Search results for: color metrics

Authors: Andrew Laming, John Hattie, Mark Wilson

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Nine Queensland Independent high schools provided deidentified student-matched ATAR and NAPLAN data for all 1217 ATAR graduates since 2020 who also sat NAPLAN at the school. Graduating cohorts from the nine schools contained a mean 100 ATAR graduates with previous NAPLAN data from their school. Excluded were vocational students (mean=27) and any ATAR graduates without NAPLAN data (mean=20). Based on Index of Community Socio-Educational Access (ICSEA) prediction, all schools had larger that predicted proportions of their students graduating with ATARs. There were an additional 173 students not releasing their ATARs to their school (14%), requiring this data to be inferred by schools. Gain was established by first converting each student’s strongest NAPLAN domain to a statewide percentile, then subtracting this result from final ATAR. The resulting ‘percentile shift’ was corrected for plausible ATAR participation at each NAPLAN level. Strongest NAPLAN domain had the highest correlation with ATAR (R2=0.58). RESULTS School mean NAPLAN scores fitted ICSEA closely (R2=0.97). Schools achieved a mean cohort gain of two ATAR rankings, but only 66% of students gained. This ranged from 46% of top-NAPLAN decile students gaining, rising to 75% achieving gains outside the top decile. The 54% of top-decile students whose ATAR fell short of prediction lost a mean 4.0 percentiles (or 6.2 percentiles prior to correction for regression to the mean). 71% of students in smaller schools gained, compared to 63% in larger schools. NAPLAN variability in each of the 13 ICSEA1100 cohorts was 17%, with both intra-school and inter-school variation of these values extremely low (0.3% to 1.8%). Mean ATAR change between years in each school was just 1.1 ATAR ranks. This suggests consecutive school cohorts and ICSEA-similar schools share very similar distributions and outcomes over time. Quantile analysis of the NAPLAN/ATAR revealed heteroscedasticity, but splines offered little additional benefit over simple linear regression. The NAPLAN/ATAR R2 was 0.33. DISCUSSION Standardised data like NAPLAN and ATAR offer educators a simple no-cost progression metric to analyse performance in conjunction with their internal test results. Change is expressed in percentiles, or ATAR shift per student, which is layperson intuitive. Findings may also reduce ATAR/vocational stream mismatch, reveal proportions of cohorts meeting or falling short of expectation and demonstrate by how much. Finally, ‘crashed’ ATARs well below expectation are revealed, which schools can reasonably work to minimise. The percentile shift method is neither value-add nor a growth percentile. In the absence of exit NAPLAN testing, this metric is unable to discriminate academic gain from legitimate ATAR-maximizing strategies. But by controlling for ICSEA, ATAR proportion variation and student mobility, it uncovers progression to ATAR metrics which are not currently publicly available. However achieved, ATAR maximisation is a sought-after private good. So long as standardised nationwide data is available, this analysis offers useful analytics for educators and reasonable predictivity when counselling subsequent cohorts about their ATAR prospects.  

Keywords: NAPLAN, ATAR, analytics, measurement, gain, performance, data, percentile, value-added, high school, numeracy, reading comprehension, variability, regression to the mean

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Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

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Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

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Authors: Shayan Mohajer Hamidi

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Federated Learning (FL) has emerged as a promising paradigm for training machine learning models on distributed data without the need for centralized data aggregation. In the realm of wireless communications, FL has the potential to leverage the vast amounts of data generated by wireless devices to improve model performance and enable intelligent applications. However, the fairness aspect of FL in wireless communications remains largely unexplored. This abstract presents an idea for fair federated learning in wireless communications, addressing the challenges of imbalanced data distribution, privacy preservation, and resource allocation. Firstly, the proposed approach aims to tackle the issue of imbalanced data distribution in wireless networks. In typical FL scenarios, the distribution of data across wireless devices can be highly skewed, resulting in unfair model updates. To address this, we propose a weighted aggregation strategy that assigns higher importance to devices with fewer samples during the aggregation process. By incorporating fairness-aware weighting mechanisms, the proposed approach ensures that each participating device's contribution is proportional to its data distribution, thereby mitigating the impact of data imbalance on model performance. Secondly, privacy preservation is a critical concern in federated learning, especially in wireless communications where sensitive user data is involved. The proposed approach incorporates privacy-enhancing techniques, such as differential privacy, to protect user privacy during the model training process. By adding carefully calibrated noise to the gradient updates, the proposed approach ensures that the privacy of individual devices is preserved without compromising the overall model accuracy. Moreover, the approach considers the heterogeneity of devices in terms of computational capabilities and energy constraints, allowing devices to adaptively adjust the level of privacy preservation to strike a balance between privacy and utility. Thirdly, efficient resource allocation is crucial for federated learning in wireless communications, as devices operate under limited bandwidth, energy, and computational resources. The proposed approach leverages optimization techniques to allocate resources effectively among the participating devices, considering factors such as data quality, network conditions, and device capabilities. By intelligently distributing the computational load, communication bandwidth, and energy consumption, the proposed approach minimizes resource wastage and ensures a fair and efficient FL process in wireless networks. To evaluate the performance of the proposed fair federated learning approach, extensive simulations and experiments will be conducted. The experiments will involve a diverse set of wireless devices, ranging from smartphones to Internet of Things (IoT) devices, operating in various scenarios with different data distributions and network conditions. The evaluation metrics will include model accuracy, fairness measures, privacy preservation, and resource utilization. The expected outcomes of this research include improved model performance, fair allocation of resources, enhanced privacy preservation, and a better understanding of the challenges and solutions for fair federated learning in wireless communications. The proposed approach has the potential to revolutionize wireless communication systems by enabling intelligent applications while addressing fairness concerns and preserving user privacy.

Keywords: federated learning, wireless communications, fairness, imbalanced data, privacy preservation, resource allocation, differential privacy, optimization

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Authors: Michelle Belinda S. Weerawardana, Gobika Thiripuranathar, Priyani A. Paranagama

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Most of fresh vegetables and fruits available in the retail markets undergo a physiological disorder in its appearance and coloration, which indeed discourages consumer purchase. A loss of millions of dollars yearly to the food industry had been due to this pronounced color reaction called Enzymatic Browning which is driven due to the catalytic activity by an oxidoreductase enzyme, polyphenol oxidase (PPO). The enzyme oxidizes the phenolic compounds which are abundantly available in fruits and vegetables as substrates into quinones, which could react with proteins in its surrounding to generate black pigments, called melanins, which are highly UV-active compounds. Annona muricata (Katu anoda) and Musa acuminata (Ash plantains) is a fruit and a vegetable consumed by Sri Lankans widely due to their high nutritional values, medicinal properties and economical importance. The objective of the present study was to evaluate and determine the effective natural anti-browning inhibitors that could prevent PPO activity in the selected fruit and vegetable. Enzyme extracts from Annona muricata (Katu anoda) and Musa acuminata (Ash plantains), were prepared by homogenizing with analytical grade acetone, and pH of each enzyme extract was maintained at 7.0 using a phosphate buffer. The extracts of inhibitors were prepared using powdered ginger rhizomes and essential oil from the bark of Cinnamomum zeylanicum. Water extracts of ginger were prepared and the essential oil from Ceylon cinnamon bark was extracted using steam distillation method. Since the essential oil is not soluble in water, 0.1µl of cinnamon bark oil was mixed with 0.1µl of Triton X-100 emulsifier and 5.00 ml of water. The effect of each inhibitor on the PPO activity was investigated using catechol (0.1 mol dm-3) as the substrate and two samples of enzyme extracts prepared. The dosages of the prepared Cinnamon bark oil, and ginger (2 samples) which were used to measure the activity were 0.0035 g/ml, 0.091 g/ml and 0.087 g/ml respectively. The measurements of the inhibitory activity were obtained at a wavelength of 525 nm using the UV-visible spectrophotometer. The results evaluated thus revealed that % inhibition observed with cinnamon bark oil, and ginger for Annona muricata was 51.97%, and 60.90% respectively. The effects of cinnamon bark oil, and ginger extract on PPO activity of Musa acuminata were 49.51%, and 48.10%. The experimental findings thus revealed that Cinnamomum zeylanicum bark oil was a more effective inhibitor for PPO enzyme present in Musa acuminata and ginger was effective for PPO enzyme present in Annona muricata. Overall both the inhibitors were proven to be more effective towards the activities of PPO enzyme present in both samples. These inhibitors can thus be corroborated as effective, natural, non-toxic, anti-browning extracts, which when added to the above fruit and vegetable will increase the shelf life and also the acceptance of the product by the consumers.

Keywords: anti-browning agent, enzymatic browning, inhibitory activity, polyphenol oxidase

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Authors: Chethana V. Casiker, Jagadishakumara B., Sunil G. M., Chaithra K., M. Soubadra Devy

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A majority of the world’s food crops depends on insects for pollination, among which bees are the most dominant taxon. Bees pollinate vegetables, fruits and oilseeds which are rich in essential micronutrients. Besides being a prerequisite for a nutritionally secure diet, agrarian economies such as India depend heavily on pollination for good yield and quality of the product. As cities all over the world expand rapidly, large tracts of green spaces are being built up. This, along with high usage of agricultural chemicals has reduced floral diversity and shrunk bee habitats. Indeed, pollinator decline is being reported from various parts of the world. Further, the FAO has reported a huge increase in the area of land under cultivation of pollinator-dependent crops. In the light of increasing demand for pollination and disappearing natural habitats, it is critical to understand whether and how urban spaces can support pollinators. To this end, this study investigates the influence of landscape and local habitat quality on bee community dynamics. To capture the dynamics of expanding cityscapes, the study employs a space for time substitution, wherein a transect along the gradient of urbanization substitutes a timeframe of increasing urbanization. This will help understand how pollinators would respond to changes induced by increasing intensity of urbanization in the future. Bengaluru, one of the fastest growing cities of Southern India, is an excellent site to study impacts associated with urbanization. With sites moving away from the Bengaluru’s centre and towards its peripheries, this study captures the changes in bee species diversity and richness along a gradient of urbanization. Bees were sampled under different land use types as well as in different types of vegetation, including plantations, croplands, fallow land, parks, lake embankments, and private gardens. The relationship between bee community metrics and key drivers such as a percentage of built-up area, land use practices, and floral resources was examined. Additionally, data collected using questionnaire interviews were used to understand people’s perceptions towards and level of dependence on pollinators. Our results showed that urban areas are capable of supporting bees. In fact, a greater diversity of bees was recorded in urban sites compared to adjoining rural areas. This suggests that bees are able to seek out patchy resources and survive in small fragments of habitat. Bee abundance and species richness correlated positively with floral abundance and richness, indicating the role of vegetation in providing forage and nesting sites which are crucial to their survival. Bee numbers were seen to decrease with increase in built-up area demonstrating that impervious surfaces could act as deterrents. Findings from this study challenge the popular notion of cities being biodiversity-bare spaces. There is indeed scope for conserving bees in urban landscapes, provided that there are city-scale planning and local initiative. Bee conservation can go hand in hand with efforts such as urban gardening and terrace farming that could help cities urbanize sustainably.

Keywords: bee, landscape ecology, urbanization, urban pollination

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Authors: A. F. Huseynov, N. T. Mardanov, J. Y. Nakhchivanski

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This practical research is aimed to improve the management quality and efficiency of public administration agencies providing e-services. The monitoring system developed will provide continuous review of the websites compliance with the selected indicators, their evaluation based on the selected indicators and ranking of services according to the quality criteria. The responsible departments in the government agencies were surveyed; the questionnaire includes issues of management and feedback, e-services provided, and the application of information systems. By analyzing the main affecting factors and barriers, the recommendations will be given that lead to the relevant decisions to strengthen the state agencies competencies for the management and the provision of their services. Component 1. E-services monitoring system. Three separate monitoring activities are proposed to be executed in parallel: Continuous tracing of e-government sites using built-in web-monitoring program; this program generates several quantitative values which are basically related to the technical characteristics and the performance of websites. The expert assessment of e-government sites in accordance with the two general criteria. Criterion 1. Technical quality of the site. Criterion 2. Usability/accessibility (load, see, use). Each high-level criterion is in turn subdivided into several sub-criteria, such as: the fonts and the color of the background (Is it readable?), W3C coding standards, availability of the Robots.txt and the site map, the search engine, the feedback/contact and the security mechanisms. The on-line survey of the users/citizens – a small group of questions embedded in the e-service websites. The questionnaires comprise of the information concerning navigation, users’ experience with the website (whether it was positive or negative), etc. Automated monitoring of web-sites by its own could not capture the whole evaluation process, and should therefore be seen as a complement to expert’s manual web evaluations. All of the separate results were integrated to provide the complete evaluation picture. Component 2. Assessment of the agencies/departments efficiency in providing e-government services. - the relevant indicators to evaluate the efficiency and the effectiveness of e-services were identified; - the survey was conducted in all the governmental organizations (ministries, committees and agencies) that provide electronic services for the citizens or the businesses; - the quantitative and qualitative measures are covering the following sections of activities: e-governance, e-services, the feedback from the users, the information systems at the agencies’ disposal. Main results: 1. The software program and the set of indicators for internet sites evaluation has been developed and the results of pilot monitoring have been presented. 2. The evaluation of the (internal) efficiency of the e-government agencies based on the survey results with the practical recommendations related to the human potential, the information systems used and e-services provided.

Keywords: e-government, web-sites monitoring, survey, internal efficiency

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Authors: Nilki Upathissa, Torin Wirasinghe

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This solution addresses the challenges faced by traditional bookstores and the limitations of digital media, striking a balance between the tactile experience of printed books and the convenience of modern technology. The book exchange system offers a sustainable alternative, empowering users to access a diverse range of books while promoting community engagement. The user-friendly interfaces incorporated into the book exchange system ensure a seamless and enjoyable experience for users. Intuitive features for book management, search, and messaging facilitate effortless exchanges and interactions between users. By streamlining the process, the system encourages readers to explore new books aligned with their interests, enhancing the overall reading experience. Central to the system's success is the hybrid recommendation engine, which leverages advanced technologies such as Long Short-Term Memory (LSTM) models. By analyzing user input, the engine accurately predicts genre preferences, enabling personalized book recommendations. The hybrid approach integrates multiple technologies, including user interfaces, machine learning models, and recommendation algorithms, to ensure the accuracy and diversity of the recommendations. The evaluation of the book exchange system with the hybrid recommendation engine demonstrated exceptional performance across key metrics. The high accuracy score of 0.97 highlights the system's ability to provide relevant recommendations, enhancing users' chances of discovering books that resonate with their interests. The commendable precision, recall, and F1score scores further validate the system's efficacy in offering appropriate book suggestions. Additionally, the curve classifications substantiate the system's effectiveness in distinguishing positive and negative recommendations. This metric provides confidence in the system's ability to navigate the vast landscape of book choices and deliver recommendations that align with users' preferences. Furthermore, the implementation of this book exchange system with a hybrid recommendation engine has the potential to revolutionize the way readers interact with printed books. By facilitating book exchanges and providing personalized recommendations, the system encourages a sense of community and exploration within the reading community. Moreover, the emphasis on sustainability aligns with the growing global consciousness towards eco-friendly practices. With its robust technical approach and promising evaluation results, this solution paves the way for a more inclusive, accessible, and enjoyable reading experience for book lovers worldwide. In conclusion, the developed book exchange system with a hybrid recommendation engine represents a progressive solution to the challenges faced by traditional bookstores and the limitations of digital media. By promoting sustainability, widening access to printed books, and fostering engagement with reading, this system addresses the evolving needs of book enthusiasts. The integration of user-friendly interfaces, advanced machine learning models, and recommendation algorithms ensure accurate and diverse book recommendations, enriching the reading experience for users.

Keywords: recommendation systems, hybrid recommendation systems, machine learning, data science, long short-term memory, recurrent neural network

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Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

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Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

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Authors: Sunil Kumar, Rajesh Sharma

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Toxic epidermal necrolysis, pruritis, rashes, lichen planus like eruption, hyper pigmentation of skin are rare toxic effects of choloroquine used over a long time. Skin and mucus membrane hyper pigmentation is generally of a bluish black or grayish color and irreversible after discontinuation of the drug. According to Ayurveda, Dushivisha is the name given to any poisonous substance which is not fully endowed with the qualities of poison by nature (i.e. it acts as an impoverished or weak poison) and because of its mild potency, it remains in the body for many years causing various symptoms, one among them being discoloration of skin.The objective of this case report is to investigate the effect of Ayurvedic management of chloroquine induced hyper-pigmentation on the line of treatment of Dushivisha. Case Report: A 26-year-old female was suffering from hyper-pigmentation of the skin over the neck, forehead, temporo-mandibular joints, upper back and posterior aspect of both the arms since 8 years had history of taking Chloroquine came to Out Patient Department of National Institute of Ayurveda, Jaipur, India in Jan. 2015. The routine investigations (CBC, ESR, Eosinophil count) were within normal limits. Punch biopsy skin studied for histopathology under hematoxylin and eosin staining showed epidermis with hyper-pigmentation of the basal layer. In the papillary dermis as well as deep dermis there were scattered melanophages along with infiltration by mononuclear cells. There was no deposition of amyloid-like substances. These histopathological findings were suggestive of Chloroquine induced hyper-pigmentation. The case was treated on the line of treatment of Dushivisha and was given Vamana and Virechana (therapeutic emesis and purgation) every six months followed by Snehana karma (oleation therapy) with Panchatikta Ghrit and Swedana (sudation). Arogyavardhini Vati -1 g, Dushivishari Vati 500 mg, Mahamanjisthadi Quath 20 ml were given twelve hourly and Aragwadhadi Quath 25 ml at bed time orally. The patient started showing lightening of the pigments after six months and almost complete remission after 12 months of the treatment. Conclusion: This patient presented with the Dushivisha effect of Chloroquineandwas administered two relevant procedures from Panchakarma viz. Vamana and Virechana. Both Vamana and Virechanakarma here referred to Shodhana karma (purification procedures) eliminates accumulated toxins from the body. In this process, oleation dislodge the toxins from the tissues and sudation helps to bring them to the alimentary tract. The line of treatment did not target direct hypo pigmentary effects; rather aimed to eliminate the Dushivisha. This gave promising results in this condition.

Keywords: Ayurveda, chloroquine, Dushivisha, hyper-pigmentation

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Authors: Nguyen J. M., Lucas G., Ruan S., Digonnet H., Antonioli D.

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Introduction: Deep Learning (DL) is a very powerful tool for analyzing image data. But for tabular data, it cannot compete with machine learning methods like XGBoost. The research question becomes: can tabular data be transformed into images that can be analyzed by simple CNNs (Convolutional Neuron Networks)? Will DL be the absolute tool for data classification? All current solutions consist in repositioning the variables in a 2x2 matrix using their correlation proximity. In doing so, it obtains an image whose pixels are the variables. We implement a technology, DeepNIC, that offers the possibility of obtaining an image for each variable, which can be analyzed by simple CNNs. Material and method: The 'ROP' (Regression OPtimized) model is a binary and atypical decision tree whose nodes are managed by a new artificial neuron, the Neurop. By positioning an artificial neuron in each node of the decision trees, it is possible to make an adjustment on a theoretically infinite number of variables at each node. From this new decision tree whose nodes are artificial neurons, we created the concept of a 'Random Forest of Perfect Trees' (RFPT), which disobeys Breiman's concepts by assembling very large numbers of small trees with no classification errors. From the results of the RFPT, we developed a family of 10 statistical information criteria, Nguyen Information Criterion (NICs), which evaluates in 3 dimensions the predictive quality of a variable: Performance, Complexity and Multiplicity of solution. A NIC is a probability that can be transformed into a grey level. The value of a NIC depends essentially on 2 super parameters used in Neurops. By varying these 2 super parameters, we obtain a 2x2 matrix of probabilities for each NIC. We can combine these 10 NICs with the functions AND, OR, and XOR. The total number of combinations is greater than 100,000. In total, we obtain for each variable an image of at least 1166x1167 pixels. The intensity of the pixels is proportional to the probability of the associated NIC. The color depends on the associated NIC. This image actually contains considerable information about the ability of the variable to make the prediction of Y, depending on the presence or absence of other variables. A basic CNNs model was trained for supervised classification. Results: The first results are impressive. Using the GSE22513 public data (Omic data set of markers of Taxane Sensitivity in Breast Cancer), DEEPNic outperformed other statistical methods, including XGBoost. We still need to generalize the comparison on several databases. Conclusion: The ability to transform any tabular variable into an image offers the possibility of merging image and tabular information in the same format. This opens up great perspectives in the analysis of metadata.

Keywords: tabular data, CNNs, NICs, DeepNICs, random forest of perfect trees, classification

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Authors: Adriana Haulica

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Powered by Machine Learning, Precise medicine is tailored by now to use genetic and molecular profiling, with the aim of optimizing the therapeutic benefits for cohorts of patients. As the majority of Machine Language algorithms come from heuristics, the outputs have contextual validity. This is not very restrictive in the sense that medicine itself is not an exact science. Meanwhile, the progress made in Molecular Biology, Bioinformatics, Computational Biology, and Precise Medicine, correlated with the huge amount of human biology data and the increase in computational power, opens new healthcare challenges. A more accurate diagnosis is needed along with real-time treatments by processing as much as possible from the available information. The purpose of this paper is to present a deeper vision for the future of Artificial Intelligence in Precise medicine. In fact, actual Machine Learning algorithms use standard mathematical knowledge, mostly Euclidian metrics and standard computation rules. The loss of information arising from the classical methods prevents obtaining 100% evidence on the diagnosis process. To overcome these problems, we introduce MEDICOMPILLS, a new architectural concept tool of information processing in Precise medicine that delivers diagnosis and therapy advice. This tool processes poly-field digital resources: global knowledge related to biomedicine in a direct or indirect manner but also technical databases, Natural Language Processing algorithms, and strong class optimization functions. As the name suggests, the heart of this tool is a compiler. The approach is completely new, tailored for omics and clinical data. Firstly, the intrinsic biological intuition is different from the well-known “a needle in a haystack” approach usually used when Machine Learning algorithms have to process differential genomic or molecular data to find biomarkers. Also, even if the input is seized from various types of data, the working engine inside the MEDICOMPILLS does not search for patterns as an integrative tool. This approach deciphers the biological meaning of input data up to the metabolic and physiologic mechanisms, based on a compiler with grammars issued from bio-algebra-inspired mathematics. It translates input data into bio-semantic units with the help of contextual information iteratively until Bio-Logical operations can be performed on the base of the “common denominator “rule. The rigorousness of MEDICOMPILLS comes from the structure of the contextual information on functions, built to be analogous to mathematical “proofs”. The major impact of this architecture is expressed by the high accuracy of the diagnosis. Detected as a multiple conditions diagnostic, constituted by some main diseases along with unhealthy biological states, this format is highly suitable for therapy proposal and disease prevention. The use of MEDICOMPILLS architecture is highly beneficial for the healthcare industry. The expectation is to generate a strategic trend in Precise medicine, making medicine more like an exact science and reducing the considerable risk of errors in diagnostics and therapies. The tool can be used by pharmaceutical laboratories for the discovery of new cures. It will also contribute to better design of clinical trials and speed them up.

Keywords: bio-semantic units, multiple conditions diagnosis, NLP, omics

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Authors: Omar Faruqe Hamim, M. Shamsul Hoque, Rich C. McIlroy, Katherine L. Plant, Neville A. Stanton

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Road safety has become an alarming issue, especially in low-middle income developing countries. The traditional approaches lack the out of the box thinking, making engineers confined to applying usual techniques in making roads safer. A socio-technical approach has recently been introduced in improving road intersections through designing with intent. This Design With Intent (DWI) approach aims to give practitioners a more nuanced approach to design and behavior, working with people, people’s understanding, and the complexities of everyday human experience. It's a collection of design patterns —and a design and research approach— for exploring the interactions between design and people’s behavior across products, services, and environments, both digital and physical. Through this approach, it can be seen that how designing with people in behavior change can be applied to social and environmental problems, as well as commercially. It has a total of 101 cards across eight different lenses, such as architectural, error-proofing, interaction, ludic, perceptual, cognitive, Machiavellian, and security lens each having its own distinct characteristics of extracting ideas from the participant of this approach. For this research purpose, a three-legged accident blackspot intersection of a national highway has been chosen to perform the DWI workshop. Participants from varying fields such as civil engineering, naval architecture and marine engineering, urban and regional planning, and sociology actively participated for a day long workshop. While going through the workshops, the participants were given a preamble of the accident scenario and a brief overview of DWI approach. Design cards of varying lenses were distributed among 10 participants and given an hour and a half for brainstorming and generating ideas to improve the safety of the selected intersection. After the brainstorming session, the participants spontaneously went through roundtable discussions regarding the ideas they have come up with. According to consensus of the forum, ideas were accepted or rejected. These generated ideas were then synthesized and agglomerated to bring about an improvement scheme for the intersection selected in our study. To summarize the improvement ideas from DWI approach, color coding of traffic lanes for separate vehicles, channelizing the existing bare intersection, providing advance warning traffic signs, cautionary signs and educational signs motivating road users to drive safe, using textured surfaces at approach with rumble strips before the approach of intersection were the most significant one. The motive of this approach is to bring about new ideas from the road users and not just depend on traditional schemes to increase the efficiency, safety of roads as well and to ensure the compliance of road users since these features are being generated from the minds of users themselves.

Keywords: design with intent, road safety, human experience, behavior

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Authors: Stephan Boehm, Julia Engel, Judith Eisser

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During the last decade communication in the Internet transformed from a broadcast to a conversational model by supporting more interactive features, enabling user generated content and introducing social media networks. Another important trend with a significant impact on electronic commerce is a massive usage shift from desktop to mobile devices. However, a presentation of product- or service-related information accumulated on websites, micro pages or portals often remains the pivot and focal point of a customer journey. A more recent change of user behavior –especially in younger user groups and in Asia– is going along with the increasing adoption of messaging applications supporting almost real-time but asynchronous communication on mobile devices. Mobile apps of this type cannot only provide an alternative for traditional one-to-one communication on mobile devices like voice calls or short messaging service. Moreover, they can be used in mobile commerce as a new marketing and sales channel, e.g., for product promotions and direct marketing activities. This requires a new way of customer interaction compared to traditional mobile commerce activities and functionalities provided based on mobile web-sites. One option better aligned to the customer interaction in mes-saging apps are so-called chatbots. Chatbots are conversational programs or dialog systems simulating a text or voice based human interaction. They can be introduced in mobile messaging and social media apps by using rule- or artificial intelligence-based imple-mentations. In this context, a comparative analysis is conducted to examine the impact of using traditional websites or chatbots for promoting a product in an impulse purchase situation. The aim of this study is to measure the impact on the customers’ user experi-ence and emotions. The study is based on a random sample of about 60 smartphone users in the group of 20 to 30-year-olds. Participants are randomly assigned into two groups and participate in a traditional website or innovative chatbot based mobile com-merce scenario. The chatbot-based scenario is implemented by using a Wizard-of-Oz experimental approach for reasons of sim-plicity and to allow for more flexibility when simulating simple rule-based and more advanced artificial intelligence-based chatbot setups. A specific set of metrics is defined to measure and com-pare the user experience in both scenarios. It can be assumed, that users get more emotionally involved when interacting with a system simulating human communication behavior instead of browsing a mobile commerce website. For this reason, innovative face-tracking and analysis technology is used to derive feedback on the emotional status of the study participants while interacting with the website or the chatbot. This study is a work in progress. The results will provide first insights on the effects of chatbot usage on user experiences and emotions in mobile commerce environments. Based on the study findings basic requirements for a user-centered design and implementation of chatbot solutions for mobile com-merce can be derived. Moreover, first indications on situations where chatbots might be favorable in comparison to the usage of traditional website based mobile commerce can be identified.

Keywords: chatbots, emotions, mobile commerce, user experience, Wizard-of-Oz prototyping

Procedia PDF Downloads 430

Authors: Al Sayed Al Soudy, Valeria Maselli, Gianluca Polese, Anna Di Cosmo

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Cephalopods are considered as a model organism with a rich behavioral repertoire. Sophisticated behaviors were widely studied and described in different species such as Octopus vulgaris, who has evolved the largest and more complex nervous system among invertebrates. In O. vulgaris, cognitive abilities in problem-solving tasks and learning abilities are associated with long-term memory and spatial memory, mediated by highly developed sensory organs. They are equipped with sophisticated eyes, able to discriminate colors even with a single photoreceptor type, vestibular system, ‘lateral line analogue’, primitive ‘hearing’ system and olfactory organs. They can recognize chemical cues either through direct contact with odors sources using suckers or by distance through the olfactory organs. Cephalopods are able to detect widespread waterborne molecules by the olfactory organs. However, many volatile odorant molecules are insoluble or have a very low solubility in water, and must be perceived by direct contact. O. vulgaris, equipped with many chemosensory neurons located in their suckers, exhibits a peculiar behavior that can be provocatively described as 'smell by touch'. The aim of this study is to establish the priority given to chemical vs. visual perception in food choice. Materials and methods: Three different types of food (anchovies, clams, and mussels) were used, and all sessions were recorded with a digital camera. During the acclimatization period, Octopuses were exposed to the three types of food to test their natural food preferences. Later, to verify if food preference is maintained, food was provided in transparent screw-jars with pierced lids to allow both visual and chemical recognition of the food inside. Subsequently, we tested alternatively octopuses with food in sealed transparent screw-jars and food in blind screw-jars with pierced lids. As a control, we used blind sealed jars with the same lid color to verify a random choice among food types. Results and discussion: During the acclimatization period, O. vulgaris shows a higher preference for anchovies (60%) followed by clams (30%), then mussels (10%). After acclimatization, using the transparent and pierced screw jars octopus’s food choices resulted in 50-50 between anchovies and clams, avoiding mussels. Later, guided by just visual sense, with transparent but not pierced jars, their food preferences resulted in 100% anchovies. With pierced but not transparent jars their food preference resulted in 100% anchovies as first food choice, the clams as a second food choice result (33.3%). With no possibility to select food, neither by vision nor by chemoreception, the results were 20% anchovies, 20% clams, and 60% mussels. We conclude that O. vulgaris uses both chemical and visual senses in an integrative way in food choice, but if we exclude one of them, it appears clear that its food preference relies on chemical sense more than on visual perception.

Keywords: food choice, Octopus vulgaris, olfaction, sensory organs, visual sense

Procedia PDF Downloads 193

Authors: Hyuk-Jin Lee

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Even though 23 years have passed in the 21st century, nation-state and nationality-centered cultural identities are still the sentiments and ideologies that dominate the world. Nevertheless, as seen in many cases in Europe, a new perspective is needed to recognize mutual exchanges and influences and to view them as natural cultural exchanges between countries. The situation in East Asia is completely different from Europe. This is presumed to be from the long tradition of having an ethnocentric state concept for at least hundreds of years, quite different from Europe, where the concept of a nation-state was established relatively recently. In other words, unlike Europe, where active exchanges took place, the problem stems from the unique characteristics of East Asia, which has a strong tradition of finding its identity in 'difference'. Thus, it would not be hard to find cultural studies or news of the three East Asian countries emphasizing differences among one another. This applies to all cultural areas, including traditional architecture. For example, in the Korean traditional architecture field, buildings with effects from neighboring countries tend to be ignored, even if they are traditional Korean architecture. In addition to this, in the case of Korea, there seems to be one more cultural harmful aftereffect caused by the 36 years of Japanese colonial rule in the early 20th century; the obsessive filtering concept of 'it must be different from Japan'. In other words, the implicit ideological coercion that the definition of 'Korean cultural heritage' should not be influenced by exchanges with Japan may be found throughout Korean studies. The architectural and cultural aspects of the vast period of time, from the Three Kingdoms era to the beginning of Joseon, which was a period in which cultural influence exchanges with neighboring countries were relatively strong compared to the late Joseon Dynasty, also reflect the 'distorted filtering' caused by finding a repulsive identity against the Japanese colonial period. It is important to look the cultural heritage and traditions as they are inductively, not deductively. If not, we may often ignore or limit our own precious cultural heritage. Conversely, If Baekje, the ancient Korean Kingdom, helped Japan in construction and craftsmen played a big role in building the ancient temple, it would be a healthier perspective to view it as a cultural exchange rather than proudly seeing it as a cultural owner's perspective because this point of view is a proper reconstruction of our ancient and medieval Asian culture (strictly speaking, the color common to East Asia at the time). In particular, this study will examine this topic by giving specific examples from each field of Korean cultural studies. In the search for cultural identity, it would be more helpful for healthy relations between countries and collaborative research in the sensitive part of the interpretation of historical facts as well as cultural circles to minimize excessive meanings on originality and difference.

Keywords: cultural heritage identity, cultural ideology, East Asia, Korea

Procedia PDF Downloads 50

Authors: E. Obreque-Slier, F. Orellana-Rodríguez, R. López-Solís

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Phenolic compounds are secondary metabolites present in some foods, such as wine. Polyphenols comprise two main groups: flavonoids (anthocyanins, flavanols, and flavonols) and non-flavonoids (stilbenes and phenolic acids). Phenolic acids are low molecular weight non flavonoid compounds that are usually grouped into benzoic (gallic, vanillinic and protocatechuic acids) and cinnamic acids (ferulic, p-coumaric and caffeic acids). Likewise, tannic acid is an important polyphenol constituted mainly by gallic acid. Phenolic compounds are responsible for important properties in foods and drinks, such as color, aroma, bitterness, and astringency. Astringency is a drying, roughing, and sometimes puckering sensation that is experienced on the various oral surfaces during or immediately after tasting foods. Astringency perception has been associated with interactions between flavanols present in some foods and salivary proteins. Despite the quantitative relevance of phenolic acids in food and beverages, there is no information about its effect on salivary proteins and consequently on the sensation of astringency. The objective of this study was assessed the interaction of several phenolic acids (gallic, vanillinic, protocatechuic, ferulic, p-coumaric and caffeic acids) with saliva. Tannic acid was used as control. Thus, solutions of each phenolic acids (5 mg/mL) were mixed with human saliva (1:1 v/v). After incubation for 5 min at room temperature, 15-μL aliquots of the mixtures were dotted on a cellulose membrane and allowed to diffuse. The dry membrane was fixed in 50 g/L trichloroacetic acid, rinsed in 800 mL/L ethanol and stained for protein with Coomassie blue for 20 min, destained with several rinses of 73 g/L acetic acid and dried under a heat lamp. Both diffusion area and stain intensity of the protein spots were semiqualitative estimates for protein-tannin interaction (diffusion test). The rest of the whole saliva-phenol solution mixtures of the diffusion assay were centrifuged and fifteen-μL aliquots of each supernatant were dotted on a cellulose membrane, allowed to diffuse and processed for protein staining, as indicated above. In this latter assay, reduced protein staining was taken as indicative of protein precipitation (precipitation test). The diffusion of the salivary protein was restricted by the presence of each phenolic acids (anti-diffusive effect), while tannic acid did not alter diffusion of the salivary protein. By contrast, phenolic acids did not provoke precipitation of the salivary protein, while tannic acid produced precipitation of salivary proteins. In addition, binary mixtures (mixtures of two components) of various phenolic acids with gallic acid provoked a restriction of saliva. Similar effect was observed by the corresponding individual phenolic acids. Contrary, binary mixtures of phenolic acid with tannic acid, as well tannic acid alone, did not affect the diffusion of the saliva but they provoked an evident precipitation. In summary, phenolic acids showed a relevant interaction with the salivary proteins, thus suggesting that these wine compounds can also contribute to the sensation of astringency.

Keywords: astringency, polyphenols, tannins, tannin-protein interaction

Procedia PDF Downloads 221

Authors: Pomila Sharma

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Rajasthan is among regions with greatest climate sensitivity and lowest adaptive capabilities. In many parts of the Rajasthan surface water which can be highly turbid and contaminated with fecal coliform bacteria is used for drinking purposes. The majority rely almost exclusively upon traditional sources of highly turbid and untreated pathogenic surface water for their domestic water needs. In many parts of rural areas of Rajasthan, it is still difficult to obtain clean water, especially remote habitations with no groundwater due to quality issues or depletion and limited feasibility to connect with surface water schemes due to low density of population in these areas to justify large infrastructure investment. The most viable sources are rain water harvesting, community managed open wells, private wells, ponds and small-scale irrigation reservoirs have often been the main traditional sources of rural drinking water. Turbidity is conventionally removed by treating the water with expensive chemicals. This study has to investigate the use of crushed seeds from the tree Moringa oleifera (drumstick) as a natural alternative to conventional coagulant chemicals. The use of Moringa oleifera seed powder can produce potable water of higher quality than the original source. Moringa oleifera a native species of northern India, the tree is now grown extensively throughout the tropics and found in many countries of Africa, Asia & South America. The seeds of tree contains significant quantities of low molecular weight, water soluble proteins which carries the positive charge when the crushed seeds are added to water. This protein binds in raw water with negatively charged turbid water with bacteria, clay, algae, etc. Under proper mixing, these particles make flocks, which may be left to settle by gravity or be removed by filtration. Using Moringa oleifera as a replacement coagulation in such surface sources of arid and semi-arid areas can meet the need for water purification in remote places of Rajasthan state of India. The present study accesses to find out laboratory based investigation of the effect of seeds of Moringa tree on its coagulation effectiveness (purification) using turbid water samples of surface source of the Rajasthan state. In this study, moringa seed powder showed that filtering with seed powder may diminish water pollution and bacterial counts. Results showed Moringa oleifera seeds coagulate 90-95% of turbidity and color efficiently leading to an aesthetically clear supernatant & reduced about 85-90% of bacterial load reduction in samples.

Keywords: bacterial load, coagulant, turbidity, water purification

Procedia PDF Downloads 118

Authors: Rubaiat S. Ahmed, Jemer Garrido, Sergey M. Motov

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Clinical informatics (CI) enables the transformation of data into a systematic organization that improves the quality of care and the generation of positive health outcomes.Innovative technology through informatics that compiles accurate data on analgesic utilization in the emergency department can enhance pain management in this important clinical setting. We aim to establish a simplified reporting system through CI to examine and assess the analgesic prescribing practices in the EDthrough executing a U.S. federal grant project on opioid reduction initiatives. Queried data points of interest from a level-one trauma ED’s electronic medical records were used to create data sets and develop informational/visual reporting dashboards (on Microsoft Excel and Google Sheets) concerning analgesic usage across several pre-defined parameters and performance metrics using CI. The data was then qualitatively analyzed to evaluate ED analgesic prescribing trends by departmental clinicians and leadership. During a 12-month reporting period (Dec. 1, 2020 – Nov. 30, 2021) for the ongoing project, about 41% of all ED patient visits (N = 91,747) were for pain conditions, of which 81.6% received analgesics in the ED and at discharge (D/C). Of those treated with analgesics, 24.3% received opioids compared to 75.7% receiving opioid alternatives in the ED and at D/C, including non-pharmacological modalities. Demographics showed among patients receiving analgesics, 56.7% were aged between 18-64, 51.8% were male, 51.7% were white, and 66.2% had government funded health insurance. Ninety-one percent of all opioids prescribed were in the ED, with intravenous (IV) morphine, IV fentanyl, and morphine sulfate immediate release (MSIR) tablets accounting for 88.0% of ED dispensed opioids. With 9.3% of all opioids prescribed at D/C, MSIR was dispensed 72.1% of the time. Hydrocodone, oxycodone, and tramadol usage to only 10-15% of the time, and hydromorphone at 0%. Of opioid alternatives, non-steroidal anti-inflammatory drugs were utilized 60.3% of the time, 23.5% with local anesthetics and ultrasound-guided nerve blocks, and 7.9% with acetaminophen as the primary non-opioid drug categories prescribed by ED providers. Non-pharmacological analgesia included virtual reality and other modalities. An average of 18.5 ED opioid orders and 1.9 opioid D/C prescriptions per 102.4 daily ED patient visits was observed for the period. Compared to other specialties within our institution, 2.0% of opioid D/C prescriptions are given by ED providers, compared to the national average of 4.8%. Opioid alternatives accounted for 69.7% and 30.3% usage, versus 90.7% and 9.3% for opioids in the ED and D/C, respectively.There is a pressing need for concise, relevant, and reliable clinical data on analgesic utilization for ED providers and leadership to evaluate prescribing practices and make data-driven decisions. Basic computer software can be used to create effective visual reporting dashboards with indicators that convey relevant and timely information in an easy-to-digest manner. We accurately examined our ED's analgesic prescribing practices using CI through dashboard reporting. Such reporting tools can quickly identify key performance indicators and prioritize data to enhance pain management and promote safe prescribing practices in the emergency setting.

Keywords: clinical informatics, dashboards, emergency department, health informatics, healthcare informatics, medical informatics, opioids, pain management, technology

Procedia PDF Downloads 120

Authors: Mebruka Mohammed, Daniel Bisrat, Asfaw Debella, Tarekegn Birhanu

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Lack of quality control standards for medicinal plants and their preparations is considered major barrier to their integration in to effective primary health care in Ethiopia. Poor quality herbal preparations led to countless adverse reactions extending to death. Denial of penetration for the Ethiopian medicinal plants in to the world’s booming herbal market is also another significant loss resulting from absence of herbal quality control system. Thus, in the present study, Gnidia stenophylla Gilg (popular antimalarial plant of south eastern Ethiopia), is standardized and a full monograph is produced that can serve as a guideline in quality control of the crude drug. Morphologically, the roots are found to be cylindrical and tapering towards the end. It has a hard, corky and friable touch with saddle brown color externally and it is relatively smooth and pale brown internally. It has got characteristic pungent odor and very bitter taste. Microscopically it has showed lignified xylem vessels, wider medullary rays with some calcium oxalate crystals, reddish brown secondary metabolite contents and slender shaped long fibres. Physicochemical standards quantified and resulted: foreign matter (5.25%), moisture content (6.69%), total ash (40.80%), acid insoluble ash (8.00%), water soluble ash (2.30%), alcohol soluble extractive (15.27%), water soluble extractive (10.98%), foaming index (100.01 ml/g), swelling index (7.60 ml/g). Phytochemically: Phenols, flavonoids, steroids, tannins and saponins were detected in the root extract; TLC and HPLC fingerprints were produced and an analytical marker was also tentatively characterized as 3-(3,4-dihydro-3,5-dihydroxy-2-(4-hydroxy-5-methylhex-1-en-2-yl)-7-methoxy-4-oxo-2H-chromen-8-yl)-5-hydroxy-2-(4-hydroxyphenyl)-7-methoxy-4H-chromen-4-one. Residue wise pesticides (i.e. DDT, DDE, g-BHC) and radiochemical levels fall below the WHO limit while Heavy metals (i.e. Co, Ni, Cr, Pb, and Cu), total aerobic count and fungal load lie way above the WHO limit. In conclusion, the result can be taken as signal that employing non standardized medicinal plants could cause many health risks of the Ethiopian people and Africans’ at large (as 80% of inhabitants in the continent depends on it for primary health care). Therefore, following a more universal approach to herbal quality by adopting the WHO guidelines and developing monographs using the various quality parameters is inevitable to minimize quality breach and promote effective herbal drug usage.

Keywords: Gnidia stenophylla Gilg, standardization/monograph, pharmacognostic, residue/impurity, quality

Procedia PDF Downloads 256

Authors: M. Arun, A. Kannan

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Textile industries cater to varied customer preferences and contribute substantially to the economy. However, these textile industries also produce a considerable amount of effluents. Prominent among these are the azo dyes which impart considerable color and toxicity even at low concentrations. Azo dyes are also used as coloring agents in food and pharmaceutical industry. Despite their applications, azo dyes are also notorious pollutants and carcinogens. Popular techniques like photo-degradation, biodegradation and the use of oxidizing agents are not applicable for all kinds of dyes, as most of them are stable to these techniques. Chemical coagulation produces a large amount of toxic sludge which is undesirable and is also ineffective towards a number of dyes. Most of the azo dyes are stable to UV-visible light irradiation and may even resist aerobic degradation. Adsorption has been the most preferred technique owing to its less cost, high capacity and process efficiency and the possibility of regenerating and recycling the adsorbent. Adsorption is also most preferred because it may produce high quality of the treated effluent and it is able to remove different kinds of dyes. However, the adsorption process is influenced by many variables whose inter-dependence makes it difficult to identify optimum conditions. The variables include stirring speed, temperature, initial concentration and adsorbent dosage. Further, the internal diffusional resistance inside the adsorbent particle leads to slow uptake of the solute within the adsorbent. Hence, it is necessary to identify optimum conditions that lead to high capacity and uptake rate of these pollutants. In this work, commercially available activated carbon was chosen as the adsorbent owing to its high surface area. A typical azo dye found in textile effluent waters, viz. the monoazo Acid Orange 10 dye (CAS: 1936-15-8) has been chosen as the representative pollutant. Adsorption studies were mainly focused at obtaining equilibrium and kinetic data for the batch adsorption process at different process conditions. Studies were conducted at different stirring speed, temperature, adsorbent dosage and initial dye concentration settings. The Full Factorial Design was the chosen statistical design framework for carrying out the experiments and identifying the important factors and their interactions. The optimum conditions identified from the experimental model were validated with actual experiments at the recommended settings. The equilibrium and kinetic data obtained were fitted to different models and the model parameters were estimated. This gives more details about the nature of adsorption taking place. Critical data required to design batch adsorption systems for removal of Acid Orange 10 dye and identification of factors that critically influence the separation efficiency are the key outcomes from this research.

Keywords: acid orange 10, activated carbon, optimum adsorption conditions, statistical design

Procedia PDF Downloads 153

Authors: Dechao Meng, Yongqi Dong, Qiyuan Feng, Zhangzhang Cui, Xiang Hu, Haoliang Huang, Genhao Liang, Huanhua Wang, Hua Zhou, Hawoong Hong, Jinghua Guo, Qingyou Lu, Xiaofang Zhai, Yalin Lu

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Great efforts have been taken to reveal the intrinsic origins of emerging ferromagnetism (FM) in strained LaCoO₃ (LCO) films. However, some macro magnetic performances of LCO are still not well understood and even controversial, such as magnetic anisotropy. Determining and understanding magnetic anisotropy might help to find the true causes of FM in turn. Perpendicular magnetic anisotropy (PMA) was the first time to be directly observed in high-quality LCO films with different thickness. The in-plane (IP) and out of plane (OOP) remnant magnetic moment ratio of 30 unit cell (u.c.) films is as large as 20. The easy axis lays in the OOP direction with an IP/OOP coercive field ratio of 10. What's more, the PMA could be simply tuned by changing the thickness. With the thickness increases, the IP/OOP magnetic moment ratio remarkably decrease with magnetic easy axis changing from OOP to IP. Such a huge and tunable PMA performance exhibit strong potentials in fundamental researches or applications. What causes PMA is the first concern. More OOP orbitals occupation may be one of the micro reasons of PMA. A cluster-like magnetic domain pattern was found in 30 u.c. with no obvious color contrasts, similar to that of LaAlO₃/SrTiO₃ films. And the nanosize domains could not be totally switched even at a large OOP magnetic field of 23 T. It indicates strong IP characters or none OOP magnetism of some clusters. The IP magnetic domains might influence the magnetic performance and help to form PMA. Meanwhile some possible nonmagnetic clusters might be the reason why the measured moments of LCO films are smaller than the calculated values 2 μB/Co, one of the biggest confusions in LCO films.What tunes PMA seems much more interesting. Totally different magnetic domain patterns were found in 180 u.c. films with cluster magnetic domains surrounded by < 110 > cross-hatch lines. These lines were regarded as structure domain walls (DWs) determined by 3D reciprocal space mapping (RSM). Two groups of in-plane features with fourfold symmetry were observed near the film diffraction peaks in (002) 3D-RSM. One is along < 110 > directions with a larger intensity, which is well match the lines on the surfaces. The other is much weaker and along < 100 > directions, which is from the normal lattice titling of films deposited on cubic substrates. The < 110 > domain features obtained from (103) and (113) 3D-RSMs exhibit similar evolution of the DWs percentages and magnetic behavior. Structure domains and domain walls are believed to tune PMA performances by transform more IP magnetic moments to OOP. Last but not the least, thick films with lots of structure domains exhibit different electrical transport behaviors. A metal-to-insulator transition (MIT) and an angular dependent negative magnetic resistivity were observed near 150 K, higher than FM transition temperature but similar to that of spin-orbital coupling related 1/4 order diffraction peaks.

Keywords: structure domain, magnetic anisotropy, magnetic domain, domain wall, 3D-RSM, strain

Procedia PDF Downloads 130

Authors: Cibele F. Oliveira, Debora P. Jaeschke, Rodrigo R. Laurino, Amanda R. Andrade, Ligia D. F. Marczak

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Raspberry is well-known as a good source of phenolic compounds, mainly anthocyanin. Some studies pointed out the importance of these bioactive compounds consumption, which is related to the decrease of the risk of cancer and cardiovascular diseases. The most consumed raspberry products are juices, yogurts, ice creams and jellies and, to ensure the safety of these products, raspberry is commonly pasteurized, for enzyme and microorganisms inactivation. Despite being efficient, the pasteurization process can lead to degradation reactions of the bioactive compounds, decreasing the products healthy benefits. Therefore, the aim of the present work was to evaluate moderate electric field (MEF) and ultrasound (US) technologies application on the pasteurization process of raspberry juice and compare the results with conventional pasteurization process. For this, phenolic compounds, anthocyanin content and physical-chemical parameters (pH, color changes, titratable acidity) of the juice were evaluated before and after the treatments. Moreover, microbiological analyses of aerobic mesophiles microorganisms, molds and yeast were performed in the samples before and after the treatments, to verify the potential of these technologies to inactivate microorganisms. All the pasteurization processes were performed in triplicate for 10 min, using a cylindrical Pyrex® vessel with a water jacket. The conventional pasteurization was performed at 90 °C using a hot water bath connected to the extraction cell. The US assisted pasteurization was performed using 423 and 508 W cm-2 (75 and 90 % of ultrasound intensity). It is important to mention that during US application the temperature was kept below 35 °C; for this, the water jacket of the extraction cell was connected to a water bath with cold water. MEF assisted pasteurization experiments were performed similarly to US experiments, using 25 and 50 V. Control experiments were performed at the maximum temperature of US and MEF experiments (35 °C) to evaluate only the effect of the aforementioned technologies on the pasteurization. The results showed that phenolic compounds concentration in the juice was not affected by US and MEF application. However, it was observed that the US assisted pasteurization, performed at the highest intensity, decreased anthocyanin content in 33 % (compared to in natura juice). This result was possibly due to the cavitation phenomena, which can lead to free radicals formation and accumulation on the medium; these radicals can react with anthocyanin decreasing the content of these antioxidant compounds in the juice. Physical-chemical parameters did not present statistical differences for samples before and after the treatments. Microbiological analyses results showed that all the pasteurization treatments decreased the microorganism content in two logarithmic cycles. However, as values were lower than 1000 CFU mL-1 it was not possible to verify the efficacy of each treatment. Thus, MEF and US were considered as potential alternative technologies for pasteurization process, once in the right conditions the application of the technologies decreased microorganism content in the juice and did not affected phenolic and anthocyanin content, as well as physical-chemical parameters. However, more studies are needed regarding the influence of MEF and US processes on microorganisms’ inactivation.

Keywords: MEF, microorganism inactivation, anthocyanin, phenolic compounds

Procedia PDF Downloads 215

Authors: Alessandro Evangelista, Vito M. Manghisi, Michele Gattullo, Enricoandrea Laviola

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In this work, we propose a custom visualization technique for Out-Of-View-Objects in Virtual and Augmented Reality applications using Head Mounted Displays. In the last two decades, Augmented Reality (AR) and Virtual Reality (VR) technologies experienced a remarkable growth of applications for navigation, interaction, and collaboration in different types of environments, real or virtual. Both environments can be potentially very complex, as they can include many virtual objects located in different places. Given the natural limitation of the human Field of View (about 210° horizontal and 150° vertical), humans cannot perceive objects outside this angular range. Moreover, despite recent technological advances in AR e VR Head-Mounted Displays (HMDs), these devices still suffer from a limited Field of View, especially regarding Optical See-Through displays, thus greatly amplifying the challenge of visualizing out-of-view objects. This problem is not negligible when the user needs to be aware of the number and the position of the out-of-view objects in the environment. For instance, during a maintenance operation on a construction site where virtual objects serve to improve the dangers' awareness. Providing such information can enhance the comprehension of the scene, enable fast navigation and focused search, and improve users' safety. In our research, we investigated how to represent out-of-view-objects in HMD User Interfaces (UI). Inspired by commercial video games such as Call of Duty Modern Warfare, we designed a customized Compass. By exploiting the Unity 3D graphics engine, we implemented our custom solution that can be used both in AR and VR environments. The Compass Bar consists of a graduated bar (in degrees) at the top center of the UI. The values of the bar range from -180 (far left) to +180 (far right), the zero is placed in front of the user. Two vertical lines on the bar show the amplitude of the user's field of view. Every virtual object within the scene is represented onto the compass bar as a specific color-coded proxy icon (a circular ring with a colored dot at its center). To provide the user with information about the distance, we implemented a specific algorithm that increases the size of the inner dot as the user approaches the virtual object (i.e., when the user reaches the object, the dot fills the ring). This visualization technique for out-of-view objects has some advantages. It allows users to be quickly aware of the number and the position of the virtual objects in the environment. For instance, if the compass bar displays the proxy icon at about +90, users will immediately know that the virtual object is to their right and so on. Furthermore, by having qualitative information about the distance, users can optimize their speed, thus gaining effectiveness in their work. Given the small size and position of the Compass Bar, our solution also helps lessening the occlusion problem thus increasing user acceptance and engagement. As soon as the lockdown measures will allow, we will carry out user-tests comparing this solution with other state-of-the-art existing ones such as 3D Radar, SidebARs and EyeSee360.

Keywords: augmented reality, situation awareness, virtual reality, visualization design

Procedia PDF Downloads 104

Authors: Michael Sonne Kristensen, Frank Loesche, James Foster, Elif Ozcan, Judy Edworthy

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Auditory alarms play an integral role in intensive care nurses’ daily work. Most medical devices in the intensive care unit (ICU) are designed to produce alarm sounds in order to make nurses aware of immediate or prospective safety risks. The utilisation of sound as a carrier of crucial patient information is highly dependent on nurses’ presence - both physically and mentally. For ICU nurses, especially the ones who work with stationary alarm devices at the patient bed space, it is a challenge to display ‘appropriate’ alarm responses at all times as they have to navigate with great flexibility in a complex work environment. While being primarily responsible for a small number of allocated patients they are often required to engage with other nurses’ patients, relatives, and colleagues at different locations inside and outside the unit. This work explores the social strategies used by a team of nurses to comprehend and react to the information conveyed by the alarms in the ICU. Two main research questions guide the study: To what extent do alarms from a patient bed space reach the relevant responsible nurse by direct auditory exposure? By which means do responsible nurses get informed about their patients’ alarms when not directly exposed to the alarms? A comprehensive video-ethnographic field study was carried out to capture and evaluate alarm-related events in an ICU. The study involved close collaboration with four nurses who wore eye-level cameras and ear-level binaural audio recorders during several work shifts. At all time the entire unit was monitored by multiple video and audio recorders. From a data set of hundreds of hours of recorded material information about the nurses’ location, social interaction, and alarm exposure at any point in time was coded in a multi-channel replay-interface. The data shows that responsible nurses’ direct exposure and awareness of the alarms of their allocated patients vary significantly depending on work load, social relationships, and the location of the patient’s bed space. Distributed listening is deliberately employed by the nursing team as a social strategy to respond adequately to alarms, but the patterns of information flow prompted by alarm-related events are not uniform. Auditory Spatiotemporal Trajectory (AST) is proposed as a methodological label to designate the integration of temporal, spatial and auditory load information. As a mixed-method metrics it provides tangible evidence of how nurses’ individual alarm-related experiences differ from one another and from stationary points in the ICU. Furthermore, it is used to demonstrate how alarm-related information reaches the individual nurse through principles of social and distributed cognition, and how that information relates to the actual alarm event. Thereby it bridges a long-standing gap in the literature on medical alarm utilisation between, on the one hand, initiatives to measure objective data of the medical sound environment without consideration for any human experience, and, on the other hand, initiatives to study subjective experiences of the medical sound environment without detailed evidence of the objective characteristics of the environment.

Keywords: auditory spatiotemporal trajectory, medical alarms, social cognition, video-ethography

Procedia PDF Downloads 171

Authors: Yen Yen Tan, Lynn Lam, Cynthia Lam, Angela Koh, Edwin Seng

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Entrepreneurial education plays a crucial role in nurturing future innovators and change-makers. Over time, significant progress has been made in refining instructional approaches to develop the necessary skills among learners effectively. Two highly valuable frameworks, Kearney's "4 Principles of Entrepreneurial Pedagogy" and Bloom's "Three Domains of Learning," serve as guiding principles in entrepreneurial education. Kearney's principles align with experiential and student-centric learning, which are crucial for cultivating an entrepreneurial mindset. The potential synergies between these frameworks hold great promise for enhancing entrepreneurial acumen among students. However, despite this potential, their integration remains largely unexplored. This study aims to bridge this gap by building upon the Business Essentials through Action (BETA) module and investigating its contributions to nurturing the entrepreneurial mindset. This study employs a quasi-experimental mixed-methods approach, combining quantitative and qualitative elements to ensure comprehensive and insightful data. A cohort of 235 students participated, with 118 enrolled in the BETA module and 117 in a traditional curriculum. Their Personal Entrepreneurial Competencies (PECs) were assessed before admission (pre-Y1) and one year into the course (post-Y1) using a comprehensive 55-item PEC questionnaire, enabling measurement of critical traits such as opportunity-seeking, persistence, and risk-taking. Rigorous computations of individual entrepreneurial competencies and overall PEC scores were performed, including a correction factor to mitigate potential self-assessment bias. The orchestration of Kearney's principles and Bloom's domains within the BETA module necessitates a granular examination. Here, qualitative revelations surface, courtesy of structured interviews aligned with contemporary research methodologies. These interviews act as a portal, ushering us into the transformative journey undertaken by students. Meanwhile, the study pivots to explore the BETA module's influence on students' entrepreneurial competencies from the vantage point of faculty members. A symphony of insights emanates from intimate focus group discussions featuring six dedicated lecturers, who share their perceptions, experiences, and reflective narratives, illuminating the profound impact of pedagogical practices embedded within the BETA module. Preliminary findings from ongoing data analysis indicate promising results, showcasing a substantial improvement in entrepreneurial skills among students participating in the BETA module. This study promises not only to elevate students' entrepreneurial competencies but also to illuminate the broader canvas of applicability for Kearney's principles and Bloom's domains. The dynamic interplay of quantitative analyses, proffering precise competency metrics, and qualitative revelations, delving into the nuanced narratives of transformative journeys, engenders a holistic understanding of this educational endeavour. Through a rigorous quasi-experimental mixed-methods approach, this research aims to establish the BETA module's effectiveness in fostering entrepreneurial acumen among students at Singapore Polytechnic, thereby contributing valuable insights to the broader discourse on educational methodologies.

Keywords: entrepreneurial education, experiential learning, pedagogical frameworks, innovative competencies

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Authors: Marina Shargorodsky

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Aim: Gestational weight gain (GWG) has been related to altering future weight-gain curves and increased risks of obesity later in life. Obesity may contribute to vascular atherosclerotic changes as well as excess cardiovascular morbidity and mortality observed in these patients. Noninvasive arterial testing, such as ultrasonographic measurement of carotid IMT, is considered a surrogate for systemic atherosclerotic disease burden and is predictive of cardiovascular events in asymptomatic individuals as well as recurrent events in patients with known cardiovascular disease. Currently, there is no consistent evidence regarding the vascular impact of excessive GWG. The present study was designed to investigate the impact of GWG on early atherosclerotic changes during late pregnancy, using intima-media thickness, as well as placental vascular circulation and inflammatory lesions and pregnancy outcomes. Methods: The study group consisted of 59 pregnant women who gave birth and underwent a placental histopathological examination at the Department of Obstetrics and Gynecology, Edith Wolfson Medical Center, Israel, in 2019. According to the IOM guidelines the study group has been divided into two groups: Group 1 included 32 women with pregnancy weight gain within recommended range; Group 2 included 27 women with excessive weight gain during pregnancy. The IMT was measured from non-diseased intimal and medial wall layers of the carotid artery on both sides, visualized by high-resolution 7.5 MHz ultrasound (Apogee CX Color, ATL). Placental histology subdivided placental findings to lesions consistent with maternal vascular and fetal vascular malperfusion according to the criteria of the Society for Pediatric Pathology, subdividing placental findings to lesions consistent with maternal vascular and fetal vascular malperfusion, as well as the inflammatory response of maternal and fetal origin. Results: IMT levels differed between groups and were significantly higher in Group 1 compared to Group 2 (0.7+/-0.1 vs 0.6+/-0/1, p=0.028). Multiple linear regression analysis of IMT included variables based on their associations in univariate analyses with a backward approach. Included in the model were pre-gestational BMI, HDL cholesterol and fasting glucose. The model was significant (p=0.001) and correctly classified 64.7% of study patients. In this model, pre-pregnancy BMI remained a significant independent predictor of subclinical atherosclerosis assessed by IMT (OR 4.314, 95% CI 0.0599-0.674, p=0.044). Among placental lesions related to fetal vascular malperfusion, villous changes consistent with fetal thrombo-occlusive disease (FTOD) were significantly higher in Group 1 than in Group 2, p=0.034). In Conclusion, the present study demonstrated that excessive weight gain during pregnancy is associated with an adverse effect on early stages of subclinical atherosclerosis, placental vascular circulation and neonatal complications. The precise mechanism for these vascular changes, as well as the overall clinical impact of weight control during pregnancy on IMT, placental vascular circulation as well as pregnancy outcomes, deserves further investigation.

Keywords: obesity, pregnancy, complications, weight gain

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Authors: Ayesha Anjum, Arbaz Basha

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Active Galactic Nuclei (AGN) are the actively accreting centers of the galaxies that host supermassive black holes. AGN emits radiation in all wavelengths and also shows variability across all the wavelength bands. The analysis of flux variability tells us about the morphology of the site of emission radiation. Some of the major classifications of AGN are (a) Blazars, with featureless spectra. They are subclassified as BLLacertae objects, Flat Spectrum Radio Quasars (FSRQs), and others; (b) Seyferts with prominent emission line features are classified into Broad Line, Narrow Line Seyferts of Type 1 and Type 2 (c) quasars, and other types. Sloan Digital Sky Survey (SDSS) is an optical telescope based in Mexico that has observed and classified billions of objects based on automated photometric and spectroscopic methods. A sample of blazars is obtained from the third Fermi catalog. For variability analysis, we searched for light curves for these objects in Wide-Field Infrared Survey Explorer (WISE) and Near Earth Orbit WISE (NEOWISE) in two bands: W1 (3.4 microns) and W2 (4.6 microns), reducing the final sample to 256 objects. These objects are also classified into 155 BLLacs, 99 FSRQs, and 2 Narrow Line Seyferts, namely, PMNJ0948+0022 and PKS1502+036. Mid-infrared variability studies of these objects would be a contribution to the literature. With this as motivation, the present work is focused on studying a final sample of 256 objects in general and the Seyferts in particular. Owing to the fact that the classification is automated, SDSS has miclassified these objects into quasars, galaxies, and stars. Reasons for the misclassification are explained in this work. The variability analysis of these objects is done using the method of flux amplitude variability and excess variance. The sample consists of observations in both W1 and W2 bands. PMN J0948+0022 is observed between MJD from 57154.79 to 58810.57. PKS 1502+036 is observed between MJD from 57232.42 to 58517.11, which amounts to a period of over six years. The data is divided into different epochs spanning not more than 1.2 days. In all the epochs, the sources are found to be variable in both W1 and W2 bands. This confirms that the object is variable in mid-infrared wavebands in both long and short timescales. Also, the sources are observed for color variability. Objects either show a bluer when brighter trend (BWB) or a redder when brighter trend (RWB). The possible claim for the object to be BWB (present objects) is that the longer wavelength radiation emitted by the source can be suppressed by the high-energy radiation from the central source. Another result is that the smallest radius of the emission source is one day since the epoch span used in this work is one day. The mass of the black holes at the centers of these sources is found to be less than or equal to 108 solar masses, respectively.

Keywords: active galaxies, variability, Seyfert galaxies, SDSS, WISE

Procedia PDF Downloads 106

Authors: Hamed Delrobai Ghoochan Atigh

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Androgenic alopecia (AGA) is a common form of hair loss, impacting approximately 50% of females, which leads to reduced self-esteem and quality of life. It causes progressive follicular miniaturization in genetically predisposed individuals. Mesotherapy -- a minimally invasive procedure, topical 2% minoxidil, and oral finasteride have emerged as popular treatment options in the realm of cosmetics. However, the efficacy of mesotherapy compared to other options remains unclear. This study aims to assess the effectiveness of mesotherapy when it is added to topical 2% minoxidil treatment on female androgenic alopecia. Mesotherapy, also known as intradermotherapy, is a technique that entails administering multiple intradermal injections of a carefully composed mixture of compounds in low doses, applied at various points in close proximity to or directly over the affected areas. This study involves a randomized controlled trial with 100 female participants diagnosed with androgenic alopecia. The subjects were randomly assigned to two groups: Group A used topical 2% minoxidil twice daily and took Finastride oral tablet. For Group B, 10 mesotherapy sessions were added to the prior treatment. The injections were administered every week in the first month of treatment, every two weeks in the second month, and after that the injections were applied monthly for four consecutive months. The response assessment was made at baseline, the 4th session, and finally after 6 months when the treatment was complete. Clinical photographs, 7-point Likert scale patient self-evaluation, and 7-point Likert scale assessment tool were used to measure the effectiveness of the treatment. During this evaluation, a significant and visible improvement in hair density and thickness was observed. The study demonstrated a significant increase in treatment efficacy in Group B compared to Group A post-treatment, with no adverse effects. Based on the findings, it appears that mesotherapy offers a significant improvement in female AGA over minoxidil. Hair loss was stopped in Group B after one month and improvement in density and thickness of hair was observed after the third month. The findings from this study provide valuable insights into the efficacy of mesotherapy in treating female androgenic alopecia. Our evaluation offers a detailed assessment of hair growth parameters, enabling a better understanding of the treatments' effectiveness. The potential of this promising technique is significantly enhanced when carried out in a medical facility, guided by appropriate indications and skillful execution. An interesting observation in our study is that in areas where the hair had turned grey, the newly regrown hair does not retain its original grey color; instead, it becomes darker. The results contribute to evidence-based decision-making in dermatological practice and offer different insights into the treatment of female pattern hair loss.

Keywords: androgenic alopecia, female hair loss, mesotherapy, topical 2% minoxidil

Procedia PDF Downloads 69

Authors: Paola Millare, Nelinda Catherine Pangilinan

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Background and Aim: Cervical cancer is the most commonly diagnosed gynecological malignancy during pregnancy. Owing to the rarity of the disease, and the complexity of all factors that have to be taken into consideration, standardization of treatment is very difficult. Cervical cancer is the second most common malignancy among women. The treatment of cancer during pregnancy is most challenging in the case of cervical cancer, since the pregnant uterus itself is affected. This report aims to present a case of cervical cancer in a pregnant woman and how to manage this case and several issues accompanied with it. Methods: This is a case of a 28 year-old, Gravida 4 Para 2 (1111), who presented with watery to mucoid, whitish, non-foul smelling and increasing in amount. Internal examination revealed normal external genitalia, parous outlet, cervix was transformed into a fungating mass measuring 5x4 cm, with left parametrial involvement, body of uterus was enlarged to 24 weeks size, no adnexal mass or tenderness. She had cervical punch biopsy, which revealed, adenocarcinoma, well-differentiated cervical tissue. Standard management for cases with stage 2B cervical carcinoma was to start radiation or radical hysterectomy. In the case of patients diagnosed with cervical cancer and currently pregnant, these kind of management will result to fetal loss. The patient still declined the said management and opted to delay the treatment and wait for her baby to reach at least term and proceed to cesarean section as route of delivery. Results: The patient underwent an elective cesarean section at 37th weeks age of gestation, with an outcome of a term, live baby boy APGAR score 7,9 birthweight 2600 grams. One month postpartum, the patient followed up and completed radiotherapy, chemotherapy and brachytherapy. She was advised to go back after 6 months for monitoring. On her last check up, an internal examination was done which revealed normal external genitalia, vagina admits 2 fingers with ease, there is a palpable fungating mass at the cervix measuring 2x2 cm. A repeat gynecologic oncologic ultrasound was done revealing cervical mass, endophytic, grade 1 color score with stromal invasion 35% post radiation reactive lymph nodes with intact paracolpium, pericervical, and parametrial involvement. The patient was then advised to undergo pelvic boost and for close monitoring of the cervical mass. Conclusion: Cervical cancer in pregnancy is rare but is a dilemma for women and their physicians. Treatment should be multidisciplinary and individualized following careful counseling. In this case, the treatment was clearly on the side of preventing the progression of cervical cancer while she is pregnant, however due to ethical reasons, the management deviates on the right of the patient to decide for her own health and her unborn child. The collaborative collection of data relating to treatment and outcome is strongly encouraged.

Keywords: cancer, cervical, ethical, pregnancy

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Authors: Djamila Chabane, Asma Rouane, Karim Arab

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Depending of the chemical substances responsible for the pharmacological effects, a future therapeutic drug might be produced by extraction from whole plants or by callus initiated from some parts. The optimized callus culture protocols now offer the possibility to use cell culture techniques for vegetative propagation and open minds for further studies on secondary metabolites and drug establishment. In Algerian traditional medicine, Pulicaria incisa (Asteraceae) is used in the treatment of daily troubles (stomachache, headhache., cold, sore throat and rheumatic arthralgia). Field findings revealed that many healers use some fresh parts (leaves, flowers) of this plant to treat skin wounds. This study aims to evaluate the healing efficiency of artisanal cream prepared from sticky mucilage isolated from calluses on dermal wounds of animal models. Callus cultures were initiated from reproductive explants (young inflorescences) excised from adult plants and transferred to a MS basal medium supplemented with growth regulators and maintained under dark for for months. Many calluses types were obtained with various color and aspect (friable, compact). Several subcultures of calli were performed to enhance the mucilage accumulation. After extraction, the mucilage extracts were tested on animal models as follows. The wound healing potential was studied by causing dermal wounds (1 cm diameter) at the dorsolumbar part of Rattus norvegicus; different samples of the cream were applied after hair removal on three rats each, including two controls (one treated by Vaseline and one without any treatment), two experimental groups (experimental group 1, treated with a reference ointment "Madecassol® and experimental group 2 treated by callus mucilage cream for a period of seventeen days. The evolution of the healing activity was estimated by calculating the percentage reduction of the area wounds treated by all compounds tested compared to the controls by using AutoCAD software. The percentage of healing effect of the cream prepared from callus mucilage was (99.79%) compared to that of Madecassol® (99.76%). For the treatment time, the significant healing activity was observed after 17 days compared to that of the reference pharmaceutical products without any wound infection. The healing effect of Madecassol® is more effective because it stimulates and regulates the production of collagen, a fibrous matrix essential for wound healing. Mucilage extracts also showed a high capacity to heal the skin without any infection. According to this pharmacological activity, we suggest to use calluses produced by in vitro culture to producing new compounds for the skin care and treatment.

Keywords: calluses, Pulicaria incisa, mucilage, Wounds

Procedia PDF Downloads 100