Due to growing environmental concerns and regulations limiting the use of harmful and toxic synthetic corrosion inhibitors, there is a high demand for sustainable corrosion inhibitors. In this study, a green and rapid technique was used to synthesize amide N-(4-aminobutyl)palmitamide (BAPA) which yielded 91.17% of the product within 2 min, compared to a low yield of 75-80% and a very long 8-10 h reaction time with the conventional thermal condensation method. The chemical structure of BAPA was analyzed by FT-IR, 1HNMR and 13CNMR spectra, as well as CHNS elemental analysis. When applied to mild steel exposed to 1 M HCl, BAPA delayed and reduced corrosion by adsorbing to the steel surface to form a protective layer. The inhibition efficiency increased with increasing amide concentration, and maximal inhibition of 91.5% was observed at 0.5 mM BAPA. The adsorption of BAPA on mild steel in an acidic solution was studied and inhibition performance was correlated with the calculated adsorption-free energy ΔGads, indicating good agreement between the experimental and adsorption findings. Surface morphology of untreated and treated mild steel coupons was evaluated by SEM, and based on density functional theory (DFT) computations and atomic charges analysis, a stronger interaction was observed between BAPA and mild steel surface leading to the formation of a compact protective film on the metallic surface. This protective film is attributed to the presence of nitrogen atoms and carbonyl group in the chemical structure of BAPA.
Radiation shielding incorporates material between the radioactive source and environment to decrease exposure to hazardous radiation. It remains to be seen whether the addition of nanoparticles effectively increases the protection of tellurite glass system from further degradation under irradiation conditions. This study revealed the gamma radiation effects on tellurite glass. The tellurite glass samples were irradiated with 50 kGy and 100 kGy gamma ray, and subsequently analysed using X-ray diffractometer (XRD), atomic force microscopy (AFM), and ultraviolet-visible spectroscopy (UV-Vis). Gamma radiation increased the creation of non-bridging oxygen (NBO) and caused colour change on TZNETi and TZNETiAl glasses. Consequently, the addition of aluminium oxides (Al2O3) was found to lower the density of glass systems. The glass samples surface roughness increased, while the optical transmission spectra decreased after 50 kGy of gamma ray irradiation. Nevertheless, the glass system maintained its transparency even after irradiation. The mass attenuation coefficient (MAC) values represented the shielding effectiveness demonstrated by the investigated glass with the addition of Al2O3. The physical, structural, optical, and radiation shielding properties showed that 69.1TeO2-20ZnO-9Na2O-1Er2O3-0.3TiO2-0.6Al2O3 (TZNETiAl) sample exhibited strong shielding properties amongst the fabricated tellurite samples.
The structural properties and characteristics of date palm fiber-based low-cost carbon nanotubes (CNTs) and nanostructured powder activated carbon (DP-NPAC) are investigated. The DP-NPAC and CNTs are prepared using an environmentally friendly method, and characterized and analyzed using field emission-scanning electron microscopy (FESEM), transmission electron microscopy (TEM), and X-ray diffraction (XRD). The results have showed that both DP-NPAC and CNTs possess crystallite structure, nano-scale, high capacity, cost-effective for multi-application that make them efficient for future fabrication and manufacturing. It is supposed that DP-NPAC biomass is to be used as potential and cost-effective precursor for synthesized CNTs.
This study introduces a compact double negative metamaterial (DNM) composed of three split rings connected slab resonator (TSRCSR) based double-layer design with a high 13.9 EMR (effective medium ratio) value. A double-layer patch is introduced to achieve the novel double negative properties, including negative behaviours of effective medium parameters, including refractive index, permittivity, and permeability with a high effective medium ratio for the miniaturised size of the introduced unconventional material that is highly suitable for microwave S and C band covering applications. The popular low-loss Rogers RT5880 (thickness 1.575 mm) substrate and copper resonator materials are utilized to develop the metamaterial unit cell that offers triple resonance between frequencies from 1 to 8 GHz. Therefore, the proposed metamaterial exhibits resonance peaks at 2.75, 5.2, and 6.3 GHz, suitable for radar, communication satellite, and long-distance telecommunication applications, respectively. The commercially available simulator known as Computer Simulation Technology (CST) is adopted to develop and simulate the 8 × 8 mm2 metamaterial design. The simulation results of the introduced TSRCSR design structure were verified by adopting the Ansys High-Frequency Structure Simulator (HFSS). Furthermore, it was then proved with the help of equivalent circuit model findings gained from the Advanced Design Structure (ADS) software. On the other hand, the analytical results were further validated by measuring the TSRCSR design utilizing a Vector Network Analyzer (VNA). These analyses become one of the novelties of this work, where the compact TSRCSR metamaterial successfully gained small discrepancies in transmission coefficient values when compared to both analytical and measurement results. The proposed metamaterial is highly suggested for communication devices for its extensive effective characteristics and compactness.
This study developed a metamaterial-inspired split-ring resonator (SRR) based inversion symmetry-shaped structure for airport surveillance radar and local area wireless network applications. The proposed device exhibited suitability for S- and C-band applications, featuring distinct resonance peaks at 2.8 and 4.9 GHz, respectively. The two-layer double negative metamaterial unit cell comprises a copper-based resonator, patch, and a low-loss substrate material known as Rogers RT5800 with a thickness of 1.575 mm. The 8 × 8 mm2 structure unit cell was identified with an effective medium ratio (EMR) of 13.4 at the resonance peak of 2.8 GHz. With the alteration of the metamaterial unit cell structure, the electric field, surface current distribution, magnetic field, and design evolution were observed, analysed, and investigated in this study. Meanwhile, the retrieved data from the reflection and transmission coefficients from CST Microwave Studio were validated using the Ansys High-Frequency Structure Simulator (HFSS) software. A Vector Network Analyzer (VNA) further measured the numerical results. Based on the findings, the proposed novel double negative metamaterial device is suitable for radar communication and satellite applications, especially airport surveillance radar (ASR) and wireless local area network (WLAN), due to its high EMR at the desired resonance frequency.
Social media's significance in higher education has increased due to its capacity to enhance participation, communication, teamwork, and information sharing. Important notifications, updates, and reminders can be promptly received by all members of the university community, assuring that information is shared with everyone. The objective of this study is to develop a model for a Customer Relationship Management (CRM) system in higher education that is based on social media and intends to increase student satisfaction, loyalty, and profitability. It blends the idea of trust with Delone Mclean success model. Partial Least Squares-Structural Equation Modeling (PLS-SEM) was used to evaluate the data that was gathered from 606 Jordanian private university students via an online survey. The findings demonstrated that user satisfaction affects social media usage and that system quality, information quality, service quality, and trust must all be considered to attain user satisfaction. This study examines how to create a CRM system based on social media in Jordanian universities. The study makes significant contribution to the development criteria for evaluating social media-based CRM systems in higher education institutions, and its broad conceptual model cloud be expanded and tested in future studies. This study is the first to investigate the use of social media to develop a CRM system for Jordanian universities. This is a novel study, and the work significantly create a set of criteria for evaluating social media-driven CRM systems in higher education. The study's expansive the model may serve as the base for more research in this field.
The HT-29 cell line, derived from human colon cancer, is valuable for biological and cancer research applications. Early detection is crucial for improving the chances of survival, and researchers are introducing new techniques for accurate cancer diagnosis. This study introduces an efficient deep learning-based method for detecting and counting colorectal cancer cells (HT-29). The colorectal cancer cell line was procured from a company. Further, the cancer cells were cultured, and a transwell experiment was conducted in the lab to collect the dataset of colorectal cancer cell images via fluorescence microscopy. Of the 566 images, 80 % were allocated to the training set, and the remaining 20 % were assigned to the testing set. The HT-29 cell detection and counting in medical images is performed by integrating YOLOv2, ResNet-50, and ResNet-18 architectures. The accuracy achieved by ResNet-18 is 98.70 % and ResNet-50 is 96.66 %. The study achieves its primary objective by focusing on detecting and quantifying congested and overlapping colorectal cancer cells within the images. This innovative work constitutes a significant development in overlapping cancer cell detection and counting, paving the way for novel advancements and opening new avenues for research and clinical applications. Researchers can extend the study by exploring variations in ResNet and YOLO architectures to optimize object detection performance. Further investigation into real-time deployment strategies will enhance the practical applicability of these models.
This study aimed to evaluate the clinical outcomes of patients with acute heart failure (AHF) stratified by mitral regurgitation (MR) in the Arabian Gulf. Patients from the Gulf CARE registry were identified from 47 hospitals in seven Arabian Gulf countries (Yemen, Oman, Kuwait, Qatar, Bahrain, the United Arab Emirates, and Saudi Arabia) from February to November 2012. The cohort was stratified into two groups based on the presence of MR. Univariable and multivariable statistical analyses were performed. The population cohort included 5005 consecutive patients presenting with AHF, of whom 1491 (29.8 %) had concomitant MR. The mean age of patients with AHF and concomitant MR was 59.2 ± 14.9 years, and 63.1 % (n = 2886) were male. A total of 58.6 % (n = 2683) had heart failure (HF) with reduced ejection fraction (EF) (HFrEF), 21.0 % (n = 961) had HF with mildly reduced EF (HFmrEF), and 20.4 % (n = 932) had HF with preserved EF (HFpEF). Patients with MR had a lower haemoglobin (Hb) level (12.4 vs. 12.7 g/dL; p
Pregnancy carries high medical and psychosocial risks that could lead pregnant women to experience serious health consequences. Providing protective measures for pregnant women is one of the critical tasks during the pregnancy period. This study proposes an emotion-based mechanism to detect the early stage of pregnancy using real-time data from Twitter. Pregnancy-related emotions (e.g., anger, fear, sadness, joy, and surprise) and polarity (positive and negative) were extracted from users' tweets using NRC Affect Intensity Lexicon and SentiStrength techniques. Then, pregnancy-related terms were extracted and mapped with pregnancy-related sentiments using part-of-speech tagging and association rules mining techniques. The results showed that pregnancy tweets contained high positivity, as well as significant amounts of joy, sadness, and fear. The classification results demonstrated the possibility of using users' sentiments for early-stage pregnancy recognition on microblogs. The proposed mechanism offers valuable insights to healthcare decision-makers, allowing them to develop a comprehensive understanding of users' health status based on social media posts.
The Metaverse, underpinned by its technical infrastructure, heavily relies on user engagement and behavior for successful integration into educational settings. Understanding its driving factors is essential for such a platform to transition from theory to practice, especially in educational settings. However, these factors remain elusive due to inconsistencies in infrastructure and environments. Therefore, this systematic review aims to fill this void by presenting an integrative view on Metaverse adoption in education. This is achieved via three primary dimensions: establishing a taxonomy of the factors influencing Metaverse adoption in education, proposing a framework for Metaverse adoption, and suggesting future research trajectories in this domain. The review systematically classifies the influential factors into four distinct categories: psychological and motivational factors, quality factors, social factors, and inhibiting factors. The proposed framework provides a structured approach for future studies investigating the Metaverse adoption in educational settings. The proposed framework also emphasizes that educational institutions should not only consider the technical prerequisites but also the social, psychological, and motivational aspects of the Metaverse. The study also pinpoints several critical research agendas to enhance our understanding of Metaverse adoption in education. The insights from this review are invaluable for educational institutions, policymakers, developers, and researchers, significantly enriching the emerging field of Metaverse adoption.
Food waste (FW) is not just a problem and challenge in Malaysia but world wide. According to a United Nation Environment Program report, approximately 931 million tonnes of food waste was produced globally in 2019. This included 61% from households, 26% from food services and the remaining 13%, from retail. The sheer magnitude of this wastage is very troubling; especially in the fact that there is no firm hope that the scale of the wastage will decrease in the near future. Most studies into food wastage have investigated the broader field of food industries such as food manufacturers, restaurants, food courts and others. This study, however, aimed to investigate FW among end-users who are students in a school, with data being collected from the school canteen. It investigated the amount of food waste before and after awareness of food waste in Malaysia was raised, and how the waste can be converted into cash. The study had four phases: 1) an awareness program for school students, 2) installation of the FW machine, 3) collection of food waste, and finally 4) data analysis. The food waste was collected, transformed into bio-fertilisers and sold to the parents. A total of 339.5 kg of food waste was collected in 38 days and this waste was transformed into 131.5 kg of bio-fertilisers for sale to parents in the same school. This simple FW conversion to bio-fertilisers undertaken in the school as a pilot project shed some light on the potential of the project to be carried out on a larger scale and with commercial interests for all schools in Malaysia. The school generated RM 1315 from the sale of the bio-fertilisers. The potential profits achievable from this conversion of FW to bio-fertilisers will be significant if the pilot study is expanded throughout Malaysia.
Palm oil is a vegetable oil that is widely used for cooking and deep-frying because of its affordability. However, repeatedly heated palm oil is also prone to oxidation due to its significant content of unsaturated fatty acids and other chemical toxicants such as glycidyl esters and 3-monochloropropane-1,2-diol (3-MCPD). Initially, the physicochemical properties such as colour, viscosity, peroxide, p-anisidine and total oxidation (TOTOX) of periodically heated palm oil were investigated. Chemical profiling and fingerprinting of six different brands of palm cooking oil during heating cycles between 90 and 360 min were conducted using Fourier transform infrared (FTIR) and 1H Nuclear Magnetic Resonance (NMR) metabolomics. In addition, the multivariate analysis was employed to evaluate the 1H NMR spectroscopic pattern of repeatedly heated palm oil with the corresponding physicochemical properties. The FTIR metabolomics showed significant different of the chemical fingerprinting subjected to heating duration, which in agreement with the result of 1H NMR metabolomics. Partial least squares (PLS) model revealed that most of the physicochemical properties of periodically heated palm oil are positively correlated (R2 values of 0.98-0.99) to their spectroscopic pattern. Based on the findings, the color of the oils darkened with increased heating time. The peroxide value (PV), p-anisidine value (p-AnV), and total oxidation (TOTOX) values increased significantly due to degradation of unsaturated compounds and oxidation products formed. We identified targeted metabolites (probable carcinogens) such as 3-monochloropropane-1,2-diol (3-MCPD) and glycidyl ester (GE), indicating the conversion of 3-MCPD to GE in repeatedly heated oils based on PCA and OPLSDA models. Our correlation analysis of NMR and physicochemical properties has shown that the conversion of 3-MCPD to GE was significantly increased from 180 to 360 min cooking time. The combination spectroscopic techniques with physicochemical properties are a reliable and robust methods to evaluate the characteristics, stability and chemical's structure changes of periodically heated palm oil, which may contribute to probable carcinogens development. This study has proven that combination of NMR and physicochemical analysis may predict the formation of the probable carcinogens of heated cooking oil over time which emphasizing the need to avoid certain heating cycles to mitigate formation of probable carcinogens during cooking process.
Accident analysis is used to discover the causes of workplace injuries and devise methods for preventing them in the future. There has been little discussion in the previous studies of the specific elements contributing to deadly construction accidents. In contrast to previous studies, this study focuses on the causes of fatal construction accidents based on management factors, unsafe site conditions, and workers' unsafe actions. The association rule mining technique identifies the hidden patterns or knowledge between the root causes of fatal construction accidents, and one hundred meaningful association rules were extracted from the two hundred and fifty-three rules generated. It was discovered that many fatal construction accidents were caused by management factors, unsafe site circumstances, and risky worker behaviors. These analyses can be used to demonstrate plausible cause-and-effect correlations, assisting in building a safer working environment in the construction sector. The study findings can be used more efficiently to design effective inspection procedures and occupational safety initiatives. Finally, the proposed method should be tested in a broader range of construction situations and scenarios to ensure that it is as accurate as possible.
The construction industry, increasingly prioritizing sustainability, necessitates an exploration of technology and management's role in mitigating material waste at construction sites. This study examines the impact of 3R, IBS, BIM, and MMA in enhancing Construction Site Performance (CSP) in the Malaysian construction sector. Seven hypotheses were formulated to assess the relationship between technology adoption, material management practices, and the moderating influence of Material Management Adoption (MMA) on CSP. Data were collected through an online survey from 295 valid responses in the Malaysian construction sector, focusing on professionals involved in solid waste management. Utilizing Partial Least Squares - Structural Equation Modeling (PLS-SEM) and Statistical Package for the Social Sciences (SPSS), the findings highlight the importance of technological integration, efficient material management, and competitive strategies in effective material waste mitigation. Furthermore, the qualitative aspect of the study, conducted among 6 solid waste organizations in Malaysia, enriches the findings by providing nuanced insights into local practices and challenges. Emphasizing the importance of contextual insights, the study addresses professionals involved in solid waste management within the Malaysian construction industry. The geographical specificity adds depth to the analysis, offering a comprehensive understanding of regional dynamics. Despite acknowledging limitations in technology and material usage, the study offers recommendations for refining waste mitigation and improving construction site performance. This research model offers actionable insights for construction site stakeholders, emphasizing the criticality of waste mitigation and CSP. The results, both quantitative and qualitative, underscore the potential of these practices within the Malaysian construction industry to foster innovation and drive positive change.
This study aims to determine the level of collaboration, in-service training and teaching resource proficiency amongst Chemistry teachers by investigating the intermediary role of collaboration for training and teaching resources competency. A total of 184 Chemistry teachers in Riau, Indonesia, have participated in the survey. Using AMOS and SPSS 25.0 software to analyse the research data, we find a high level of collaboration, training and teaching resource proficiency amongst Chemistry teachers. Male teachers have higher proficiency level on all aspects than female teachers. The MANOVA test results show a significant difference in teacher resource competency based on gender. Male teachers are significantly more proficient than their female counterparts. However, they do not significantly differ in terms of collaboration and in-service training. The structural equation modelling test results show that collaboration has a significant role in Chemistry teachers' involvement in training and teaching resources. These research findings encourage relevant parties to design effective collaborations amongst Chemistry teachers. They also offer new insights for Chemistry teachers to keep on mastering teaching resources nationally and internationally.
The solar receiver is considered the cornerstone of the solar tower power system. In particular, it receives high-temperature heat flux rays, and extracts the maximum heat energy to be transferred to the heat transfer fluid, while minimising any thermal and mechanical stresses. Reducing the solar receiver size helps to reduce the loss of spillage; consequently, the thermal stress increases. Using a solar receiver with inserted triangular longitudinal fins enhances the heat transfer as well as strengthens the receiver tube. This study aims to optimise the number of fins, heat flux aiming point, heat transfer fluid, nanoparticle effect with molten salt as the base fluid, and type of receiver material. Non-uniform heat flux with the cosine and Gaussian effects have been considered. When the number of fins (N) increases, the maximum temperature (Tmax) decreases and the heat transfer is enhanced. When N = 20, Tmax = 656.4 K and when N = 1, Tmax = 683.55, while the efficiency for N = 1 is greater by 3% compared to when N = 20. The cosine distribution of heat flux has a higher maximum temperature than the Gaussian distribution by 29% and is 102% higher in receiver efficiency. The thermal efficiency when the heat flux is aimed at the middle point of the receiver is higher by 10% compared with a lower or upper aiming point. Using Al2O3 nanoparticles with a concentration of 0.5 wt.% increases the thermal efficiency by 14% more than when using pure molten salt when Re = 38000. Using liquid sodium is not required to monitor the peak heat flux, and by adding triangular fins the displacement and thermal stress are 6.5 % lower compared to a smooth receiver.
Conventional drugs used to treat Tuberculosis (TB) are becoming ineffective due to the occurrence of multiple drug resistant strains of tuberculosis (TB). This has made the TB disease a a serious global health dilemma. Hence, there is desperate necessity for the advancement of new drugs. In this work, the chemical reactivity and bioactivity of several analogs ofpyrazinamide (PZA) were investigated. PZA is one of the first-line of drugs used to treat tuberculosis and is a key contributor to shortening the treatment time for the disease. Chemical reactivity descriptors of pyrazinamide (PZA) and its analogs of acetylsalicyclic acid and salicyclic acid were investigated using conceptual density functional theory in water as a solvent at the MN12SX/Def2TZVP level of theory. Results have shown that all PZA analogs have improved their global and local reactivity indeces as compared to pyrazinamide based on its electronegativity, electrodonating power, electroaccepting power, eletrophilicity, global hardness and dual descriptor condensed fukui indexes. Moreover, their pKa values are slightly higher than PZA. In terms of its drug-likeness, all PZA analogs passed the Lipinski's Rule of Five criteria. Furthermore, their bioactivity scores are significantly better than pyrazinamide indicating good reaction to G-Protein Coupled Receptor (GPCR) ligands, kinase inhibitors, ion channel modulators, nuclear receptor ligands, protease inhibitors and other enzyme targets. Overall, the PZA analogs are found to be promising anti-tuberculosis drugs. Based on global and local reactivity descriptors, pKa and bioactivity scores, PZA analog of 5-n-Octanoylsalicylic acid is the most reactive among the PZA analogs tested.
Gynura procumbens is an edible flowering plant that has been utilized as traditional therapy for numerous diseases. The current experiment investigates the hepatoprotective potentials of the ethanol extract of Gynura procumbens leaf (EEGPL) against thioacetamide (TAA)-induced liver cirrhosis in rats. Thirty Sprague Dawley rats were randomly divided into 5 clusters: A, rats received orally 10% Tween 80 and intraperitoneal (i.p) inoculation of sterile distal water; B, rats received orally10% Tween 80; C, rats received orally daily 50 mg/kg of silymarin, while groups; D and E, rats received orally daily doses of 200 and 400 mg/kg of EEGPL, respectively. Furthermore, B-E clusters received 200 mg/kg thioacetamide (i.p) three times a week for 60 days. The liver gross morphology of rats that received only TAA (B) revealed irregular rough surface layers compared to smoother livers of rats that received EEGPL. Histopathology of group B revealed clear hepatic necrosis and fibrous connective tissue, which were significantly reduced in C-E groups. EEGPL treatment caused a significant down-regulation of PCNA and α-SMA protein expressions. Antioxidant (SOD and CAT) enzymes in hepatic homogeneity were meaningfully lower, and MDA levels were significantly higher in TAA controls compared to those of C-E groups. Moreover, EEGPL treatment caused a reduction of TNF-α and IL-6 and increased expression of IL-10 cytokines. Therefore, the hepatoprotective potentials of EEGPL might be contributed to its modulation of detoxification enzymes, anti-inflammatory, and antioxidant activities.
The prime objective of this research was to investigate procrastination as a prospectively constructive element of the creative process among employees working at different hierarchical levels in a Chinese organization. Building on self-determination theory, this research postulates a connection between procrastination and creativity through the incubation of knowledge absorption, autonomous motivation and task engagement as boundary conditions. Data was collected from 213 individuals from the workforce and their immediate managers belonging to a Chinese furniture company; then analyzed with Mplus for simple regression analysis, mediated moderated analyses, and coefficient estimates of all the study variables. The outcomes of this investigation showed an inverse relationship between procrastination with creativity, while creativity being strongest in the medium levels of procrastination; however, when autonomous motivation and/or task engagement are strong, procrastination depicts an inverted-U-shaped association; however, in scenarios where both autonomous motivation and the task engagement are low, procrastination has a negative linear relationship. With the results of this research, we have shown that moderate procrastination has a causal effect on the generation of creative ideas. This research demonstrated that as long as employees had strong autonomous drive or high task engagement, their supervisors awarded them better ratings when they procrastinated moderately on their assignments. Limitations and future research directions were also discussed.
Customer Relationship Management (CRM) is a method of management that aims to establish, develop, and improve relationships with targeted customers in order to maximize corporate profitability and customer value. There have been many CRM systems in the market. These systems are developed based on the combination of business requirements, customer needs, and industry best practices. The impact of CRM systems on the customers' satisfaction and competitive advantages as well as tangible and intangible benefits are widely investigated in the previous studies. However, there is a lack of studies to assess the quality dimensions of these systems to meet an organization's CRM strategy. This study aims to investigate customers' satisfaction with CRM systems through online reviews. We collected 5172 online customers' reviews from 8 CRM systems in the Google play store platform. The satisfaction factors were extracted using Latent Dirichlet Allocation (LDA) and grouped into three dimensions; information quality, system quality, and service quality. Data segmentation is performed using Learning Vector Quantization (LVQ). In addition, feature selection is performed by the entropy-weight approach. We then used the Adaptive Neuro Fuzzy Inference System (ANFIS), the hybrid of fuzzy logic and neural networks, to assess the relationship between these dimensions and customer satisfaction. The results are discussed and research implications are provided.