Search results for: psychotherapy tool

Authors: Victor Bloch, Eerikki Kaila, Reetta Palva

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Field robots are an important tool for enhancing efficiency and decreasing the climatic impact of food production. There exists a number of commercial field robots; however, since this technology is still new, the robot advantages and limitations, as well as methods for optimal using of robots, are still unclear. In this study, the performance of a commercial field robot for seeding and weeding was assessed. A research 2-ha sugar beet field with 0.5m row width was used for testing, which included robotic sowing of sugar beet and weeding five times during the first two months of the growing. About three and five percent of the field were used as untreated and chemically weeded control areas, respectively. The plant detection was based on the exact plant location without image processing. The robot was equipped with six seeding and weeding tools, including passive between-rows harrow hoes and active hoes cutting inside rows between the plants, and it moved with a maximal speed of 0.9 km/h. The robot's performance was assessed by image processing. The field images were collected by an action camera with a height of 2 m and a resolution 27M pixels installed on the robot and by a drone with a 16M pixel camera flying at 4 m height. To detect plants and weeds, the YOLO model was trained with transfer learning from two available datasets. A preliminary analysis of the entire field showed that in the areas treated by the robot, the weed average density varied across the field from 6.8 to 9.1 weeds/m² (compared with 0.8 in the chemically treated area and 24.3 in the untreated area), the weed average density inside rows was 2.0-2.9 weeds / m (compared with 0 on the chemically treated area), and the emergence rate was 90-95%. The information about the robot's performance has high importance for the application of robotics for field tasks. With the help of the developed method, the performance can be assessed several times during the growth according to the robotic weeding frequency. When it’s used by farmers, they can know the field condition and efficiency of the robotic treatment all over the field. Farmers and researchers could develop optimal strategies for using the robot, such as seeding and weeding timing, robot settings, and plant and field parameters and geometry. The robot producers can have quantitative information from an actual working environment and improve the robots accordingly.

Keywords: agricultural robot, field robot, plant detection, robot performance

Procedia PDF Downloads 87

Authors: Angelis P. Barlampas

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The purpose of this study is to inform the reader, about the various applications of artificial intelligence (AI), in cardiac imaging. AI grows fast and its role is crucial in medical specialties, which use large amounts of digital data, that are very difficult or even impossible to be managed by human beings and especially doctors.Artificial intelligence (AI) refers to the ability of computers to mimic human cognitive function, performing tasks such as learning, problem-solving, and autonomous decision making based on digital data. Whereas AI describes the concept of using computers to mimic human cognitive tasks, machine learning (ML) describes the category of algorithms that enable most current applications described as AI. Some of the current applications of AI in cardiac imaging are the follows: Ultrasound: Automated segmentation of cardiac chambers across five common views and consequently quantify chamber volumes/mass, ascertain ejection fraction and determine longitudinal strain through speckle tracking. Determine the severity of mitral regurgitation (accuracy > 99% for every degree of severity). Identify myocardial infarction. Distinguish between Athlete’s heart and hypertrophic cardiomyopathy, as well as restrictive cardiomyopathy and constrictive pericarditis. Predict all-cause mortality. CT Reduce radiation doses. Calculate the calcium score. Diagnose coronary artery disease (CAD). Predict all-cause 5-year mortality. Predict major cardiovascular events in patients with suspected CAD. MRI Segment of cardiac structures and infarct tissue. Calculate cardiac mass and function parameters. Distinguish between patients with myocardial infarction and control subjects. It could potentially reduce costs since it would preclude the need for gadolinium-enhanced CMR. Predict 4-year survival in patients with pulmonary hypertension. Nuclear Imaging Classify normal and abnormal myocardium in CAD. Detect locations with abnormal myocardium. Predict cardiac death. ML was comparable to or better than two experienced readers in predicting the need for revascularization. AI emerge as a helpful tool in cardiac imaging and for the doctors who can not manage the overall increasing demand, in examinations such as ultrasound, computed tomography, MRI, or nuclear imaging studies.

Keywords: artificial intelligence, cardiac imaging, ultrasound, MRI, CT, nuclear medicine

Procedia PDF Downloads 78

Authors: Selin Guleroglu, Ilker Kahraman, E. Selahattin Umdu

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In today’s world, the building sector has a significant impact on primary energy consumption and CO₂ emissions. While new buildings must have high energy performance as indicated by the Energy Performance Directive in Buildings (EPBD), published by the European Union (EU), the energy performance of the existing buildings must also be enhanced with cost-efficient methods. Turkey has a high historical building density similar to south European countries, and the high energy consumption is the main contributor in the energy consumptioın of Turkey, which is rather higher than European counterparts. Historic buildings spread around Turkey for four main climate zones covering very similar climate characteristics to both the north and south European countries. The case study building is determined as the most common building type in Turkey. This study aims to investigate energy retrofit measures covering but not limited to passive and active measures to improve the energy performance of the historical buildings located in different climatic zones within the limits of preservation of the historical value of the building as a crucial constraint. Passive measures include wall, window, and roof construction elements, and active measures HVAC systems in retrofit scenarios. The proposed methodology can help to reach up to 30% energy saving based on primary energy consumption. DesignBuilder, an energy simulation tool, is used to determine the energy performance of buildings with suggested retrofit measures, and the Net Present Value (NPV) method is used for cost analysis of them. Finally, the most efficient energy retrofit measures for all buildings are determined by analyzing primary energy consumption and the cost performance of them. Results show that heat insulation, glazing type, and HVAC system has an important role in energy saving. Also, it found that these parameters have a different positive or negative effect on building energy consumption in different climate zones. For instance, low e glazing has a positive impact on the energy performance of the building in the first zone, while it has a negative effect on the building in the forth zone. Another important result is applying heat insulation has minimum impact on building energy performance compared to other zones.

Keywords: energy performance, climatic zones, historic building, energy retrofit measures, NPV

Procedia PDF Downloads 174

Authors: Maggie Hui

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Risk management is not a new concept; however, it is an uncharted area as applied to the translation process and translator training. Serving as one of the self-discovery activities in their practicum course, a two-cycle experiment was carried out with a class of 13 MA translation students with an attempt to explore their risk management while translating in a simulated setting that involves translator-client relations. To test the effects of the main variable of translators’ interaction with the simulated clients, the researcher employed control-group translators and two experiment groups (with Group A being the translator in Cycle 1 and the client in Cycle 2, and Group B on the client position in Cycle 1 and the translator position in Cycle 2). Experiment cycle 1 aims to explore if there would be any behavioral difference in risk management between translators with interaction with the simulated clients, i.e. experiment group A, and their counterparts without such interaction, i.e. control group. Design of Cycle 2 concerns the order of playing different roles of the translator and client in the experiment, and provides information to compare behavior of translators of the two experiment groups. Since this is process-oriented research, it is necessary to hypothesize what was happening in the translators’ minds. The researcher made use of a user-friendly screen-voice recording freeware to record subjects’ screen activities, including every word the translator typed and every change they made to the rendition, the websites they browsed and the reference tools they used, in addition to the verbalization of their thoughts throughout the process. The research observes the translation procedures subjects considered and finally adopted, and looks into the justifications for their procedures, in order to interpret their risk management. The qualitative and quantitative results of this study have some implications for translator training: (a) the experience of being a client seems to reinforce the translator’s risk aversion; (b) the use of role-playing simulation can empower students’ learning by enhancing their attitudinal or psycho-physiological competence, interpersonal competence and strategic competence; and (c) the screen-voice recordings serve as a helpful tool for learners to reflect on their rendition processes, i.e. what they performed satisfactorily and unsatisfactorily while translating and what they could do for improvement in future translation tasks.

Keywords: risk management, screen-voice recordings, simulated translator-client relations, translation pedagogy, translation process-oriented research

Procedia PDF Downloads 263

Authors: David W. Taylor, Fernando Lourenço, Carolyn Branston, Paul Tucker

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There are an increasing number of students at Universities in the United Kingdom engaging in entrepreneurship role-play to explore business start-up as a career alternative to employment. These role-play activities have been shown to have a positive influence on students’ entrepreneurial intentions. Universities also play a role in developing graduates’ awareness of social responsibility. However, social responsibility is often missing from these entrepreneurship role-plays. It is important that these role-play activities include the development of values that support social responsibility, in-line with those running hybrid, humane and sustainable enterprises, and not simply focus on profit. The Young Enterprise (YE) Start-Up programme is an example of a role-play activity that is gaining in popularity amongst United Kingdom Universities seeking ways to give students insight into a business start-up. A Post-92 University in the North-West of England has adapted the traditional YE Directorship roles (e.g., Marketing Director, Sales Director) by including a Corporate Social Responsibility (CSR) Director in all of the team-based YE Start-Up businesses. The aim for introducing this Directorship was to observe if such a role would help create a more socially responsible value-system within each company and in turn shape business decisions. This paper investigates role-play as a tool to help enterprise educators develop socially responsible attitudes and values in nascent entrepreneurs. A mixed qualitative methodology approach has been used, which includes interviews, role-play, and reflection, to help students develop positive value characteristics through the exploration of unethical and selfish behaviors. The initial findings indicate that role-play helped CSR Directors learn and gain insights into the importance of corporate social responsibility, influenced the values and actions of their YE Start-Ups, and increased the likelihood that if the participants were to launch a business post-graduation, that the intent would be for the business to be socially responsible. These findings help inform educators on how to develop socially responsible nascent entrepreneurs within a traditionally profit orientated business model.

Keywords: student entrepreneurship, young enterprise, social responsibility, role-play, values

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Authors: Abdul Basit Kiani, Maryam Kiani

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Online developers now have the tools necessary to create online apps that are not only reliable but also highly interactive, thanks to the introduction of JavaScript frameworks and APIs. The objective is to give a broad overview of the recent advances in the area. The fusion of machine learning (ML) and artificial intelligence (AI) has expanded the possibilities for web development. Modern websites now include chatbots, clever recommendation systems, and customization algorithms built in. In the rapidly evolving landscape of modern websites, it has become increasingly apparent that user engagement and personalization are key factors for success. To meet these demands, websites now incorporate a range of innovative technologies. One such technology is chatbots, which provide users with instant assistance and support, enhancing their overall browsing experience. These intelligent bots are capable of understanding natural language and can answer frequently asked questions, offer product recommendations, and even help with troubleshooting. Moreover, clever recommendation systems have emerged as a powerful tool on modern websites. By analyzing user behavior, preferences, and historical data, these systems can intelligently suggest relevant products, articles, or services tailored to each user's unique interests. This not only saves users valuable time but also increases the chances of conversions and customer satisfaction. Additionally, customization algorithms have revolutionized the way websites interact with users. By leveraging user preferences, browsing history, and demographic information, these algorithms can dynamically adjust the website's layout, content, and functionalities to suit individual user needs. This level of personalization enhances user engagement, boosts conversion rates, and ultimately leads to a more satisfying online experience. In summary, the integration of chatbots, clever recommendation systems, and customization algorithms into modern websites is transforming the way users interact with online platforms. These advanced technologies not only streamline user experiences but also contribute to increased customer satisfaction, improved conversions, and overall website success.

Keywords: Javascript, machine learning, artificial intelligence, web development

Procedia PDF Downloads 79

Authors: Goodness Onwuka, Khaled Abou-El-Hossein

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The increase in the demand for precision optics, coupled with the absence of much research output in the ultra high precision grinding of precision optics as compared to the ultrahigh precision diamond turning of optical metals has fostered the need for more research in the ultra high precision grinding of an optical lens. Furthermore, the increase in the stringent demands for nanometric surface finishes through lapping, polishing and grinding processes necessary for the use of borosilicate-crown glass in the automotive and optics industries has created the demand to effectively monitor the surface roughness during the production process. Acoustic emission phenomenon has been proven as useful monitoring technique in several manufacturing processes ranging from monitoring of bearing production to tool wear estimation. This paper introduces a rare and unique approach with the application of acoustic emission technique to monitor the surface roughness of borosilicate-crown glass during an ultra high precision grinding process. This research was carried out on a 4-axes Nanoform 250 ultrahigh precision lathe machine using an ultra high precision grinding spindle to machine the flat surface of the borosilicate-crown glass with the tip of the grinding wheel. A careful selection of parameters and design of experiment was implemented using Box-Behnken method to vary the wheel speed, feed rate and depth of cut at three levels with a 3-center point design. Furthermore, the average surface roughness was measured using Taylor Hobson PGI Dimension XL optical profilometer, and an acoustic emission data acquisition device from National Instruments was utilized to acquire the signals while the data acquisition codes were designed with National Instrument LabVIEW software for acquisition at a sampling rate of 2 million samples per second. The results show that the raw and root mean square amplitude values of the acoustic signals increased with a corresponding increase in the measured average surface roughness values for the different parameter combinations. Therefore, this research concludes that acoustic emission monitoring technique is a potential technique for monitoring the surface roughness in the ultra high precision grinding of borosilicate-crown glass.

Keywords: acoustic emission, borosilicate-crown glass, surface roughness, ultra high precision grinding

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Authors: Svenja Pieritz, Jakab Pilaszanovich

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Collaborative Problem Solving (CPS) is recognized as being one of the most important skills of the 21st century with having a potential impact on education, job selection, and collaborative systems design. Therefore, CPS has been adopted in several standardized tests, including the Programme for International Student Assessment (PISA) in 2015. A significant challenge of evaluating CPS is the underlying interplay of cognitive and social skills, which requires a more holistic assessment. However, the majority of the existing tests are using a questionnaire-based assessment, which oversimplifies this interplay and undermines ecological validity. Two major difficulties were identified: Firstly, the creation of a controllable, real-time environment allowing natural behaviors and communication between at least two people. Secondly, the development of an appropriate method to collect and synthesize both cognitive and social metrics of collaboration. This paper proposes a more holistic and automated approach to the assessment of CPS. To address these two difficulties, a multiplayer problem-solving game called Sea of Light was developed: An environment allowing students to deploy a variety of measurable collaborative strategies. This controlled environment enables researchers to monitor behavior through the analysis of game actions and chat. The according solution for the statistical model is a combined approach of Natural Language Processing (NLP) and Bayesian network analysis. Social exchanges via the in-game chat are analyzed through NLP and fed into the Bayesian network along with other game actions. This Bayesian network synthesizes evidence to track and update different subdimensions of CPS. Major findings focus on the correlations between the evidences collected through in- game actions, the participants’ chat features and the CPS self- evaluation metrics. These results give an indication of which game mechanics can best describe CPS evaluation. Overall, Sea of Light gives test administrators control over different problem-solving scenarios and difficulties while keeping the student engaged. It enables a more complete assessment based on complex, socio-cognitive information on actions and communication. This tool permits further investigations of the effects of group constellations and personality in collaborative problem-solving.

Keywords: bayesian network, collaborative problem solving, game-based assessment, natural language processing

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Authors: Stefan Andersson, Balram Panjwani, Bernd Wittgens, Jan Erik Olsen

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Polycyclic Aromatic hydrocarbons are organic compounds consisting of only hydrogen and carbon aromatic rings. PAH are neutral, non-polar molecules that are produced due to incomplete combustion of organic matter. These compounds are carcinogenic and interact with biological nucleophiles to inhibit the normal metabolic functions of the cells. Norways, the most important sources of PAH pollution is considered to be aluminum plants, the metallurgical industry, offshore oil activity, transport, and wood burning. Stricter governmental regulations regarding emissions to the outer and internal environment combined with increased awareness of the potential health effects have motivated Norwegian metal industries to increase their efforts to reduce emissions considerably. One of the objective of the ongoing industry and Norwegian research council supported "SCORE" project is to reduce potential PAH emissions from an off gas stream of a ferroalloy furnace through controlled combustion. In a dedicated combustion chamber. The sizing and configuration of the combustion chamber depends on the combined properties of the bulk gas stream and the properties of the PAH itself. In order to achieve efficient and complete combustion the residence time and minimum temperature need to be optimized. For this design approach reliable kinetic data of the individual PAH-species and/or groups thereof are necessary. However, kinetic data on the combustion of PAH are difficult to obtain and there is only a limited number of studies. The paper presents an evaluation of the kinetic data for some of the PAH obtained from literature. In the present study, the oxidation is modelled for pure PAH and also for PAH mixed with process gas. Using a perfectly stirred reactor modelling approach the oxidation is modelled including advanced reaction kinetics to study influence of residence time and temperature on the conversion of PAH to CO2 and water. A Chemical Reactor Network (CRN) approach is developed to understand the oxidation of PAH inside the combustion chamber. Chemical reactor network modeling has been found to be a valuable tool in the evaluation of oxidation behavior of PAH under various conditions.

Keywords: PAH, PSR, energy recovery, ferro alloy furnace

Procedia PDF Downloads 273

Authors: Denise Levy, Anna Lucia C. H. Villavicencio

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Food irradiation is a processing and preservation technique to eliminate insects and parasites and reduce disease-causing microorganisms. Moreover, the process helps to inhibit sprouting and delay ripening, extending fresh fruits and vegetables shelf-life. Nevertheless, most Brazilian consumers seem to misunderstand the difference between irradiated food and radioactive food and the general public has major concerns about the negative health effects and environmental contamination. Society´s judgment and decision making are directly linked to perceived benefits and risks. The web-based project entitled ‘Scientific information about food irradiation: Internet as a tool to approach science and society’ was created by the Nuclear and Energetic Research Institute (IPEN), in order to offer an interdisciplinary approach to science education, integrating economic, ethical, social and political aspects of food irradiation. This project takes into account that, misinformation and unfounded preconceived ideas impact heavily on the acceptance of irradiated food and purchase intention by the Brazilian consumer. Taking advantage of the potential value of the Internet to enhance communication and education among general public, a research study was carried out regarding the possibilities and trends of Information and Communication Technologies among the Brazilian population. The content includes concepts, definitions and Frequently Asked Questions (FAQ) about processes, safety, advantages, limitations and the possibilities of food irradiation, including health issues, as well as its impacts on the environment. The project counts on eight self-instructional interactive web courses, situating scientific content in relevant social contexts in order to encourage self-learning and further reflections. Communication is a must to improve public understanding of science. The use of information technology for quality scientific divulgation shall contribute greatly to provide information throughout the country, spreading information to as many people as possible, minimizing geographic distances and stimulating communication and development.

Keywords: food irradiation, multimedia learning tools, nuclear science, society and education

Procedia PDF Downloads 248

Authors: Awatif Habeeb Al-Shamare

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The number of social media users amongst special education teachers and parents of children with Down Syndrome (DS) is increasing annually. This is also the case in the Kingdom of Saudi Arabia (KSA). However, according to the best of the author’s knowledge, there are no qualitative studies which testify to the true nature of the interaction between teachers and parents when using social media, nor the role of social media in supporting and assisting parents and teachers with regards to the children’s educational needs in KSA. Therefore, this ongoing study aims to identify the role of social media in supporting parents and teachers of DS students, with a special emphasis on early intervention services in KSA. By bridging the knowledge gap on social media and special education in KSA and presenting socially relevant and applied information on the topic, this research provides a theoretical and practical base for the establishment of appropriate and effective programmes between the ministries of Information and Special Education in particular. A qualitative approach was selected because it was the most suitable approach for exploring the participants’ experiences, which could not be determined through scientific tests. Interviewing, chosen as the research instrument, allowed the researcher to obtain a detailed understanding of the topic linked to the study objectives. Initially, a pilot study was conducted at the Daycare Center in May 2016. Its aim was to examine and refine the methodology and assess whether the questions were understood with the potential for re-drafting them, if necessary. The main study consists of five teachers and five mothers with experience of using social media and with links to the Daycare Center. Thematic Analysis has been chosen for analysing the findings because it is a flexible method that allows themes to emerge from the data. Results of the current study are still in the initial stages, but the preliminary findings are as follows: (1) social media is an important tool in encouraging parents and teachers to access the necessary information and knowledge about, and experience in, early intervention services; (2) it acts as a support network for the parents; (3) it helps raise awareness about DS and the need for early intervention; (4) it can be used to put pressure on the government for an expansion in early intervention services, and finally (5) its use can be problematic in that parents and teachers face some difficulties and challenges when using the different platforms. It can be concluded that social media plays a significant role in the lives of teachers and parents with special needs children in KSA.

Keywords: down syndrome, early intervention services, social media, support parents and teachers

Procedia PDF Downloads 146

Authors: Man-Yun Liu, Emily Chia-Yu Su

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Alzheimer's disease (AD) is the public health crisis of the 21st century. AD is a degenerative brain disease and the most common cause of dementia, a costly disease on the healthcare system. Unfortunately, the cause of AD is poorly understood, furthermore; the treatments of AD so far can only alleviate symptoms rather cure or stop the progress of the disease. Currently, there are several ways to diagnose AD; medical imaging can be used to distinguish between AD, other dementias, and early onset AD, and cerebrospinal fluid (CSF). Compared with other diagnostic tools, blood (plasma) test has advantages as an approach to population-based disease screening because it is simpler, less invasive also cost effective. In our study, we used blood biomarkers dataset of The Alzheimer’s disease Neuroimaging Initiative (ADNI) which was funded by National Institutes of Health (NIH) to do data analysis and develop a prediction model. We used independent analysis of datasets to identify plasma protein biomarkers predicting early onset AD. Firstly, to compare the basic demographic statistics between the cohorts, we used SAS Enterprise Guide to do data preprocessing and statistical analysis. Secondly, we used logistic regression, neural network, decision tree to validate biomarkers by SAS Enterprise Miner. This study generated data from ADNI, contained 146 blood biomarkers from 566 participants. Participants include cognitive normal (healthy), mild cognitive impairment (MCI), and patient suffered Alzheimer’s disease (AD). Participants’ samples were separated into two groups, healthy and MCI, healthy and AD, respectively. We used the two groups to compare important biomarkers of AD and MCI. In preprocessing, we used a t-test to filter 41/47 features between the two groups (healthy and AD, healthy and MCI) before using machine learning algorithms. Then we have built model with 4 machine learning methods, the best AUC of two groups separately are 0.991/0.709. We want to stress the importance that the simple, less invasive, common blood (plasma) test may also early diagnose AD. As our opinion, the result will provide evidence that blood-based biomarkers might be an alternative diagnostics tool before further examination with CSF and medical imaging. A comprehensive study on the differences in blood-based biomarkers between AD patients and healthy subjects is warranted. Early detection of AD progression will allow physicians the opportunity for early intervention and treatment.

Keywords: Alzheimer's disease, blood-based biomarkers, diagnostics, early detection, machine learning

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Authors: Paul Shize Li, Frank Alber

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A fundamental task of clinical genomics is to unravel the functions of genes and their associations with disorders. Although experimental biology has made efforts to discover and elucidate the molecular mechanisms of individual genes in the past decades, still about 40% of human genes have unknown functions, not to mention the diseases they may be related to. For those biologists who are interested in a particular gene with unknown functions, a powerful computational method tailored for inferring the functions and disease relevance of uncharacterized genes is strongly needed. Studies have shown that genes strongly linked to each other in multiple biological networks are more likely to have similar functions. This indicates that the densely connected subgraphs in multiple biological networks are useful in the functional and phenotypic annotation of uncharacterized genes. Therefore, in this work, we have developed an integrative network approach to identify the frequent local clusters, which are defined as those densely connected subgraphs that frequently occur in multiple biological networks and consist of the query gene that has few or no disease or function annotations. This is a local clustering algorithm that models multiple biological networks sharing the same gene set as a three-dimensional matrix, the so-called tensor, and employs the tensor-based optimization method to efficiently find the frequent local clusters. Specifically, massive public gene expression data sets that comprehensively cover dynamic, physiological, and environmental conditions are used to generate hundreds of gene co-expression networks. By integrating these gene co-expression networks, for a given uncharacterized gene that is of biologist’s interest, the proposed method can be applied to identify the frequent local clusters that consist of this uncharacterized gene. Finally, those frequent local clusters are used for function and disease annotation of this uncharacterized gene. This local tensor clustering algorithm outperformed the competing tensor-based algorithm in both module discovery and running time. We also demonstrated the use of the proposed method on real data of hundreds of gene co-expression data and showed that it can comprehensively characterize the query gene. Therefore, this study provides a new tool for annotating the uncharacterized genes and has great potential to assist clinical genomic diagnostics.

Keywords: local tensor clustering, query gene, gene co-expression network, gene annotation

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Authors: Zena F. Mushtaq, Iqbal M. Abbas

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Background: Diabetes mellitus during pregnancy is one of the major medical and social problems with increasing prevalence in last decades and may lead to more vulnerable to dental problems and increased risk for periodontal diseases. Objectives: To assess oral hygiene behaviors among pregnant women with diabetes who attended primary health care centers and find out the relationship between oral hygiene behaviors and studied variables. Methodology: A cross sectional design was conducted from 7 July to 30 September 2014 on non probability (convenient sample) of 150 pregnant women with diabetes was selected from twelve Primary Health Care Centers at Baghdad city. Questionnaire format is tool for data collection which had designed and consisted of three main parts including: socio demographic, reproductive characteristics and items of oral hygiene behaviors among pregnant women with diabetes. Reliability of the questionnaire was determined through internal consistency of correlation coefficient (R= 0.940) and validity of content was determined through reviewing it by (12) experts in different specialties and was determined through pilot study. Descriptive and inferential statistics were used to analyze collected data. Result: Result of study revealed that (35.3%) of study sample was (35-39) years old with mean and SD is (X & SD = 33.57 ± 5.54) years, and (34.7%) of the study sample was graduated from primary school and less, half of the study sample was government employment and self employed, (42.7%) of the study sample had moderate socioeconomic status, the highest percentage (70.0%) of the study sample was nonsmokers, The result indicates that oral hygiene behaviors have moderate mean score in all items. There are no statistical significant association between oral hygiene domain and studied variables. Conclusions: All items related to health behavior concerning oral hygiene is in moderate mean of score, which may expose pregnant women with diabetes to high risk of periodontal diseases. Recommendations: Dental care provider should perform a dental examination at least every three months for each pregnant woman with diabetes, explanation of the effect of DM on periodontal health, oral hygiene instruction, oral prophylaxis, professional cleaning and treatment of periodontal diseases(scaling and root planing) when needed.

Keywords: diabetes, health behavior, pregnant women, oral hygiene

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Authors: Athanasios A. Gavrilidis, Mihai R. Nita, Larissa N. Stoia, Diana A. Onose

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Contemporary global environmental challenges must be primarily addressed at local levels. Cities are under continuous pressure as they must ensure high quality of life levels for their citizens and at the same time to adapt and address specific environmental issues. Innovative solutions using natural features or mimicking natural systems are endorsed by the scientific community as efficient approaches for both mitigating climate change effects and the decrease of environmental quality and for maintaining high standards of living for urban dwellers. The aim of this study was to assess whether Romanian cities’ authorities are considering nature-based innovation as solutions for their planning, management, and environmental issues. Data were gathered by applying 140 questionnaires to urban authorities throughout the country. The questionnaire was designed for assessinglocal policy makers’ perspective over the efficiency of nature-based innovations as a tool to address specific challenges. It also focused on extracting data about financing sources and challenges they must overcome for adopting nature-based approaches. The gather results from the municipalities participating in our study were statistically processed, and they revealed that Romanian city managers acknowledge the benefits of nature-based innovations, but investments in this sector are not on top of their priorities. More than 90% of the selected cities have agreed that in the last 10 years, their major concern was to expand the grey infrastructure (roads and public amenities) using traditional approaches. When asked how they would react if faced with different socio-economic and environmental challenges, local urban managers indicated investments nature-based solutions as a priority only in case of biodiversity loss and extreme weather, while for other 14 proposed scenarios, they would embrace the business-as-usual approach. Our study indicates that while new concepts of sustainable urban planning emerge within the scientific community, local authorities need more time to understand and implement them. Without the proper knowledge, personnel, policies, or dedicated budgets, local administrators will not embrace nature-based innovations as solutions for their challenges.

Keywords: nature based innovations, perception analysis, policy making, urban planning

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Authors: Iyad Al-Attar

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Air filters are widely used in gas turbines applications to ensure that the large mass (500kg/s) of clean air reach the compressor. The continuous demand of high availability and reliability has highlighted the critical role of air filter performance in providing enhanced air quality. In addition to being challenged with different environments [tropical, coastal, hot], gas turbines confront wide array of atmospheric contaminants with various concentrations and particle size distributions that would lead to performance degradation and components deterioration. Therefore, the role of air filters is of a paramount importance since fouled compressor can reduce power output and availability of the gas turbine to over 70 % throughout operation. Consequently, accurate filter performance prediction is critical tool in their selection considering their role in minimizing the economic impact of outages. In fact, actual performance of Efficient Particulate Air [EPA] filters used in gas turbine tend to deviate from the performance predicted by laboratory results. This experimental work investigates the initial pressure drop and fractional efficiency curves of full-scale pleated V-shaped EPA filters used globally in gas turbine. The investigation involved examining the effect of different operational conditions such as flow rates [500 to 5000 m3/h] and design parameters such as pleat count [28, 30, 32 and 34 pleats per 100mm]. This experimental work has highlighted the underlying reasons behind the reduction in filter permeability due to the increase of flow rates and pleat density. The reasons, which led to surface area losses of filtration media, are due to one or combination of the following effects: pleat-crowding, deflection of the entire pleated panel, pleat distortion at the corner of the pleat and/or filtration medium compression. This paper also demonstrates that the effect of increasing the flow rate has more pronounced effect on filter performance compared to pleating density. This experimental work suggests that a valid comparison of the pleat densities should be based on the effective surface area, namely, the area that participates in the filtration process, and not the total surface area the pleat density provides. Throughout this study, optimal pleat count that satisfies both initial pressure drop and efficiency requirements may not have necessarily existed.

Keywords: filter efficiency, EPA Filters, pressure drop, permeability

Procedia PDF Downloads 239

Authors: Sadaf Rafiq, Muhammad Waqas, Shakeel Ahmad Khan, Nisar Ahmad

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Everyday life information seeking (ELIS) is considered as the mastery of life. It plays an important role in daily problem solving activities. Female students living in university hostels need variety of information to fulfil their everyday information needs. To find accurate and timely information is really challenging for females students who move from rural areas for educational purposes. These challenges involve culture differences, stress, financial issues, homesickness, diet needs and change in sleeping and eating habits. These complications create numerous problems for female students to adjust themselves in new and unfamiliar environment. Although the Internet has increased the ease of seeking everyday life information to survive successfully but there is still uncertainty to fully rely on the quality of information available on the web. Pakistan is an underdeveloped country where limited budget is allocated for educational institutions to enable them in developing well established hostels for their students. Female students who pursue for higher education has to stay at hostels for years to obtain education goals. It really becomes very difficult for them to spend life in hostels if they are not properly facilitated with relevant information sources to acquire everyday life information. The proposed study attempts to investigate the everyday life information seeking behavior of female students who are living in university and private hostels of Lahore. It investigates the various sources of information used by female students. It also identifies the problems faced by the female students in accessing everyday life information. The results of this study will be helpful for university management to understand their information need and provide required information sources which are essential for them to spend a comfortable, successful and peaceful life in hostels and achieve their educational goals. To achieve the objectives of the study, we will use quantitative research approach by using questionnaire as a data collection tool. The population of this study will be the university students living in public and private hostels of Lahore, Pakistan. This study will increase the understanding of everyday life information seeking behavior of female students living in hostels. Results of the study will be helpful for hostel administrations to better understand the students’ everyday life information needs and provide high quality of information services and living environment.

Keywords: everyday, information seeking, hostel, female

Procedia PDF Downloads 151

Authors: Bhawna Shivan

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Indian monuments have been spoken of as for variety, extent, completeness and beauty unsurpassed perhaps unequaled in world. India’s monumental heritage is a part and parcel of India today. The underlying issue with the monumental heritage in contemporary times is that these monuments suffered many times with various degrees of threats/ pressures which hampered their beauty. In the current situation, the urbanization policies for sustainable development and tourism management pay no attention to the basic point of conservation and protection of these cultural heritages rather they focus more on profit earned from these sites. Many times rich heritage is found balancing between conflicting pressures of conservation of heritage elements with sustainability and local economic development. There is a need of a new attitude to India’s independent and democratic ideology. The paper will enquire about the historical perspective by analyzing and understanding the importance of Mughal Architecture while focusing on Humayun Tomb while assessing the value and sentiment people attach to these monuments. It will also put the focus on the future of these monuments in the era of globalization and urbanization. The role of public and private authorities for conservation and sustainable development of these monuments. As well as assessing other facilities like toilets, parking, eatery joint, Museum with Display of structural representation and display of books, and a mobile shop. The research will be helpful in assessing the importance of heritage buildings whether they are a tool of enhancing ‘Tourism Industry’ for Central and State Government or really there is still some future of these monuments. Can we still consider these heritage sites as the integral part of our society in this urbanized world? The study will also analyze the attitude of the central and state government towards a building when it declared as a ‘World Heritage Site’. The study will also examine how the Youth and other aged generations append their sentimental values towards them, say (what is their purpose of coming to a heritage site, what makes them coming here, how they view this particular monument) Apart from this, probing the factors such as rapid growth of cities and its population, increasing value of urban land and effect of globalization on urban growth pattern that are capable of producing a variety of threats and pressures on any monument for instance Humayun Tomb.

Keywords: globalization, monuments, tourism, urban heritage

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Authors: H. S. Niroshani, W. M. Ediri Arachchi, R. Tudugala, U. J. M. A. L. Jayasinghe, U. M. U. J. Jayasekara, P. B. Hewavithana

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Mammography is used as a screening tool for early diagnosis of breast cancer. It is also useful in refining the diagnosis of breast cancer either by assessment or work up after a suspicious area in the breast has been detected. In order to detect breast cancer accurately and at the earliest possible stage, the image must have an optimum contrast to reveal mass densities and spiculated fibrous structures radiating from them. In addition, the spatial resolution must be adequate to reveal the suffusion of micro calcifications and their shape. The above factors can be optimized by implementing an effective QA programme to enhance the accurate diagnosis of mammographic imaging. Therefore, the radiographer’s knowledge on QA is greatly instrumental in routine mammographic practice. The aim of this study was to assess the radiographer’s knowledge on Quality Assurance and Quality Control programmes in relation to mammographic procedures. A cross-sectional study was carried out among all radiographers working in each mammography setting in Sri Lanka. Pre-tested, anonymous self-administered questionnaires were circulated among the study population and duly filled questionnaires returned within a period of three months were taken into the account. The data on demographical information, knowledge on QA programme and associated QC tests, overall knowledge on QA and QC programmes were obtained. Data analysis was performed using IBM SPSS statistical software (version 20.0). The total response rate was 59.6% and the average knowledge score was 54.15±11.29 SD out of 100. Knowledge was compared on the basis of education level, special training of mammography, and the years of working experience in a mammographic setting of the individuals. Out of 31 subjects, 64.5% (n=20) were graduate radiographers and 35.5% (n=11) were diploma holders while 83.9% (n=26) of radiographers have been specially trained for mammography and 16.1% (n=5) have not been attended for any special training for mammography. It is also noted that 58.1% (n=18) of individuals possessed their experience of less than one year and rest 41.9% (n=13) of them were greater than that. Further, the results found that there is a significant difference (P < 0.05) in the knowledge of QA and overall knowledge on QA and QC programme in the categories of education level and working experience. Also, results imply that there was a significant difference (P < 0.05) in the knowledge of QC test among the groups of trained and non-trained radiographers. This study reveals that education level, working experience and the training obtained particularly in the field of mammography have a significant impact on their knowledge on QA and QC in mammography.

Keywords: knowledge, mammography, quality assurance, quality control

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Authors: Daria Lozovskaia

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This paper is focused on the news coverage of public opinion polls about Russian full-scale invasion of Ukraine in Russian state-controlled media. After the announcement of the start of the so-called “Special Military Operation” on February 24, 2022, the number of publications of the results of public opinion polls increased many times over, and the poll numbers began to be discussed on social media and in the Kremlin’s official informational agenda. Headlines like "72 Percent of Russian Citizens Support the Operation " or "Russians Believe in Victory in the Special Military Operation" have become prominent parts of Russian state propaganda news stories and newspapers. At the same time, public opinion in Russia, as a concept and model, differs from the generally accepted democratic concept and has its own specifics. As a result, public opinion polls and their results, especially after February 24, have a number of features in the form of the dominance of the discourse of political elites in the media, which leads to a decrease in public awareness, the prevalence of the effect of joining the majority and a high number of non-responses due to fear of reprisals. The aim of this study was to determine the role of public opinion polls in the system of Russian war propaganda in Ukraine. For this purpose, were selected publications of the Russian media, the agenda of which corresponds to the official information policy of the Russian authorities. First, using frame analysis for the categories "Explicit trust", "Implicit trust", "Implicit distrust" and "Explicit distrust", provided by Irina Dusakova, the broadcast level of trust in the data of public opinion polls was determined. The results of this phase of the study showed that the Russian media broadcast an absolute level of confidence in public opinion polls regarding support for the war in Ukraine. The second stage of the study was the content analysis of publications. The categories of this analysis were derived from Anna Morelli's 10 Principles of Military Propaganda and Haavard Koppang's Definition of Propaganda to determine the purposes of the use of public opinion polls by Russian propaganda. The results of the study not only confirmed the widespread hypothesis that public opinion polls in Russia are used as a tool of state propaganda, but also showed that their purpose is to demonstrate the consolidation of society in support of the war and President Vladimir Putin.

Keywords: propaganda, public opinion, public opinion polls, Russian studies

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Authors: Yelin Zhao, Xinxiu Li, Martin Smelik, Oleg Sysoev, Firoj Mahmud, Dina Mansour Aly, Mikael Benson

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Background: Early diagnosis of pancreatic cancer is clinically challenging due to vague, or no symptoms, and lack of biomarkers. Polygenic risk score (PRS) scores may provide a valuable tool to assess increased or decreased risk of PC. This study aimed to develop such PRS by filtering genetic variants identified by GWAS using transcriptional programs identified by single-cell RNA sequencing (scRNA-seq). Methods: ScRNA-seq data from 24 pancreatic ductal adenocarcinoma (PDAC) tumor samples and 11 normal pancreases were analyzed to identify differentially expressed genes (DEGs) in in tumor and microenvironment cell types compared to healthy tissues. Pathway analysis showed that the DEGs were enriched for hundreds of significant pathways. These were clustered into 40 “programs” based on gene similarity, using the Jaccard index. Published genetic variants associated with PDAC were mapped to each program to generate program PRSs (pPRSs). These pPRSs, along with five previously published PRSs (PGS000083, PGS000725, PGS000663, PGS000159, and PGS002264), were evaluated in a European-origin population from the UK Biobank, consisting of 1,310 PDAC participants and 407,473 non-pancreatic cancer participants. Stepwise Cox regression analysis was performed to determine associations between pPRSs with the development of PC, with adjustments of sex and principal components of genetic ancestry. Results: The PDAC genetic variants were mapped to 23 programs and were used to generate pPRSs for these programs. Four distinct pPRSs (P1, P6, P11, and P16) and two published PRSs (PGS000663 and PGS002264) were significantly associated with an increased risk of developing PC. Among these, P6 exhibited the greatest hazard ratio (adjusted HR[95% CI] = 1.67[1.14-2.45], p = 0.008). In contrast, P10 and P4 were associated with lower risk of developing PC (adjusted HR[95% CI] = 0.58[0.42-0.81], p = 0.001, and adjusted HR[95% CI] = 0.75[0.59-0.96], p = 0.019). By comparison, two of the five published PRS exhibited an association with PDAC onset with HR (PGS000663: adjusted HR[95% CI] = 1.24[1.14-1.35], p < 0.001 and PGS002264: adjusted HR[95% CI] = 1.14[1.07-1.22], p < 0.001). Conclusion: Compared to published PRSs, scRNA-seq-based pPRSs may be used not only to assess increased but also decreased risk of PDAC.

Keywords: cox regression, pancreatic cancer, polygenic risk score, scRNA-seq, UK biobank

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Authors: Alica Höpken, Hergen Pargmann

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The resource-efficient planning of the complex production planning processes in the meat industry and the reduction of food waste is a permanent challenge. The complexity of the production planning process occurs in every part of the supply chain, from agriculture to the end consumer. It arises from long and uncertain planning phases. Uncertainties such as stochastic yields, fluctuations in demand, and resource variability are part of this process. In the meat industry, waste mainly relates to incorrect storage, technical causes in production, or overproduction. The high amount of food waste along the complex supply chain in the meat industry could not be reduced by simple solutions until now. Therefore, resource-efficient production planning by conventional methods is currently only partially feasible. The realization of intelligent, automated production planning is basically possible through the application of machine learning algorithms, such as those of reinforcement learning. By applying the adapted design thinking method, machine learning methods (especially reinforcement learning algorithms) are used for the complex production planning process in the meat industry. This method represents a concretization to the application area. A resource-efficient production planning process is made available by adapting the design thinking method. In addition, the complex processes can be planned efficiently by using this method, since this standardized approach offers new possibilities in order to challenge the complexity and the high time consumption. It represents a tool to support the efficient production planning in the meat industry. This paper shows an elegant adaption of the design thinking method to apply the reinforcement learning method for a resource-efficient production planning process in the meat industry. Following, the steps that are necessary to introduce machine learning algorithms into the production planning of the food industry are determined. This is achieved based on a case study which is part of the research project ”REIF - Resource Efficient, Economic and Intelligent Food Chain” supported by the German Federal Ministry for Economic Affairs and Climate Action of Germany and the German Aerospace Center. Through this structured approach, significantly better planning results are achieved, which would be too complex or very time consuming using conventional methods.

Keywords: change management, design thinking method, machine learning, meat industry, reinforcement learning, resource-efficient production planning

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Authors: Shoaib Rasool

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Migration trends in rural areas of Gujrat are increasing day by day among illiterate people as they consider it as a source of attraction and charm of destination. It affects the life standard both positive and negative way to their families left behind in the context of poverty, socio-economic status and life standards. It also promotes material items and as well as social indicators of living, housing conditions, schooling of their children’s, health seeking behavior and to some extent their family environment. The nature of the present study is to analyze socio-economic conditions regarding life standard of emigrant families left behind in rural areas of Gujrat district, Pakistan. A survey design was used on 150 families selected from rural areas of Gujrat districts through purposive sampling technique. A well-structured questionnaire was administered by the researcher to explore the nature of the study and for further data collection process. The measurement tool was pretested on 20 families to check the workability and reliability before the actual data collection. Statistical tests were applied to draw results and conclusion. The preliminary findings of the study show that emigration has left deep social-economic impacts on life standards of rural families left behind in Gujrat. They improved their life status and living standard through remittances. Emigration is one of the major sources of development of economy of household and it also alleviate poverty at house household level as well as community and country level. The rationale behind migration varies individually and geographically. There are popular considered attractions in Pakistan includes securing high status, improvement in health condition, coping other, getting married then to acquire nationality, using the unfair means, opting educational visas etc. Emigrants are not only sending remittances but also returning with newly acquired skills and valuable knowledge to their country of origin because emigrants learn new methods of living and working. There are also women migrants who experience social downward mobility by engaging in jobs that are beneath their educational qualifications.

Keywords: emigration, life standard, families, left behind, rural area, Gujrat

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Authors: Roberto Rosenhaim, Marcos Antonio Crus Moreira, Robson da Cunha, Gerson Gomes Cunha

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This work provides details on the wind speed behavior within cities of Arraial do Cabo and São Pedro da Aldeia located in the Lakes Region of the State of Rio de Janeiro, Brazil. This region has one of the best potentials for wind power generation. In interurban layer, wind conditions are very complex and depend on physical geography, size and orientation of buildings and constructions around, population density, and land use. In the same context, the fundamental surface parameter that governs the production of flow turbulence in urban canyons is the surface roughness. Such factors can influence the potential for power generation from the wind within the cities. Moreover, the use of wind on a small scale is not fully utilized due to complexity of wind flow measurement inside the cities. It is difficult to accurately predict this type of resource. This study demonstrates how fuzzy logic can facilitate the assessment of the complexity of the wind potential inside the cities. It presents a decision support tool and its ability to deal with inaccurate information using linguistic variables created by the heuristic method. It relies on the already published studies about the variables that influence the wind speed in the urban environment. These variables were turned into the verbal expressions that are used in computer system, which facilitated the establishment of rules for fuzzy inference and integration with an application for smartphones used in the research. In the first part of the study, challenges of the sustainable development which are described are followed by incentive policies to the use of renewable energy in Brazil. The next chapter follows the study area characteristics and the concepts of fuzzy logic. Data were collected in field experiment by using qualitative and quantitative methods for assessment. As a result, a map of the various points is presented within the cities studied with its wind viability evaluated by a system of decision support using the method multivariate classification based on fuzzy logic.

Keywords: behavior of winds, wind power, fuzzy logic, sustainable development

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Authors: Keshav Prasad Kandel, Balaram Khadka, Karan Bhatta, Basu Dev Ghimire

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Earthquakes still exist as a threating disaster. Being able to predict earthquakes will certainly help prevent substantial loss of life and property. Perhaps, Very Low Frequency/Low Frequency (VLF/LF) signal band (3-30 kHz), which is effectively reflected from D-layer of ionosphere, can be established as a tool to predict earthquake. On May 20 and May 29, 2012, earthquakes of magnitude 6.1 and 5.8 respectively struck Emilia-Romagna of Italy. A year back, on August 24, 2016, an earthquake of magnitude 6.2 struck Central Italy (42.7060 N and 13.2230 E) at 1:36 UT. We present the results obtained from the US Navy VLF Transmitter’s NSY signal of 45.9 kHz transmitted from Niscemi, in the province of Sicily, Italy and received at the Kiel Longwave Monitor, Germany for 2012 and 2016. We analyzed the terminator times, their individual differences and nighttime fluctuation counts. We also analyzed trends, dispersion and nighttime fluctuation which gave us a possible precursors to these earthquakes. Since perturbations in VLF amplitude could also be due to various other factors like lightning, geomagnetic activities (storms, auroras etc.) and solar activities (flares, UV flux, etc.), we filtered the possible perturbations due to these agents to guarantee that the perturbations seen in VLF/LF amplitudes were as a precursor to Earthquakes. As our TRGCP path is North-south, the sunrise and sunset time in transmitter and receiver places matches making pathway for VLF/LF smoother and therefore hoping to obtain more natural data. To our surprise, we found many clear anomalies (as precursors) in terminator times 5 days to 16 days before the earthquakes. Moreover, using night time fluctuation method, we found clear anomalies 5 days to 13 days prior to main earthquakes. This exactly correlates with the findings of previous authors that ionospheric perturbations are seen few days to one month before the seismic activity. In addition to this, we were amazed to observe unexpected decrease of dispersion on certain anomalies where it was supposed to increase, thereby not supporting our finding to some extent. To resolve this problem, we devised a new parameter called dispersion nighttime (dispersion). On analyzing, this parameter decreases significantly on days of nighttime anomalies thereby supporting our precursors to much extent.

Keywords: D-layer, TRGCP (Transmitter Receiver Great Circle Path), terminator times, VLF/LF

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Authors: Valentina Manna, Oscar Pisanti

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The term sibling has been adopted by Italian brothers and sisters of people with disabilities, to define themselves as a group with shared features. This choice is due to the importance of underlying the centrality of what being a brother/sister means to these people because of and beyond the disability. Being a sibling offers great opportunities to develop empathy and relational skills but it may also amplify the typical dynamics of fraternal relationships dealing with envy, rivalry and concern. This outlines a condition of potential developmental risk for the non-disabled sibling, being at the same time a great resource for the child with special needs, as actor of an intimate relationship usually lasting after that one with parents. However, young siblings are often unheeded in their needs for comprehension of disability and not considered as persons requiring attention themselves. Moreover, scholars have scarcely undertaken an exploration of siblings’ perspective as competent contributors for producing knowledge useful to the benefit of families with special needs children. This contribution describes a preventive intervention for young siblings (6 – 16 years) of children with Down syndrome, by means of a psychodynamic-oriented group where participants could communicate, explore and share their emotional experiences as siblings. Based on a participatory approach, the program represents an action-research project, involving siblings as key experts for our understanding of siblings’ lives. The initiative used social media and video technologies to rise children’s voice: as a final product, participants were involved in the realization of a video campaign –which they defined ‘a difficult advertising’– built on the insights generated by the program and addressed to other siblings to help them facing and recognizing resources and difficulties related to their status. The final video campaign realized by the participants summarizes the main themes emerged during the intervention; as revealed by a thematic analysis, they are related to the difficulty in feeling to have a personal identity, to face disability as a form of ‘untought known’ and to integrate ambivalent emotions. In conclusion, the group device revealed its efficacy as a preventive tool: it allowed participants to deeply reflect on their own experiences and to communicate them for the first time in a verbal and mentalized form.

Keywords: down syndrome, group, siblings, prevention

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Authors: Andleeb Zahra, Itrat Rubab, Sumaira Malik, Amina Khan, Muhammad Jawad Khan, M. Qaiser Fatmi

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Oral squamous cell carcinoma (OSCC) is one of the most common cancers worldwide. Recent studies have highlighted the role of miRNA in disease pathology, indicating its potential use in an early diagnostic tool. miRNAs are small, double stranded, non-coding RNAs that regulate gene expression by deregulating mRNAs. miRNAs play important roles in modifying various cellular processes such as cell growth, differentiation, apoptosis, and immune response. Dis-regulated expression of miRNAs is known to affect the cell growth, and this may function as tumor suppressors or oncogenes in various cancers. Objectives: The main objectives of this study were to characterize the extracellular miRNAs involved in oral cancer (OC) to assist early detection of cancer as well as to propose a list of genes that can potentially be used as biomarkers of OC. We used gene expression data by microarrays already available in literature. Materials and Methods: In the first step, a total of 318 miRNAs involved in oral carcinoma were shortlisted followed by the prediction of their target genes. Simultaneously, the differentially expressed genes (DEGs) of oral carcinoma from all experiments were identified. The common genes between lists of DEGs of OC based on experimentally proven data and target genes of each miRNA were identified. These common genes are the targets of specific miRNA, which is involved in OC. Finally, a list of genes was generated which may be used as biomarker of OC. Results and Conclusion: In results, we included some of pathways in cancer to show the change in gene expression under the control of specific miRNA. Ingenuity pathway analysis (IPA) provided a list of major biomarkers like CDH2, CDK7 and functional enrichment analysis identified the role of miRNA in major pathways like cell adhesion molecules pathway affected by cancer. We observed that at least 25 genes are regulated by maximum number of miRNAs, and thereby, they can be used as biomarkers of OC. To better understand the role of miRNA with respect to their target genes further experiments are required, and our study provides a platform to better understand the miRNA-OC relationship at genomics level.

Keywords: biomarkers, gene expression, miRNA, oral carcinoma

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Authors: Chahrazed Salhi, Ayoub Zeroual, Yasmina Hamitouche

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Soil water erosion poses a significant threat to the watersheds in Algeria today. The degradation of storage capacity in large dams over the past two decades, primarily due to erosion, necessitates a comprehensive understanding of the factors that contribute to soil erosion. The Isser watershed, located in the Northwestern region of Algeria, faces additional challenges such as recurrent droughts and the presence of delicate marl and clay outcrops, which amplify its susceptibility to water erosion. This study aims to employ advanced techniques such as Geographic Information Systems (GIS) and Remote Sensing (RS), in conjunction with the Canonical Correlation Analysis (CCA) method and Soil Water Assessment Tool (SWAT) model, to predict specific erosion patterns and analyze the key factors influencing erosion in the Isser basin. To accomplish this, an array of data sources including rainfall, climatic, hydrometric, land use, soil, digital elevation, and satellite data were utilized. The application of the SWAT model to the Isser basin yielded an average annual soil loss of approximately 16 t/ha/year. Particularly high erosion rates, exceeding 12 T/ha/year, were observed in the central and southern parts of the basin, encompassing 41% of the total basin area. Through Canonical Correlation Analysis, it was determined that vegetation cover and topography exerted the most substantial influence on erosion. Consequently, the study identified significant and spatially heterogeneous erosion throughout the study area. The impact of land topography on soil loss was found to be directly proportional, while vegetation cover exhibited an inverse proportional relationship. Modeling specific erosion for the Ladrat dam sub-basin estimated a rate of around 39 T/ha/year, thus accounting for the recorded capacity loss of 17.80% compared to the bathymetric survey conducted in 2019. The findings of this research provide valuable decision-support tools for soil conservation managers, empowering them to make informed decisions regarding soil conservation measures.

Keywords: Isser watershed, RS, CCA, SWAT, vegetation cover, topography

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Authors: Komal Ghafoor, Tauqir Ahmad, Murtaza Hanif, Hira Zaheer

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Assistive technology has been developed to support visually impaired people in their social interactions. Conversation assistive technology is designed to enhance communication skills, facilitate social interaction, and improve the quality of life of visually impaired individuals. This technology includes speech recognition, text-to-speech features, and other communication devices that enable users to communicate with others in real time. The technology uses natural language processing and machine learning algorithms to analyze spoken language and provide appropriate responses. It also includes features such as voice commands and audio feedback to provide users with a more immersive experience. These technologies have been shown to increase the confidence and independence of visually impaired individuals in social situations and have the potential to improve their social skills and relationships with others. Overall, conversation-assistive technology is a promising tool for empowering visually impaired people and improving their social interactions. One of the key benefits of conversation-assistive technology is that it allows visually impaired individuals to overcome communication barriers that they may face in social situations. It can help them to communicate more effectively with friends, family, and colleagues, as well as strangers in public spaces. By providing a more seamless and natural way to communicate, this technology can help to reduce feelings of isolation and improve overall quality of life. The main objective of this research is to give blind users the capability to move around in unfamiliar environments through a user-friendly device by face, object, and activity recognition system. This model evaluates the accuracy of activity recognition. This device captures the front view of the blind, detects the objects, recognizes the activities, and answers the blind query. It is implemented using the front view of the camera. The local dataset is collected that includes different 1st-person human activities. The results obtained are the identification of the activities that the VGG-16 model was trained on, where Hugging, Shaking Hands, Talking, Walking, Waving video, etc.

Keywords: dataset, visually impaired person, natural language process, human activity recognition

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Authors: Angélique Laurent, Marie-Josée Letarte, Jean-Pascal Lemelin, Marie-France Morin

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This study aims at exploring teacher-child interactions within learning contexts in public prekindergartens of the province of Québec (Canada). It is based on previous research showing that teacher-child interactions in preschools have direct and determining effects on the quality of early childhood education and could directly or indirectly influence child development. However, throughout a typical preschool day, children experience different learning contexts to promote their learning opportunities. Depending on these specific contexts, teacher-child interactions could vary, for example, between free play and shared book reading. Indeed, some studies have found that teacher-directed or child-directed contexts might lead to significant variations in teacher-child interactions. This study drew upon both the bioecological and the Teaching Through Interactions frameworks. It was conducted through a descriptive and correlational design. Fifteen teachers were recruited to participate in the study. At Time 1 in October, they completed a diary to report the learning contexts they proposed in their classroom during a typical week. At Time 2, seven months later (May), they were videotaped three times in the morning (two weeks’ time between each recording) during a typical morning class. The quality of teacher-child interactions was then coded with the Classroom Assessment Scoring System (CLASS) through the contexts identified. This tool measures three main domains of interactions: emotional support, classroom organization, and instruction support, and10 dimensions scored on a scale from 1 (low quality) to 7 (high quality). Based on the teachers’ reports, five learning contexts were identified: 1) shared book reading, 2) free play, 3) morning meeting, 4) teacher-directed activity (such as craft), and 5) snack. Based on preliminary statistical analyses, little variation was observed within the learning contexts for each domain of the CLASS. However, the instructional support domain showed lower scores during specific learning contexts, specifically free play and teacher-directed activity. Practical implications for how preschool teachers could foster specific domains of interactions depending on learning contexts to enhance children’s social and academic development will be discussed.

Keywords: teacher practices, teacher-child interactions, preschool education, learning contexts, child development

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