Green Intellectual Capital And Green Supply Chain Performance: Does Big Data Analytics Capabilities Matter?

In light of global environmental concerns growing, environmental awareness within firms has become more important than before, and many scholars and researchers have argued the importance of environmental management in promoting sustainable organizational performance, especially in the context of supply chains. Thus, the current study aimed at identifying the impact of the components of green intellectual capital (green human capital, green structural capital, green relational capital) on green supply chain performance in the manufacturing sector in Jordan, as well as identifying the moderating role of big data analytics capabilities. To achieve this aim, we developed a conceptual model of Structural Equation Modelling-Partial Least squares and tested through the Smart-PLS software on a sample of 438 respondents. Empirical results showed that each of the components of green intellectual capital and big data analytics explains 71.1% of the variance in green supply chain performance and that all components of green intellectual capital have a statistically significant impact on green supply chain performance. The results also revealed that the relationship between green relational capital and green supply chain performance is moderated through big data analytics capabilities. Finally, this study made a theoretical and managerial implications to the supply chain literature and industry

User acceptance and adoption of smart homes: A decade long systematic literature review

This survey aims to provide a coherent and bibliometric overview of the theories and constructs employed in smart homes acceptance and adoption literature. To achieve the study aims, we con-ducted a systematic search for every article related to the SH concept, services and applications, user acceptance and adoption, and integrated IoT home appliances and devices, in 10 major library databases, namely, IEEE Digital Library, ACM Digital Library, Association for Information Systems (AIS), Elsevier, Emerald, Taylor and Francis, Wiley InterScience, Springer, Inderscience, and Hindawi. These databases contain literature focusing on smart home adoption using IoT tech-nology. 40 research articles of journal and peer-reviewed conferences were found relating to our research objective, presented and distributed chronologically, by publisher, country, theory and model, key construct, and with full bibliometrics for each article. Additionally, this survey includes a word cloud and a taxonomy of the entire factors used to understand users’ acceptance and adoption of smart homes in different contexts and applications. This study has many ad-vantages in covering the current research gap in the literature and also the researchers identify theoretical and practical research implications, research limitations, and recommendations for improving the acceptance and usage of smart homes literature

THE PREVALENCE OF HELICBACTER PYLORI AMONG PATIENTS COMPLAINING FROM ABDOMINAL PAIN

Helicobacter pylori has been associated with a number of gastrointestinal disorders including gastritis, peptic ulcer disease, gastric adenocarcinoma and gastric mucosa-associated lymphoid tissue (MALT) lymphoma. The present study was conducted to determine the prevalence of Helicobacter pylori infection among patients complaining from abdominal pain and visiting internal medicine clinics. It was also purposed to investigate the relationship between both age and sex with Helicobacter pylori infection. A retrospective study was conducted and included 101patients with abdominal pain. The results showed that the prevalence of IgG against Helicobacter pylori infection is 85%, while about 38.6% of cases were positive for IgA against Helicobacter pylori. No significant relationships were found for IgG, IgA with age and sex (p value >0.05). Taken together, the study showed high prevalence of H. pylori infection among patients complaining of abdominal pain. H.pylori infection is not associated significantly with age and sex

Optimisation of arsenic adsorption from water by carbon nanofibres grown on powdered activated carbon impregnated with nickel

Contamination of water due to arsenic (As) is increasing in many parts of the world. The removal of As from aqueous solution by using impregnated carbon nanofibres (CNFs) as the adsorbent is reported in this paper. The effects of pH, CNFs dosage, contact time and initial concentration of arsenic were studied at room temperature (±25°C). The interactions among the parameters were also investigated. The data obtained from the adsorption experiment were analysed using statistical software in order to develop a regression equation to represent the optimum operating conditions. The interactions of each parameters were considered during this analysis and the result indicated that the highest removal (97.25%) of As can be attained at pH 6, initial concentration of arsenic of 0.08 mg L-1, contact time of 60 min and CNF dosage of 200 mg L-1. Comparison between impregnated CNF and Powdered Activated Carbon (PAC) were also done and it is determined that impregnated CNF has better removal compared to PAC alone. The final concentration of As after the treatment using CNFs was about 8 ~ 10 times less than that of using PAC. Therefore, it can be concluded that CNFs are highly potential for the adsorption of As from water

Understanding Trust Drivers of S-commerce

Trust has emerged as a pillar in the acceptance and use of new technologies in the ever-changing digital landscape, notably in the booming field of social commerce. The importance of this study lies in the fact that it explores in-depth the aspects of customer trust in Instashopping using new constructs that have yet to be explored in s-commerce literature. Focusing on Instashopping, the research proposed a multi-dimensional model of trust to examine the dynamics of user trust in social commerce platforms and analyses the effects of various factors, including institution-based trust, disposition to trust, personal inventiveness, perceived page quality, and overall web experience. Structural equation modelling and confirmatory factor analysis were used to examine data from 267 responses in a survey of university students in the United Arab Emirates who have used Instagram for shopping. The analysis showed that user trust and trusting beliefs were significantly influenced by the disposition to trust, institution-based trust, and general web experience. Still, no significant association was found between perceived site quality and trusting beliefs. These findings highlight the crucial part that user trust plays in social commerce platform success and how important it is for online platforms to build and maintain user trust. The work also contributes theoretically to the knowledge body by comprehensively analysing trust dynamics in social commerce. In practice, the knowledge gained can help organisations plan their strategy for gaining and keeping client trust, which is essential for long-term success in the digital arena. To ensure long-term success, organisations must emphasise building and maintaining customer trust

Internet of things important roles in hybrid photovoltaic and energy storage system: a review

Renewable energy systems have become integral components of the electrical grid, offering environmental benefits and cost-effective power generation. Technological advancements have introduced internet of things (IoT) devices with robust data collection and execution capabilities. Solar photovoltaic systems, reliant on unpredictable solar radiation, require hybrid systems incorporating various renewable energy sources and energy storage to ensure system stability. Successful operation necessitates data gathering through IoT devices, which have played a crucial role in enhancing system sustainability. This paper provides a comprehensive review of the role of IoT in photovoltaic systems and energy storage, highlighting its significant contributions to system efficiency, fault detection, output prediction, system stability, and load management. The study underscores the critical dependence of advancements in the renewable energy sector on IoT systems

The optimum condition for the synthesis of carbon nanofibers on activated carbon to remove lead from aqueous solution

Optimum process condition for the production of Carbon Nanofibers (CNFs) to remove lead ion (Pb) from aqueous solution is reported here. The CNFs were produced on the catalyst (Ni2+) impregnated palm oil-based cheap Powder Activated Carbon (PAC). Locally fabricated Chemical Vapour Deposition (CVD) system was used while acetylene (C2H2) was the carbon source. The porous nano-composite product is named “PAC-CNFs”, which was synthesized through a process using impregnated oil palm shell based PAC as a solid substrate. Design Expert 6.0.8 software was used to design the experimental plan and to determine the optimized process parameters for the growth of CNFs by using sorption capacity for Pb2+ by the PAC-CNFs adsorbent, as a response. The effect of different factors on the growth of CNFs including the temperature of CNFs growth (550 to 750 °C), time of growth (30 to 60 min), and the ratio of input C2H2/H2 gases (0.25 to 1.0) was evaluated. The predicted values for the sorption capacity of Pb2+ by the PAC-CNFs were in close agreement with the experimental data (R2 = 0.99). The optimal process condition: temperature for the growth of CNFs, time, and C2H2/H2 ratio was determined as 637 °C, 30 min, and 1.0, respectively. The CNFs grown under the optimized condition exhibited sorption capacity of 77 mg/g in removing Pb2+ from synthetic wastewater containing lead (Pb2+) ion

Immobilization of fungal biomass with multi-walled carbon nanotubes as biosorbent

Aim: This study was mainly highlighted on a combination of fungal biomass onto MWCNTs in order to enhance the positive integration of impurities removal in aqueous solution. Methodology and results: The immobilization of fungal biomass and MWCNTs was done in a batch liquid medium with several factors such as agitation speed, dose of MWCNTs, pH and inoculum dosage that were conducted with one factor at one time (OFAT) method. Basically, to verify the functional group of MWCNTs, Aspergillus niger biomass and immobilized A. niger biomass, the FTIR was applied and FESEM was done to demonstrate and compare the image of the immobilized A. niger biomass with MWCNTs and fungal biomass alone. The finding showed the best agitation speed, dose of MWCNTs, pH and inoculum dosage were 150 rpm, 0.5 g, 5-6 and 2% respectively. FTIR indicates the presents of the functional groups like –OH (3270 cm -1 ), C-O (1619 cm -1 ) and –CH (2915 cm -1 ) while FESEM illustrates the images of the wrapped MWCNTs on A. niger biomass. Conclusion, significance and impact of study: The conventional technique of adsorption of fungal biomass alone not showing a favorable removal of impurities. Thus, the immobilization of fungal biomass (A. niger) with multi-walled carbon nanotubes (MWCNTs) was a good combination since both have potential functional group to accumulate to each other and has a tendency to remove effectively and efficiently the impurities in aqueous solution

License plate recognition system

License Plate recognition (LPR) system is a key to many traffic related applications such as road traffic monitoring or parking lots access control. This paper proposes an automatic license plate recognition system for Saudi Arabian license plates. The system presents an algorithm for the extraction of license plate and segmentation of characters. Recognition is done using template matching. However the proposed work seems to be the first attempt towards the recognition of Saudi Arabian license plates. The performance of the system has been investigated on real images of about 710 vehicles captured under various illumination conditions. Recognition of about 96% shows that the system is quite efficient