Preeclampsia is one of the leading causes of maternal mortality, which is a serious problem during pregnancy, which is further complicated by issues related to pathophysiology and etiology. The focus of this research is on the early detection of preeclampsia by using machine learning with multiple algorithms. Specifically, the aim of this study is to identify the causes of preeclampsia. A total of 21 articles were obtained from four scientific databases, namely ScienceDirect, Scopus, IEEE, and PubMed, which were published between 2018 and 2022, using several keywords such as Artificial Intelligence, Machine Learning, Prediction, and Preeclampsia. The method of the review adhered to the principles outlined in a guideline published by Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA). The systematic review of these articles was focused on the accuracy of prediction of preeclampsia using machine learning. The results showed machine learning was the most popular me.....

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Fake news and disinformation (FNaD) are increasingly being circulated through various online and social networking platforms, causing widespread disruptions and influencing decision-making perceptions. Despite the growing importance of detecting fake news in politics, relatively limited research efforts have been made to develop artificial intelligence (AI) and machine learning (ML) oriented FNaD detection models suited to minimize supply chain disruptions (SCDs). Using a combination of AI and ML, and case studies based on data collected from Indonesia, Malaysia, and Pakistan, we developed a FNaD detection model aimed at preventing SCDs. This model based on multiple data sources has shown evidence of its effectiveness in managerial decision-making. Our study further contributes to the supply chain and AI-ML literature, provides practical insights, and points to future research directions. 2022, The Author(s)...

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When COVID-19 spread in China in December 2019, thousands of studies have focused on this pandemic. Each presents a unique perspective that reflects the pandemics main scientific disciplines. For example, social scientists are concerned with reducing the psychological impact on the human mental state especially during lockdown periods. Computer scientists focus on establishing fast and accurate computerized tools to assist in diagnosing, preventing, and recovering from the disease. Medical scientists and doctors, or the frontliners, are the main heroes who received, treated, and worked with the millions of cases at the expense of their own health. Some of them have continued to work even at the expense of their lives. All these studies enforce the multidisciplinary work where scientists from different academic disciplines (social, environmental, technological, etc.) join forces to produce research for beneficial outcomes during the crisis. One of the many branches is computer science a.....

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Polyvinylidene fluoride (PVDF)/titanium dioxide (TiO2)/graphene oxide (GO)-based hybrid membrane was blended with polymer additive of polyvinyl alcohol (PVA), polyvinylpyrrolidone (PVP) and poly (methyl methacrylate) (PMMA) through phase inversion method. A triple-tail surfactant was utilised to assist the initial GO synthesis and achieve better GO dispersion in the polymer matrix. The effect of incorporating different polymer additives was investigated based on methylene blue (MB) dye rejection and antifouling performance. Experimental results showed that the incorporation of PVP in the polymer matrix resulted in the highest pure water flux (635.897 l/m2?h) and permeability (255.833 l/m2 h?MPa) as well as 57.56% MB dye rejection rate. Interestingly, PVDF-TiO2/GO/PMMA presented higher dye rejection rate (79.18%) and flux recovery ratio (FRR) value (86.46%) than other fabricated membranes. Overall, the incorporation of different polymer additives successfully alters the morphology, prop.....

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In the last few years, the trend in health care of embracing artificial intelligence (AI) has dramatically changed the medical landscape. Medical centres have adopted AI applications to increase the accuracy of disease diagnosis and mitigate health risks. AI applications have changed rules and policies related to healthcare practice and work ethics. However, building trustworthy and explainable AI (XAI) in healthcare systems is still in its early stages. Specifically, the European Union has stated that AI must be human-centred and trustworthy, whereas in the healthcare sector, low methodological quality and high bias risk have become major concerns. This study endeavours to offer a systematic review of the trustworthiness and explainability of AI applications in healthcare, incorporating the assessment of quality, bias risk, and data fusion to supplement previous studies and provide more accurate and definitive findings. Likewise, 64 recent contributions on the trustworthiness of AI in.....

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The adoption of STEP-NC on CNC machines has been one of the most enduring difficulties in daily operations. It is not outside of the realm of possibility to put this solution into practice by techniques that are indirect, interpretative, or adaptive. In this implementation, the interpreted approachs performance was noticeably better than the indirect methods. In this particular field, a substantial amount of investigation still needs to be carried out. This investigation focuses on a better interpreted STEP-NC programming paradigm, and a novel data interpretation approach along with algorithm design are presented. The system has been contributed with the latest hybrid method, which combines the indirect and interpreted strategies for constructing tool paths. In addition, the interpretation algorithm has been updated to incorporate a method for extracting data in two layers (entity and string). The entirety of the system is made up of a variety of software tools and algorithms for the p.....

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Forests are vital in combating climate change by storing and sequestrating CO2 from the atmosphere. Measuring the influence of land use/land cover (LULC) changes on the capacity of carbon storage (CS) within forest ecosystems presents a significant challenge. This study employs remote sensing techniques to examine the changes in spatiotemporal patterns of CS in the Chittagong Hill Tracts (CHT), resulting from LULC alterations between 1996 and 2021. LULC change patterns were identified for six different years utilizing the Google Earth Engine (GEE). The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model was combined with GEE to evaluate the changing patterns of CS. The study discovered that the CHT region experienced a loss of 21.65 106 Mg of CS, owing to a 21% reduction in vegetation cover (2862.85 km^2) during the study period. The central city area (Chittagong) accounted for the most significant loss of CS (7.99 106 Mg), while the suburban areas of Khagrachari (0.....

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The technology deployment in smart e-tourism brings high potential in terms of customer data, events, reservations, and others. It acts as an effective and personalized guide to aid travelers. There is an increasing variety of smart e-tourism apps with multiple categories and criteria, but in terms of decision making, this presents a multicriteria complex problem to determine the best app from a group of available options with high criteria subjectivity. Literature reviews have evaluated and modeled the existing smart e-tourism apps alternatives, but informational uncertainty remains. The fuzzy sets and Multi-Attribute Decision Analysis (MADA) were used to handle the subjectivity issue. However, this process includes levels of uncertainty, which affects the decisions made and still an open issues. Spherical fuzzy rough sets (SFRSs) environment are useful in this situation for resolving fuzziness and ambiguity. This paper proposed a decision modeling approach for smart E-Tourism data ma.....

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The aim of the present study was to extract of Polyalthia sclerophylla leave (LPS) and identify its chemical constituents using Gas chromatography-Mass (GS-Mass) spectrometry and classical phytochemicals methods. This study included as well the evaluated of the bio-medical properties of LPS using antibacterial (against six bacteria species) and cytotoxicity (M-63 human cell line) activities. Three different solvent system i.e. methanol (MeOH), dichloromethane (DCM) and hexane were used to extract the LPS, three samples were obtained and labelled as MLPS, DLPS, and HLPS, respectively, and evaluated their biomedical activities. Phytochemical screening results showed to present glycosides and terpenoids in MLPS, DLPS, and HLPS, while alkaloids did not detect the presence in all extracts. GC-Mass results were detected to present 21 chemical compounds, the higher percentages were cyclobutanone, 2-methyl-2-oxiranyl-, 2-Undecanol and Pyridine, 2,3,4,5-tetrahydro-3-methyl-, while 1,6-Heptadien.....

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Based on the theories of professional identity and emotional labor, this study investigates the mediating role of emotional labor in the relationship between self-professional identity and labor productivity among front-line employees in hotels. Drawing upon a validated scale, a survey was conducted with 238 front-line employees working in high-star hotels to examine the impact mechanism of self-professional identity on labor productivity. The findings reveal that self-professional identity significantly and positively influences labor productivity among hotel front-line employees. Self-professional identity is identified as the antecedent variable of emotional labor, whereby it enhances the deep acting of front-line staff while reducing surface acting and improving natural acting. Emotional labor acts as an intermediary between self-professional identity and labor productivity. However, different dimensions of emotional labor exhibit notable variations in their mediating effects and i.....

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