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Pluronic f127 encapsulated titanium dioxide nanoparticles: Evaluation of physiochemical properties for biological applications
The infections caused by bacteria that are resistant to drugs are very bad for human health and kill thousands of people every year. Also, both human actions and natural processes make surface waters more likely to have drug-resistant bacteria grow and spread in the environment. Because of this, researchers need to find new ways to treat bacterial infections quickly becoming resistant to drugs as soon as possible. Drug delivery systems based on nanoparticles have enhanced biocompatibility, biocidal properties, pharmacokinetics, tumor targeting, and stability while exhibiting non-toxicity to normal cells and overcoming drug resistance. In the present work, the pluronic-F127 encapsulated titanium dioxide (PF127/TiO2) nanoparticles (NPs) were prepared by a green process using Morinda citrifolia leaf extract. X-ray diffraction patterns (XRD) revealed that synthesized NPs exhibit an anatase structure. FESEM and TEM images of synthesized PF127/TiO2 NPs showed a polymorphic structure and an average particle size of 5060 nm. The chemical composition of the prepared NPs, which included elements like carbon, titanium, and oxygen, was identified using the EDAX spectrum. With the DLS spectrum, the hydrodynamic sizes of PF127/TiO2 NPs were 176 nm. In the FTIR spectrum, the metal oxide stretching bands like O-Ti-O were located at 664 cm?1 for PF127/TiO2 NPs. The surface defects, including Ti and O vacancies, were studied using the photoluminescence spectrum. The prepared PF127/TiO2 NPs exhibited significant microbial activity for inhibiting hospital pathogenic bacterial and fungal strains, specifically (Staphylococcus aureus) S. aureus, (Streptococcus pneumoniae) S. pneumonia, (Klebsiella pneumoniae) K. pneumonia, (Shigella dysenteriae) S. dysenteriae and (Candida albicans) C. albicans. In addition, PF127/TiO2 NPs had highly anti-cancer properties against human blood cancer (MOLT-4) cell lines. Furthermore, we found that synthesized PF127/TiO2 NPs exhibited anti-inflammatory activity. 2023 -
Big Data Analytics Tools and Applications for Modern Business World
In the modern world, data is the unavoidable word. The digital environment in almost all our day to day life is linked with digital data. Effective data management is one of the important tasks. The gradual growth of technology in recent years, the generation of data has increased exponentially. Everything, ranging from sending a mail to simply browsing the internet generates data and this is collected and stored. This data has countless uses in various fields such as medicine, business, agriculture and marketing, but most of the time it goes unused. Business intelligence is a key factor in the current business world. Business growth is purely depending on technology. Technology is not only used in manufacturing it is applied to getting the customer. The data analytics is still in its earlier stages and has a long way to go before it yields favourable results. It is a good time as any to start working in this domain to utilize its prowess. This article has discussed the opportunities and growth of data analytics in the research domain. It can face soon when it reaches its advance stages. The big data is handling a larger amount of data in a conventional and non-conventional manner. Technology is playing a vital role to handle larger data from the database. This article is to discuss data analytics application in modern industry. In the technical perspective, big data Map-reduce is an advanced tool and for simulation part, R tool is used. 2020 IEEE. -
Machine Learning Algorithms for Predictive Maintenance in Hybrid Renewable Energy Microgrid Systems
The rapid expansion of hybrid renewable energy microgrid systems presents new challenges in maintaining system reliability and performance. This paper explores the application of machine learning algorithms for predictive maintenance in such systems, focusing on the early detection of potential failures to optimize operational efficiency and reduce downtime. By integrating real-time data from solar, wind, and storage components, the proposed models predict the remaining useful life (RUL) of critical components. The results demonstrate significant improvements in predictive accuracy, offering a robust solution for enhancing the reliability and longevity of renewable energy microgrids. The Authors, published by EDP Sciences. -
Spectroscopic Study of Late-type Emission-line Stars Using the Data from LAMOST DR6
Low-mass emission-line stars belong to various evolutionary stages, from pre-main-sequence young stars to evolved stars. In this work, we present a catalog of late-type (F0 to M9) emission-line stars from the LAMOST Data Release 6. Using the scipy package, we created a Python code that finds the emission peak at H? in all late-type stellar spectra. A data set of 38,152 late-type emission-line stars was obtained after a rigorous examination of the photometric quality flags and the signal-to-noise ratio of the spectra. Adopting well-known photometric and spectroscopic methods, we classified our sample into 438 infrared (IR) excess sources, 4669 post-main-sequence candidates, 9718 Fe/Ge/Ke sources, and 23,264 dMe sources. From a crossmatch with known databases, we found that 29,222 sources, comprising 65 IR excess sources, 7899 Fe/Ge/Ke stars, 17,533 dMe stars, and 3725 PtMS candidates, are new detections. We measured the equivalent width of the major emission lines observed in the spectra of our sample of emission-line stars. Furthermore, the trend observed in the line strengths of major emission lines over the entire late-type spectral range is analyzed. We further classified the sample into four groups based on the presence of hydrogen and calcium emission lines. This work presents a large data set of late-type emission-line stars, which can be used to study active phenomena in late-type stars. 2024 National Astronomical Observatories, CAS and IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved. -
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Information and communication technology integration in education by harare secondary school teachers in relation to school technology culture and their educational leader competencies
Information and Communication Technology (ICT) integration in education refers newlineto using technology in teaching and learning processes. The use of Information and Communication Technology (ICT) in the classroom would solve a lot of the problems related to Zimbabwean secondary school education. It motivates students to learn by providing a variety of learning activities such as watching videos, viewing pictures and models and online quizzes. This interests students who are digital natives and is more applicable to their everyday experiences. newlineStudent participation increases when ICT is used in the classroom as students are newlineconversant with the use of technology. ICT integration in education also allows students to learn in circumstances where there are shortages of teachers. The culture which exists in a school and the competencies of the educational leaders cannot be ignored when planning for and assessing the outcome of ICT integration programs. This study focused on Information and Communication newlineTechnology Integration in Education by Harare Secondary School Teachers, in relation to School Technology Culture and their Educational Leader Competencies . A survey was carried out in government and private secondary schools in Harare, Zimbabwe during the period from October 2012 to mid-2013. The population was all the secondary school teachers in Harare district of Zimbabwe. According to the data obtained from the Ministry of Education in October 2012, the target population of secondary school teachers in Harare was 4 244. The sample size was calculated based on an equation cited from Camorin and Calmorin (2007:230). This newlinegave a sample of 248 teachers from Harare secondary schools. 140 were females and 108 males. Four research instruments were used for data collection: a proforma on demographics, the ICT Integration questionnaire (ICTIQ), the School Technology Culture (STC) Scale and the Educational Leader Competency (ELC) scale. -
Sustainability and Gender Equality: SDG5Gender Differences in Bargaining in the Housing Market
This chapter investigates whether gender differences exist in bargaining behaviour in the housing market. The impact of personality dispositions, location preferences and other such variables on the individuals willingness and ability to bargain and obtain a concession is studied. The variables were estimated using a 5-point Likert scale, and the final dataset was analysed by implementing logistic regression model. Findings suggest that gender, product knowledge, bargaining disposition, role of agent and reference price significantly impact bargaining behaviour. The study validates the need to attain the fifth Sustainable Development Goal, i.e. Gender Equality. The current emphasis is to ensure full participation of women in decision-making capabilities by 2030 (UN Women, Progress on the sustainable development goals: the gender snapshot, UN Women, New York, 2022), but it is found that men bargain more than women in the rental housing market. The chapter contributes to existing literature by studying gender differences in the rental housing market and justifies the findings with the help of primary data analysis. 2024 The Author(s). -
A Worldwide Test of the Predictive Validity of Ideal Partner Preference Matching
Ideal partner preferences (i.e., ratings of the desirability of attributes like attractiveness or intelligence) are the source of numerous foundational findings in the interdisciplinary literature on human mating. Recently, research on the predictive validity of ideal partner preference matching (i.e., Do people positively evaluate partners who match vs. mismatch their ideals?) has become mired in several problems. First, articles exhibit discrepant analytic and reporting practices. Second, different findings emerge across laboratories worldwide, perhaps because they sample different relationship contexts and/or populations. This registered reportpartnered with the Psychological Science Acceleratoruses a highly powered design (N = 10,358) across 43 countries and 22 languages to estimate preference-matching effect sizes. The most rigorous tests revealed significant preference-matching effects in the whole sample and for partnered and single participants separately. The corrected pattern metric that collapses across 35 traits revealed a zero-order effect of ? =.19 and an effect of ? =.11 when included alongside a normative preference-matching metric. Specific traits in the level metric (interaction) tests revealed very small (average ? =.04) effects. Effect sizes were similar for partnered participants who reported ideals before entering a relationship, and there was no consistent evidence that individual differences moderated any effects. Comparisons between stated and revealed preferences shed light on gender differences and similarities: For attractiveness, mens and (especially) womens stated preferences underestimated revealed preferences (i.e., they thought attractiveness was less important than it actually was). For earning potential, mens stated preferences underestimatedand womens stated preferences overestimatedrevealed preferences. Implications for the literature on human mating are discussed. 2024 American Psychological Association -
Elementary Methods for Generating Three-Dimensional Coordinate Estimation and Image Reconstruction from Series of Two-Dimensional Images
The increase in computational power in recent years has opened a new door for image processing techniques. Three-dimensional object recognition, identification, pose estimation, and mapping are becoming popular. The need for real-world objects to be mapped into three-dimensional spatial representation is greatly increasing, especially considering the heap jump we obtained in the past decade in virtual reality and augmented reality. This paper discusses an algorithm to convert an array of captured images into estimated 3D coordinates of their external mappings. Elementary methods for generating three-dimensional models are also discussed. This framework will help the community in estimating three-dimensional coordinates of a convex-shaped object from a series of two-dimension images. The built model could be further processed for increasing the resemblance of the input object in terms of its shapes, contour, and texture. 2021 Naived George Eapen et al. -
Security Aspects for Mutation Testing in Mobile Applications
Due to the increase in the number of Android Platform Devices, there are more and more applications being developed across various domains. It is interesting to see the involvement of bugs/crashes even in the deployed applications even though it has been through various test phases. Unit tests are essential in a well-trusted testing environment; however, it does not guarantee that the range of test caries every component of the application. This writes up discusses the overview of mutation testing method concerning Android Applications. Even though mutation testing is found out to be very effective in other applications, it is not that easy to implement the same for an Android Developed Application because of additional resources it would hold. Further, various measures for mutation testing are discussed with types of mutant operators, tools etc. The current studies of mutation analysis mainly focus on testing all the functionalities irrespective of the resource usage. However, the target of the future mutation tests must be also to evaluate the efficiency of the applications under the same test cases. 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Energy Intelligence: The Smart Grid Perspective
Smart grids enable a two-way data-driven flow of electricity, allowing systematic communication along the distribution line. Smart grids utilize various power sources, automate the process of energy distribution and fault identification, facilitate better power usage, etc. Artificial Intelligence plays an important role in the management of power grids, making it even smarter. With the help of Artificial Intelligence and Internet of Things, smart grids can optimize the energy consumption, provide continuous feedback on usage, and monitor live usage statistics, thereby making the energy intelligent. Smart grids require specific hardware to continuously monitor and adapt to the requirements of the system. By enabling energy intelligence, we empower building-level and city-level optimizations that make use of green energy, thereby contributing more toward sustainable development. Thus, the multifaceted energy management system uses sustainable and renewable energy sources, combined with smart devices to provide a two-way communication system to optimize the end-to-end distribution of energy, beneficial to both suppliers and consumers. The Author(s), under exclusive license to Springer Nature Switzerland AG 2023. -
Message from IEEE InC4 2024 General Chair
[No abstract available] -
Outcome Evaluation of Child Sponsorship Programme of A Non-Governmental Organization
Child sponsorship programme is a vital tool for the integral development of the children at risk. Family based child sponsorship programme is one of the best services for the marginalized children which ensure their education while also respecting the rights of the children. The current study attempts to evaluate the outcome of child sponsorship programme of a non-Governmental organization newlinethrough a mixed method. Quasi-experimental post-test only design is the methodology used to conduct the study. The study evaluated the programme with regard to Self-esteem, Achievement motivation and family functioning of the sponsored children. The data was collected from 80 individuals for the quantitative study; using 3 standardized scales. Thematic analysis of qualitative data collected by interviewing 5 pairs of beneficiaries of the child sponsorship programme. The data was analysed using SPSS and R. The findings that there is a significant difference in terms of self-esteem and achievement motivation between the two groups of children. With regard to family newlinefunctioning conflict is much lesser among sponsored children (M=20.75) while compared to non-sponsored children (M=43.80). In terms of parenting and intimacy, the sponsored children are having higher score. Also, it was found out that self-esteem significantly mediated the impact of family functioning on achievement motivation of the individual(plt0.05). It is noticed that the effect of family functioning on achievement motivation was 0.504 and the direct effect was found to be 0.333. Selfesteem was found to strengthen the impact of family functioning on achievement motivation.Academic excellence improves the employability of respondents. Employment of newlinethose who received sponsorship can provide financial stability to the family. Therefore, this evaluation study confirmed the phenomenal effect of child sponsorship newlinein realizing inclusivity goals, as well as facilitate the personal, familial, economic, and social growth of sponsored children. -
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Low temparature synthesis of non-toxic monoclinic yttrium oxide quantum dots for display and biomedical applications /
Patent Number: 202141053609, Applicant: Soorya G Nath.
Monoclinic Y203 quantum dots were synthesized at low temperature using urea as the fuel. The sample preparation was done using simple laboratory hot air oven and the synthesis temperature was maintained at 90°C throughout the experiment. Prepared samples were characterized using x ray diffraction (XRD), Raman spectroscopy, high resolution transmission electron microscopy (HRTEM), UV- Vis absorption spectroscopy and photoluminescence (PL) Studies. -
Smart saviour system for women /
Patent Number: 202041038520, Applicant: Dr, E A Mary Anita.
The invention is directed to an loT based system for alerting the group of predetermined volunteers and officials located near the site of crime occurring to the end user. The system includes a manual activated push button switch for utilizing at times of distress occurring to the women which activation generates the alert signals to be transmitted wirelessly through the WiFi module to the central processing server. -
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AI Driven Finite Element Analysis on Spur Gear Assembly to Enhance the Fatigue Life and Minimized the Contact Pressure*
The major goal of the current research is to carry out mathematical and finite element analysis on spur gear assemblage to improve fatigue life as well as minimize contact pressure among contact teeth by modifying the face width of spur gear. AI automates FEA simulations and analyses, speeding up the design process. The investigation presented above was conducted using three separate 3d models of driving gear. The equivalent stress for the spur gear assembly of design-3 has decreased up to 13.45% in comparison to design-1, and the fatigue life has increased up to 81.59% at 600 N m, according to the results. Further AI models shall predict stress distribution, contact pressure, and other relevant factors in spur gear assemblies. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Analyzing the Inter-relationships of Business Recovery Challenges in the Manufacturing Industry: Implications for Post-pandemic Supply Chain Resilience
The COVID-19 pandemic brought about a rapid change in the global business environment, leading to increased risks of supply and demand disruptions. As society and the industry continue to acclimate to the new normal, the contributions of the manufacturing industry are critical in the recovery process. However, the existing literature lacks a framework to analyze the manufacturing sectors challenges during the recovery to enhance supply chain resilience (SCR). To address this gap, this study develops a framework for business recovery, especially in the manufacturing sector. A broad literature examination and expert survey were conducted to identify the critical potential business recovery challenges. Further, the interplay of business recovery challenges was analyzed using mixed methodologies such as total interpretive structure model and the cross-impact matrix multiplication applied to classification (MICMAC) to foster a framework that can assist the manufacturing industry in improving SCR. The study found that challenges like lack of flexible policies for handling disruptions and lack of management support toward building resilience have the highest driving power impeding business recovery. Other challenges, such as lack of reconfiguring production lines, lack of product competencies to meet disturbances, and less adoption of robust technologies are also identified as major challenges. The implications of the study offer valuable insights into global manufacturing industries. It also has significant propositions for the Pacific region. The Pacific region faces unique challenges, including geographic isolation, resource dependency, diverse economies, climate vulnerabilities, and complex trade relationships. The suggested frameworks adaptability and applicability to these regional characteristics enable businesses and policymakers in the Pacific to better understand and address the specific dynamics of post-pandemic recovery, ultimately contributing to enhanced SCR tailored to the regions needs. The study enriches the existing SCR literature by analyzing inter-relationships between business recovery challenges in the manufacturing industrys post-pandemic context. The Author(s) under exclusive licence to Global Institute of Flexible Systems Management 2024. -
Examining the facilitators of I4.0 practices to attain stakeholders collaboration: a circular perspective
The fourth industrial revolution (I4.0) has changed the traditional business model, bringing various benefits, including increased efficiency and productivity in organizations. However, to attain success in I4.0 practices requires collaboration from various stakeholders. This study objectives to identify the facilitators of I4.0 practices that can lead to successful collaboration among stakeholders from a circular perspective. An extensive literature review is performed to identify 14 potential facilitators. Further, the study adopts a mixed methodology of Best-Worst Method (BWM) and Interpretive Structural Modeling (ISM) to analyze the interconnectedness among the identified facilitators. BWM method was used to determine the relative importance of the identified facilitators, while ISM technique was used to determine the relationships between the facilitators of I4.0 practices. The findings from the study reveal that to strengthen stakeholder collaboration, organizations need to focus more on training and capacity-building programs and create more opportunities for technology exchange. 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.