Search results for: Digital Image Correlation (DIC)

Authors: Mohamed Gherbi

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The informal trade has invaded the Algerian cities, especially in their peripherals. About 1368 informal markets have been registrated during 2013 where the important ones are known by Doubaï Markets. They appeared since the adoption of the new system of the economy market in 1990. It permitted the intervention of new actors: the importers but also the fake ones. The majority of them were 'ex-Trabendistes' who have chosen to settle and invest in big and small cities of center and east of Algeria, mainly Algiers, El Eulma, Aïn El Fekroun, Tadjnenent, and Aïn M’lila. This study will focus on the case of the city of El Eulma which contains more of 1000 importers (most of them are fake). They have changed the image and architecture of some important streets of the city, without respecting rules of urbanism such as those included in the building permit for instance. The case of 'Doubaï' place in El Eulma illustrates this situation. This area is not covered by a Soil Occupation Plan (responsible of the design of urban spaces), even if this last covers other zones nearby surrounding of it. These importers helped by the wholesale and retail traders installed in 'Doubaï' place, have converted spaces inside and outside of residential buildings in deposits and sales of goods. They have squatted sidewalks to expose their goods imported predominantly from the South-East Asian countries. The scenery that reigns resembles partly to the bazaar of the Middle East and Chinese cities like Yiwu. These signs characterize the local ambiance and give the particularity to this part of the city. A customer tide from different cities and outside of Algeria comes daily to visit this district. The other zones surrounding have underwent the same change and have followed the model of 'Doubaï' place. Consequently, the mechanical movement has finished by stifling an important part of the city and the prices of land and real estate have reached exorbitant values and can be compared to prices charged in Paris due to the rampant speculation that has reached alarming dimensions. Similarly, renting commercial premises did not escape this logic. This paper will explain the reasons responsible of this change, the logic of importers through their acts in different spaces of the city.

Keywords: Doubaï place, design of urban spaces, fake importers, informal trade

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Authors: Arditya Nugraha, Herry Gunawan, Agung P. Widodo

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The various possible strategies to find hydrocarbon are explored within a wide ranging of efforts. It started to identify petroleum concept in the basin. The main objectives of this paper are to integrate and develop information, knowledge, and evaluation from Indonesia’s sedimentary basins system in terms of their suitability for exploration activity and estimate the hydrocarbon potential available. The system which compiled data information and knowledge and comprised exploration and production data of all basins in Indonesia called as Basin Professor which stands for Basin Professional and Processor. Basin Professor is a website application using Geography Information System which consists of all information about basin montage, basin summary, petroleum system, stratigraphy, development play, risk factor, exploration history, working area, regional cross section, well correlation, prospect & lead inventory and infrastructure spatial. From 82 identified sedimentary basins, North Sumatra, Central Sumatra, South Sumatera, East Java, Kutai, and Tarakan basins are respectively positioned of the Indonesia’ s mature basin and the most productive basin. The Eastern of Indonesia also have many hydrocarbon potential and discovered several fields in Papua and East Abadi. Basin Professor compiled the well data in all of the basin in Indonesia from mature basin to frontier basin. Well known geological data, subsurface mapping, prospect and lead, resources and established infrastructures are the main factors make these basins have higher suitability beside another potential basin. The hydrocarbon potential resulted from this paper based on the degree of geological data, petroleum, and economic evaluation. Basin Professor has provided by a calculator tool in lead and prospect for estimate the hydrocarbon reserves, recoverable in place and geological risk. Furthermore, the calculator also defines the preliminary economic evaluation such as investment, POT IRR and infrastructures in each basin. From this Basin Professor, petroleum companies are able to estimate that Indonesia has a huge potential of hydrocarbon oil and gas reservoirs and still interesting for hydrocarbon exploration and production activity.

Keywords: basin summary, petroleum system, resources, economic evaluation

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Authors: G. Scremin, I. Y. Suh, S. Doukas

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Spectators follow their favorite sports teams for different reasons. While some attend a sporting event simply for its entertainment value, others do so because of the personal sense of achievement and accomplishment their connection with a sports team creates. Moreover, the level of identity spectators feel toward their favorite sports team falls in a broad continuum. Some are mere spectators. For those spectators, their association to a sports team has little impact on their self-image. Others are die-hard fans who are proud of their association with their team and whose connection with that team is an important reflection of who they are. Several motives for sports consumption can be used to explain the level of spectator support in a variety of sports. Those motives can also be used to explain the variance in the identification, attachment, and loyalty spectators feel toward their favorite sports team. Motives for sports consumption can be used to discriminate the degree of identification spectators have with their favorite sports team. In this study, motives for sports consumption was used to discriminate the level of identity spectators feel toward their sports team. It was hypothesized that spectators with a strong level of team identity would report higher rates of interest in player, interest in sports, and interest in team than spectators with a low level of team identity. And spectators with a low level of team identity would report higher rates for entertainment value, bonding with friends or family, and wholesome environment. Football spectators in the United States and England were surveyed about their motives for football consumption and their level of identification with their favorite football team. To assess if the motives of sports fans differed by level of team identity and allegiance to an American or English football team, a Multivariate Analysis of Variance (MANOVA) under the General Linear Model (GLM) procedure found in SPSS was performed. The independent variables were level of team identity and allegiance to an American or English football team, and the dependent variables were the sport fan motives. A tripartite split (low, moderate, high) was used on a composite measure for team identity. Preliminary results show that effect of team identity is statistically significant (p < .001) for at least nine of the 17 motives for sports consumption assessed in this investigation. These results indicate that the motives of spectators with a strong level of team identity differ significantly from spectators with a low level of team identity. Those differences can be used to discriminate the degree of identification spectators have with their favorite sports team. Sports marketers can use these methods and results to develop identity profiles of spectators and create marketing strategies specifically designed to attract those spectators based on their unique motives for consumption and their level of team identification.

Keywords: fan identification, market segmentation of sports fans, motives for sports consumption, team identity

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Authors: Khalil Trigui, Rafik Ben Said, Fourat Akrout, Neji Aloui

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In this study, we examined in the first part the eco-biology of Artemia (A.salina) collected from Sahline Salt Lake (governorate of Monastir: Tunisia) during an annual cycle. The correlations between environmental factors and some biological parameters of Artemia were determined. The results obtained showed that the environmental factors affected the biology of Artemia. The highest abundance was recorded in May (550 ± 2,16 ind/l) and all life history stages existed with different seasonal proportions. The Artemia population is bisexual with ovoviviparous reproduction at the beginning and oviparous at the end of the life cycle. We also recorded the dominance of males at the start and the females at the end of the cycle. During all the study period, the size of mature females is bigger than that of males. The fertility obtained resulted in a significant production of cysts compared to the nauplii. A negative correlation with highly significant effect was deduced between environmental factors (temperature and salinity) and the production of nauplii (ovoviviparity) in contrast with dissolved oxygen. In the second part of our work is consecrated to the mastery of breeding Artemia. For this, we tested the effect of five external factors (temperature, salinity, dissolved oxygen, light intensity and food) on the survival of this crustacean. Thereby, the survival rates of Artemia were affected by the different values of studied factors. The recorded results showed that Artemia salina has an optimum temperature ranged from 25 to 27°C with a survival rate ranging from 84 to 88%. The optimal salinity to breed Artemia salina was 37 psu (62 ± 0,23%). Nevertheless, this crustacean was able to survive and withstand the salinity of 0 psu (freshwater). The optimum concentration of dissolved oxygen was 7mg/l with a survival rate of 87,11 ± 0,04%. An optimum light intensity of 10 lux revealed a survival rate equal to 85,33 ± 0,01%. The results also showed that the preferred micro-algae by Artemia is Dunaliella salina with a maximum survival rate of the order of 80 ± 0,15%. There is a significant effect for all experienced parameters on the survival of Artemia reared except the nature of food.

Keywords: Artemia salina, biology, breeding, ecology, Sahline salt lake

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Authors: Ilirian Laçi, Alketa Spahiu

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Big strums of thyroid glandule observed by a simple viewing can be witnessed in everyday life. Medical cabinets evidence patients withpalpablenodes of thyroid glandule, mainly nodes of the size of 10 millimeters. Further, more cases which have resulted in negative under palpation have resulted in positive at ultrasound examination. Therefore, the use of ultrasound for diagnosing has increased the number of patients with nodes of thyroid glandule in the last couple of decades in all countries, Albania included. Thus, there has been evidence of an increased number of patients affected by this pathology, where female patients dominate. Demographically, the capital shows high numbers due to the high population, but of interest is the high incidence of those areas distanced from the sea. While regarding related pathologies, no significant link was evidenced, an element of ancestry was evident in the nodes of the thyroid glandule. When we talk of nodes of the thyroid glandule, we should consider hyperplasia, neoplasia, and inflammatory diseases that cause nodes of the thyroid glandule. This increase parallels the world’s increase of the incidence of thyroid glandule, with malign cases, which are at about 5% and are not depended on size. Given the numbers, with most thyroid glandule nodes being benign, the main objective of the examination of the nodes was the determination of benign and malign cases to avoid undue surgery. Subject of this study were 212 patients that underwent fine-needle aspiration (FNA) under ultrasound guidance at the Medical University Center of Tirana. All the patients came to the Mother Teresa University Hospital from public and private hospitals and other polyclinics. These patients had an ultrasound examination before visiting the Center of Nuclear Medicine for a scintigraph of thyroid glandule in the period September 2016 and September 2017. To correlate, all patients had been examined via ultrasound of the thyroid glandule prior to the scintigraph. The ultrasound included evaluation of the number of nodes, their size, their solid, cystic, or solid-cystic structure, echogenicity according to the gray scale, the presence of calcification, the presence of lymph nodes, the presence of adenopathy, and the correlation of the cytology results from the Laboratory of Pathological Anatomy of Medical University Center of Tirana.

Keywords: thyroid nodes, fine needle aspiration, ultrasound, scintigraphy

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Authors: Heewon Jeong, Seongpyo Kim, Joon Ha Kim

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Over the last few tens of years, the coastal regions of Korea have experienced red tide algal blooms, which are harmful and toxic to both humans and marine organisms due to their potential threat. It was accelerated owing to eutrophication by human activities, certain oceanic processes, and climate change. Previous studies have tried to monitoring and predicting the algae concentration of the ocean with the bio-optical algorithms applied to color images of the satellite. However, the accurate estimation of algal blooms remains problems to challenges because of the complexity of coastal waters. Therefore, this study suggests a new method to identify the concentration of red tide algal bloom from images of geostationary ocean color imager (GOCI) which are representing the water environment of the sea in Korea. The method employed GOCI images, which took the water leaving radiances centered at 443nm, 490nm and 660nm respectively, as well as observed weather data (i.e., humidity, temperature and atmospheric pressure) for the database to apply optical characteristics of algae and train deep learning algorithm. Convolution neural network (CNN) was used to extract the significant features from the images. And then artificial neural network (ANN) was used to estimate the concentration of algae from the extracted features. For training of the deep learning model, backpropagation learning strategy is developed. The established methods were tested and compared with the performances of GOCI data processing system (GDPS), which is based on standard image processing algorithms and optical algorithms. The model had better performance to estimate algae concentration than the GDPS which is impossible to estimate greater than 5mg/m³. Thus, deep learning model trained successfully to assess algae concentration in spite of the complexity of water environment. Furthermore, the results of this system and methodology can be used to improve the performances of remote sensing. Acknowledgement: This work was supported by the 'Climate Technology Development and Application' research project (#K07731) through a grant provided by GIST in 2017.

Keywords: deep learning, algae concentration, remote sensing, satellite

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Authors: Mehdi Naserian, Mohammad Jooshaki, Mahmud Fotuhi-Firuzabad, Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee

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In recent years, the development of communication infrastructure and smart meters have facilitated the utilization of demand-side resources which can enhance stability and economic efficiency of power systems. Direct load control programs can play an important role in the utilization of demand-side resources in the residential sector. However, investments required for installing control equipment can be a limiting factor in the development of such demand response programs. Thus, selection of consumers with higher potentials is crucial to the success of a direct load control program. Heating, ventilation, and air conditioning (HVAC) systems, which due to the heat capacity of buildings feature relatively high flexibility, make up a major part of household consumption. Considering that the consumption of HVAC systems depends highly on the ambient temperature and bearing in mind the high investments required for control systems enabling direct load control demand response programs, in this paper, a recent solution is presented to uncover consumers with high air conditioner demand among large number of consumers and to measure the demand response potential of such consumers. This can pave the way for estimating the investments needed for the implementation of direct load control programs for residential HVAC systems and for estimating the demand response potentials in a distribution system. In doing so, we first cluster consumers into several groups based on the correlation coefficients between hourly consumption data and hourly temperature data using K-means algorithm. Then, by applying a recent algorithm to the hourly consumption and temperature data, consumers with high air conditioner consumption are identified. Finally, demand response potential of such consumers is estimated based on the equivalent desired temperature setpoint changes.

Keywords: communication infrastructure, smart meters, power systems, HVAC system, residential HVAC systems

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Authors: C. J. Rossouw, T. I. van Niekerk

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The global manufacturing industry is utilizing the internet and cloud-based services to further explore the anatomy and optimize manufacturing processes in support of the movement into the Fourth Industrial Revolution (4IR). The 4IR from a third world and African perspective is hindered by the fact that many manufacturing systems that were developed in the third industrial revolution are not inherently equipped to utilize the internet and services of the 4IR, hindering the progression of third world manufacturing industries into the 4IR. This research focuses on the development of a non-invasive and cost-effective cyber-physical IoT system that will exploit a machine’s vibration to expose semantic characteristics in the manufacturing process and utilize these results through a real-time cloud-based machine condition monitoring system with the intention to optimize the system. A microcontroller-based IoT sensor was designed to acquire a machine’s mechanical vibration data, process it in real-time, and transmit it to a cloud-based platform via Wi-Fi and the internet. Time-frequency Fourier analysis was applied to the vibration data to form an image representation of the machine’s behaviour. This data was used to train a Convolutional Neural Network (CNN) to learn semantic characteristics in the machine’s behaviour and relate them to a state of operation. The same data was also used to train a Convolutional Autoencoder (CAE) to detect anomalies in the data. Real-time edge-based artificial intelligence was achieved by deploying the CNN and CAE on the sensor to analyse the vibration. A cloud platform was deployed to visualize the vibration data and the results of the CNN and CAE in real-time. The cyber-physical IoT system was deployed on a semi-automated metal granulation machine with a set of trained machine learning models. Using a single sensor, the system was able to accurately visualize three states of the machine’s operation in real-time. The system was also able to detect a variance in the material being granulated. The research demonstrates how non-IoT manufacturing systems can be equipped with edge-based artificial intelligence to establish a remote machine condition monitoring system.

Keywords: IoT, cyber-physical systems, artificial intelligence, manufacturing, vibration analytics, continuous machine condition monitoring

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Authors: Beatriz Botella-Gil, Patricio Martínez-Barco, Lea Canales

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The Internet and ICT are an integral element of and omnipresent in our daily lives. Technologies have changed the way we see the world and relate to it. The number of companies in the ICT sector is increasing every year, and there has also been an increase in the work that occurs online, from sending e-mails to the way companies promote themselves. In social life, ICT’s have gained momentum. Social networks are useful for keeping in contact with family or friends that live far away. This change in how we manage our relationships using electronic devices and social media has been experienced differently depending on the age of the person. According to currently available data, people are increasingly connected to social media and other forms of online communication. Therefore, it is no surprise that violent content has also made its way to digital media. One of the important reasons for this is the anonymity provided by social media, which causes a sense of impunity in the victim. Moreover, it is not uncommon to find derogatory comments, attacking a person’s physical appearance, hobbies, or beliefs. This is why it is necessary to develop artificial intelligence tools that allow us to keep track of violent comments that relate to violent events so that this type of violent online behavior can be deterred. The objective of our research is to create a guide for detecting and recording violent messages. Our annotation guide begins with a study on the problem of violent messages. First, we consider the characteristics that a message should contain for it to be categorized as violent. Second, the possibility of establishing different levels of aggressiveness. To download the corpus, we chose the social network Twitter for its ease of obtaining free messages. We chose two recent, highly visible violent cases that occurred in Spain. Both of them experienced a high degree of social media coverage and user comments. Our corpus has a total of 633 messages, manually tagged, according to the characteristics we considered important, such as, for example, the verbs used, the presence of exclamations or insults, and the presence of negations. We consider it necessary to create wordlists that are present in violent messages as indicators of violence, such as lists of negative verbs, insults, negative phrases. As a final step, we will use automatic learning systems to check the data obtained and the effectiveness of our guide.

Keywords: human language technologies, language modelling, offensive language detection, violent online content

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Authors: Mohamad Mahdi Namdari

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In today's rapidly changing and evolving business competition, companies and organizations require advanced and efficient tools to manage their markets and sales networks. Big data analysis, quick response in competitive markets, process and operations optimization, and forecasting customer behavior are among the concerns of executive managers. Artificial intelligence, as one of the emerging technologies, has provided extensive capabilities in this regard. The use of artificial intelligence in market and sales network management can lead to improved efficiency, increased decision-making accuracy, and enhanced customer satisfaction. Specifically, AI algorithms can analyze vast amounts of data, identify complex patterns, and offer strategic suggestions to improve sales performance. However, many companies are still distant from effectively leveraging this technology, and those that do face challenges in fully exploiting AI's potential in market and sales network management. It appears that the general public's and even the managerial and academic communities' lack of knowledge of this technology has caused the managerial structure to lag behind the progress and development of artificial intelligence. Additionally, high costs, fear of change and employee resistance, lack of quality data production processes, the need for updating structures and processes, implementation issues, the need for specialized skills and technical equipment, and ethical and privacy concerns are among the factors preventing widespread use of this technology in organizations. Clarifying and explaining this technology, especially to the academic, managerial, and elite communities, can pave the way for a transformative beginning. The aim of this research is to elucidate the capacities of artificial intelligence in market and sales network management, identify its opportunities and benefits, and examine the existing challenges and obstacles. This research aims to leverage AI capabilities to provide a framework for enhancing market and sales network performance for managers. The results of this research can help managers and decision-makers adopt more effective strategies for business growth and development by better understanding the capabilities and limitations of artificial intelligence.

Keywords: artificial intelligence, market management, sales network, big data analysis, decision-making, digital marketing

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Authors: R. Bhattu Babajee, Marie Sandrine Estelle Benoit

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The past decades have witnessed a considerable institutional shift towards Central Bank Independence across economies of the world. The motivation behind such a change is the acceptance that increased central bank autonomy has the power of alleviating inflation bias. Hence, studying whether Central Bank Independence acts as a significant factor behind the price stability in the African economies or whether this macroeconomic aim in these countries result from other economic, political or social factors is a pertinent issue. The main research objective of this paper is to assess the relationship between central bank autonomy and inflation in African economies where inflation has proved to be a serious problem. In this optic, we shall measure the degree of CBI in Africa by computing the turnover rates of central banks governors thereby studying whether decisions made by African central banks are affected by external forces. The purpose of this study is to investigate empirically the association between Central Bank Independence (CBI) and inflation for 10 African economies over a period of 17 years, from 1995 to 2012. The sample includes Botswana, Egypt, Ghana, Kenya, Madagascar, Mauritius, Mozambique, Nigeria, South Africa, and Uganda. In contrast to empirical research, we have not been using the usual static panel model for it is associated with potential mis specification arising from the absence of dynamics. To this issue a dynamic panel data model which integrates several control variables has been used. Firstly, the analysis includes dynamic terms to explain the tenacity of inflation. Given the confirmation of inflation inertia, that is very likely in African countries there exists the need for including lagged inflation in the empirical model. Secondly, due to known reverse causality between Central Bank Independence and inflation, the system generalized method of moments (GMM) is employed. With GMM estimators, the presence of unknown forms of heteroskedasticity is admissible as well as auto correlation in the error term. Thirdly, control variables have been used to enhance the efficiency of the model. The main finding of this paper is that central bank independence is negatively associated with inflation even after including control variables.

Keywords: central bank independence, inflation, macroeconomic variables, price stability

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Authors: Kyung Hwa Shin

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Primary school music education plays a crucial role in nurturing students' musical abilities and fostering a lifelong appreciation for music. As we embark on the 21st century, it becomes imperative to explore advanced approaches that can effectively engage and empower students in the realm of music. This study aims to shed light on the aspects of primary school music education in South Korea, with a specific focus on the incorporation of the Zoltán Kodály Concept. The Zoltán Kodály Concept, developed by Hungarian composer and educator Zoltán Kodály (Kodály, 1974) advocates for a holistic music education that integrates singing, movement, and music literacy. This concept has gained recognition worldwide for its effectiveness in developing musicianship and enhancing music learning experiences. This study will delve into the ways in which the Zoltán Kodály Concept has been adapted and implemented in the context of South Korean primary school music education. It will highlight the benefits of this approach in nurturing students' musical skills, fostering creativity, and promoting cultural understanding through music. Furthermore, it will enhance the delivery of the Kodály-based curriculum challenges posed by the 21st-century digital age. Drawing on this research, pedagogical practices, and case studies, this study will provide valuable insights into the practical applications of the Zoltán Kodály Concept in South Korean primary school music education. It will discuss the impact of this approach on student engagement, motivation, and achievement, as well as the role of teachers in facilitating effective implementation. Additionally, it will address the professional development opportunities available to music educators to enhance their pedagogical skills in line with the Kodály philosophy. Ultimately, it aims to inspire and empower educators, policymakers, and researchers to embrace the Zoltán Kodály Concept as a transformative and forward-thinking approach to primary school music education in the 21st century. By embracing current aspects and progressive methodologies, South Korea can continue to strengthen its music education system and cultivate a generation of musically literate and culturally enriched individuals.

Keywords: primary school music education, Zoltán Kodály concept, 21st century, South Korea, music literacy, pedagogy, curriculum

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Authors: T. Ewetumo, K. D. Adedayo, Festus Ben

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Knowledge of the thermal properties of foods is of fundamental importance in the food industry to establish the design of processing equipment. However, for tropical fruit juice, there is very little information in literature, seriously hampering processing procedures. This research work describes the development of an instrument for automated thermal conductivity and thermal diffusivity measurement of tropical fruit juice using a transient thermal probe technique based on line heat principle. The system consists of two thermocouple sensors, constant current source, heater, thermocouple amplifier, microcontroller, microSD card shield and intelligent liquid crystal. A fixed distance of 6.50mm was maintained between the two probes. When heat is applied, the temperature rise at the heater probe measured with time at time interval of 4s for 240s. The measuring element conforms as closely as possible to an infinite line source of heat in an infinite fluid. Under these conditions, thermal conductivity and thermal diffusivity are simultaneously measured, with thermal conductivity determined from the slope of a plot of the temperature rise of the heating element against the logarithm of time while thermal diffusivity was determined from the time it took the sample to attain a peak temperature and the time duration over a fixed diffusivity distance. A constant current source was designed to apply a power input of 16.33W/m to the probe throughout the experiment. The thermal probe was interfaced with a digital display and data logger by using an application program written in C++. Calibration of the instrument was done by determining the thermal properties of distilled water. Error due to convection was avoided by adding 1.5% agar to the water. The instrument has been used for measurement of thermal properties of banana, orange and watermelon. Thermal conductivity values of 0.593, 0.598, 0.586 W/m^o C and thermal diffusivity values of 1.053 ×〖10〗^(-7), 1.086 ×〖10〗^(-7), and 0.959 ×〖10〗^(-7) 〖m/s〗^2 were obtained for banana, orange and water melon respectively. Measured values were stored in a microSD card. The instrument performed very well as it measured the thermal conductivity and thermal diffusivity of the tropical fruit juice samples with statistical analysis (ANOVA) showing no significant difference (p>0.05) between the literature standards and estimated averages of each sample investigated with the developed instrument.

Keywords: thermal conductivity, thermal diffusivity, tropical fruit juice, diffusion equation

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Authors: Daniel Gebreslassie Mekonnen

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Effective leadership has a crucial role in excelling in the overall success of a school. Today there is much attention given to school leadership, without which schools can never be successful. Therefore, the study was aimed at investigating the role of principals’ leadership styles and their emotional intelligence on the work motivation and job performance of teachers in Addis Ababa, Ethiopia. The study, thus, first examined the relationship between work motivation and job performance of the teachers in relation to the perceived leadership styles and emotional intelligence of principals. Second, it assessed the mean differences and the interaction effects of the principals’ leadership styles and emotional intelligence on the work motivation and job performance of the teachers. Finally, the study investigated whether principals’ leadership styles and emotional intelligence variables had significantly predicted the work motivation and job performance of teachers. As a means, a quantitative approach and descriptive research design were employed to conduct the study. Three hundred sixteen teachers were selected using multistage sampling techniques as participants of the study from the eight sub-cities in Addis Ababa. The main data-gathering instruments used in this study were the path-goal leadership questionnaire, emotional competence inventory, multidimensional work motivation scale, and job performance appraisal scale. The quantitative data were analyzed by using the statistical techniques of Pearson–product-moment correlation analysis, two-way analysis of variance, and stepwise multiple regression analysis. Major findings of the study have revealed that the work motivation and job performance of the teachers were significantly correlated with the perceived participative leadership style, achievement-oriented leadership style, and emotional intelligence of principals. Moreover, the emotional intelligence of the principals was found to be the best predictor of the teachers’ work motivation, whereas the achievement-oriented leadership style of the principals was identified as the best predictor of the job performance of the teachers. Furthermore, the interaction effects of all four path-goal leadership styles vis-a-vis the emotional intelligence of the principals have shown differential effects on the work motivation and job performance of teachers. Thus, it is reasonable to conclude that emotional intelligence is the sine qua non of effective school leadership. Hence, this study would be useful for policymakers and educational leaders to come up with policies that would enhance the role of emotional intelligence on school leadership effectiveness. Finally, pertinent recommendations were drawn from the findings and the conclusions of the study.

Keywords: emotional intelligence, leadership style, job performance, work motivation

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Authors: K. Hariohm, V. Prakash, J. Saravana Kumar

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Introduction and Rationale: Increased scope of Physiotherapy (PT) practice also has contributed to research in the field of PT. It is essential to determine the production and quality of the clinical trials from India since, it may reflect the scientific growth of the profession. These trends can be taken as a baseline to measure our performance and also can be used as a guideline for the future trials. Objective: To quantify and analyze qualitatively the RCT’s from India from the period 2000-2013’ May, and classify data for the information process. Methods: Studies were searched in the Medline database using the key terms “India”, “Indian”, “Physiotherapy”. Clinical trials only with PT authors were included. Trials out of scope of PT practice and on animals were excluded. Retrieved valid articles were analyzed for published year, type of participants, area of study, PEDro score, outcome measure domains of impairment, activity, participation; ‘a priori’ sample size calculation, region, and explanation of the intervention. Result: 45 valid articles were retrieved from the year 2000-2013’ May. The majority of articles were done on symptomatic participants (81%). The frequencies of conditions repeated more were low back pain (n-7) and diabetes (n-4). PEDro score with mode 5 and upper limit of 8 and lower limit 4 was found. 97.2% of studies measure the outcome at the impairment level, 34% in activity level, and 27.8% in participation level. 29.7% of studies did ‘a priori’ sample size calculation. Correlation of year trend and PEDro score found to be not significant (p>.05). Individual PEDro item analysis showed, randomization (100%), concealment (33%) baseline (76%), blinding-subject, therapist, assessor (9.1%, 0%, 10%), follow-up (89%) ITT (15%), statistics between groups (100%), measures of variance (88 %). Conclusion: The trend shows an upward slope in terms of RCTs published from India which is a good indicator. The qualitative analysis showed some gaps in the clinical trial design, which can be expected to be, fulfilled by the future researchers.

Keywords: RCT, PEDro, physical therapy, rehabilitation

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Authors: Soodabeh Shahid Sales, Azam Rastgar Moghadam, Mehrane Mehramiz, Malihe Entezari, Kazem Anvari, Mohammad Sadegh Khorrami, Saeideh Ahmadi Simab, Ali Moradi, Seyed Mahdi Hassanian, Majid Ghayour-Mobarhan, Gordon A. Ferns, Amir Avan

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Background Esophageal cancer has been reported as the eighth most common cancer universal and the seventh cause of cancer-related death in men .recent studies have revealed that cytochrome P450, family 1, subfamily B, polypeptide 1, which plays a role in metabolizing xenobiotics, is associated with different cancers. Therefore in the present study, we investigated the impact of CYP1B1-rs1056836 on esophagus squamous cell carcinoma (ESCC) patients. Method: 317 subjects, with and without ESCC were recruited. DNA was extracted and genotyped via Real-time PCR-Based Taq Man. Kaplan Meier curves were utilized to assess overall and progression-free survival. To evaluate the relationship between patients clinicopathological data, genotypic frequencies, disease prognosis, and patients survival, Pearson chi-square and t-test were used. Logistic regression was utilized to assess the association between the risk of ESCC and genotypes. Results: the genotypic frequency for GG, GC, and CC are respectively 58.6% , 29.8%, 11.5% in the healthy group and 51.8%, 36.14% and 12% in ESCC group. With respect to the recessive genetic inheritance model, an association between the GG genotype and stage of ESCC were found. Also, statistically significant results were not found for this variation and risk of ESCC. Patients with GG genotype had a decreased risk of nodal metastasis in comparison with patients with CC/CG genotype, although this link was not statistically significant. Conclusion: Our findings illustrated the correlation of CYP1B1-rs1056836 as a potential biomarker for ESCC patients, supporting further studies in larger populations in different ethnic groups. Moreover, further investigations are warranted to evaluate the association of emerging marker with dietary intake and lifestyle.

Keywords: Cytochrome P450, esophagus squamous cell carcinoma, dietary intake, lifestyle

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Authors: N. Haj Salem, M. Belhadj, S. Ben Jomâa, R. Dhouieb, S. Saadi, M. A. Mesrati, A. Chadly

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Introduction: The hyoid bone is considered as one of many bones used to identify a missed person. There is a specificity of each population group in human identifications. Objective: To analyze the relationship between age, sex and metric parameters of hyoid bone in Tunisian population sample, using CT-scan. Materials and Methods: A prospective study was conducted in the Department of Forensic Medicine of FattoumaBourguiba Hospital of Monastir-Tunisia during 4 years. A total of 240 samples of hyoid bone were studied. The age of cases ranged from 18 days to 81 years. The specimens were collected only from the deceased of known age. Once dried, each hyoid bone was scanned using CT scan. For each specimen, 10 measurements were taken using a computer program. The measurements consisted of 6 lengths and 4 widths. A regression analysis was used to estimate the relationship between age, sex, and different measurements. For age estimation, a multiple logistic regression was carried out for samples ≤ 35 years. For sex determination, ROC curve was performed. Discriminant value finally retained was based on the best specificity with the best sensitivity. Results: The correlation between real age and estimated age was good (r²=0.72) for samples aged 35 years or less. The unstandardised canonical function equation was estimated using three variables: maximum length of the right greater cornua, length from the middle of the left joint space to the middle of the right joint space and perpendicular length from the centre point of a line between the distal ends of the right and left greater cornua to the centre point of the anterior view of the body of the hyoid bone. For sex determination, the ROC curve analysis reveals that the area under curve was at 81.8%. Discriminant value was 0.451 with a specificity of 73% and sensibility of 79%. The equation function was estimated based on two variables: maximum length of the greater cornua and maximum length of the hyoid bone. Conclusion: The findings of the current study suggest that metric analysis of the hyoid bone may predict the age ≤ 35 years. Sex estimation seems to be more reliable. Further studies dealing with the fusion of the hyoid bone and the current study could help to achieve more accurate age estimation rates.

Keywords: anthropology, age estimation, CT scan, sex determination, Tunisia

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Authors: Tamara Matevosyan

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In this globalized world, intercultural communication is becoming essential for understanding communication among people, for developing understanding of cultures, to appreciate the opportunities and challenges that each culture presents to people. Moreover, it plays an important role in developing an ideal personification to understand different behaviors in different cultures. Native speakers assimilate sociolinguistic knowledge in natural conditions, while it is a great problem for language learners, and in this context feature films reveal cultural peculiarities and involve students in real communication. As we know nowadays the key role of language learning is the development of intercultural competence as communicating with someone from a different cultural background can be exciting and scary, frustrating and enlightening. Intercultural competence is important in FL learning classroom and here feature films can perform as essential tools to develop this competence and overcome the intercultural gap that foreign students face. Current proposal attempts to reveal the correlation of the given culture and language through feature films. To ensure qualified, well-organized and practical classes on Intercultural Communication for language learners a number of methods connected with movie watching have been implemented. All the pre-watching, while watching and post-watching methods and techniques are aimed at developing students’ communicative competence. The application of such activities as Climax, Role-play, Interactive Language, Daily Life helps to reveal and overcome mistakes of cultural and pragmatic character. All the above-mentioned activities are directed at the assimilation of the language vocabulary with special reference to the given culture. The study dwells into the essence of culture as one of the core concepts of intercultural communication. Sometimes culture is not a priority in the process of language learning which leads to further misunderstandings in real life communication. The application of various methods and techniques with feature films aims at developing students’ cultural competence, their understanding of norms and values of individual cultures. Thus, feature film activities will enable learners to enlarge their knowledge of the particular culture and develop a fundamental insight into intercultural communication.

Keywords: climax, intercultural competence, interactive language, role-play

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Authors: I. Stacher, B. Schrank, K. Stiehl, K. A. Woodcock

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Background: The need and desire for connectedness and belonging to a peer group is a major concern in middle childhood. This is particularly true for the period of school transition when making and maintaining friendships is put to the test. Social relations are important for enhancing self-esteem, confidence, and mental health. Conflicts with peers and victimization mark challenges in the complex social environment of early adolescents. Thus, the promotion of supportive peer relationships is an important social goal. The current literature lacks an in-depth analysis of young people’s experiences connected to making and maintaining friendships. Aim: This qualitative study aims to understand the factors that facilitate and hinder friendship and peer relations within the complex context of school transition. Methods: Youth engagement workshops at primary and secondary schools were conducted with 53 classes (N = 906 pupils; M age = 10.44; SD = .912) in 29 different schools across lower Austria. A big poster was created with the entire class, collecting early adolescents’ ideas on ways they can support each other in the school environment. Then, students were divided into smaller groups and encouraged to share their personal experiences of friendship. Verbatim quotes from students were collected on observation sheets and sticky notes during the activities. A thematic analysis was conducted. Results: Early adolescents describe facilitating factors that allow them to connect with peers. These descriptions are mainly on a behavioral level and are relevant for face-to-face and digital contact, e.g., practical and emotional support, spending time together, pleasure and fun. Specific challenges such as offensive actions, betrayal, and lack of emotion regulation exist and need to be addressed if aiming to reduce barriers between peers. Conclusion: Knowing first-hand experiences, desires, and barriers for making and maintaining friends at the time of school transition will help researchers to develop preventive health programs that adequately address the needs and preferences of today’s youth.

Keywords: youth voice, experts by experience, friendship, peer relations, primary-secondary school, transition

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Authors: Alison Marshall

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“Santo Niño in Canada – Religion, Migration, and the Filipino Underside” seeks to explore the intersection of religion, migration and the Filipino underside through research participant narratives, archival research, and fieldwork on the cult of Santo Niño in Canada. Santo Niño is the single most revered saint in Filipino religiosity. According to popular lore, the original statue of Santo Niño was brought to the Philippines by Portuguese explorer Ferdinand Magellan in 1521, who claimed the islands on behalf of Spain. While Santo Niño is meant to be a manifestation of Jesus as a child, in Filipino thought and culture he very much resembles pre-Hispanic spirits, as well as patron saints introduced by the Spanish. Santo Niño shrines appear in churches, restaurants, businesses, and homes throughout the diaspora suggesting that he was much more than a Catholic image. He represents a deity who often shares a business or home shrine with non-Christian statues such as lucky cats, the Buddha, Guanyin, and Guangong, and sometimes the Chinese God of the Earth. He represents how Christian culture has been refashioned through indigenous, Chinese, Malay, and Indonesian influences. He embodies the religious superstructure that defines Christian piety and habits. On the one hand, he stands for Jesus, a pious son of God, and yet, on the other hand, he can be a simple vindictive child who punishes those who ignore him. Santo Niño is a complex character linked to the past before Christianity. As Filipinos engage with Santo Niño in Canada, they connect to him as Jesus, the son of God. They are also connecting to a childlike figure who sometimes uses his spiritual power to punish. A hybrid figure who comes came into being at the beginning of the Spanish colonial moment, he is maintained throughout the American one and continues to be a powerful reminder of Filipino identity and resilience when people leave the Philippines for migrant work. As this paper argues, Santo Niño beliefs, practices, and stories unite people in the diaspora regardless of language, gender, or nation. Santo Niño enables one to think about and understand what it means to be Filipino and living migrant lives in the diaspora today. In this way, the cult of Santo Niño expresses both Catholic orthodoxy and the heterodox Filipino underside that includes the use of magical amulets, healing, visions, and spirit mediumship.

Keywords: ethnography, migration, Philippines, religion

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Authors: Robert Cazar, Nathaly Maza

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Energy drinks and sports drinks are quite popular among young adults and teenagers worldwide. Some concerns regarding their health effects – particularly those of the energy drinks - have been raised based on scientific findings. Differentiating between these two types of drinks by means of their chemical properties seems to be an instructive task. Chemometrics provides the most appropriate strategy to do so. In this study, a discrimination analysis of the energy and sports drinks has been carried out applying chemometric methods. A set of eleven samples of available commercial brands of drinks – seven energy drinks and four sports drinks – were collected. Each sample was characterized by eight chemical variables (carbohydrates, energy, sugar, sodium, pH, degrees Brix, density, and citric acid). The data set was standardized and examined by exploratory chemometric techniques such as clustering and principal component analysis. As a preliminary step, a variable selection was carried out by inspecting the variable correlation matrix. It was detected that some variables are redundant, so they can be safely removed, leaving only five variables that are sufficient for this analysis. They are sugar, sodium, pH, density, and citric acid. Then, a hierarchical clustering `employing the average – linkage criterion and using the Euclidian distance metrics was performed. It perfectly separates the two types of drinks since the resultant dendogram, cut at the 25% similarity level, assorts the samples in two well defined groups, one of them containing the energy drinks and the other one the sports drinks. Further assurance of the complete discrimination is provided by the principal component analysis. The projection of the data set on the first two principal components – which retain the 71% of the data information – permits to visualize the distribution of the samples in the two groups identified in the clustering stage. Since the first principal component is the discriminating one, the inspection of its loadings consents to characterize such groups. The energy drinks group possesses medium to high values of density, citric acid, and sugar. The sports drinks group, on the other hand, exhibits low values of those variables. In conclusion, the application of chemometric methods on a data set that features some chemical properties of a number of energy and sports drinks provides an accurate, dependable way to discriminate between these two types of beverages.

Keywords: chemometrics, clustering, energy drinks, principal component analysis, sports drinks

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Authors: Jolanta Uszko, Tomasz Wloch, Aneta Pirowska, Roman Nowobilski

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Introduction: Phantom phenomena are often reported by subjects who have undergone limb amputation. Mostly, patients feel the amputated part of the limb as if it was still attached to the body. Two types of phantom phenomena: painless (phantom sensation) and painful (phantom pain) were described. Triggers of phantom sensations and phantom pain, as well as fully effective treatment, have not been clearly described yet. Purpose: To assess the influence of psychosocial factors and some clinical conditions on the occurrence of phantom phenomena in amputee athletes. Subjects: 21 men (age: 31 years, SD = 7.5 years) after lower or upper extremity amputation, who regularly performed high-intensity sports (Amp Football Team Players) were included to the study. Method and equipment: In the research, the following method and tools were used: Questionnaire [Pirowska] adapted for athletes with disabilities, Numerical Rating Scale (NRS) - for phantom pain assessment, McGill Pain Assessment Questionnaire (short version), Beck's Depression Inventory (BDI), State Trait Anxiety Inventory (STAI): X-1 and X-2, shortened version of The World Health Organization Quality of Life (WHOQOLBREFF). Results: In the study group, the lower leg amputations with traumatic etiology were predominant. Phantom sensations were present in all subjects. Half of the respondents claimed to experience phantom sensations at least once a day, paroxysmally. There was a prevalence of phantom sensations characterized as incomplete, immobile limb. Phantom pain was reported by over 85% of respondents. The nature of phantom pain was frequently described as stabbing, squeezing, shooting, pulsing, tiring. There was a significant correlation between phantom pain intensity and anxiety, quality of life, depressive tendencies, perception of phantom pain as the obstacle in daily functioning and intensity of the limb pain before amputation. Conclusions: The etiology of phantom phenomena is complex. Psychological factors seem to have a significant influence on the intensity of the phantom pain. Particular attention should be paid to patients who complain about persistent limb pain before the amputation. These are patients with an increased risk of the phantom pain of relatively high intensity.

Keywords: amputation, phantom pain, phantom sensations, adaptive sports

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Authors: Sheelagh Heugh, Michael Upton, Kriya Kalidas, Stephen Breen

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This article aims to create awareness of the opportunities and issues the artificial intelligence (AI) tool GPT-3 (Generative Pre-trained Transformer-3) brings to higher education. Technological disruptors have featured in higher education (HE) since Konrad Klaus developed the first functional programmable automatic digital computer. The flurry of technological advances, such as personal computers, smartphones, the world wide web, search engines, and artificial intelligence (AI), have regularly caused disruption and discourse across the educational landscape around harnessing the change for the good. Accepting AI influences are inevitable; we took mixed methods through participatory action research and evaluation approach. Joining HE communities, reviewing the literature, and conducting our own research around Chat GPT-3, we reviewed our institutional approach to changing our current practices and developing policy linked to assessments and the use of Chat GPT-3. We review the impact of GPT-3, a high-powered natural language processing (NLP) system first seen in 2020 on HE. Historically HE has flexed and adapted with each technological advancement, and the latest debates for educationalists are focusing on the issues around this version of AI which creates natural human language text from prompts and other forms that can generate code and images. This paper explores how Chat GPT-3 affects the current educational landscape: we debate current views around plagiarism, research misconduct, and the credibility of assessment and determine the tool's value in developing skills for the workplace and enhancing critical analysis skills. These questions led us to review our institutional policy and explore the effects on our current assessments and the development of new assessments. Conclusions: After exploring the pros and cons of Chat GTP-3, it is evident that this form of AI cannot be un-invented. Technology needs to be harnessed for positive outcomes in higher education. We have observed that materials developed through AI and potential effects on our development of future assessments and teaching methods. Materials developed through Chat GPT-3 can still aid student learning but lead to redeveloping our institutional policy around plagiarism and academic integrity.

Keywords: artificial intelligence, Chat GPT-3, intellectual property, plagiarism, research misconduct

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Authors: Mpho Mokoatle, Darlington Mapiye, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on $k$-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0%, 80.5%, 80.5%, 63.6%, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms.

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: Darlington Mapiye, Mpho Mokoatle, James Mashiyane, Stephanie Muller, Gciniwe Dlamini

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Great advances in high-throughput sequencing technologies have resulted in availability of huge amounts of sequencing data in public and private repositories, enabling a holistic understanding of complex biological phenomena. Sequence data are used for a wide range of applications such as gene annotations, expression studies, personalized treatment and precision medicine. However, this rapid growth in sequence data poses a great challenge which calls for novel data processing and analytic methods, as well as huge computing resources. In this work, a machine and statistical learning approach for DNA sequence classification based on k-mer representation of sequence data is proposed. The approach is tested using whole genome sequences of Mycobacterium tuberculosis (MTB) isolates to (i) reduce the size of genomic sequence data, (ii) identify an optimum size of k-mers and utilize it to build classification models, (iii) predict the phenotype from whole genome sequence data of a given bacterial isolate, and (iv) demonstrate computing challenges associated with the analysis of whole genome sequence data in producing interpretable and explainable insights. The classification models were trained on 104 whole genome sequences of MTB isoloates. Cluster analysis showed that k-mers maybe used to discriminate phenotypes and the discrimination becomes more concise as the size of k-mers increase. The best performing classification model had a k-mer size of 10 (longest k-mer) an accuracy, recall, precision, specificity, and Matthews Correlation coeffient of 72.0 %, 80.5 %, 80.5 %, 63.6 %, and 0.4 respectively. This study provides a comprehensive approach for resampling whole genome sequencing data, objectively selecting a k-mer size, and performing classification for phenotype prediction. The analysis also highlights the importance of increasing the k-mer size to produce more biological explainable results, which brings to the fore the interplay that exists amongst accuracy, computing resources and explainability of classification results. However, the analysis provides a new way to elucidate genetic information from genomic data, and identify phenotype relationships which are important especially in explaining complex biological mechanisms

Keywords: AWD-LSTM, bootstrapping, k-mers, next generation sequencing

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Authors: A. Dashti, M. Eskandari, L. Farahmand, P. Parvin, A. Jafargholi

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Breast Cancer is one of the most considerable diseases in the United States and other countries and is the second leading cause of death in women. Common breast cancer treatments would lead to adverse side effects such as loss of hair, nausea, and weakness. These complications arise because these cancer treatments damage some healthy cells while eliminating the cancer cells. In an effort to address these complications, laser radiation was utilized and tested as a targeted cancer treatment for breast cancer. In this regard, tissue engineering approaches are being employed by using an electrospun scaffold in order to facilitate the growth of breast cancer cells. Polycaprolacton (PCL) was used as a material for scaffold fabricating because of its biocompatibility, biodegradability, and supporting cell growth. The specific breast cancer cells have the ability to create a three-dimensional cell cluster due to the spontaneous accumulation of cells in the porosity of the scaffold under some specific conditions. Therefore, we are looking for a higher density of porosity and larger pore size. Fibers showed uniform diameter distribution and final scaffold had optimum characteristics with approximately 40% porosity. The images were taken by SEM and the density and the size of the porosity were determined with the Image. After scaffold preparation, it has cross-linked by glutaraldehyde. Then, it has been washed with glycine and phosphate buffer saline (PBS), in order to neutralize the residual glutaraldehyde. 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromidefor (MTT) results have represented approximately 91.13% viability of the scaffolds for cancer cells. In order to create a cluster, Michigan Cancer Foundation-7 (MCF-7, breast cancer cell line) and Michigan Cancer Foundation-10A (MCF-10A, human mammary epithelial cell line) cells were cultured on the scaffold in 24 well plate for five days. Then, we have exposed the cluster to the laser diode 808 nm radiation to investigate the effect of laser on the tumor with different power and time. Under the same conditions, cancer cells lost their viability more than the healthy ones. In conclusion, laser therapy is a viable method to destroy the target cells and has a minimum effect on the healthy tissues and cells and it can improve the other method of cancer treatments limitations.

Keywords: breast cancer, electrospun scaffold, polycaprolacton, laser diode, cancer treatment

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Authors: J. Banski

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Regardless of residence place, the type of business and the social system, an individual or groups of people use the accumulated knowledge and continuously deepen and expand its scope. Knowledge is needed by human beings to carry out certain tasks, achieve desired goals or make decisions. Knowledge is an attribute of the people of a region and is identified with the total experience and information that its residents and institutions possess, including the ability to use it. It is subject to constant development, which is the result of both the deepening and exchange of knowledge among the residents of a particular area, as well as the influx of knowledge with newly arriving residents. A good example of the aforementioned processes is in rural areas, where we are dealing with two basic groups of people between whom knowledge transfer takes place. The first group is made up of people who have lived in the village for a long time, while the second group is made up of people who migrate temporarily or permanently to the countryside. The English-language literature uses the terms oldtimers and newcomers for these groups, respectively. Newcomers, usually possessing different life experiences, cultural patterns and competencies, can be rich sources of knowledge for villagers. At the same time, the latter, with different knowledge and experience, along with knowledge of local conditions and customs, can also be an important source of knowledge for incomers to the countryside. The countryside is a particularly interesting environment for studying social interactions and the accompanying transfer of knowledge. This is because it is characterized by a high intensity of neighborly contact and a high level of trust in the private sphere. As a result of the migratory influx of new residents, the social and cultural image of the countryside is changing due to the interpenetration of urban and rural life patterns. Research on rural-urban knowledge transfer is both an opportunity to halt negative trends in the social and economic development of rural areas and support the establishment of a basis for rural renewal. This paper discusses the results of research on urban-rural knowledge transfer based on case studies carried out in a dozen villages from different regions of Poland. Their purpose was to answer three basic research questions: 1) what types of knowledge are transferred between urban and rural residents? 2) what are the main directions and intensity in knowledge transfer? And 3) what are the consequences of knowledge transfer between urban and rural residents?

Keywords: rural areas, villages, newcomers, knowledge transfer, Poland

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Authors: Elyas Palantei, Dewiani, Farid Armin, Ardiansyah

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High precision of printed microwave sensor utilized for sensing and monitoring the potential breast cancer existed in women breast tissue was optimally computed. The single element of UWB printed sensor that successfully modeled through several numerical optimizations was multiple fabricated and incorporated with woman bra to form the spherical sensors array. One sample of UWB microwave sensor obtained through the numerical computation and optimization was chosen to be fabricated. In overall, the spherical sensors array consists of twelve stair patch structures, and each element was individually measured to characterize its electrical properties, especially the return loss parameter. The comparison of S11 profiles of all UWB sensor elements is discussed. The constructed UWB sensor is well verified using HFSS programming, CST programming, and experimental measurement. Numerically, both HFSS and CST confirmed the potential operation bandwidth of UWB sensor is more or less 4.5 GHz. However, the measured bandwidth provided is about 1.2 GHz due to the technical difficulties existed during the manufacturing step. The configuration of UWB microwave sensing and monitoring system implemented consists of 12 element UWB printed sensors, vector network analyzer (VNA) to perform as the transceiver and signal processing part, the PC Desktop/Laptop acting as the image processing and displaying unit. In practice, all the reflected power collected from whole surface of artificial breast model are grouped into several numbers of pixel color classes positioned on the corresponding row and column (pixel number). The total number of power pixels applied in 2D-imaging process was specified to 100 pixels (or the power distribution pixels dimension 10x10). This was determined by considering the total area of breast phantom of average Asian women breast size and synchronizing with the single UWB sensor physical dimension. The interesting microwave imaging results were plotted and together with some technical problems arisen on developing the breast sensing and monitoring system are examined in the paper.

Keywords: UWB sensor, UWB microwave imaging, spherical array, breast cancer monitoring, 2D-medical imaging

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Authors: Kottaridi Klimentia, Demopoulos Vasilis, Sidiropoulos Anastasios, Ihara Diego, Nikolaidis Vasileios, Antonopoulos Dimitrios

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Aflatoxins are highly poisonous and carcinogenic compounds produced by species of the genus Aspergillus spp. that can infect a variety of agricultural foods, including dried figs. Biological and environmental factors, such as population, pathogenicity, and aflatoxinogenic capacity of the strains, topography, soil, and climate parameters of the fig orchards, are believed to have a strong effect on aflatoxin levels. Existing methods for aflatoxin detection and measurement, such as high performance liquid chromatography (HPLC), and enzyme-linked immunosorbent assay (ELISA), can provide accurate results, but the procedures are usually time-consuming, sample-destructive, and expensive. Predicting aflatoxin levels prior to crop harvest is useful for minimizing the health and financial impact of a contaminated crop. Consequently, there is interest in developing a tool that predicts aflatoxin levels based on topography and soil analysis data of fig orchards. This paper describes the development of a risk assessment tool for the contamination of aflatoxin on dried figs, based on the location and altitude of the fig orchards, the population of the fungus Aspergillus spp. in the soil, and soil parameters such as pH, saturation percentage (SP), electrical conductivity (EC), organic matter, particle size analysis (sand, silt, clay), the concentration of the exchangeable cations (Ca, Mg, K, Na), extractable P, and trace of elements (B, Fe, Mn, Zn and Cu), by employing machine learning methods. In particular, our proposed method integrates three machine learning techniques, i.e., dimensionality reduction on the original dataset (principal component analysis), metric learning (Mahalanobis metric for clustering), and k-nearest neighbors learning algorithm (KNN), into an enhanced model, with mean performance equal to 85% by terms of the Pearson correlation coefficient (PCC) between observed and predicted values.

Keywords: aflatoxins, Aspergillus spp., dried figs, k-nearest neighbors, machine learning, prediction

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Authors: Shehu Isyaku

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The general objective of the study was to investigate ‘the relationship between the external business environment and the sustainability of micro, small and medium enterprises (MSMEs) in Jigawa state’, Nigeria. Specifically, the study was to examine the relationship between 1) the economic environment, 2) the social environment, 3) the technological environment, and 4) the political environment and the sustainability of MSMEs in Jigawa state, Nigeria. The study was drawn on Resource-Based View (RBV) Theory and Knowledge-Based View (KBV). The study employed a descriptive cross-sectional survey design. A researcher-made questionnaire was used to collect data from the 350 managers/owners who were selected using stratified, purposive and simple random sampling techniques. Data analysis was done using means and standard deviations, factor analysis, Correlation Coefficient, and Pearson Linear Regression analysis. The findings of the study revealed that the sustainability potentials of the managers/owners were rated as high potential (economic, environmental, and social sustainability using 5 5-point Likert scale. Mean ratings of effectiveness of the external business environment were; as highly effective. The results from the Pearson Linear Regression Analysis rejected the hypothesized non-significant effect of the external business environment on the sustainability of MSMEs. Specifically, there is a positive significant relationship between 1) economic environment and sustainability; 2) social environment and sustainability; 3) technological environment and sustainability and political environment and sustainability. The researcher concluded that MSME managers/owners have a high potential for economic, social and environmental sustainability and that all the constructs of the external business environment (economic environment, social environment, technological environment and political environment) have a positive significant relationship with the sustainability of MSMEs. Finally, the researcher recommended that 1) MSME managers/owners need to develop marketing strategies and intelligence systems to accumulate information about the competitors and customers' demands, 2) managers/owners should utilize the customers’ cultural and religious beliefs as an opportunity that should be utilized while formulating business strategies.

Keywords: business environment, sustainability, small and medium enterprises, external business environment

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