IOP Conference Series: Materials Science and Engineering

As per ISO and ASTM standards, nanoparticles are particles of sizes ranging from 1 to 100nm with one or more dimensions. The nanoparticles are generally classified into the organic, inorganic and carbon based particles in nanometric scale that has improved properties compared to larger sizes of respective materials. The nanoparticles show enhanced properties such as high reactivity, strength, surface area, sensitivity, stability, etc. because of their small size. The nanoparticles are synthesised by various methods for research and commercial uses that are classified into three main types namely physical, chemical and mechanical processes that has seen a vast improvement over time. This paper presents a review on nanoparticles, their types, properties, synthesis methods and its applications in the field of environment.

Day by day the cases of heart diseases are increasing at a rapid rate and it's very Important and concerning to predict any such diseases beforehand. This diagnosis is a difficult task i.e. it should be performed precisely and efficiently. The research paper mainly focuses on which patient is more likely to have a heart disease based on various medical attributes. We prepared a heart disease prediction system to predict whether the patient is likely to be diagnosed with a heart disease or not using the medical history of the patient. We used different algorithms of machine learning such as logistic regression and KNN to predict and classify the patient with heart disease. A quite Helpful approach was used to regulate how the model can be used to improve the accuracy of prediction of Heart Attack in any individual. The strength of the proposed model was quiet satisfying and was able to predict evidence of having a heart disease in a particular individual by using KNN and Logistic Regression which showed a good accuracy in comparison to the previously used classifier such as naive bayes etc. So a quiet significant amount of pressure has been lift off by using the given model in finding the probability of the classifier to correctly and accurately identify the heart disease. The Given heart disease prediction system enhances medical care and reduces the cost. This project gives us significant knowledge that can help us predict the patients with heart disease It is implemented on the.pynb format.

The fake news on social media and various other media is wide spreading and is a matter of serious concern due to its ability to cause a lot of social and national damage with destructive impacts. A lot of research is already focused on detecting it. This paper makes an analysis of the research related to fake news detection and explores the traditional machine learning models to choose the best, in order to create a model of a product with supervised machine learning algorithm, that can classify fake news as true or false, by using tools like python scikit-learn, NLP for textual analysis. This process will result in feature extraction and vectorization; we propose using Python scikit-learn library to perform tokenization and feature extraction of text data, because this library contains useful tools like Count Vectorizer and Tiff Vectorizer. Then, we will perform feature selection methods, to experiment and choose the best fit features to obtain the highest precision, according to confusion matrix results.

Digital marketing is an integral part of the process of digital business transformation. It incorporates new marketing techniques that are based on information and communication technologies. For this reason, its application in practice is a prerequisite for the successful development of the business in the contemporary market conditions. The object of this paper is the digital marketing and the subject is the digital marketing advantages and disadvantages. The first purpose of this paper is to systemize the various terms for digital marketing used in the specialized literature and the Internet and to show the differences between them. The second is to present the characteristics of the main advantages and disadvantages of digital marketing. Knowing them in depth, companies will be able to develop effective digital marketing strategies that have high potential to achieve company goals and at the same time are suitable to their profile. Thereby, they will be able to determine to what extent and which tools of the whole digital marketing palette are best suited to their marketing activities.

Soursop (Annona muricata) is a plant that is widely available in Indonesia. Of all parts of the soursop plant, the leaves are the most interesting parts to be studied. Soursop leaves are the most interesting part to be investigated because soursop leaves have many benefits and benefits that have been applied in the health sector, both traditional and modern. This is because soursop leaves contain many active compounds such as alkaloids, terpenoids, flavonoids, tannins, saponins, acetogenins, and others. The purpose of this review is to compare the best methods commonly used to extract active compounds from soursop leaves. The methods studied were maceration, soxhletation and microwave assisted extraction (MAE). The mechanism of the extraction processes and the percentage of yield achieved from the three methods are also reviewed. The results of the review show that MAE is the method that produces the highest yield of the three methods with a yield of 33.98%. This method also has another advantage that is a shorter extraction time.

In Muslim countries, mosques that designate areas for women's prayer rarely allow women to line up directly behind men in the same hall, as was the practice in the Prophet's Mosque during his lifetime. In many Arab countries, it is common to separate men's prayer place from women's, particularly in smaller mosques. The distance between the two prayer areas vary from one mosque to another. The majority of mosques in Muslim countries house specified places of prayer for women, which take shape of small rooms in the basement, on the ground floor, in a closed balcony or in a small building attached to the mosque. This paper aims to analyze the accessibility, permeability and scope of participation of women in the Mosque in the current scenario of modern world.

Development of financial management theory developed rapidly; forming branches roots. Start with Value of the firm theory, capital structure theory up to investment theory. Investment theory; behavioural finance is relatively new field that combine behavioural, psychological, economics and finance. This paper aims to develop conceptual Framework of factors that Influence Financial Literacy. Research in factors that influence financial literacy gives new development of financial theory through perception view. This research use qualitative study with grounded theory model of financial literacy. Moreover, this research gives implication in comprehensive framework that can be used in developing future research.

The uses of Artificial Intelligence (AI) seems to be relevant in many fields nowadays due to its ability in providing a simulation of human intelligence processes that are handled by machines; in particular computer systems. This paper concerns with reviewing the uses of AI in language teaching and learning. In particular, it reviews the research on the uses of AI in its application in the learning and teaching of language. Qualitative research method; specifically content analysis, is employed as the technique to review the articles that are obtained from relevant databases. Findings from the study reveal that there are four (4) themes emerge in the uses of AI in relation to teaching and learning a language. The uses of AI for pedagogy, therefore, prove that its uses eases language teaching and learning.

The aim of the study was to investigate the financial behavior of employees regarding financial literacy and spending habits based on gender. The cluster sampling was used in this study and 60 employees consist of 30 male and 30 females were chosen and the analytical method used is different test of independent sample t-test for normally distributed data, while Mann-Whitney test for distributed data is not normal. The result showed that financial literacy behavior and spending habits between male and female employees were not different. Male and female employees had low level of financial literacy and they had tight spending habits the study also found that male and female employees did not have appropriate knowledge to manage their financial especially in managing investment and loan. This result in increasingly tight spending which caused they still have to deal with the monthly instalment payment in the long run.

Not all information posted on the internet is deemed 'trustworthy.' Some articles, especially those related to politics, seem to display traces of bias, whether they be for or against the Philippine administration. This research aims to determine if a news article—and by extension, a news outlet—is biased based on its sentiments and use of lexica. Data were harvested from chosen websites and news outlets provided by Alexa. These data underwent pre-processing and were scored based on their sentiments with the use of SentiWordNet. The resulting scores were then fed into the Inverse Reinforcement Model, which determined whether an article is biased or not. With the use of Inquirer, Philstar, Manila Bulletin, The Manila Times, and Journal Online news articles, the system was able to detect bias with an accuracy rating of 0.89, precision of 1, recall of 0.60 and F-Measure of 0.75.

This volume of the IOP Conference Series: Materials Science and Engineering contains papers from the 17th Workshop of the European Microbeam Analysis Society (EMAS) on Modern Developments and Applications in Microbeam Analysis, which took place from the 7th to the 11th of May 2023 at the Auditorium Maximum of the Jagiellonian University, Krakow, Poland.

The primary aim of this series of workshops is to assess the state-of-the-art and reliability of microbeam analysis techniques. The workshops also provide a forum where students and young scientists starting out on a career in microbeam analysis can meet and discuss with the established experts. The Krakow meeting was organised within the usual EMAS format, comprising invited plenary lectures by internationally recognised experts, poster presentations by the participants and round-table discussions on the key topics led by specialists in the field. EMAS2023 was organized in collaboration with the Institute of Metallurgy and Materials Science of the Polish Academy of Sciences, Krakow, Poland. The technical programme included the following topics: Electron probe microanalysis (EPMA); Electron backscatter diffraction (EBSD); Software tools; Focussed ion beam; Combined techniques in SEM; and materials applications of microbeam analysis and their applications.

As at previous workshops, there was also a special oral session for Early Career Scientists. The best presentation by an early career scientist was awarded with an invitation to attend the 2024 Microscopy and Microanalysis meeting in Cleveland, Ohio. The prize went to Maria Wątroba, EMPA - Swiss Federal Labs. Materials Testing and Research, Thun (CH), for her presentation entitled: "Experimental analysis of plastic deformation in single-crystalline and ultrafine-grained Zn micropillars" (by M. Wątroba, W. Bednarczyk, C. Tian, J. Michler and J. Schwiedrzik).

List of Acknowledgements and International Scientific Committee are available in this pdf.

All papers published in this volume have been reviewed through processes administered by the Editors. Reviews were conducted by expert referees to the professional and scientific standards expected of a proceedings journal published by IOP Publishing.

• Type of peer review: Double Anonymous

• Conference submission management system: Morressier

• Number of submissions received: 15

• Number of submissions sent for review: 15

• Number of submissions accepted: 15

• Acceptance Rate (Submissions Accepted / Submissions Received × 100): 100

• Average number of reviews per paper: 2

• Total number of reviewers involved: 20

• Contact person for queries:

Name: Luc Van't dack

Email: luc.vantdack@uantwerpen.be

Affiliation: EMAS - European Microbeam Analysis Society

For quantitative electron probe microanalysis matrix effects have to be considered. Conventional matrix correction procedures in use today assume a homogeneous composition for the bulk sample (known as ZAF correction) or heterogeneity only in depth for thin films (ϕ(ρz) models). But when heterogeneity is expected in lateral directions, only Monte Carlo and deterministic simulations could be used for accurate matrix correction. These simulations are computationally expensive and slow. In this work, we introduce a novel analytical model for the multi-dimensional ionisation probability distribution ϕ(ρr, ρz) for a material bombarded with electrons, which could be used for fast matrix correction as an alternative to simulations. By fitting the model onto ionisation probability distributions generated by Monte Carlo simulations, we show that our model can adequately describe the simulated distributions.

This work concludes our systematic investigations of the spatial analytical resolution at different primary electron energies and specimens with different atomic numbers [1-4]. The aim of the entire study was to determine the qualitative and especially the quantitative analytical spatial resolutions that can actually be achieved in practise. For this purpose, we prepared test specimen by evaporating thin metallic layers (Al, Ag and Au) with various thicknesses on top of non-fluorescent substrates. To determine the depth resolution, the layers were analysed from the top. The measurements were carried out using a field emission electron microprobe, but the results are also applicable to SEM-EDS and SEM-WDS.

This work now evaluates the quantitative analytical depth resolution measured with electron energies from 4 to 15 keV on eight gold layer specimens with different layer thicknesses from 30 to 1,030 nm. By varying the primary electron energy E₀, we determined the minimum value of E₀ for which the depth of the signal source volume is identical to the layer thickness. This value is defined as the depth resolution, which is identical to the ionisation range of the atomic shell under consideration. With respect to the excitation energy of the characteristic X-rays, the depth resolution for the quantitative element analysis for Au (Mα at 4 kV) is found to be below 50 nm. It should be noted that the applied electron energies fulfil the 2-times overvoltage criteria resulting in reasonable X-ray signals with good signal-to-noise ratio.

The experimental results were cross-checked with simulations and calculations. While we found a good agreement with Monte Carlo simulations, the well-known Castaing-formula predicts smaller values for all primary electron energies. The deviation increases for decreasing energies. Since we regard test specimens without any disturbing secondary fluorescence, the measurements presented in this paper are very helpful for further improvements of calculations, MC simulations and other approximations.

This conference proceeding reports on the usage and applications of a high numerical aperture mirror for cathodoluminescence and other photon-based spectroscopies in a scanning transmission electron microscope.