 21st century learning that is studentcentered, and technology needs in education according to the Malaysian Education Development Plan. The objectives of the study include the development of an E-Module to identify learning needs based on the Thunkable application in Form 2 RBT. This study uses the design of the E-Module development with the ADDIE model, which involves analysis, design, development, implementation, and evaluation, as well as applying constructivism theory. Semi-structured interviews with three teachers who have taught for 3 years in RBT subjects at SMK Pendamaran Jaya to obtain information on the need for teaching aids to be produced. In connection with that, a second semi-structured interview was conducted with three experts, namely two experienced lecturers in the field of RBT who have served for 10 years and an RBT teacher who has served for 5 years as a validity assessor expert in providing comments on the built module. The results of the interview show that this TrizMinds Learning E-Module can help students understand the topic of physical contradiction for the subtopics of space separation and time separation. Therefore, various suggestions and improvements have been put forward to improve this application in order to achieve the educational goals of the School Transformation Program 2025 (TS25), which is part of the efforts of the Malaysian Ministry of Education towards improving the quality of students and schools in order to be in line with the current needs of education in the country.

Physical contradictions; 21st-century learning; education technology; Reka Bentuk dan Teknologi (RBT)

Energy Management Systems (EMS) play a vital role in optimizing energy usage, reducing environmental impact, and enhancing energy efficiency in both microgrid and residential applications. The increasing complexity of energy systems, coupled with advancements in artificial intelligence (AI) and demand response mechanisms, has led to rapid evolution in EMS research. However, this progress has resulted in fragmented knowledge, making it difficult to discern overarching trends and identify key contributions in the field. This study addresses the following questions: What are the major trends, influential works, and future directions in EMS research over the past five decades? To answer this, a comprehensive scientometric analysis of 3,709 publications (1973–2023) was conducted using the Web of Science database and analyzed through CiteSpace. The analysis reveals significant shifts in EMS research, transitioning from traditional microgrid-focused studies to broader applications in smart homes, AI-driven load scheduling, and advanced optimization techniques. Key findings highlight the growing emphasis on integrating AI, machine learning, and real-time decision-making to enhance the responsiveness and sustainability of EMS. Additionally, the study identifies critical contributions from influential publications that provide a roadmap for developing next-generation EMS frameworks. These works emphasize the importance of addressing emerging challenges, such as the need for adaptive load management, enhanced grid stability, and increased reliance on renewable energy sources. By synthesizing historical trends and future directions, this study offers valuable insights for researchers, practitioners, and policymakers to advance innovations in energy management, contributing to a more sustainable and efficient energy landscape.

Energy management systems; environmental impact; sustainability; scientometric analysis

Microalgae protein hydrolysate enriched in peptide was produced by the enzymatic hydrolysis of Nannochloropsis sp. To obtain smaller peptides fractions, an ultrafiltration membrane was used to fractionate the hydrolysate, which contained a wide range of peptide sizes. However, a significant limitation of ultrafiltration membranes is flux reduction time due to fouling. This study investigates the influence of operational parameters variables such as flow rate, transmembrane pressure and pH on flux reduction and membrane fouling behaviour. Three membrane configurations (10 kDa, 5 kDa and two-stage 10/5 kDa) were evaluated. Kumar’s pore-blocking models were applied to the optimal configuration with the largest permeate flux to analyse fouling mechanism. The results showed that permeate flux was declined over time and stabilized within 20 to 35 minutes under all conditions. The best performance for microalgae protein hydrolysate fractionation was observed with two-stage 10/5 kDa membrane at a flow rate of 23 ml/min, TMP of 1.5 bar, and pH 2. The standard pore-blocking model effectively predicted the flux reduction, confirming the role of membrane fouling in performance decline. This study highlights that optimizing ultrafiltration membrane parameters and selecting the appropriate membrane configuration can mitigate fouling effects, enhancing flux stability and peptide transmission.

Microalgae protein hydrolysate; membrane fouling; flux reduction; ultrafiltration membrane; pore blocking model

Sodium bismuth titanate (NBT) has emerged as a promising material for energy storage and dielectric applications in advanced ceramics, particularly when modified through substitutional doping. This systematic literature review evaluates the impact of various substitutional dopants on the structural, electrical, and dielectric characteristics of NBT-based ceramics, addressing the urgent need for a comprehensive understanding of how compositional modifications can be leveraged to optimize material performance. A critical challenge lies in determining the most effective dopants and concentrations that can simultaneously enhance energy storage density, improve dielectric properties, and maintain thermal stability under demanding operating conditions. To address this, an extensive analysis of academic publications indexed in Scopus and Web of Science was conducted, focusing on studies published between 2022 and 2024. Following the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) framework, 29 relevant studies were identified and systematically examined. The findings were organized into three thematic areas: (1) phase transitions induced by dopants that enable superior energy storage performance, (2) microstructural tailoring to refine electrical conductivity and dielectric behavior, and (3) structural modifications that contribute to functional stability across wide temperature ranges. Evidence from these studies consistently indicates that both A-site and B-site substitutional doping particularly with rare earth and transition metal ions can significantly broaden the functional capabilities of NBT ceramics. In summary, this review emphasizes the innovative role of substitutional doping in advancing NBT-based ceramics and provides a valuable reference point for future research aimed at optimizing lead-free dielectric materials for high-performance capacitors and energy storage applications.

Sodium bismuth titanate; (NBT); substitution; doping; energy storage; systematic literature review

In Pakistan, rapid urbanization and construction demand have depleted clay resources and increased environmental degradation. This study explores a novel approach to enhance the sustainability of fired clay bricks by incorporating almond shell powder and walnut shell powder as additive at varying concentrations (A5, A10, A15, W5, W10, and W15). The raw materials were analysed using X-ray diffraction to assess their mineral composition. Experimental results show that increasing additives content leads to a higher loss on ignition, with maximum values of 17.2% for A15 and 12.6% for W15. Water absorption also increases significantly, reaching 25% for A15 and 26% for W15, indicating higher porosity. As additives concentration rises, the bulk density of the bricks decreases, with values of 1186 kg/m³ for A15 and 1360 kg/m³ for W15. While compressive strength decreased with the increase in additives content, the bricks containing lower additives concentrations (A5 and W5) exhibited optimal strengths of 14.85 MPa and 15.2 MPa. Scanning electron microscopy (SEM) revealed a clear correlation between additives concentration and pore formation within the bricks. Energy dispersive spectroscopy (EDS) was utilized to further investigate the elemental composition. Notably, thermal insulation properties improved with higher additives concentrations, suggesting the potential for enhanced energy efficiency in construction applications. Results highlight the potential of almond and walnut shell powders, as a sustainable alternative to traditional claybased bricks, offering a pathway to reduce the environmental impact of construction materials while mitigating the depletion of clay resources.

agricultural waste; eco-friendly; sustainable development; composites; microscopic characteristics

Geographic Information Systems (GIS) play a pivotal role in earthquake risk assessment, providing a comprehensive framework for understanding, analyzing, and mitigating the impact of earthquakes. This article explores the integration of GIS conceptual design with Entity-Relationship (ER) diagram development, enhancing the spatial database design for earthquake risk assessment. The complexity of earthquake events introduces challenges in designing a conceptual model that accounts for their dynamic nature, including aftershocks and evolving seismic patterns, demanding a framework capable of capturing these layered interactions. Achieving high spatial resolution to address localized risks while managing large datasets adds another layer of complexity, necessitating careful design considerations. The goal of this research is to develop a GIS-based conceptual design for earthquake risk assessment. This involves identifying essential spatial and attribute data; conducting a systematic review and user requirement analysis; and developing an ER diagram to represent the conceptual structure. The resulting model organizes data into three core modules: the hazard layer, cadastral layer, and potential risk layer. The cadastral layer supports both hazard and risk analyses. The hazard layer incorporates fault lines, historical earthquake data, geology, and seismic zones, aiding in land-use planning and emergency responses. The potential risk layer produces seismic vulnerability maps that encompass social, economic, physical, and environmental aspects. These outputs contribute to determining the earthquake risk levels for both populations and constructions, providing valuable insights for risk assessment and management. By integrating ER diagram development, this approach enhances data organization and supports more effective earthquake risk management through a robust and scalable GIS framework.

GIS conceptual design; earthquake risk assessment; ER diagram

This paper presents the design, modeling, and experimental assessment of a wrist exoskeleton actuated by Shape Memory Alloy (SMA) springs to support flexion-extension and radial-ulnar deviation of the wrist. A dynamic model based on the Euler-Lagrange formulation was developed and simulated to estimate the joint torque requirements, which ranged from 0.26–0.32 Nm for standard wrist movements. A prototype is fabricated and tested incorporating four SMA spring actuators fixed on an arm splint, with targeted actuation for generating different wrist motion. Experimental findings revealed that the prototype delivered torque values surpassing simulation requirements for flexion (0.332 Nm) and extension (0.328 Nm) motions, whereas lower torque was observed for radial and ulnar deviations, likely due to actuator placement and frictional losses. The actuation cycle frequency for flexion-extension was measured to be 0.018 Hz, primarily constrained by the thermal characteristics of the SMA springs. Another important observation is enhanced speed during SMA reversal motion (from extension to flexion) resulted from antagonistic actuation of the SMA. To further improve the torque and speed generation, an optimal SMA actuator with reduced thermal mass (thinner diameter, bundle configuration) and active cooling can be designed. Overall, the SMA-driven wrist exoskeleton exhibits promising potential as a lightweight, wearable system for effective wrist joint assistance.

Shape memory alloy; actuator; artificial muscle; wrist exoskeleton; flexion-extension; radial-ulnar deviation

Millimeter-wave 5G devices need compact MIMO arrays that provide high gain while minimizing inter-port coupling; conventional arrays struggle to balance gain, bandwidth, and isolation in small footprints.This article discusses a compact, high-performance four-port orthogonal MIMO antenna system for millimeter-wave 5G uses that works in bands n257(26.50–29.50 GHz), n258(24.25–27.50 GHz), and n261(27.50–28.35 GHz). Each of the four ports has a 4x4 sub-array with a total of 16 elements (individual element small size with dimensions of 0.32λ0×0.26λ0 excluding feed), along with a 13x10 double-negative (DNG) metamaterial reflector. The antenna is built on a Rogers 5880 substrate, which is well-known for having great dielectric characteristics. The antenna has dimensions of 4.86λ₀ × 4.81λ₀ × 0.073λ₀, but it has a high gain of 14.3 dBi, a wide spread of 8.06 GHz, and a 97% radiation efficiency. Adding metamaterials that have negative permittivity, permeability, and refractive index greatly improves performance by getting excellent isolation of more than -32.7 dB and increasing the bandwidth by 200 MHz. The metamaterial’s unit cell was modeled with CST and validated by showing an identical circuit in ADS. A prototype antenna design was Fabricated and measured and the results were closely matched the simulations. Five machine-learning regression models were also used to verify and evaluate the antenna’s performance, including its gain. Support Vector Regression (SVR) and Extreme Gradient Boosting (XGB) methods were the most accurate, with 96% or more prediction accuracy. The results show that the suggested MIMO antenna system based on metamaterials works well and can be used in real-life 5G scenarios.

MIMO antenna; antenna array; 5G; metamaterial; gain, ML