Search results for: animal artificial insemination

Authors: M. Juffrie, Siti Helmyati, Toto Sudargo, B. J. Istiti Kandarina

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Background: Iron fortification is one potential way to overcome anemia but it can cause gut microbiota imbalance. Probiotics addition can increase the growth of good gut bacteria while prebiotics can support the probiotics growth. Tempeh is rich in nutrients required for hemoglobin synthesis, such as protein, vitamin B12, vitamin C, zinc, iron and copper. Objective: To know the efficacy of fermented tempeh extract fortified with iron and synbiotic in maintain gut microbiota balance. Methods: Fermented synbiotic tempeh extract was made using Lactobacillus plantarum Dad13 and Fructo-oligosaccharides. A total of 32 anemic Wistar rats underwent the iron repletion phase then divided into 4 groups, given: 1) Fermented synbiotic tempeh extract with 50 ppm Fe/NaFeEDTA (Na), 2) Fermented synbiotic tempeh extract with 50 ppm Fe/FeSO4 (Fe), 3) Fermented synbiotic tempeh extract (St), and 4) not receive any interventions (Co). Rats were feed AIN-93 free Fe during intervention. Gut microbiota was measured with culture technique using selective media agar while hemoglobin concentration (Hb) was measured with photometric method before and after intervention. Results: There were significant increase in Hb after intervention in Na, Fe, and St, 6.85 to 11.80; 6.41 to 11.48 and 6.47 to 11.03 mg/dL, respectively (p <0.05). Co did not show increase in Hb (6.40 vs. 6.28 mg/dL). Lactobacilli increased in all groups while both of Bifidobacteria increased and E. coli decreased only in Na and St groups. Conclusion: Iron fortification of fermented synbiotic tempeh extract can increase hemoglobin concentrations in anemic animal, increase Lactobacilli and decrease E. coli. It can be an alternative solution to conduct iron fortification without deteriorate the gut microbiota.

Keywords: tempeh, synbiotic, iron, haemoglobin, gut microbiota

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Authors: Yu Wen Wang, Shyh Ming Kuo, Hsia Ying Cheng, Yu Chiuan Wu

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Liver fibrosis is caused by the activation of hepatic stellate cells in the liver to secrete excessive and deposition of extracellular matrix. In recent years, many treatment strategies have been developed to reduce the activation of hepatic stellate cells and therefore to increase the decomposition of extracellular matrix. Bacopa monnieri, an herbaceous plant of the scrophulariaceae, containing saponins and glycosides, which with antioxidant, anti-inflammation, pain relief and free radical scavenging characteristics. This study was to evaluate the inhibition of hepatic stellate cell activity by Bacopa monnieri extract and its therapeutic potential in treating thioacetamide-induced liver fibrosis in rats. The results showed that the IC50 of Bacopa monnieri extract was 0.39 mg/mL. Bacopa monnieri extract could effectively reduce H2O2-induced hepatic stellate cells inflammation. In the TAA-induced liver fibrosis animal studies, albumin secretion recovered to normal level after treated with Bacopa monnieri extract for 2-w, and fibrosis related proteins, α-SMA and TGF-1levels decreased indicating the extract exerted therapeutic effect on the liver fibrosis. However, inflammatory factors TNF- obviously decreased after 4-w treatment. In summary, we could successfully extract the main component-Bacopaside I from the plant and acquired a potential therapy using this component in treating TAA-induced liver fibrosis in rat.

Keywords: anti-inflammatory, Bacopa monnieri, fibrosis, hepatic stellate cells, water extract

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Authors: Khairul Bariah Sulaiman, Tajul Aris Yang

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Fermentation is well known as an essential process in cocoa beans. Besides to develop the precursor of cocoa flavour, it also induce the colour changes in the beans.The fermentation process is reported to be influenced by duration of pod storage and fermentation. Therefore, this study was conducted to evaluate colour of Malaysian cocoa beans and how the pods storage and fermentation duration using shallow box technique will effect on it characteristics. There are two factors being studied ie duration of cocoa pod storage (0, 2, 4, and 6 days) and duration of cocoa fermentation (0, 1, 2, 3, 4 and 5 days). The experiment is arranged in 4 x 6 factorial design with 24 treatments and arrangement is in a Completely Randomised Design (CRD). The produced beans is inspected for colour changes under artificial light during cut test and divided into four groups of colour namely fully brown, purple brown, fully purple and slaty. Cut tests indicated that cocoa beans which are directly dried without undergone fermentation has the highest slaty percentage. However, application of pods storage before fermentation process is found to decrease the slaty percentage. In contrast, the percentages of fully brown beans start to dominate after two days of fermentation, especially from four and six days of pods storage batch. Whereas, almost all batch have percentage of fully purple less than 20%. Interestingly, the percentage of purple brown beans are scattered in the entire beans batch regardless any specific trend. Meanwhile, statistical analysis using General Linear Model showed that the pods storage has a significant effect on the colour characteristic of the Malaysian dried beans compared to fermentation duration.

Keywords: cocoa beans, colour, fermentation, shallow box

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Authors: Konysbek Aksaule

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The purpose of this work is to explore new and effective ways of teaching English to students who are studying a foreign language since the timeliness of the problem disclosed in this article is due to the high level of English proficiency that potential specialists must have due to high competition in the context of global globalization. The article presents an analysis of the feasibility and effectiveness of using an authentic feature film in teaching English to students. The methodological basis of the study includes an assessment of the level of students' proficiency in a foreign language, the stage of evaluating the film, and the method of selecting the film for certain categories of students. The study also contains a list of practical tasks that can be applied in the process of viewing and perception of an original feature film in a foreign language, and which are aimed at developing language skills such as speaking and listening. The results of this study proved that teaching English to students through watching an original film is one of the most effective methods because it improves speech perception, speech reproduction ability, and also expands the vocabulary of students and makes their speech fluent. In addition, learning English through watching foreign films has a huge impact on the cultural views and knowledge of students about the country of the language being studied and the world in general. Thus, this study demonstrates the high potential of using authentic feature film in English lessons for pedagogical science and methods of teaching English in general.

Keywords: university, education, students, foreign language, feature film

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Authors: Raouf Hassan

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Biogas energy production from sewage sludge is an economically feasible and eco-friendly in nature. Sewage sludge is considered nutrient-rich substrates, but had lower values of carbone which consider an energy source for anaerobic bacteria. The lack or lower values of carbone-to-nitrogen ratio (C/N) reduced biogas yield and fermentation rate. Anaerobic co-digestion of sewage sludge offers several benefits over mono-digestion such as optimize nutrient balance, increased cost-efficiency and increased degradation rate. The high produced amounts of animal manures, which reach up to 90% of the total collected organic wastes, are recommended for the co-digestion with sewage sludge, especially with the limitations of industrial substrates. Moreover, cattle manures had high methane production potential (500 m3/t vsadded). When mixed with sewage sludge the potential methane production increased with increasing cattle manure content. In this paper, the effect of cattle manure (CM) addition as co-substrates on the sewage sludge (SS) anaerobic digestion performance was investigated under mesophilic conditions (35°C) using anaerobic batch reactors. The batch reactors were operated with a working volume 0.8 liter, and a hydraulic retention time of 30 days. The research work focus on studying two main parameters; the biogas yield (expressed as VSS) and pH values inside the reactors.

Keywords: anaerobic digestion, sewage sludge, cattle manure, mesophilic, biogas yield, pH

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Authors: Maria Magdy Danial Riad

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Background: In the United Kingdom (UK), pharmacists' roles have expanded considerably in recent decades to encompass clinical practice through more direct patient care. However, dispensing and compounding remain core activities for pharmacists. A lack of marketed preparations for species-specific animal use results in veterinary pharmacy practice compounding, retaining its prominence. Current participation by pharmacists to support this sphere of practice would appear to be minimal. Objectives: This study was undertaken to determine the opinions and views toward the practice of veterinary pharmacy by a cross-sectional group of pharmacists. Methods: Research data were collected via a self-administered survey questionnaire distributed at the 2012 annual conference of the Royal Pharmaceutical Society. Sampling was purposive, with a random distribution of the questionnaire to pharmacists during the conference sessions. Key findings: Interaction by pharmacists with veterinary pharmacies is currently minimal, primarily due to a lack of knowledge of veterinary medicines. Respondents revealed a lack of veterinary pharmacy courses during their undergraduate studies. This has led to situations where some veterinary prescriptions are dispensed without adequate checks being performed by the pharmacist. Pharmacists, on occasion, do not dispense veterinary prescriptions presented to them due to insufficient knowledge of veterinary medicines and/or a lack of consultable reference sources. The effect on practice is that pharmacists do not always participate as fully as would seem logical. Conclusions: Pharmacists' participation in veterinary pharmacy is limited by a lack of knowledge of veterinary medicines, mostly resulting from inadequate tuition on veterinary pharmacy during their initial education.

Keywords: veterinary pharmacy, veterinary medicines, pharmacy education, pharmacists continuing professional development

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Authors: Glynn K. Pindihama, Rabelani Mudzielwana, Ndamulelo Lilimu

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Wastewater treatment effluents, particularly sludges, are known to be potential sources of heavy metal contamination in the environment, depending on how the sludge is managed. Maintenance of wastewater treatment infrastructure in developing countries such as South Africa has become an issue of grave concern, with many wastewater treatment facilities in dilapidating states. Among the problems is the vandalism of the periphery fence to many wastewater treatment facilities, resulting in livestock, such as cows from neighboring villages, grazing within the facilities. This raises human health risks since dried sludge from the treatment plants is usually spread on the grass around the plant, resulting in heavy metal contamination. Animal products such as meat and milk from these cows thus become an indirect route to heavy metals to humans. This study assessed heavy metals in sludges from 3 wastewater treatment plants in Limpopo Province of South Africa. In addition, cow dung and sludge liquors were collected from these plants and evaluated for their heavy metal content. The sludge and cow dung were microwave-digested using the aqua-regia method, and all samples were analyzed for heavy metals using ICP-OES. The loadings of heavy metals in the sludge were in the order Cu>Zn>Ni>Cr>Cd>As>Hg. In cow dung, the heavy metals were in the order Fe>Cu>Mn>Zn>Cr>Pb>Co>Cd. The levels of Zn and Cu in the sludge liquors where the animals were observed drinking were, in some cases, above the permissible limit for livestock consumption. Principal component and correlation analysis are yet to be done to determine if there is a correlation between the heavy metals in the cow dung and sludge and sludge liquors.

Keywords: cow dung, heavy metals, sludge, wastewater treatment plants, sludge.

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Authors: Akinbo Razak Yinka, Adesanya Kehinde Kazeem, Oladokun Oluwagbenga Peter

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Time series data are sequences of observations collected over a period of time. Such data can be used to predict health outcomes, such as disease progression, mortality, hospitalization, etc. The Statistical approach is based on mathematical models that capture the patterns and trends of the data, such as autocorrelation, seasonality, and noise, while Neural methods are based on artificial neural networks, which are computational models that mimic the structure and function of biological neurons. This paper compared both parametric and non-parametric time series models of patients treated for malaria in Maternal and Child Health Centres in Lagos State, Nigeria. The forecast methods considered linear regression, Integrated Moving Average, ARIMA and SARIMA Modeling for the parametric approach, while Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM) Network were used for the non-parametric model. The performance of each method is evaluated using the Mean Absolute Error (MAE), R-squared (R2) and Root Mean Square Error (RMSE) as criteria to determine the accuracy of each model. The study revealed that the best performance in terms of error was found in MLP, followed by the LSTM and ARIMA models. In addition, the Bootstrap Aggregating technique was used to make robust forecasts when there are uncertainties in the data.

Keywords: ARIMA, bootstrap aggregation, MLP, LSTM, SARIMA, time-series analysis

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Authors: Aishwarya Rai

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This study explores the transformative influence of generative AI on startups, businesses, and industries. We will explore how large businesses can benefit in the area of customer operations, where AI-powered chatbots can improve self-service and agent effectiveness, greatly increasing efficiency. In marketing and sales, generative AI could transform businesses by automating content development, data utilization, and personalization, resulting in a substantial increase in marketing and sales productivity. In software engineering-focused startups, generative AI can streamline activities, significantly impacting coding processes and work experiences. It can be extremely useful in product R&D for market analysis, virtual design, simulations, and test preparation, altering old workflows and increasing efficiency. Zooming into the retail and CPG industry, industry findings suggest a 1-2% increase in annual revenues, equating to $400 billion to $660 billion. By automating customer service, marketing, sales, and supply chain management, generative AI can streamline operations, optimizing personalized offerings and presenting itself as a disruptive force. While celebrating economic potential, we acknowledge challenges like external inference and adversarial attacks. Human involvement remains crucial for quality control and security in the era of generative AI-driven transformative innovation. This talk provides a comprehensive exploration of generative AI's pivotal role in reshaping businesses, recognizing its strategic impact on customer interactions, productivity, and operational efficiency.

Keywords: generative AI, digital transformation, LLM, artificial intelligence, startups, businesses

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Authors: Alireza Barari, Saeed Shirali

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The etiology of obesity is heterogeneous with several factors, and the pathophysiology of obesity has recently related to leptin, oxidative damage, and inflammation. Silybum marianum have a health-promoting perspective and has shown that bioactive molecules of silymarin have the antioxidant and antitumor properties and can affect secretion of hormones and enzyme activity in animal. This study aimed to evaluate the antioxidant effects and changes in hormonal levels and body composition after silymarin consumption. Forty-five healthy untrained colleges male take part in the 4-week investigation. The subjects were assigned to 5 groups: endurance training, Silymarin with endurance training, strength training with placebo, Silymarin with strength training or placebo. Body fat percentage and Blood sample analysis were measured before and after the intervention to assay leptin, adiponectin and paraoxonase in the sample of subject's serum. There was a considerable decrease in body fat percent and a significant increase in VO2 max in 'Strength training' and 'Strength training with Silymarin' groups. But, no significant changes in levels of leptin, adiponectinin, and paraoxanase (PON) that were observed between exercise and exercise with Silymarin in these groups. We observed reduction in body fat% and increase in adiponectin induced by exercise for 4 weeks in untrained healthy men. Silybin, could not effectively improve all parameters and don’t prevent the progression of cell damage by antioxidant activity of PON.

Keywords: anti-inflammatory activity, antioxidant activity, silymarin, body composition, paraoxonase (PON)

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Authors: S. Bilal, S. A. Bhat, I. Hussain, J. D. Parrah, S. P. Ahmad, M. R. Mir

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Background: The wound healing involves a highly coordinated cascade of cellular and immunological response over a period including coagulation, inflammation, granulation tissue formation, epithelialization, collagen synthesis and tissue remodeling. Wounds in aged heal more slowly than those in younger, mainly because of comorbidities that occur as one age. The present study is about the influence of age on wound healing. 1x1cm^2 (100 mm) wounds were created on the back of the animal. The animals were divided into two groups; one group had animals in the age group of 3-9 months while another group had animals in the age group of 15-21 months. Materials and Methods: 24 clinically healthy rabbits in the age group of 3-21 months were used as experimental animals and divided into two groups viz A and B. All experimental parameters, i.e., Excision wound model, Measurement of wound area, Protein extraction and estimation, Protein extraction and estimation and DNA extraction and estimation were done by standard methods. Results: The parameters studied were wound contraction, hydroxyproline, glucosamine, protein, and DNA. A significant increase (p<0.005) in the hydroxyproline, glucosamine, protein and DNA and a significant decrease in wound area (p<0.005) was observed in the age group of 3-9 months when compared to animals of an age group of 15-21 months. Wound contraction together with hydroxyproline, glucosamine, protein and DNA estimations suggest that advanced age results in retarded wound healing. Conclusion: The decrease wound contraction and accumulation of hydroxyproline, glucosamine, protein and DNA in group B animals may be associated with the reduction or delay in growth factors because of the advancing age.

Keywords: age, wound healing, excision wound, hydroxyproline, glucosamine

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Authors: Şevket Evci, Mehmet Akif Karsli

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The aim of this study is to determine nutrient contents, in situ ruminal degradation kinetics and protein fractions of screenings bean (B), chick pea (ChP), red lentil (RL) and green lentil (GL) that is used as residue in grain legume packing industry. For this purpose, four samples of each legumes species-a total of 16 samples, collected from different parts of our country were utilized. Feedstuffs used in the experiment were incubated for 0, 2 4, 8, 12, 24, and 48 hours in the rumen of 3 ruminally cannulated Akkaraman rams as duplicate. The nutrient contents, in situ ruminal dry matter (DM), organic matter (OM) and crude protein (CP) degradabilities and fractions, and escape protein contents were evaluated. The highest OM and CP contents were observed in RL (P<0.05). Chick pea had the highest ether extract (EE) content and EE values were 3.47, 6.72, 2.26, 8.66 % for RL, B, GL and ChP, respectively (P<0.05). Crude fiber (CF), ADF, and NDF contents were the highest in RL and the lowest in ChP. CF values were 24.03, 10.80, 4.09 and 3.57 % for RL, GL, B and ChP (P<0.05). Acid detergent insoluble nitrogen content of samples did not differ. Escape protein content was the highest in RL and the lowest in B (P<0.05). After 48 h incubation, the lowest OM and CP degradabilities were observed in RL. While the highest OM degradability was seen in ChP the highest CP degradability was observed in B (P<0.05). The lowest water soluble OM and CP contents were observed in RL whereas the highest potentially degradable OM and CP contents were seen in B and ChP (P<0.05). Both rate of OM and CP degradations (k-1) did not differ among samples (P>0.05). In conclusion, it was noted that feedstuffs (GL, ChP and B) used in the experiment except RL had a greater ruminal degradibilities of both OM and CP and moreover, had a higher escape protein contents, except B. It was thought that these feedstuffs can be substituted with some of common protein sources used in animal nutrition.

Keywords: in situ, nutrient contents, ruminant, subsieve

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Authors: Alireza Javed, Keivan Jamshidi

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Reactive amyloidosis is a condition that complicates a long list of chronic inflammation, chronic infectious, malignant, and hereditary disorders. In the present study the potential effects of two amyloidogenic substances: ie. AgNO3 and Freund's Adjuvant (AF) with that of vitamin free casein, on spatio-temporal pattern of experimental amyloidosis in mice, were compared. For this purpose, a total of 40 male Swees mice, obtained from Pasteur Institute Tehran, after being weighted were randomly divided into 4 groups including 2 treatments, 1 control (vitamin free casein) and 1 positive control (normal saline). At the end of 3rd, 5th and 7th weeks of experiment 3 mice were randomly selected and euthnised. Spleen sample of each animal obtained and preserved in 10% neutral buffer formalin. Sample were then processed through different stages of dehydration, clearing and impregnation and finally embedded in paraffin blocks. Sections of 5µm thickness then cut and stained by alkaline Congo red techniques. Spleen weights and the data obtained from the microscopic quantitative analysis did show no significant differences between groups A and B, A and C, and B and C. However, significant differences were observed between groups A and D, B and D, and C and D respectively. It is concluded that two compounds ie; AgNO3 and Freund's Adjuvant have the same potential, as does vitamin free casein have, in spatio – temporal pattern of experimental amyloidosis in mice.

Keywords: amyloidosis, mice, AgNO3, Freund's Adjuvant

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Authors: Summer Hassan, David Crossman

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Myocardial fibrosis (MF) has been loosely defined as the process occurring in the pathological remodeling of the myocardium due to excessive production and deposition of extracellular matrix (ECM) proteins, including collagen. This reduces tissue compliance and accelerates progression to heart failure, as well as affecting the electrical properties of the myocytes resulting in arrhythmias. Microscopic interrogation of MF is key to understanding the molecular orchestrators of disease. It is well-established that recruitment and stimulation of myofibroblasts result in Collagen deposition and the resulting expansion in the ECM. Many types of Collagens have been identified and implicated in scarring of tissue. In a series of experiments conducted at our lab, we aim to elucidate the role collagen VI plays in the development of myocardial fibrosis and its direct impact on myocardial function. This was investigated through an animal experiment in Rats with Collagen VI knockout diseased and healthy animals as well as Collagen VI wild diseased and healthy rats. Echocardiogram assessments of these rats ensued at four-time points, followed by microscopic interrogation of the myocardium aiming to correlate the role collagen VI plays in myocardial function. Our results demonstrate a deterioration in cardiac function as represented by the ejection fraction in the knockout healthy and diseased rats. This elucidates a potential protective role that collagen-VI plays following a myocardial insult. Current work is dedicated to the microscopic characterisation of the fibrotic process in all rat groups, with the results to follow.

Keywords: heart failure, myocardial fibrosis, collagen, echocardiogram, confocal microscopy

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Authors: Jean-Francois Rajotte, Martin Sotir, Frank Gouineau

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The installation and management of traffic monitoring devices can be costly from both a financial and resource point of view. It is therefore important to take advantage of in-place infrastructures to extract the most information. Here we show how low-quality urban road traffic images from cameras already available in many cities (such as Montreal, Vancouver, and Toronto) can be used to estimate traffic flow. To this end, we use a pre-trained neural network, developed for object detection, to count vehicles within images. We then compare the results with human annotations gathered through crowdsourcing campaigns. We use this comparison to assess performance and calibrate the neural network annotations. As a use case, we consider six months of continuous monitoring over hundreds of cameras installed in the city of Montreal. We compare the results with city-provided manual traffic counting performed in similar conditions at the same location. The good performance of our system allows us to consider applications which can monitor the traffic conditions in near real-time, making the counting usable for traffic-related services. Furthermore, the resulting annotations pave the way for building a historical vehicle counting dataset to be used for analysing the impact of road traffic on many city-related issues, such as urban planning, security, and pollution.

Keywords: traffic monitoring, deep learning, image annotation, vehicles, roads, artificial intelligence, real-time systems

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Authors: S. Abera, T. Gidey, W. Terefe

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Introduction: Testing for HIV is the key entry point to HIV prevention, treatment, and care and support services. Hence, predictive data mining techniques can greatly benefit to analyze and discover new patterns from huge datasets like that of EDHS 2011 data. Objectives: The objective of this study is to build a predictive modeling for HIV testing and identify determinants of HIV testing for adults with age above fourteen years using data mining techniques. Methods: Cross-Industry Standard Process for Data Mining (CRISP-DM) was used to predict the model for HIV testing and explore association rules between HIV testing and the selected attributes among adult Ethiopians. Decision tree, Naïve-Bayes, logistic regression and artificial neural networks of data mining techniques were used to build the predictive models. Results: The target dataset contained 30,625 study participants; of which 16, 515 (53.9%) were women. Nearly two-fifth; 17,719 (58%), have never been tested for HIV while the rest 12,906 (42%) had been tested. Ethiopians with higher wealth index, higher educational level, belonging 20 to 29 years old, having no stigmatizing attitude towards HIV positive person, urban residents, having HIV related knowledge, information about family planning on mass media and knowing a place where to get testing for HIV showed an increased patterns with respect to HIV testing. Conclusion and Recommendation: Public health interventions should consider the identified determinants to promote people to get testing for HIV.

Keywords: data mining, HIV, testing, ethiopia

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Authors: Ibrahim Sani, J. T. Amodu, M. R. Hassan, R. J. Tanko, N. Adamu

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This study investigated the digestibility of Brachiaria ruziziensis and Centrosema pascuorum hay mixtures at varying proportions in Yankasa rams. Twelve Yankasa rams with average initial weight 10.25 ± 0.1 kg were assigned to three dietary treatments of B. ruziziensis and C. pascuorum hay at different mixtures (75BR:25CP, 50BR:50CP and 25BR:75CP, respectively) in a Completely Randomized Design (CRD) for a period of 14 days. Concentrate diet was given to the experimental animals as supplement at fixed proportion, while the forage mixture (basal diet) was fed at 3% body weight. Animals on 50BR:50CP had better nutrient digestibility (crude protein, acid and neutral detergent fibre, ether extract and nitrogen free extract) than other treatment diets, except in dry matter digestibility (87.35%) which compared with 87.54% obtained in 25BR:75CP treatment diet and also organic matter digestibility. All parameters taken on nitrogen balance with the exception of nitrogen retained were significantly higher (P < 0.05) in animals fed 25BR:75CP diet, but were statistically similar with values obtained for animals on 50BR:50CP diet. From results obtained in this study, it is concluded that mixture of 25%BR75%CP gave the best nutrient digestibility and nitrogen balance in Yankasa rams. It is therefore recommended that B. ruziziensis and C. pascuorum should be fed at 50:50 mixture ratio for enhanced animal growth and performance in Nigeria.

Keywords: B. ruziziensis, C. pascuorum, digestibilty, rams, Yankasa

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Authors: Sushma Ghogale

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With a surge in user-generated content or feedback or reviews on the internet, it has become possible and important to know consumers' opinions about products and services. This data is important for both potential customers and businesses providing the services. Data from social media is attracting significant attention and has become the most prominent channel of expressing an unregulated opinion. Prospective customers look for reviews from experienced customers before deciding to buy a product or service. Several websites provide a platform for users to post their feedback for the provider and potential customers. However, the biggest challenge in analyzing such data is in extracting latent features and providing term-level analysis of the data. This paper proposes an approach to use topic modeling to classify the reviews into topics and conduct sentiment analysis to mine the opinions. This approach can analyse and classify latent topics mentioned by reviewers on business sites or review sites, or social media using topic modeling to identify the importance of each topic. It is followed by sentiment analysis to assess the satisfaction level of each topic. This approach provides a classification of hotel reviews using multiple machine learning techniques and comparing different classifiers to mine the opinions of user reviews through sentiment analysis. This experiment concludes that Multinomial Naïve Bayes classifier produces higher accuracy than other classifiers.

Keywords: latent Dirichlet allocation, topic modeling, text classification, sentiment analysis

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Authors: Begna Tulu, Gobena Ameni

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Understanding the types of Mycobacterium bovis (M. bovis) strains circulating in a country and exploring its zoonotic potential has significant contribution in the effort to design control strategies. The main aim of this study was to review and compile the results of studies conducted on M. bovis genotyping and its zoonotic potential of M. bovis in Ethiopia. A systematic search and review of articles published on M. bovis strains in Ethiopia were made. PubMed and Google Scholar databases were considered for the search while the keywords used were 'Mycobacteria,' 'Mycobacterium bovis,' 'Bovine Tuberculosis' and 'Ethiopia.' Fourteen studies were considered in this review and a total of 31 distinct strains of M. bovis (N=211) were obtained; the most dominant strains were SB0133 (N=62, 29.4%), SB1176 (N=61, 28.9%), and followed by SB0134 and SB1476 each (N=18, 8.5%). The clustering rate of M. bovis strains was found to be 42.0%. On the other hand, 6 strains of M. bovis were reported from human namely; SB0665 (N=4), SB0303 (N=2), SB0982 (N=2), SB0133 (N=1), SB1176 (N=1), and 1 new strain. Similarly, a total of 8 strains (N=13) of M. tuberculosis bacteria were also identified from animal subjects; namely SIT149 (N=3), SIT1 (N=2), SIT1688 (n=2), SIT262 (N=2), SIT53 (N=1), SIT59 (N=1), and one new-Ethiopian strain. The result showed that the genetic diversity of M. bovis strains reported from Ethiopia are less diversified and highly clustered. And also the result underlines that there is an ongoing active transmission of M. bovis and M. tuberculosis between human and animals in Ethiopia because a significant number strains of both type of bacteria were reported from human and animals.

Keywords: mycobacterium bovis, Mycobacterium tuberculosis, zoonotic potential, genetic diversity, Ethiopia

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Authors: Mohammad Bakhshandeh

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Structural Health Monitoring (SHM) is a crucial and necessary practice that plays a vital role in ensuring the safety and integrity of critical structures, and in particular, bridges. The continuous monitoring of bridges for signs of damage or degradation through Bridge Health Monitoring (BHM) enables early detection of potential problems, allowing for prompt corrective action to be taken before significant damage occurs. Although all monitoring techniques aim to provide accurate and decisive information regarding the remaining useful life, safety, integrity, and serviceability of bridges, understanding the development and propagation of damage is vital for maintaining uninterrupted bridge operation. Over the years, extensive research has been conducted on BHM methods, and experts in the field have increasingly adopted new methodologies. In this article, we provide a comprehensive exploration of the various BHM approaches, including sensor-based, non-destructive testing (NDT), model-based, and artificial intelligence (AI)-based methods. We also discuss the challenges associated with BHM, including sensor placement and data acquisition, data analysis and interpretation, cost and complexity, and environmental effects, through an extensive review of relevant literature and research studies. Additionally, we examine potential solutions to these challenges and propose future research ideas to address critical gaps in BHM.

Keywords: structural health monitoring (SHM), bridge health monitoring (BHM), sensor-based methods, machine-learning algorithms, and model-based techniques, sensor placement, data acquisition, data analysis

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Authors: Halefom Kidane

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This study aims to assess the wind resource potential and characterize the urban area wind patterns in Hawassa City, Ethiopia. The estimation and characterization of wind resources are crucial for sustainable urban planning, renewable energy development, and climate change mitigation strategies. A secondary data collection method was used to carry out the study. The collected data at 2 meters was analyzed statistically and extrapolated to the standard heights of 10-meter and 30-meter heights using the power law equation. The standard deviation method was used to calculate the value of scale and shape factors. From the analysis presented, the maximum and minimum mean daily wind speed at 2 meters in 2016 was 1.33 m/s and 0.05 m/s in 2017, 1.67 m/s and 0.14 m/s in 2018, 1.61m and 0.07 m/s, respectively. The maximum monthly average wind speed of Hawassa City in 2016 at 2 meters was noticed in the month of December, which is around 0.78 m/s, while in 2017, the maximum wind speed was recorded in the month of January with a wind speed magnitude of 0.80 m/s and in 2018 June was maximum speed which is 0.76 m/s. On the other hand, October was the month with the minimum mean wind speed in all years, with a value of 0.47 m/s in 2016,0.47 in 2017 and 0.34 in 2018. The annual mean wind speed was 0.61 m/s in 2016,0.64, m/s in 2017 and 0.57 m/s in 2018 at a height of 2 meters. From extrapolation, the annual mean wind speeds for the years 2016,2017 and 2018 at 10 heights were 1.17 m/s,1.22 m/s, and 1.11 m/s, and at the height of 30 meters, were 3.34m/s,3.78 m/s, and 3.01 m/s respectively/Thus, the site consists mainly primarily classes-I of wind speed even at the extrapolated heights.

Keywords: artificial neural networks, forecasting, min-max normalization, wind speed

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Authors: Liu Wei-Hsien, Chuang Hsiao-Li, Huang Yen-Te, Wu Chien-Chen, Chou Geng-Ting, Tsai Ying-Chieh

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Intestinal microflora play an important role in communication along the gut-brain axis. Probiotics, defined as live bacteria or bacterial products, confer a significant health benefit to the host. Here we administered Lactobacillus plantarum PS128 (PS128) to the germ-free (GF) mouse to investigate the impact of the gut-brain axis on emotional behavior. Administration of live PS128 significantly increased the total distance traveled in the open field test; it decreased the time spent in the closed arm and increased the time spent and total entries into the open arm in the elevated plus maze. In contrast, heat-killed PS128 caused no significant changes in the GF mice. Treatment with live PS128 significantly increased levels of both serotonin and dopamine in the striatum, but not in the prefrontal cortex or hippocampus. However, live PS128 did not alter pro- or anti-inflammatory cytokine production by mitogen-stimulated splenocytes. The above data indicate that the normalization of emotional behavior correlated with monoamine neurotransmission, but not with immune activity. Our findings suggest that daily intake of the probiotic PS128 could ameliorate neuropsychiatric disorders such as anxiety and excessive psychological stress.

Keywords: dopamine, hypothalamic-pituitary-adrenal axis, intestinal microflora, serotonin

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Authors: Aya Belal, Ahmed Maher Eltair, Maggie Ahmed Mashaly

Abstract:

Geopolymer concrete is gaining recognition as a sustainable alternative to conventional Portland Cement concrete due to its environmentally friendly nature, which is a key goal for Smart City initiatives. It has demonstrated its potential as a reliable material for the design of structural elements. However, the production of Geopolymer concrete is hindered by batch-to-batch variations, which presents a significant challenge to the widespread adoption of Geopolymer concrete. To date, Machine learning has had a profound impact on various fields by enabling models to learn from large datasets and predict outputs accurately. This paper proposes an integration between the current drift to Artificial Intelligence and the composition of Geopolymer mixtures to predict their mechanical properties. This study employs Python software to develop machine learning model in specific Decision Trees. The research uses the percentage oxides and the chemical composition of the Alkali Solution along with the curing conditions as the input independent parameters, irrespective of the waste products used in the mixture yielding the compressive strength of the mix as the output parameter. The results showed 90 % agreement of the predicted values to the actual values having the ratio of the Sodium Silicate to the Sodium Hydroxide solution being the dominant parameter in the mixture.

Keywords: decision trees, geopolymer concrete, machine learning, smart cities, sustainability

Procedia PDF Downloads 64

Authors: Shao Qi

Abstract:

The article uses the CiteSpace knowledge graph analysis tool to sort and visualize the journal literature on urban plants and habitats in the Web of Science and China National Knowledge Infrastructure databases. Based on a comprehensive interpretation of the visualization results of various data sources and the description of the intrinsic relationship between high-frequency keywords using knowledge mapping, the research hotspots, processes and evolution trends in this field are analyzed. Relevant case studies are also conducted for the hotspot contents to explore the means of landscape intervention and synthesize the understanding of research theories. The results show that (1) from 1999 to 2022, the research direction of urban plants and habitats gradually changed from focusing on plant and animal extinction and biological invasion to the field of human urban habitat creation, ecological restoration, and ecosystem services. (2) The results of keyword emergence and keyword growth trend analysis show that habitat creation research has shown a rapid and stable growth trend since 2017, and ecological restoration has gained long-term sustained attention since 2004. The hotspots of future research on urban plants and habitats in China may focus on habitat creation and ecological restoration.

Keywords: research trends, visual analysis, habitat creation, ecological restoration

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Authors: Saad Chahba, Rabia Sehab, Ahmad Akrad, Cristina Morel

Abstract:

Nowadays, the electric machines used in urban electric vehicles are, in most cases, three-phase electric machines with or without a magnet in the rotor. Permanent Magnet Synchronous Machine (PMSM) and Induction Machine (IM) are the main components of drive trains of electric and hybrid vehicles. These machines have very good performance in healthy operation mode, but they are not redundant to ensure safety in faulty operation mode. Faced with the continued growth in the demand for electric vehicles in the automotive market, improving the reliability of electric vehicles is necessary over the lifecycle of the electric vehicle. Multiphase electric machines respond well to this constraint because, on the one hand, they have better robustness in the event of a breakdown (opening of a phase, opening of an arm of the power stage, intern-turn short circuit) and, on the other hand, better power density. In this work, a diagnosis approach using a neural network for an open circuit fault or more of a five-phase induction machine is developed. Validation on the simulator of the vehicle drivetrain, at reduced power, is carried out, creating one and more open circuit stator phases showing the efficiency and the reliability of the new approach to detect and to locate on-line one or more open phases of a five-induction machine.

Keywords: electric vehicle drivetrain, multiphase drives, induction machine, control, open circuit (OC) fault diagnosis, artificial neural network

Procedia PDF Downloads 179

Authors: Tsai-chun Lai, Szu-ju Fu, Tzu-lin Lee, Yuh-Lien Chen

Abstract:

There is much evidence that exposure to fine particulate matter (PM) from air pollution increases the risk of cardiovascular morbidity and mortality. According to previous reports, PM in the air enters the respiratory tract, contacts the alveoli, and enters the blood circulation, leading to the progression of cardiovascular disease. PM pollution may also lead to cardiometabolic disturbances, increasing the risk of cardiovascular disease. The effects of PM on cardiac function and mitochondrial damage are currently unknown. We used mice and rat cardiomyocytes (H9c2) as animal and in vitro cell models, respectively, to simulate an air pollution environment using PM. These results indicate that the apoptosis-related factor PUMA, a regulator of apoptosis upregulated by p53, is increased in mice treated with PM. Apoptosis was aggravated in cardiomyocytes treated with PM, as measured by TUNEL assay and Annexin V/PI. Western blot results showed that CASPASE3 was significantly increased and BCL2 (B-cell lymphoid 2) was significantly decreased under PM treatment. Concurrent exposure to PM increases mitochondrial reactive oxygen species (ROS) production by MitoSOX Red staining. Furthermore, using Mitotracker staining, PM treatment significantly shortened mitochondrial length, indicating mitochondrial fission. The expression of mitochondrial fission-related proteins p-DRP1 (phosphodynamics-related protein 1) and FIS1 (mitochondrial fission 1 protein) was significantly increased. Based on these results, the exposure to PM worsens mitochondrial function and leads to cardiomyocyte apoptosis.

Keywords: particulate matter, cardiomyocyte, apoptosis, mitochondria

Procedia PDF Downloads 86

Authors: Seyed Esmail Seyedi Bariran, Khairul Salleh Mohamed Sahari

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In multi-echelon supply chain networks, optimal supplier selection significantly depends on the accuracy of suppliers’ performance prediction. Different methods of multi criteria decision making such as ANN, GA, Fuzzy, AHP, etc have been previously used to predict the supplier performance but the “black-box” characteristic of these methods is yet a major concern to be resolved. Therefore, the primary objective in this paper is to implement an artificial intelligence-based gene expression programming (GEP) model to compare the prediction accuracy with that of ANN. A full factorial design with %95 confidence interval is initially applied to determine the appropriate set of criteria for supplier performance evaluation. A test-train approach is then utilized for the ANN and GEP exclusively. The training results are used to find the optimal network architecture and the testing data will determine the prediction accuracy of each method based on measures of root mean square error (RMSE) and correlation coefficient (R2). The results of a case study conducted in Supplying Automotive Parts Co. (SAPCO) with more than 100 local and foreign supply chain members revealed that, in comparison with ANN, gene expression programming has a significant preference in predicting supplier performance by referring to the respective RMSE and R-squared values. Moreover, using GEP, a mathematical function was also derived to solve the issue of ANN black-box structure in modeling the performance prediction.

Keywords: Supplier Performance Prediction, ANN, GEP, Automotive, SAPCO

Procedia PDF Downloads 403

Authors: Kemka Ihemelandu, Chukwuemeka Ihemelandu

Abstract:

Melanoma remains a public health crisis, with incidence rates increasing rapidly in the past decades. Improving diagnostic accuracy to decrease misdiagnosis using Artificial intelligence (AI) continues to be documented. Unfortunately, unintended racially biased outcomes, a product of lack of diversity in the dataset used, with a noted class imbalance favoring lighter vs. darker skin tone, have increasingly been recognized as a problem.Resulting in noted limitations of the accuracy of the Convolutional neural network (CNN)models. CNN models are prone to biased output due to biases in the dataset used to train them. Our aim in this study was the optimization of convolutional neural network algorithms to mitigate bias in the automated diagnosis of melanoma. We hypothesized that our proposed training algorithms based on a data augmentation method to optimize the diagnostic accuracy of a CNN classifier by generating new training samples from the original ones will reduce bias in the automated diagnosis of melanoma. We applied geometric transformation, including; rotations, translations, scale change, flipping, and shearing. Resulting in a CNN model that provided a modifiedinput data making for a model that could learn subtle racial features. Optimal selection of the momentum and batch hyperparameter increased our model accuracy. We show that our augmented model reduces bias while maintaining accuracy in the automated diagnosis of melanoma.

Keywords: bias, augmentation, melanoma, convolutional neural network

Procedia PDF Downloads 195

Authors: Jonas Colin

Abstract:

Standing at the vanguard of AI development, Alpha represents an unprecedented synthesis of logical rigor and human abstraction, meticulously crafted to mirror the user's unique persona and personality, a feat previously unattainable in AI development. Alpha, an avant-garde artefact in the realm of artificial intelligence, epitomizes a paradigmatic shift in personalized digital interaction, amalgamating user-specific dialogic patterns with the sophisticated algorithmic prowess of OpenAI's GPT-3.5 to engender a platform for enhanced metacognitive engagement and individualized user experience. Underpinned by a sophisticated algorithmic framework, Alpha integrates vast datasets through a complex interplay of neural network models and symbolic AI, facilitating a dynamic, adaptive learning process. This integration enables the system to construct a detailed user profile, encompassing linguistic preferences, emotional tendencies, and cognitive styles, tailoring interactions to align with individual characteristics and conversational contexts. Furthermore, Alpha incorporates advanced metacognitive elements, enabling real-time reflection and adaptation in communication strategies. This self-reflective capability ensures continuous refinement of its interaction model, positioning Alpha not just as a technological marvel but as a harbinger of a new era in human-computer interaction, where machines engage with us on a deeply personal and cognitive level, transforming our interaction with the digital world.

Keywords: chatbot, GPT 3.5, metacognition, symbiose

Procedia PDF Downloads 44

Authors: Sebahat Seker

Abstract:

Since there is a parallel connection between drinking water quality and public health, studies on drinking and domestic water are of vital importance. Ardahan Province is one of the provinces located in the Northeast Anatolian Region, where animal husbandry and agriculture are carried out economically. City mains water uses underground spring water as a source and is chlorinated and given to the city center by gravity. However, mains water cannot be used outside the central district of the city, and the majority of the people meet their drinking and utility water needs from the wells they have opened individually. The water element, which is vital for all living things, is the most important substance that sustains life for humans. Under normal conditions, a healthy person consumes approximately 1.8-2 liters of water. The quality and use of potable water is one of the most important issues in terms of health. The quality parameters of drinking and utility water have been revealed by the scientific world. Scientific studies on drinking water quality in the world and its impact on public health are among the most popular topics. Although our country is surrounded by water on three sides, potable water resources are very few. In the Eastern Anatolia Region, it is difficult for the public to access drinking and utility water due to the difficult conditions both climatically and geographically. In this study, samples taken from drinking and utility water at certain intervals from the stations determined, and water quality parameters will be determined. The fact that such a study has not been carried out in the region before and the knowledge of the local people about water quality is very important in terms of its original and widespread effect.

Keywords: water quality, modelling, evaluation, northeastern anatolia

Procedia PDF Downloads 182