Search results for: ML observability platform

Authors: P. Saee, Baiju Gopal

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YouTube has seen a surge in the recent years in the number of creators opening up about their mental illness on the video-sharing platform. In documenting their mental health, YouTubers perform an identity of their mental illness in the online world. Identity performance is a theory under identity research that has been readily applied to illness narratives and internet studies. Furthermore, in India, suffering from mental illnesses is regarded with stigma, making the act of taking mental health from a personal to a public space on YouTube a phenomenon worth exploring. Thus, the aim of this paper is to analyse the mental illness narratives of Indian YouTubers for understanding its performance in the virtual world. For this purpose, thematic narrative analysis on the interviews of four Indian YouTubers was conducted. This data was synthesized with analysis of the videos the YouTubers had uploaded on their channel sharing about their mental illness. The narratives of the participants shed light on two significant presentations that they engage in: (a) the identity of a survivor/fighter and (b) the identity of a silent sufferer. Further, the participants used metaphors to describe their illness, thereby co-constructing a corresponding identity based on their particular metaphors. Lastly, the process of bringing mental illness from back stage to front stage on YouTube involves a shift in the audience, from being rejecting and invalidating in real life to being supportive and encouraging in the virtual space. Limitations and implications for future research were outlined.

Keywords: cyber-psychology, internet, media, mental health, mental illness, technology

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Authors: Rabson Banda

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This abstract delves into the transformative journey of Rabson Banda, a visionary leader in Zambia who has harnessed the power of photovoice, mental fitness, and entrepreneurship to combat substance use disorders in the face of limited job opportunities in Africa. Rabson's personal battle with alcohol-induced disorder serves as the foundation for his pioneering work in establishing Elevated Initiatives, a grassroots organization dedicated to empowering individuals struggling with addiction through innovative approaches. Through the lens of photovoice, Rabson Banda amplifies the voices of those affected by substance abuse, providing a platform for self-expression and healing. By intertwining mental fitness techniques and entrepreneurial skills, he equips individuals with the tools needed to break free from the cycle of addiction and chart a new path toward holistic wellness and economic independence. Rabson Banda's story embodies resilience, hope, and the unwavering belief in the transformative power of community-driven initiatives. His work not only addresses the immediate challenges of substance use disorders but also addresses the root causes of addiction by advocating for increased job opportunities and economic empowerment in Zambia and across Africa for decent job creation and Entrepreneurship: A Lived Experience of Alcohol-Induced Disorder and Recovery in Zambia.

Keywords: mental fitness, entrepreneurship, photovoice, descent jobs

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Authors: L. Ereku, R. E. Mackay, A. Naveenathayalan, K. Ajayi, W. Balachandran

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Over the past decade the increase of sexually transmitted infections (STIs) especially in the developing world due to high cost and lack of sufficient medical testing have given rise to the need for a rapid, low cost point of care medical diagnostic that is disposable and most significantly reproduces equivocal results achieved within centralised laboratories. This paper present the development of a disposable PDMS microfluidic cartridge incorporating blisters filled with reagents required for isothermal DNA amplification in clinical diagnostics and point-of-care testing. In view of circumventing the necessity for external complex microfluidic pumps, designing on-chip pressurised fluid reservoirs is embraced using finger actuation and blister storage. The fabrication of the blisters takes into consideration three proponents that include: material characteristics, fluid volume and structural design. Silicone rubber is the chosen material due to its good chemical stability, considerable tear resistance and moderate tension/compression strength. The case of fluid capacity and structural form go hand in hand as the reagent need for the experimental analysis determines the volume size of the blisters, whereas the structural form has to be designed to provide low compression stress when deformed for fluid expulsion. Furthermore, the top and bottom section of the blisters are embedded with miniature polar opposite magnets at a defined parallel distance. These magnets are needed to lock or restrain the blisters when fully compressed so as to prevent unneeded backflow as a result of elasticity. The integrated chip is bonded onto a large microscope glass slide (50mm x 75mm). Each part is manufactured using a 3D printed mould designed using Solidworks software. Die-casting is employed, using 3D printed moulds, to form the deformable blisters by forcing a proprietary liquid silicone rubber through the positive mould cavity. The set silicone rubber is removed from the cast and prefilled with liquid reagent and then sealed with a thin (0.3mm) burstable layer of recast silicone rubber. The main microfluidic cartridge is fabricated using classical soft lithographic techniques. The cartridge incorporates microchannel circuitry, mixing chamber, inlet port, outlet port, reaction chamber and waste chamber. Polydimethylsiloxane (PDMS, QSil 216) is mixed and degassed using a centrifuge (ratio 10:1) is then poured after the prefilled blisters are correctly positioned on the negative mould. Heat treatment of about 50C to 60C in the oven for about 3hours is needed to achieve curing. The latter chip production stage involves bonding the cured PDMS to the glass slide. A plasma coroner treater device BD20-AC (Electro-Technic Products Inc., US) is used to activate the PDMS and glass slide before they are both joined and adequately compressed together, then left in the oven over the night to ensure bonding. There are two blisters in total needed for experimentation; the first will be used as a wash buffer to remove any remaining cell debris and unbound DNA while the second will contain 100uL amplification reagents. This paper will present results of chemical cell lysis, extraction using a biopolymer paper membrane and isothermal amplification on a low-cost platform using the finger actuated blisters for reagent storage. The platform has been shown to detect 1x105 copies of Chlamydia trachomatis using Recombinase Polymerase Amplification (RPA).

Keywords: finger actuation, point of care, reagent storage, silicone blisters

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Authors: Robert van Ling, Alexander Schwahn, Shanhua Lin, Ken Cook, Frank Steiner, Rowan Moore, Mauro de Pra

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Purpose: Demonstration of fast high resolution charge variant analysis for monoclonal antibody (mAb) therapeutics within 5 minutes. Methods: Three commercially available mAbs were used for all experiments. The charge variants of therapeutic mAbs (Bevacizumab, Cetuximab, Infliximab, and Trastuzumab) are analyzed on a strong cation exchange column with a linear pH gradient separation method. The linear gradient from pH 5.6 to pH 10.2 is generated over time by running a linear pump gradient from 100% Thermo Scientific™ CX-1 pH Gradient Buffer A (pH 5.6) to 100% CX-1 pH Gradient Buffer B (pH 10.2), using the Thermo Scientific™ Vanquish™ UHPLC system. Results: The pH gradient method is generally applicable to monoclonal antibody charge variant analysis. In conjunction with state-of-the-art column and UHPLC technology, ultra fast high-resolution separations are consistently achieved in under 5 minutes for all mAbs analyzed. Conclusion: The linear pH gradient method is a platform method for mAb charge variant analysis. The linear pH gradient method can be easily optimized to improve separations and shorten cycle times. Ultra-fast charge variant separation is facilitated with UHPLC that complements, and in some instances outperforms CE approaches in terms of both resolution and throughput.

Keywords: charge variants, ion exchange chromatography, monoclonal antibody, UHPLC

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Authors: Mark Williams

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The digital revolution has radically transformed our social environment creating vast opportunities for interconnectivity and social interaction. This revolution, however, has also changed the reach and impact of hate crime, with social media providing a new platform to victimize and harass users in their homes. In this way, developments in the information and communication technologies have exacerbated and facilitated the commission of hate crime, increasing its prevalence and impact. Unfortunately, legislators, policymakers and criminal justice professionals have struggled to keep pace with these technological developments, reducing their ability to intervene in, regulate and govern the commission of hate crimes online. This work is further complicated by the global nature of this crime due to the tendency for offenders and victims to reside in multiple different jurisdictions, as well as the need for criminal justice professionals to obtain the cooperation of private companies to access information required for prosecution. Drawing on in-depth interviews with key criminal justice professionals and policymakers with detailed knowledge in this area, this paper examines the specific challenges the police and prosecution services face as they attempt to intervene in and prosecute the commission of hate crimes online. It is argued that any attempt to reduce online othering, such as the commission of hate crimes online, must be multifaceted, collaborative and involve both innovative technological solutions as well as internationally agreed ethical and legal frameworks.

Keywords: cybercrime, digital policing, hate crime, social media

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Authors: Mahua Banerjee, Debtanu Maiti

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Zero-tillage cultivation is a farming practice that reduces costs while maintaining harvests and protecting the environment. Innovative partnerships among researchers, farmers, and other actors in the agricultural value chain have enabled the adoption of zero-tillage to sow rice in the Indo-Gangetic Plains, increasing farmers' incomes, fostering more sustainable use of soil and water, and providing a platform for cropping diversification and the introduction of other resource-conserving practices. A field experiment was conducted in the farmer’s field of Ausgram I Block, Burdwan, West Bengal, India under sandy loam soil with soil pH of 5.2, which is low in Nitrogen, medium in Phosphorus and Potassium. There were three techniques of tillage-T1: Zero tillage in Rice, T2: conventional tillage in Rice, T3: Rice grown with Drum seeder and three varieties namely V1: MTU 7029 V2-MTU 1010, V3: Pratikha thus making nine treatment combinations which were replicated thrice and the experiment was laid out in Factorial Randomised Block Design. Among the three varieties, rice variety MTU 7029 gave higher yield in all the tillage techniques. The highest yield was obtained under Zero tillage followed by conventional tillage. From economic analysis it was revealed that the benefit:cost ratio was higher in Zero tillage and rice cultivation by drum seeder. Zero-till is increasingly being adopted because it gives more yield at less cost, saves labour and farmer time. Farmers will be interested in this technology once they overcome their tillage biases.

Keywords: economics, Indo-Gangetic plain, rice, zero tillage, yield

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Authors: Jummalla Aashrith, N. L. Shiva Sai, K. Bhavya Sri

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The swift progress of web technology has not only amassed a vast reservoir of internet data but also triggered a substantial surge in data generation. The internet has metamorphosed into one of the dynamic hubs for online education, idea dissemination, as well as opinion-sharing. Notably, the widely utilized social networking platform Twitter is experiencing considerable expansion, providing users with the ability to share viewpoints, participate in discussions spanning diverse communities, and broadcast messages on a global scale. The upswing in online engagement has sparked a significant curiosity in subjective analysis, particularly when it comes to Twitter data. This research is committed to delving into sentiment analysis, focusing specifically on the realm of Twitter. It aims to offer valuable insights into deciphering information within tweets, where opinions manifest in a highly unstructured and diverse manner, spanning a spectrum from positivity to negativity, occasionally punctuated by neutrality expressions. Within this document, we offer a comprehensive exploration and comparative assessment of modern approaches to opinion mining. Employing a range of machine learning algorithms such as Naive Bayes and Logistic Regression, our investigation plunges into the domain of Twitter data streams. We delve into overarching challenges and applications inherent in the realm of subjectivity analysis over Twitter.

Keywords: machine learning, sentiment analysis, visualisation, python

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Authors: Shang-Hua Wu, Rong-Chi Chang, Horng–Twu Liaw

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Nowadays, competencies of e-learning project personnel are very important in assisting them in offering courses, serving students in an effective way, leveraging advantages, strengthen their relationships with potential students, etc. among e-learning platforms, MOOCs has recently attracted increasing focuses in distance education since it can be conducted for a large numbers of virtual learners. Nonetheless, since MOOCs is a relatively new e-learning platform, top concerns have been paid to what competencies are important for e-learning personnel to consider. Taking this need, this research aimed to carry out an in-depth exploration of competency requirements of MOOCs (e-learning) project personnel in Taiwan vocational schools. Data were collected through thorough literature reviews and discussions and competency analysis was carried out using Delphi technique questionnaires. The results show that that MOOCs (e-learning) project personnel’ professional competency lie in three main dimensions, among which ‘demand analysis competency’ (i.e., containing 10 major competences and 48 subordinate capabilities) is the most important competency, followed by ‘project management competency’ (i.e., comprising 6 major competences and 31 secondary capabilities), and finally ‘digital content production competency’ (i.e., including 12 major competences and 79 secondary capabilities). As such, in Taiwan context with different organizational scales and market sizes, the e-learning competency items and unique experience/ achievements throughout the promotion process obtained in this research will provide useful references for academic institutions in promoting e-learning.

Keywords: competency analysis, Delphi technique questionnaire, e-learning, massive open online courses

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Authors: Majid Samiee Zonoozian

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For such important constructions as jacket type platforms, scrupulous attention in analysis, design and calculation processes is needed. The reliability assessment method has been established into an extensively used method to behavior safety calculation of jacket platforms. In the present study, a methodology for the reliability calculation of an offshore jacket platform in contradiction of the extreme wave loading state is available. Therefore, sensitivity analyses are applied to acquire the nonlinear response of jacket-type platforms against extreme waves. The jacket structure is modeled by applying a nonlinear finite-element model with regards to the tubular members' behave. The probability of a member’s failure under extreme wave loading is figured by a finite-element reliability code. The FORM and SORM approaches are applied for the calculation of safety directories and reliability indexes have been detected. A case study for a fixed jacket-type structure positioned in the Persian Gulf is studied by means of the planned method. Furthermore, to define the failure standards, equations suggested by the 21st version of the API RP 2A-WSD for The jacket-type structures’ tubular members designing by applying the mixed axial bending and axial pressure. Consequently, the effect of wave Loades in the reliability index was considered.

Keywords: Jacket-Type structure, reliability, failure probability, tubular members

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Authors: Sanaz Seraj, Shohre Rouhani

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Recently, graphene has gained much attention because of its unique optical, mechanical, electrical, and thermal properties. Graphene has been used as a key material in the technological applications in various areas such as sensors, drug delivery, super capacitors, transparent conductor, and solar cell. It has a superior quenching efficiency for various fluorophores. Based on these unique properties, the optical sensors with graphene materials as the energy acceptors have demonstrated great success in recent years. During quenching, the emission of a fluorophore is perturbed by a quencher which can be a substrate or biomolecule, and due to this phenomenon, fluorophore-quencher has been used for selective detection of target molecules. Among fluorescence dyes, 1,8-naphthalimide is well known for its typical intramolecular charge transfer (ICT) and photo-induced charge transfer (PET) fluorophore, strong absorption and emission in the visible region, high photo stability, and large Stokes shift. Derivatives of 1,8-naphthalimides have found applications in some areas, especially fluorescence sensors. Herein, the fluorescence quenching of graphene oxide has been carried out on a naphthalimide dye as a fluorescent probe model. The quenching ability of graphene oxide on naphthalimide dye was studied by UV-VIS and fluorescence spectroscopy. This study showed that graphene is an efficient quencher for fluorescent dyes. Therefore, it can be used as a suitable candidate sensing platform. To the best of our knowledge, studies on the quenching and absorption of naphthalimide dyes by graphene oxide are rare.

Keywords: fluorescence, graphene oxide, naphthalimide dye, quenching

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Authors: Leman Korkmaz, Bahar Bahtiyar-Saygan

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Objective: The COVID-19 pandemic has been affecting the whole world since the beginning of 2020. In addition to health-related and financial effects, there seem to be significant psychological effects as well, among them those related to people’s views and representations of marriage and divorce. Background: Although various impacts of COVID-19 have been investigated since the beginning of the pandemic, there is a limited number of studies on its effects concerning relationships. This research aims to understand how the COVID-19 pandemic affects the views on and representations of marriage and divorce by conducting two studies. Method: In the first study, one-to-one semi-structured interviews were conducted with 31 participants (20 single and 11 married individuals) to investigate their evaluations regarding the effect of COVID-19 on people’s views of marriage in general and their own views of marriage in particular. In the second study, 298 entries on the most frequently used online social platform in Turkey (EkşiSözlük) under two separate headings for COVID-19 impact on marriage and divorce were analyzed, and meaningful thematic units were formed. Results: The findings of the thematic analysis indicated that participants mostly mentioned both the positive and negative effects of COVID-19 on the views and representations of marriage. There were both common (e.g., loneliness, violence, etc.) and distinct (e.g., sexuality, positive and negative effects on attitudes towards marriage, etc.) thematic units between the results of the two studies. Implications: There are considerable implications discussed in light of the literature on Terror Management Theory, Attachment Theory, stress research, and growth perspective.

Keywords: COVID-19 pandemic, divorce, marriage, relationships, representations, views

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Authors: Geetakshi Arora, Danish Malhotra

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Diabetic wounds are serious health issues and often fail to heal, leading to limb amputation that makes the life of the patient miserable. Delayed wound healing has been characterized by an increase in matrix metalloproteinase-9 (MMP-9). Thus research throughout the world has been going on to develop selective MMP-9 inhibitors for aiding diabetic wound healing. Bioactive constituents from natural sources always served as potential leads in drug development with high rates of success. Considering the need for novel selective MMP-9 inhibitors and the importance of natural bioactive compounds in drug development, we have screened a library of bioactive constituents from plant sources that were effective in diabetic wound healing on human MMP-9 (hMMP-9) using molecular docking studies. Screened constituents are ranked according to their dock score, ∆G value (binding affinity), and Ligand efficiency evaluated from FleXX docking and Hyde scoring modules available with drug designing platform LeadIT. Rhamnocitrin showed the highest correlation between dock score, ∆G value (binding affinity), and Ligand efficiency was further explored for binding interactions with hMMP-9. The overall study suggest that Rhamnocitrin is sufficiently decorated with both hydrophilic and hydrophobic substitutions that perfectly block hMMP-9 and act as a potential lead in the design and development of selective hMMP-9 inhibitors.

Keywords: MMP-9, diabetic wound, molecular docking, phytoconstituents

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Authors: Itamir de Morais Barroca Filho, Cephas A. S. Barreto, Ramon Malaquias, Cezar Miranda Paula de Souza, Arthur Costa Gorgônio, João C. Xavier-Júnior, Mateus Firmino, Fellipe Matheus Costa Barbosa

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Information and Communication Technologies (ICT) in healthcare are crucial for efficiently delivering medical healthcare services to patients. These ICTs are also known as e-health and comprise technologies such as electronic record systems, telemedicine systems, and personalized devices for diagnosis. The focus of e-health is to improve the quality of health information, strengthen national health systems, and ensure accessible, high-quality health care for all. All the data gathered by these technologies make it possible to help clinical staff with automated decisions using machine learning. In this context, we collected patient data, such as heart rate, oxygen saturation (SpO2), blood pressure, respiration, and others. With this data, we were able to develop machine learning models for patients’ risk of death and estimate the length of stay in ICU beds. Thus, this paper presents the methodology for applying machine learning techniques to develop these models. As a result, although we implemented these models on an IoT healthcare platform, helping clinical staff in healthcare in an ICU, it is essential to create a robust clinical validation process and monitoring of the proposed models.

Keywords: ICT, e-health, machine learning, ICU, healthcare

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Authors: Ying Han, Weirong Chen, Qi Li

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An energy management method based on equivalent hydrogen consumption minimum strategy is proposed in this paper aiming at the direct-current (DC) microgrid consisting of photovoltaic cells, fuel cells, energy storage devices, converters and DC loads. The rational allocation of fuel cells and battery devices is achieved by adopting equivalent minimum hydrogen consumption strategy with the full use of power generated by photovoltaic cells. Considering the balance of the battery’s state of charge (SOC), the optimal power of the battery under different SOC conditions is obtained and the reference output power of the fuel cell is calculated. And then a droop control method based on time-varying droop coefficient is proposed to realize the automatic charge and discharge control of the battery, balance the system power and maintain the bus voltage. The proposed control strategy is verified by RT-LAB hardware-in-the-loop simulation platform. The simulation results show that the designed control algorithm can realize the rational allocation of DC micro-grid energy and improve the stability of system.

Keywords: DC microgrid, equivalent minimum hydrogen consumption strategy, energy management, time-varying droop coefficient, droop control

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Authors: Loai AbdAllah, Mahmoud Kaiyal

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Missing values in real-world datasets are a common problem. Many algorithms were developed to deal with this problem, most of them replace the missing values with a fixed value that was computed based on the observed values. In our work, we used a distance function based on Bhattacharyya distance to measure the distance between objects with missing values. Bhattacharyya distance, which measures the similarity of two probability distributions. The proposed distance distinguishes between known and unknown values. Where the distance between two known values is the Mahalanobis distance. When, on the other hand, one of them is missing the distance is computed based on the distribution of the known values, for the coordinate that contains the missing value. This method was integrated with Wikaya, a digital health company developing a platform that helps to improve prevention of chronic diseases such as diabetes and cancer. In order for Wikaya’s recommendation system to work distance between users need to be measured. Since there are missing values in the collected data, there is a need to develop a distance function distances between incomplete users profiles. To evaluate the accuracy of the proposed distance function in reflecting the actual similarity between different objects, when some of them contain missing values, we integrated it within the framework of k nearest neighbors (kNN) classifier, since its computation is based only on the similarity between objects. To validate this, we ran the algorithm over diabetes and breast cancer datasets, standard benchmark datasets from the UCI repository. Our experiments show that kNN classifier using our proposed distance function outperforms the kNN using other existing methods.

Keywords: missing values, incomplete data, distance, incomplete diabetes data

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Authors: Raymond Xu, Cindy Jingru Wang

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Social media has become a globally connected and influencing platform. Social media data, such as tweets, can help predict the spread of pandemics and provide individuals and healthcare providers early warnings. Public psychological reactions and opinions can be efficiently monitored by AI models on the progression of dominant topics on Twitter. However, statistics show that as the coronavirus spreads, so does an infodemic of misinformation due to pandemic-related factors such as unemployment and lockdowns. Social media algorithms are often biased toward outrage by promoting content that people have an emotional reaction to and are likely to engage with. This can influence users’ attitudes and cause confusion. Therefore, social media is a double-edged sword. Combating fake news and biased content has become one of the essential tasks. This research analyzes the variety of methods used for fake news detection covering random forest, logistic regression, support vector machines, decision tree, naive Bayes, BoW, TF-IDF, LDA, CNN, RNN, LSTM, DeepFake, and hierarchical attention network. The performance of each method is analyzed. Based on these models’ achievements and limitations, a multi-dimensional AI framework is proposed to achieve higher accuracy in infodemic detection, especially pandemic-related news. The model is trained on contextual content, images, and news metadata.

Keywords: artificial intelligence, fake news detection, infodemic detection, image recognition, sentiment analysis

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Authors: Dada Kolawole Segun

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Transdermal drug delivery has gained popularity as a non-invasive method for controlled drug release compared to traditional delivery routes. Dissolvable transdermal patches have emerged as a promising platform for delivering a variety of drugs due to their ease of use. The objective of this research was to create and characterize dissolvable transdermal patches using various compositions and ratios of hyaluronic acid and zinc oxide nanoparticles. A micromolding technique was utilized to fabricate the patches, which were subsequently characterized using scanning electron microscopy, atomic force microscopy, and tensile strength testing. In vitro drug release studies were conducted to evaluate the drug release kinetics of the patches. The study found that the mechanical strength and dissolution properties of the patches were influenced by the hyaluronic acid and zinc oxide nanoparticle ratios used in the fabrication process. Moreover, the patches demonstrated controlled delivery of model drugs through the skin, highlighting their potential for transdermal drug delivery applications. The results suggest that dissolvable transdermal patches can be tailored to meet specific requirements for drug delivery applications using different compositions and ratios of hyaluronic acid and zinc oxide nanoparticles. This development has the potential to improve treatment outcomes and patient compliance in various therapeutic areas.

Keywords: transdermal drug delivery, characterization, skin permeation, biodegradable materials

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Authors: Vijay Kumar, Mack Moyo, Johannes Van Staden

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Lachenalia viridiflora is a critically endangered bulbous plant with high potential on the international floriculture market. In the present study, an efficient protocol for in vitro plantlet regeneration through somatic embryogenesis was developed. Embryogenic callus was established on Murashige and Skoog (MS) basal medium supplemented with various concentrations and combinations of picloram and thidiazuron (TDZ). A high number of SEs (28.5 ± 1.49) with at different developmental stages of somatic embryos (SEs: globular embryos, torpedo and cotyledon embryo with bipolar characteristics) was obtained on Murashige and Skoog (MS) (Murashige and Skoog 1962) medium with 2.5 μM picloram, and 1.0 μM TDZ. Histological and scanning electron microscopic (SEM) analysis confirmed the presence of somatic embryos. Mature somatic embryos germinated and developed into plantlets after 6 weeks on half/full strength MS medium. High plant regeneration frequency (91.11 %) was achieved on full-strength MS medium supplemented with 5 μM phloroglucinol (PG). Well-developed healthy plantlets were successfully acclimatized in the greenhouse with a survival rate of 80%. The result of this study is beneficial in the mass propagation of high-quality Lachenalia viridiflora clonal plants for the commercial horticultural market and also provides a platform for future genetic transformation studies on the plant.

Keywords: horticultural plant, Lachenalia viridiflora, phloroglucinol, somatic embryogenesis, thidiazuron

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Authors: Du T. Tran, Anh M. N. Nguyen

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Writing skill is one of the productive abilities and plays a vital role in encouraging communication. Although certain hurdles limit students from enhancing their writing skills, the introduction and widespread use of internet technology impact their education significantly. In this context, the research aims to investigate the effects of electronic portfolios (e-portfolios) on English as a foreign language (EFL) high school students’ writing ability, learners’ and instructors’ attitudes towards the use of e-portfolios in writing classes at high schools in Binh Duong province. The sample includes 15 teachers and 300 twelfth graders at 03 high schools in Binh Duong province. Facebook was chosen as an e-portfolio platform where the students created and developed their personal e-portfolios. The data were collected both quantitatively and qualitatively through mixed methods using the tools of a pre-test, a post-test (for students), questionnaires (for both teachers and students), and a semi-structured interview (for teachers in charge of the course). The survey results show that e-portfolios considerably impact EFL high school students writing abilities. The research findings also reveal challenges and technological drawbacks. For the optimal use of e-portfolios in writing courses in particular and for other language courses in general, recommendations are made for school managers, instructors, and learners to optimize the effects and for further research to shed more light on the topic

Keywords: attitudes, electronic portfolios, English writing ability, Vietnamese high school students

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Authors: Atikah Binti Azudin, Nurin Nazlah Binti Muhamad Yani, Nur Alya Nadhirah Binti Naaidith, Nur Amylia Wahida Binti Mat Ayob, Nurshamimi Shakirah Binti Suboh, Nur Auni Batrisyia Binti Md. Zaini, Nur Aziemah Binti Mohamad, Nurul Suffiyah Binti Sa’Dun, Sabrina Sasha Izzati Binti Zubaile, Umi Huwaina Binti Ahmiruddin, Wan Nur Shafawati Binti Wan Ghazali

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A hazard alert is intended to provide brief information about significant incidents or existing difficulties in Department workplaces. The alert gives guidelines for proper processes, practices, and controls to be applied. When operated in accordance with the manufacturer's instructions, any machine or tool utilized at work provides a safe and dependable platform for workers to accomplish job duties. However, when not utilized appropriately, the machine might pose a major hazard to employees. Employers have a duty to keep employees safe in this scenario. This Hazard Alert outlines specific occupational dangers and the controls that employers must apply to prevent injury or fatal accidents. There have been several cases of hazard alerts in Malaysia, which have had a negative impact on a few workers. Looking on the bright side, we can overcome every incident in a variety of ways. One of these is that only qualified individuals operate mobile machinery and equipment. In addition, employees may also perform frequent pre-use inspections of machinery to discover and fix flaws. Hazard alert is very important, and this study would cover a variety of subjects, including the methods employed.

Keywords: safe, hazard, impacts, duties.

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Authors: Tran Duong Nguyen, Marwan Shagar, Qinghao Zeng, Aras Maqsoodi, Pardis Pishdad, Eunhwa Yang

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Construction supply chain management (CSCM) involves the collaboration of many disciplines and actors, which generates vast amounts of data. However, inefficient, fragmented, and non-standardized data storage often hinders this data exchange. The industry has adopted building information modeling (BIM) -a digital representation of a facility's physical and functional characteristics to improve collaboration, enhance transmission security, and provide a common data exchange platform. Still, the volume and complexity of data require tailored information categorization, aligning with stakeholders' preferences and demands. To address this, artificial intelligence (AI) can be integrated to handle this data’s magnitude and complexities. This research aims to develop an integrated and efficient approach for data exchange in CSCM by utilizing AI. The paper covers five main objectives: (1) Investigate existing framework and BIM adoption; (2) Identify challenges in data exchange; (3) Propose an integrated framework; (4) Enhance data transmission security; and (5) Develop data exchange in CSCM. The proposed framework demonstrates how integrating BIM and other technologies, such as cloud computing, blockchain, and AI applications, can significantly improve the efficiency and accuracy of data exchange in CSCM.

Keywords: construction supply chain management, BIM, data exchange, artificial intelligence

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Authors: Zuzana Chaloupková, Zdeňka Marková, Václav Ranc, Radek Zbořil

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Prostate cancer is now one of the most serious oncological diseases in men with an incidence higher than that of all other solid tumors combined. Diagnosis of prostate cancer usually involves detection of related genes or detection of marker proteins, such as PSA. One of the new potential markers is PSMA (prostate specific membrane antigen). PSMA is a unique membrane bound glycoprotein, which is considerably overexpressed on prostate cancer as well as neovasculature of most of the solid tumors. Commonly applied methods for a detection of proteins include techniques based on immunochemical approaches, including ELISA and RIA. Magnetically assisted surface enhanced Raman spectroscopy (MA-SERS) can be considered as an interesting alternative to generally accepted approaches. This work describes a utilization of MA-SERS in a detection of PSMA in human blood. This analytical platform is based on magnetic nanocomposites Fe3O4@Ag, functionalized by a low-molecular selector labeled as JB303. The system allows isolating the marker from the complex sample using application of magnetic force. Detection of PSMA is than performed by SERS effect given by a presence of silver nanoparticles. This system allowed us to analyze PSMA in clinical samples with limits of detection lower than 1 ng/mL.

Keywords: diagnosis, cancer, PSMA, MA-SERS, Ag nanoparticles

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Authors: Argyro Maria Skourmalla

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Internationalization and management of linguistic diversity in Higher Education (HE) have gained much attention in research in the last few years. Internationalization policies in HE aims at promoting the dual role of Higher Education Institutions (HEIs), civilization and competitiveness. In the context of the European Union, the European Education Area initiative aims at “inclusive national education and training systems” through networking and exchange between HEIs. However, the use of English as a ‘lingua academica’ in the place of the official, national, and regional/minority languages raises questions regarding linguistic diversity, linguistic rights and concerns that have to do with the scientific weakening of these languages. In fact, the European Civil Society Platform for Multilingualism, in the Declaration for Multilingualism in Higher Education, draws attention to the use of English at the expense of other regional/national languages and the impact of English-only language policy on an epistemological level. The above issues were brought up during semi-structured interviews with lecturing staff coming from three multilingual Universities in Europe. Lecturers shared their experiences and the practices they use to manage linguistic diversity in these three Universities. Findings show that even though different languages are used in teaching across disciplines, English -or ‘Globish’ as mentioned during an interview- is widely used in research. Despite English being accepted as the “lingua academica,” issues regarding loss of identity come up

Keywords: higher education, internationalization, linguistic diversity, teaching, research, English

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Authors: Branislav Timotijevic, Yves Petremand, Markus Luetzelschwab, Dara Bayat, Laurent Aebi

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Optical miniaturized sensors with remote readout are required devices for the monitoring in harsh electromagnetic environments. As an example, in turbo and hydro generators, excessively high vibrations of the end-windings can lead to dramatic damages, imposing very high, additional service costs. A significant change of the generator temperature can also be an indicator of the system failure. Continuous monitoring of vibrations, temperature, humidity, and gases is therefore mandatory. The high electromagnetic fields in the generators impose the use of non-conductive devices in order to prevent electromagnetic interferences and to electrically isolate the sensing element to the electronic readout. Metal-free sensors are good candidates for such systems since they are immune to very strong electromagnetic fields and given the fact that they are non-conductive. We have realized miniature optical accelerometer and temperature sensors for a remote sensing of the harsh environments using the common, inexpensive silicon Micro Electro-Mechanical System (MEMS) platform. Both devices show highly linear response. The accelerometer has a deviation within 1% from the linear fit when tested in a range 0 – 40 g. The temperature sensor can provide the measurement accuracy better than 1 °C in a range 20 – 150 °C. The design of other type of sensors for the environments with high electromagnetic interferences has also been discussed.

Keywords: optical MEMS, temperature sensor, accelerometer, remote sensing, harsh environment

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Authors: Pauli P.Y. Lai

Abstract:

Students with Special Education Needs (SEN) face many challenges in learning. Various challenges include difficulty in handwriting, slow understanding and assimilation, difficulty in paying attention during class, and lack of communication skills. To engage students with Special Education Needs in class with general students, Blackboard Collaborate is used as a teaching and learning tool to deliver a lecture with interactive activities. Blackboard Collaborate provides a good platform to create and enhance active, collaborative and interactive learning experience whereby the SEN students can easily interact with their general peers and the instructor by using the features of drawing on a virtual whiteboard, file sharing, classroom chatter, breakout room, hand-raising feature, polling, etc. By integrating a blended learning approach with Blackboard Collaborate, the students with Special Education Needs could engage in interactive activities with ease in class. Our research aims at exploring and discovering the use of Blackboard Collaborate for inclusive education based on a qualitative design with in-depth interviews. Being served in a general education environment, three university students with different kinds of learning disabilities have participated in our study. All participants agreed that functions provided by Blackboard Collaborate have enhanced their learning experiences and helped them learn better. Their academic performances also showed that SEN students could perform well with the help of technology. This research studies different aspects of using Blackboard Collaborate to create an inclusive learning environment for SEN students.

Keywords: blackboard collaborate, enhanced learning experience, inclusive education, special education needs

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Authors: Ulemu Maseko

Abstract:

This research is a critical assessment of the empowerment of Muslim women in Malawi. The study assessed, evaluated, and analyzed how the Muslim Women Organization (MWO) has influenced gender equality and women empowerment in different Islamic communities. In analyzing the data collected for this research, the study has examined the following topics: The way MWO has interpreted Islamic women’s rights, the various stereotypes Muslim women face, and lastly, the factors contributing to the limitation of Muslim women’s rights in Malawi. Towards this analysis, the study revealed that women groups such as MWO are crucial in understanding Muslim women and the different dynamics related to their empowerment. Therefore, it is necessary to understand how Muslim women comprehend various Islamic sources and how they link religion to their position and participation in society. To achieve the scope of this study, relevant works of literature that best described Islam in Malawi, Muslim women groups, and women empowerment in Malawi were used, coupled with a qualitative research approach that involved interviews, focus group discussions, and participant observations. In addition, phenomenology and feminist theoretical frameworks were used to examine and analyze the findings. Based on the findings, it can be concluded that MWO is a significant body for gender equality and women empowerment initiatives in the Malawian Islamic community. Since its establishment in 1985 till the time of this study, MWO has been an imperative driving force towards an Islamic women’s discourse that uses Islamic teachings, faith, policies, and practices to justify the role of the Muslim woman in society. This has been enlightening for their platform and has given them more confidence to justify the empowerment of Muslim women and support different initiatives towards social change.

Keywords: Islam, women, empowerment, Malawi

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Authors: Noora Al Muftah, Reda Rawi, Richard Thompson, Halima Bensmail

Abstract:

Clinical responses to anticancer therapies are often restricted to a subset of patients. In some cases, mutated cancer genes are potent biomarkers of response to targeted agents. There is an urgent need to identify biomarkers that predict which patients with are most likely to respond to treatment. Systematic efforts to correlate tumor mutational data with biologic dependencies may facilitate the translation of somatic mutation catalogs into meaningful biomarkers for patient stratification. To identify genomic features associated with drug sensitivity and uncover new biomarkers of sensitivity and resistance to cancer therapeutics, we have screened and integrated a panel of several hundred cancer cell lines from different databases, mutation, DNA copy number, and gene expression data for hundreds of cell lines with their responses to targeted and cytotoxic therapies with drugs under clinical and preclinical investigation. We found mutated cancer genes were associated with cellular response to most currently available Glioma cancer drugs and some frequently mutated genes were associated with sensitivity to a broad range of therapeutic agents. By linking drug activity to the functional complexity of cancer genomes, systematic pharmacogenomic profiling in cancer cell lines provides a powerful biomarker discovery platform to guide rational cancer therapeutic strategies.

Keywords: cancer, gene network, Lasso, penalized regression, P-values, unbiased estimator

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Authors: Nzeaka Emmanuel Ezimako

Abstract:

With the advent of new media, especially X, the government's previous foundation of media power and control in Nigeria has been diminished because they can no longer regulate the public sphere to control social action and reactions. This study examined how IPOB (Indigenous People of Biafra) resistance and the 2020 #Endsars aborted revolution were able to control public discourse during social upheavals, as well as how the new media have diminished the influence that the government and media owners once had over Nigerians. This study is significant because it recognizes the social transformation brought about by the emergence of new media, particularly with the most widely used social media platform in Nigeria, X, and how citizen media activity is altering the media ecosystem and challenging the government and private media owners' hegemony over news coverage in Nigeria to the point where the government saw X as a blatant threat to its hegemony and banned it in 2021. This study used a triangulation of qualitative and quantitative analysis with 300 respondents (n=300) from different sectors of the media practitioners, scholars, and university students in Nigeria to draw a conclusion in line with Democratic Participant Media Theory, which questions the necessity for centralized media regulated by the government and conglomerates. The contributions to filling the gap in the literature are meant to aid readers in comprehending how X has developed into a dominant force in Nigerian media, particularly during the crisis. The study offers recommendations for media executives, policymakers, and the public on how to manage the media conflict that has developed because of the loss of official government oversight of the mass media due to the emergence of X in the media space.

Keywords: Twitter, new media, regulations, dominance, resistance

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Authors: Jie Zhao, Meng Su

Abstract:

Image recognition, as one of the most critical technologies in computer vision, works to help machine-like robotics understand a scene, that is, if deployed appropriately, will trigger the revolution in remote sensing and industry automation. With the developments of AI technologies, there are many prevailing and sophisticated neural networks as technologies developed for image recognition. However, computer vision platforms as hardware, supporting neural networks for image recognition, as crucial as the neural network technologies, need to be more congruently addressed as the research subjects. In contrast, different computer vision platforms are deterministic to leverage the performance of different neural networks for recognition. In this paper, three different computer vision platforms – Jetson Nano(with 4GB), a standalone laptop(with RTX 3000s, using CUDA), and Google Colab (web-based, using GPU) are explored and four prominent neural network architectures (including AlexNet, VGG(16/19), GoogleNet, and ResNet(18/34/50)), are investigated. In the context of pairwise usage between different computer vision platforms and distinctive neural networks, with the merits of recognition accuracy and time efficiency, the performances are evaluated. In the case study using public imageNets, our findings provide a nuanced perspective on optimizing image recognition tasks across Edge-AI platforms, offering guidance on selecting appropriate neural network structures to maximize performance under hardware constraints.

Keywords: alexNet, VGG, googleNet, resNet, Jetson nano, CUDA, COCO-NET, cifar10, imageNet large scale visual recognition challenge (ILSVRC), google colab

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Authors: Walter Bernhofer, Peter Haber, Tobias Mayer, Manfred Mayr, Markus Ziegler

Abstract:

Current preventive maintenance measures are cost intensive and not efficient. With the available sensor data of state of the art internet of things devices new possibilities of automated data processing emerge. Current advances in data science and in machine learning enable new, so called predictive maintenance technologies, which empower data scientists to forecast possible system failures. The goal of this approach is to cut expenses in preventive maintenance by automating the detection of possible failures and to improve efficiency and quality of maintenance measures. Additionally, a centralization of the sensor data monitoring can be achieved by using this approach. This paper describes the approach of three students to define a reference architecture for a predictive maintenance solution in the internet of things domain with a connected smartphone app for service technicians. The reference architecture is validated by a case study. The case study is implemented with current Microsoft Azure cloud technologies. The results of the case study show that the reference architecture is valid and can be used to achieve a system for predictive maintenance execution with the cloud components of Microsoft Azure. The used concepts are technology platform agnostic and can be reused in many different cloud platforms. The reference architecture is valid and can be used in many use cases, like gas station maintenance, elevator maintenance and many more.

Keywords: case study, internet of things, predictive maintenance, reference architecture

Procedia PDF Downloads 252