Search results for: food science

Authors: Chun Chen Yea, Wen Huei Chou

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Many chemical changes in the atmosphere and the ocean are invisible to the naked eye, but they have profound impacts. These changes not only confirm the phenomenon of global carbon pollution, but also forewarn that more changes are coming. The carbon dioxide gases emitted from the burning of fossil fuels dissolve into the ocean and chemically react with seawater to form carbonic acid, which increases the acidity of the originally alkaline seawater. This gradual acidification is occurring at an unprecedented rate and will affect the effective formation of carapace of some marine organisms such as corals and crustaceans, which are almost entirely composed of calcium carbonate. The carapace of these organisms will become more dissoluble. Acidified seawater not only threatens the survival of marine life, but also negatively impacts the global ecosystem via the food chain. Faced with the threat of ocean acidification, all humans are duty-bound. The industrial sector outputs the highest level of carbon dioxide emissions in Taiwan, and the petrochemical industry is the major contributor. Ever since the construction of Formosa Plastics Group's No. 6 Naphtha Cracker Plant in Yunlin County, there have been many environmental concerns such as air pollution and carbon dioxide emission. The marine life along the coast of Yunlin is directly affected by ocean acidification arising from the carbon emissions. Societal change demands our willingness to act, which is what social advocacy promotes. This study uses digital storytelling for social advocacy and ocean acidification as the subject of a visual narrative in visualization to demonstrate the subsequent promotion of social advocacy. Storytelling can transform dull knowledge into an engaging narrative of the crisis faced by marine life. Digital dissemination is an effective social-work practice. The visualization promoting awareness on ocean acidification disseminated via social media platforms, such as Facebook and Instagram. Social media enables users to compose their own messages and share information across different platforms, which helps disseminate the core message of social advocacy.

Keywords: digital storytelling, visualization, ocean acidification, social advocacy

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Authors: Naohiro Nakamura

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Analysis methods to accurately estimate the behavior of buildings when earthquakes occur is very important for improving the seismic safety of such buildings. Recently, the use of damping devices has increased significantly and there is a particular need to appropriately evaluate the behavior of buildings with such devices during earthquakes in the design stage. At present, however, the accuracy of the analysis evaluations is not sufficient. One reason is that the accuracy of current analysis methods has not been appropriately verified because there is very limited data on the behavior of actual buildings during earthquakes. Many types of shaking table test of large structures are performed at the '3-Dimensional Full-Scale Earthquake Testing Facility' (nicknamed 'E-Defense') operated by the National Research Institute of Earth Science and Disaster Prevention (NIED). In this study, simulations using 3- dimensional analysis models were conducted on shaking table test of a 5-story steel-frame structure with dampers. The results of the analysis correspond favorably to the test results announced afterward by the committee. However, the suitability of the parameters and models used in the analysis and the influence they had on the responses remain unclear. Hence, we conducted additional analysis and studies on these models and parameters. In this paper, outlines of the test are shown and the utilized analysis model is explained. Next, the analysis results are compared with the test results. Then, the additional analyses, concerning with the hysteresis curve of the dampers and the beam-end stiffness of the frame, are investigated.

Keywords: three-dimensional analysis, E-defense, full-scale experimen, vibration control damper

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Authors: Singh Baljinder, Sharma Navneet

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Foeniculum vulgare Miller is a biennial medicinal and aromatic plant belonging to the family Apiaceae (Umbelliferaceae). It is a hardy, perennial–umbelliferous herb with yellow flowers and feathery leaves. The aim is to study the control of blood glucose in alloxan induced diabetic mice.Method used for extraction was continuous hot percolation method in which Soxhlet apparatus was used.95%ethanol was used as solvent. Male albino mice weighing about 20-25 g obtained from Guru Angad Dev University of Veterinary Science, Ludhiana were used for the study. Diabetes was induced by a single i.p. injection of 125 mg/kg of alloxan monohydrate in sterile saline (11). After 48 h, animals with serum glucose level above 200 mg/dl (diabetic) were selected for the study. Blood samples from mice were collected by retro-orbital puncture (ROP) technique. Serum glucose levels were determined by glucose oxidase and peroxidase method. Single administration (single dose) of aqueous extract of fennel (25, 50, and 100 mg/kg, p.o.) in diabetic Swiss albino mice, showed reduction in serum glucose level after 45 min. Maximum reduction in serum glucose level was seen at doses of 100 mg/kg. Aqueous extract of fennel in all doses except 25 mg/kg did not cause any significant decrease in blood glucose. It may be said that the aqueous extract of fennel decreased the serum glucose level and improved glucose tolerance owing to the presence of aldehyde moiety. The aqueous extract of fennel has antihyperglycemic activity as it lowers serum glucose level in diabetic mice.

Keywords: Foeniculum vulgare Miller, antihyperglycemic, diabetic mice, Umbelliferaceae

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Authors: Yi-Fung Lin, Yuan-Mei Liao

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Background: Pain is common among patients with cancer and is also one of the most disturbing symptoms. As this suffering is subjective, if patients proactively participate in their pain self-management, pain could be alleviated effectively. However, not everyone can carry out self-management very well because human behavior is a product of the cognition process. In this process, we can see that "self-efficacy" plays an essential role in affecting human behaviors. Methods: We used the eight steps of concept analysis proposed by Walker and Avant to clarify the concept of “self-efficacy for cancer pain management.” A comprehensive literature review was conducted for relevant publications that were published during the period of 1977 to 2021. We used several keywords, including self-efficacy, self-management, concept analysis, conceptual framework, and cancer pain, to search the following databases: PubMed, CINAHL, Web of Science, and Embase. Results: We identified three defining attributes for the concept of self-efficacy for cancer pain management, including pain management abilities, confidence, and continuous pain monitoring, and recognized six skills related to pain management abilities: problem-solving, decision-making, resource utilization, forming partnerships between medical professionals and patients, planning actions, and self-regulation. Five antecedents for the concept of self-efficacy for cancer pain management were identified: pain experience, existing cancer pain, pain-related knowledge, a belief in pain management, and physical/mental state. Consequences related to self-efficacy for cancer pain management were achievement of pain self-management, well pain control, satisfying quality of life, and containing motivation. Conclusions: This analysis provides researchers with a clearer understanding of the concept of “self-efficacy for cancer pain management.” The findings presented here provide a foundation for future research and nursing interventions to enhance self-efficacy for cancer pain management.

Keywords: cancer pain, concept analysis, self-efficacy, self-management

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Authors: Iraj Rezaei, Kamal Al Din Niknami

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Tapeh Zagheh is an important prehistoric site located in the central plateau of Iran, which has settlement layers of the Neolithic and Chalcolithic periods. For this research, 38 soil samples were collected from different parts of the site, as well as two samples from its outside as witnesses. Then the samples were analyzed by XRF. The purpose of this research was to identify some places with special usage for human activities in Tapeh Zagheh by measuring the amount of some special elements in the soil. The result of XRF analysis shows a significant amount of P and K in samples No.3 (fourth floor) and No.4 (third floor), probably due to certain activities such as food preparation and consumption. Samples No.9 and No.10 can be considered suitable examples of the hearths of the prehistoric period in the central plateau of Iran. The color of these samples was completely darkened due to the presence of ash, charcoal, and burnt materials. According to the XRF results, the soil of these hearths has very high amounts of elements such as P, Ca, Mn, S, K, and significant amounts of Ti, Fe, and Na. In addition, the elemental composition of sample No. 14, which was taken from a home waster, also has very high amounts of P, Mn, Mg, Ti, and Fe and high amounts of K and Ca. Sample No. 11, which is related to soil containing large amounts of waster of the kiln, along with a very strong increase in Cl and Na, the amount of elements such as K, Mg, and S has also increased significantly. It seems that the reason for the increase of elements such as Ti and Fe in some Tapeh Zagheh floors (for example, samples number 1, 2, 3, 4, 5) was the use of materials such as ocher mud or fire ash in the composition of these floors. Sample No. 13, which was taken from an oven located in the FIX trench, has very high amounts of Mn, Ti, and Fe and high amounts of P and Ca. Sample No. 15, which is related to House No. VII (probably related to a pen or a place where animals were kept) has much more phosphate compared to the control samples, which is probably due to the addition of animal excrement and urine to the soil. Sample No. 29 was taken from the north of the industrial area of Zagheh village (place of pottery kilns). The very low amount of index elements in sample No. 29 shows that the industrial activities did not extend to the mentioned point, and therefore, the range of this point can be considered as the boundary between the residential part of the Zagheh village and its industrial part.

Keywords: prehistory, multi-elemental analysis, Tapeh Zagheh, XRF

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Authors: N. W. I. A. Jayawardana, W. A. T. A. Jayalath, W. M. T. Madhujith, U. Ralapanawa, R. S. Jayasekera, S. A. S. B. Alagiyawanna, A. M. K. R. Bandara, N. S. Kalupahana

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There is mounting evidence to the effect that dietary and lifestyle changes affect the incidence of non-communicable diseases (NCDs). This study was conducted to investigate the association of diet, physical activity, smoking, alcohol consumption and duration of sleep with overweight, obesity, hypertension and diabetes in a cohort of males from the Central Province of Sri Lanka. A total of 2694 individuals aged between 17 – 68 years (Mean = 31) were included in the study. Body Mass Index cutoff values for Asians were used to categorize the participants as normal, overweight and obese. The dietary data were collected using a food frequency questionnaire [FFQ] and data on the level of physical activity, smoking, alcohol consumption and sleeping hours were obtained using a self-administered validated questionnaire. Systolic and diastolic blood pressure, random blood glucose levels were measured to determine the incidence of hypertension and diabetes. Among the individuals, the prevalence of overweight and obesity were 34% and 16.4% respectively. Approximately 37% of the participants suffered from hypertension. Overweight and obesity were associated with older age men (P<0.0001), frequency of smoking (P=0.0434), alcohol consumption level (P=0.0287) and the quantity of lipid intake (P=0.0081). Consumption of fish (P=0.6983) and salty snacks (P=0.8327), sleeping hours (P=0.6847) and the level of physical activity were not significantly (P=0.3301) associated with the incidence of overweight and obesity. Based on the fitted model, only age was significantly associated with hypertension (P < 0.001). Further, age (P < 0.0001), sleeping hours (P=0.0953) and consumption of fatty foods (P=0.0930) were significantly associated with diabetes. Age was associated with higher odds of pre diabetes (OR:1.089;95% CI:1.053,1.127) and diabetes (OR:1.077;95% CI:1.055,1.1) whereas 7-8 hrs. of sleep per day was associated with lesser odds of diabetes (OR:0.403;95% CI:0.184,0.884). High prevalence of overweight, obesity and hypertension in working-age males is a threatening sign for this area. As this population ages in the future and urbanization continues, the prevalence of above risk factors will likely to escalate.

Keywords: age, males, non-communicable diseases, obesity

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Authors: Mehwish Asghar

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Breast Cancer (BC) is a common type of cancer among women. Its screening is usually performed using different imaging modalities such as magnetic resonance imaging, mammogram, X-ray, CT, etc. Among these modalities’ mammogram is considered a powerful tool for diagnosis and screening of breast cancer. Sophisticated machine learning approaches have shown promising results in complementing human diagnosis. Generally, machine learning methods can be divided into two major classes: one is Radiomics analysis (RA), where image features are extracted manually; and the other one is the concept of convolutional neural networks (CNN), in which the computer learns to recognize image features on its own. This research aims to improve the incidence of early detection, thus reducing the mortality rate caused by breast cancer through the latest advancements in computer science, in general, and machine learning, in particular. It has also been aimed to ease the burden of doctors by improving and automating the process of breast cancer detection. This research is related to a relative analysis of different techniques for the implementation of different models for detecting and classifying breast cancer. The main goal of this research is to provide a detailed view of results and performances between different techniques. The purpose of this paper is to explore the potential of a convolutional neural network (CNN) w.r.t feature extractor and as a classifier. Also, in this research, it has been aimed to add the module of Radiomics for comparison of its results with deep learning techniques.

Keywords: breast cancer (BC), machine learning (ML), convolutional neural network (CNN), radionics, magnetic resonance imaging, artificial intelligence

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Authors: Alexander Musyoki, Collins Odour

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Over the past few years, the bakery industry in Kenya has experienced significant growth largely in part to the increased adoption of technology and automation in their processes; more specifically due to the adoption of bakery management systems to help in running bakeries. While they have been largely responsible for the improved productivity and efficiency in bakeries, most of them are now outdated and pose more challenges than benefits. The proposed online bakery management system mentioned in this paper aims to address this by allowing bakery owners to track inventory, budget, job progress, and data analytics on each job and in doing so, promote the Sustainable Development Goals 3 and 12, which aim to ensure healthy lives and promote sustainable economic growth as the proposed benefits of these features include scalability, easy accessibility, reduced acquisition costs, better reliability, and improved functionality that will allow bakeries to become more competitive, reduce waste and track inventory more efficiently. To better understand the challenges, a comprehensive study has been performed to assess these traditional systems and try to understand if an online bakery management system can prove to be advantageous to bakery owners. The study conducted gathered feedback from bakery owners and employees in Nairobi County, Kenya using an online survey with a response rate of about 86% from the target population. The responses cited complex and hard to use bakery management systems (59.7%), lack of portability from one device to the other (58.1%) and high acquisition costs (51.6%) as the top challenges of traditional bakery management systems. On the other hand, some of the top benefits that most of the respondents would realize from the online bakery management system was better reliability (58.1%) and reduced acquisition costs (58.1%). Overall, the findings suggest that an online bakery management system has a lot of advantages over traditional systems and is likely to be well-received in the market. In conclusion, the proposed online bakery management system has the potential to improve the efficiency and competitiveness of small-sized bakeries in Nairobi County. Further research is recommended to expand the sample size and diversity of respondents and to conduct more in-depth analyses of the data collected.

Keywords: ICT, technology and automation, bakery management systems, food innovation

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Authors: Muhammad Saleem

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Background: Inattentive food choices and engagement in excessive physical activities by male athletes can potentially lead to adverse health consequences. Objective: The aim was to ascertain the occurrence of risk factors associated with the Male Athlete Triad among young elite athletes in Pakistan. Methodology: In 2018, a cross-sectional study based on questionnaires was conducted at the Pakistan Sports Board. The study aimed to explore the risk factors related to the Male Athlete Triad in young elite athletes who were part of national training camps in major metropolitan areas. The study included proficient male elite athletes aged 18 to 25 years, capable of understanding the English questionnaire. The athletes completed a survey encompassing aspects like demographic information, educational background, Body Mass Index (BMI), sports involvement, and hours of participation. Additionally, they filled out the Eating Attitude Test-26 (EAT-26) and questionnaires assessing risks of amenorrhea and low bone mineral density. The prevalence of risk factors for each of the three components was individually evaluated. The collected data underwent analysis using SPSS-20, with descriptive statistics being applied. Results: The study comprised a sample of 90 elite athletes (mean age: 23.57 ± 2.37 years, mean BMI: 21.97 ± 1.90) engaged in various sports. The EAT-26 results indicated that 50% of athletes were at risk of developing an eating disorder. Moreover, 83.3% exhibited disordered eating behaviors that necessitated referral. Risks for amenorrhea were observed in 15% of the participants, and regarding low bone mineral density, notable risks were absent except for the consumption of caffeinated beverages, which was noted in 51.7% of participants. Conclusion: The study identified a significant prevalence of disordered eating risk among male elite athletes in Pakistan. However, the risks associated with amenorrhea and low bone mineral density were not a major concern in this particular group.

Keywords: 1. health and physical education risk factors male athlete associated with the male athlete traid in young elite athlete from pakistan., 2. sports sciences pakistan, 3. risk factors sports sciences pakistan, 4. triad and young elite athlete from pakistan

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Authors: Godfrey Muiya Mukala

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This research looks at an array of fields in Sub-Saharan Africa comprising agriculture, food enterprises, medicine, organisms genetically modified, microbiology, and nanotechnology that can be gained from biotechnological research and development. Findings into dangerous organisms, mainly bacterial germs, rickettsia, fungi, parasites, or organisms that are genetically engineered, have immensely posed questions attributed to the biological danger they bring forth to human beings and the environment because of their uncertainties. In addition, the recurrence of previously managed diseases or the inception of new diseases are connected to biosafety challenges, especially in rural set-ups in low and middle-income countries. Notably, biotechnology laboratories are required to adopt biosafety measures to protect their workforce, community, environment, and ecosystem from unforeseen materials and organisms. Sensitization and inclusion of educational frameworks for laboratory workers are essential to acquiring a solid knowledge of harmful biological agents. This is in addition to human pathogenicity, susceptibility, and epidemiology to the biological data used in research and development. This article reviews and analyzes research intending to identify the proper implementation of universally accepted practices in laboratory safety and biological hazards. This research identifies ideal microbiological methods, adequate containment equipment, sufficient resources, safety barriers, specific training, and education of the laboratory workforce to decrease and contain biological hazards. Subsequently, knowledge of standardized microbiological techniques and processes, in addition to the employment of containment facilities, protective barriers, and equipment, is far-reaching in preventing occupational infections. Similarly, reduction of risks and prevention may be attained by training, education, and research on biohazards, pathogenicity, and epidemiology of the relevant microorganisms. In this technique, medical professionals in rural setups may adopt the knowledge acquired from the past to project possible concerns in the future.

Keywords: sub-saharan africa, biotechnology, laboratory, infections, health

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Authors: Vesna Bosilj Vukšić, Lucija Ivančić, Dalia Suša Vugec

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While struggling to succeed in today’s complex market environment and provide better customer experience and services, enterprises encompass digital transformation as a means for reaching competitiveness and foster value creation. A digital transformation process consists of information technology implementation projects, as well as organizational factors such as top management support, digital transformation strategy, and organizational changes. However, to the best of our knowledge, there is little evidence about digital transformation endeavors in organizations and how they perceive it – is it only about digital technologies adoption or a true organizational shift is needed? In order to address this issue and as the first step in our research project, a literature review is conducted. The analysis included case study papers from Scopus and Web of Science databases. The following attributes are considered for classification and analysis of papers: time component; country of case origin; case industry and; digital transformation concept comprehension, i.e. focus. Research showed that organizations – public, as well as private ones, are aware of change necessity and employ digital transformation projects. Also, the changes concerning digital transformation affect both manufacturing and service-based industries. Furthermore, we discovered that organizations understand that besides technologies implementation, organizational changes must also be adopted. However, with only 29 relevant papers identified, research positioned digital transformation as an unexplored and emerging phenomenon in information systems research. The scarcity of evidence-based papers calls for further examination of this topic on cases from practice.

Keywords: digital strategy, digital technologies, digital transformation, literature review

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Authors: Habes Moh’d Khalifeh Hatamleh, Shukri Refai Ibrahim Marashdh

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The study came with the aim of identifying the most prominent quantitative, qualitative, and technological challenges facing the higher education system in Jordan as a dilemma in light of the technological revolution that had a radical contribution to changing the face of science and knowledge in various fields of higher education in Jordan. Human societies that require the adoption of scientific research and its basics as a clear entrance aimed at serving the community and upgrading it civilly. The number of private and public universities has increased, and many students have been accepted for all levels of study in the bachelor’s, higher diploma, master’s and doctoral programs, and the quantitative growth has been accompanied by many negatives, which requires renewal and development in the field of higher education, which led to the emergence of many challenges, and the qualitative challenge in terms of relevance, quality and goodness constitutes an important requirement for the improvement of teaching, scientific research and services in light of the social demand for higher education, in order to reach the quality. The real challenge facing our country is to enter the civilization of advanced technology, which has become the main factor and the starting point for preparing staff capable of accomplishing this transformation and creating an appropriate educational environment for the student to help him to use the sources of knowledge. This study can provide a set of recommendations and proposals that may contribute to addressing challenges and contributing to improving educational outcomes in light of the requirements of the labor market and the needs of society.

Keywords: quantitative, qualitative, technological, challenges, higher education

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Authors: Habes Moh’d Khalifeh Hatamleh, Shukri Refai Ibrahim Marashdh

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The study came with the aim of identifying the most prominent quantitative, qualitative, and technological challenges facing the higher education system in Jordan as a dilemma in light of the technological revolution that had a radical contribution to changing the face of science and knowledge in various fields of higher education in Jordan. Human societies that require the adoption of scientific research and its basics as a clear entrance aimed at serving the community and upgrading it civilly. The number of private and public universities has increased, and many students have been accepted for all levels of study in the bachelor’s, higher diploma, master’s and doctoral programs, and the quantitative growth has been accompanied by many negatives, which requires renewal and development in the field of higher education, which led to the emergence of many challenges, and the qualitative challenge in terms of relevance, quality and goodness constitutes an important requirement for the improvement of teaching, scientific research and services in light of the social demand for higher education, in order to reach the quality. The real challenge facing our country is to enter the civilization of advanced technology, which has become the main factor and the starting point for preparing staff capable of accomplishing this transformation and creating an appropriate educational environment for the student to help him to use the sources of knowledge. This study can provide a set of recommendations and proposals that may contribute to addressing challenges and contributing to improving educational outcomes in light of the requirements of the labor market and the needs of society.

Keywords: quantitative, qualitative, technological, challenges, higher education

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Authors: Hui-Fang Lee, Meng-Chu Liu, Wen-Chi Lu, Hsuan-Jung Hsieh

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The purpose of the study was to examine the effect of health program on the fitness ability of abnormal BMI students of Ching-Yun University of Science and Technology. In order to achieve this purpose, self-regulation theory and dietary education were applied, and the effect of 10-week sports activities and three-day diet records on pre-test and post-test of fitness activities was analyzed. There were 40 original participants. Then, nine people who were with normal BMI, low attendance or unfinished fitness test were eliminated from this research. The valid samples were 31 (77.5%) participants. The fitness activities included sit-bending, one minute sit-up, standing long jump, and three-minute stage boarding. The averages of three-day diet records were compared, and differences of pre-test and post-test of the four fitness activities were analyzed with paired-samples t test. The results showed that there was a significant difference between pre-test and post of male students’ BMI and one minute sit-up. Females’ sit-bending and one minute sit-up had the same effect. Females had high fat intake in three-day diet records. The research showed that the use of self-regulation theory and dietary education, the implementation of sports activities and three-day diet records could significantly enhance the physical fitness indicators or effects. While in the course of sports, we should guide students to think about the gap between self-behavior and ideal behavior, then realize the main reasons and improving methods, and finally go towards the goal and improve the effect of physical fitness.

Keywords: self-regulation theory, dietary education, three-day diet records, physical fitness

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Authors: R. N. Pateriya, T. K. Bhattacharya

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In India, rice-wheat cropping system occupies the major area and contributes about 40% of the country’s total food grain production. It is necessary that production of rice and wheat must keep pace with growing population. However, various factors such as degradation in natural resources, shift in cropping pattern, energy constraints etc. are causing reduction in the productivity of these crops. Seedbed for rice after wheat is difficult to prepare due to presence of straw and stubbles, and require excessive tillage operations to bring optimum tilth. In addition, delayed sowing and transplanting of rice is mainly due to poor crop residue management, multiplicity of tillage operations and non-availability of the power source. With increasing concern for fuel conservation and energy management, farmers might wish to estimate the best cultivation system for more productivity. The widest spread method of tilling land is ploughing with mould board plough. However, with the mould board plough upper layer of soil is neither always loosened at the desired extent nor proper mixing of different layers are achieved. Therefore, additional operations carried out to improve tilth. The farmers are becoming increasingly aware of the need for minimum tillage by minimizing the use of machines. Soil management can be achieved by using the combined active-passive tillage machines. A study was therefore, undertaken in wheat-harvested field to study the impact of conventional and modified tillage practices on paddy crop cultivation. Tillage treatments with tractor as a power source were selected during the experiment. The selected level of tillage treatments of tractor machinery management were (T1:- Direct Sowing of Rice), (T2:- 2 to 3 harrowing and no Puddling with manual transplanting), (T3:- 2 to 3 harrowing and Puddling with paddy harrow with manual transplanting), (T4:- 2 to 3 harrowing and Puddling with Rotavator with manual transplanting). The maximum output was obtained with treatment T1 (7.85 t/ha)) followed by T4 (6.4 t/ha), T3 (6.25 t/ha) and T2 (6.0 t/ha)) respectively.

Keywords: crop residues, cropping system, minimum tillage, yield

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Authors: Wale Agbaje

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The aim of this research study is to assess the impact of financial statement fraud on profitability of some selected Nigerian manufacturing firms covering (2002-2016). The specific objectives focused on to ascertain the effect of incorrect asset valuation on return on assets (ROA) and to ascertain the relationship between improper expense recognition and return on assets (ROA). To achieve these objectives, descriptive research design was used for the study while secondary data were collected from the financial reports of the selected firms and website of security and exchange commission. The analysis of covariance (ANCOVA) was used and STATA II econometric method was used in the analysis of the data. Altman model and operating expenses ratio was adopted in the analysis of the financial reports to create a dummy variable for the selected firms from 2002-2016 and validation of the parameters were ascertained using various statistical techniques such as t-test, co-efficient of determination (R2), F-statistics and Wald chi-square. Two hypotheses were formulated and tested using the t-statistics at 5% level of significance. The findings of the analysis revealed that there is a significant relationship between financial statement fraud and profitability in Nigerian manufacturing industry. It was revealed that incorrect assets valuation has a significant positive relationship and so also is the improper expense recognition on return on assets (ROA) which serves as a proxy for profitability. The implication of this is that distortion of asset valuation and expense recognition leads to decreasing profit in the long run in the manufacturing industry. The study therefore recommended that pragmatic policy options need to be taken in the manufacturing industry to effectively manage incorrect asset valuation and improper expense recognition in order to enhance manufacturing industry performance in the country and also stemming of financial statement fraud should be adequately inculcated into the internal control system of manufacturing firms for the effective running of the manufacturing industry in Nigeria.

Keywords: Althman's Model, improper expense recognition, incorrect asset valuation, return on assets

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Authors: S. Zith Dey Babu, S. Kour, S. Verma, C. Verma, V. Pathania, A. Agrawal, V. Chaudhary, A. Manoj Puthur, R. Goyal, A. Pal, T. Danti Dey, A. Kumar, K. Wadhwa, O. Ved

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Background: Skin cancer is now is the buzzing button in the field of medical science. The cyst's pandemic is drastically calibrating the body and well-being of the global village. Methods: The extracted image of the skin tumor cannot be used in one way for diagnosis. The stored image contains anarchies like the center. This approach will locate the forepart of an extracted appearance of skin. Partitioning image models has been presented to sort out the disturbance in the picture. Results: After completing partitioning, feature extraction has been formed by using genetic algorithm and finally, classification can be performed between the trained and test data to evaluate a large scale of an image that helps the doctors for the right prediction. To bring the improvisation of the existing system, we have set our objectives with an analysis. The efficiency of the natural selection process and the enriching histogram is essential in that respect. To reduce the false-positive rate or output, GA is performed with its accuracy. Conclusions: The objective of this task is to bring improvisation of effectiveness. GA is accomplishing its task with perfection to bring down the invalid-positive rate or outcome. The paper's mergeable portion conflicts with the composition of deep learning and medical image processing, which provides superior accuracy. Proportional types of handling create the reusability without any errors.

Keywords: computer-aided system, detection, image segmentation, morphology

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Authors: Sengly Sroy, Elodie Arnaud, Adrien Servent, Sokneang In, Sylvie Avallone

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In Cambodia, fish plays an important role for local community in term of food habits, preference and contribution to several nutritional intakes. Consumed on a daily basis, fishes and their derivatives products are good sources of proteins, essential fatty acids and fat-soluble vitamins. They mainly obtain from the Tonle Sap Lake but, during the last decade, the fish population decreased drastically due to climate change and human activities as well. Contamination by agricultural residues and heavy metals were identified. However, fishes are currently used in several nutrition programs for children and pregnant women to improve their nutritional status. The aim of our work was to characterize the nutritional profile and contamination of 10 fish species consumed near the Tonle Sap Lake with a special attention to fatty acid and fat-soluble vitamin profiles. Fish samples were analyzed for their nutritional profiles (AOAC methods for macronutrients and micronutrients), their lipid content (Folch modified method), their Fatty acid (FAME method), their vitamin A (HPLC) and their heavy metals (ICP-MS). The total lipid contents ranged from 1.43 to 10.00% according to fish species. Lipid profile was mainly dominated by saturated fat (from 47.95 to 57.32%) but some fish species were particularly rich in ω-3 and ω-6 especially eicosapentaenoic acid EPA (3.05%) and docosahexaenoic acid DHA (2.82%). The more the fishes were fats, the more they contained vitamin A, DHA and EPA. Vitamin A is particularly abundant in small fishes (250.10 μg RE/100 g) compare to big ones (13.77 μg RE/100 g) because they are consumed as a whole with their organs (liver) and head. However, the contents of heavy metal in some species are higher than the maximum permitted level (MPL) from codex alimentarius, especially Mn. The results obtained provided important information on the most interesting fish in term of human nutrition and the potential risk of contaminants. The fatty acids are important for child development and pregnant women. These data are useful for supply chain stakeholders and the people in charge of nutrition program.

Keywords: fat-soluble vitamin, fatty acid, freshwater fish, lipid content, Tonle Sap Lake

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Authors: Abha Cherkani Hassani, Imane Ghanname, Nezha Mouane

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Background: This is the first systematic review summarizing 43 years of research from 36 countries in the assessment of cadmium in breast milk; a suitable matrix in human biomonitoring. Objectives: To report from the published literature the levels of cadmium in breast milk and the affecting factors causing the increase of cadmium concentrations; also to gather several quantitative data which might be useful to evaluate the international degrees of maternal and infant exposure. Methods: We reviewed the literature for studies reporting quantitative data about cadmium levels in human breast milk in the world that have been published between 1971 and 2014 and that are available on Pubmed, Science direct and Google scholar. The aim of the study, country, period of samples collection, size of samples, sampling method, time of lactation, mother’s age, area of residence, cadmium concentration and other information were extracted. Results: 67 studies were selected and included in this systematic review. Some concentrations greatly exceed the limit of the WHO, However about 50% of the studies had less than 1 µg/l cadmium concentration (the recommendation of the WHO); as well many factors have shown their implication in breast milk contamination by Cadmium as lactation stage, smoking, diet, supplement intake, interaction with other mineral elements, age of mothers, parity and other parameters. Conclusion: Breast milk is a pathway of maternal excretion of cadmium. It is also a biological indicator of the degree of environmental pollution and cadmium exposure of the lactating women and the nourished infant. Therefore preventive measures and continuous monitoring are necessary.

Keywords: breast milk, cadmium level, factors, systematic review

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Authors: Lohendy Munoz-Vargas, Stephen O. Opiyo, Rose Digianantonio, Michele L. Williams, Asela Wijeratne, Gregory Habing

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Non-typhoidal Salmonella enterica is a zoonotic pathogen with critical importance in animal and public health. The persistence of Salmonella on farms affects animal productivity and health, and represents a risk for food safety. The intestinal microbiota plays a fundamental role in the colonization and invasion of this ubiquitous microorganism. To overcome the colonization resistance imparted by the gut microbiome, Salmonella uses invasion strategies and the host inflammatory response to survive, proliferate, and establish infections with diverse clinical manifestations. Cattle serve as reservoirs of Salmonella, and periparturient cows have high prevalence of Salmonella shedding; however, to author`s best knowledge, little is known about the association between the gut microbiome and the onset of Salmonella shedding during the periparturient period. Thus, the objective of this study was to assess the association between changes in bacterial communities and the onset of Salmonella shedding in cattle approaching parturition. In a prospective cohort study, fecal samples from 98 dairy cows originating from four different farms were collected at four time points relative to calving (-3 wks, -1 wk, +1 wk, +3 wks). All 392 samples were cultured for Salmonella. Sequencing of the V4 region of the 16S rRNA gene using the Illumina platform was completed to evaluate the fecal microbiome in a selected sample subset. Analyses of microbial composition, diversity, and structure were performed according to time points, farm, and Salmonella onset status. Individual cow fecal microbiomes, predominated by Bacteroidetes, Firmicutes, Spirochaetes, and Proteobacteria phyla, significantly changed before and after parturition. Microbial communities from different farms were distinguishable based on multivariate analysis. Although there were significant differences in some bacterial taxa between Salmonella positive and negative samples, our results did not identify differences in the fecal microbial diversity or structure for cows with and without the onset of Salmonella shedding. These data suggest that determinants other than the significant changes in the fecal microbiome influence the periparturient onset of Salmonella shedding in dairy cattle.

Keywords: dairy cattle, microbiome, periparturient, Salmonella

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Authors: Maria A. Castillo H., Andres R. Leandro, Jose F. Bienvenido B.

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In 2015, Guatemala officially adopted the Sustainable Development Goals (SDG) according to the 2030 Agenda agreed by the United Nations Organization. In 2016, these objectives and goals were reviewed, and the National Priorities were established within the K'atún 2032 National Development Plan. In 2019 and 2021, progress was evaluated with 120 defined indicators, and the need to improve quality and availability of statistical data necessary for the analysis of sustainability indicators was detected, so the values to be reached in 2024 and 2032 were adjusted. The need for greater agricultural technology is one of the priorities established within SDG 2 "Zero Hunger". Within this area, protected agricultural production provides greater productivity throughout the year, reduces the use of chemical products to control pests and diseases, reduces the negative impact of climate and improves product quality. During the crisis caused by Covid-19, there was an increase in exports of fruits and vegetables produced in greenhouses from Guatemala. However, this information has not been considered in the 2021 revision of the Plan. The objective of this study is to evaluate the information available on Greenhouse Agricultural Production and its integration into the Sustainability Indicators for Guatemala. This study was carried out in four phases: 1. Analysis of the Goals established for SDG 2 and the indicators included in the K'atún Plan. 2. Analysis of Environmental, Social and Economic Indicator Models. 3. Definition of territorial levels in 2 geographic scales: Departments and Municipalities. 4. Diagnosis of the available data on technological agricultural production with emphasis on Greenhouses at the 2 geographical scales. A summary of the results is presented for each phase and finally some recommendations for future research are added. The main contribution of this work is to improve the available data that allow the incorporation of some agricultural technology indicators in the established goals, to evaluate their impact on Food Security and Nutrition, Employment and Investment, Poverty, the use of Water and Natural Resources, and to provide a methodology applicable to other production models and other geographical areas.

Keywords: greenhouses, protected agriculture, sustainable indicators, Guatemala, sustainability, SDG

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Authors: Akhila Vasudev, Himanshu Kaushik, Tadikonda Venkata Bharat

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A large number of mine tailings are produced every year as part of the extraction process of phosphates, gold, copper, and other materials. Mine tailings are high in water content and have very slow dewatering behavior. The efficient design of tailings dam and economical disposal of these slurries requires the knowledge of tailings consolidation behavior. The large-strain consolidation theory closely predicts the self-weight consolidation of these slurries as the theory considers the conservation of mass and momentum conservation and considers the hydraulic conductivity as a function of void ratio. Classical laboratory techniques, such as settling column test, seepage consolidation test, etc., are expensive and time-consuming for the estimation of hydraulic conductivity variation with void ratio. Inverse estimation of the constitutive relationships from the measured settlement versus time curves is explored. In this work, inverse analysis based on metaheuristics techniques will be explored for predicting the hydraulic conductivity parameters for mine tailings from the base excess pore water pressure dissipation curve and the initial conditions of the mine tailings. The proposed inverse model uses particle swarm optimization (PSO) algorithm, which is based on the social behavior of animals searching for food sources. The finite-difference numerical solution of the forward analytical model is integrated with the PSO algorithm to solve the inverse problem. The method is tested on synthetic data of base excess pore pressure dissipation curves generated using the finite difference method. The effectiveness of the method is verified using base excess pore pressure dissipation curve obtained from a settling column experiment and further ensured through comparison with available predicted hydraulic conductivity parameters.

Keywords: base excess pore pressure, hydraulic conductivity, large strain consolidation, mine tailings

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Authors: Baker Ssekitto, Ambrose Mbogo

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The study reveals that indeed agriculture employs over 70% of Uganda’s population, of which majority are youth and women. The study further reveals that over 70% of the farmers are smallholder farmers based in rural areas, whose operations are greatly affected by; climate change, weak digital skills, limited access to productivity knowledge along value chains, limited access to quality farm inputs, weak logistics systems, limited access to quality extension services, weak business intelligence, limited access to quality markets among others. It finds that the emerging 4th industrial revolution powered by artificial intelligence, 5G and data science will provide possibilities of addressing some of these challenges. Furthermore, the study finds that despite rapid development of ICT4Agric Innovation, their uptake is constrained by a number of factors including; limited awareness of these innovations, low internet and smart phone penetration especially in rural areas, lack of appropriate digital skills, inappropriate programmes implementation models which are project and donor driven, limited articulation of value addition to various stakeholders among others. Majority of farmers and other value chain actors lacked knowledge and skills to harness the power of ICTs, especially their application of ICTs in monitoring and evaluation on quality of service in the extension system and farm level processes.

Keywords: artificial intelligence, productivity, ICT4agriculture, value chain, logistics

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Authors: Bouchiha Hanene, Rouabhi Rachid, Bouchama Khaled, Djebar Berrebbah Houraya, Djebar Mohamed Reda

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Recently, some natural products such as essentials oils (EOs) have been used in the fields as alternative to synthetic compounds, to minimize the negative impacts to the environment. This fact has led to questions about the possible impact of EOs on ecosystems. Currently in toxicology, the use of alternative models can help to understand the mechanisms of toxic action, at different levels of organization of ecosystems. Algae, protozoa and bacteria form the base of the food chain and protozoan cells are used as bioindicators often of pollution in environment. Unicellular organisms offer the possibility of direct study of independent cells with specific characteristics of individual cells and whole organisms at the same time. This unicellular facilitates the study of physiological processes, and effects of pollutants at the cellular level, which makes it widely used to assess the toxic effects of various xenobiotics. This study aimed to verify the effects of EOs of one famous plant used tremendously in our folk medicine, namely Artemisia herba alba in causing acute toxicity (24 hours) and chronic (15 days) toxicity for model cellular (Paramecium sp). To this end, cellular’s of paramecium were exposed to various concentrations (Three doses were chosen) of EOs extracted from plant (Artemisia herba alba). In the first experiment, the cellular s cultures were exposed for 48 hours to different concentrations to determine the median lethal concentration (DL50). We followed the evolution of physiological parameters (growth), biochemical (total proteins, respiratory metabolism), as well as the variations of a bio marker the GSH. Our results highlighted a light inhibition of the growth of the protozoa as well as a disturbance of the contents of total proteins and a reduction in the reduced rate of glutathione. The polarographic study revealed a stimulation of the consumption of O2 and this at the treated cells.

Keywords: essential oils, protozoa, bio indicators, toxicity, Growth, bio marker, proteins, polarographic

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Authors: Sara ElElimy, Samir Moustafa

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Mobile network operators start to face many challenges in the digital era, especially with high demands from customers. Since mobile network operators are considered a source of big data, traditional techniques are not effective with new era of big data, Internet of things (IoT) and 5G; as a result, handling effectively different big datasets becomes a vital task for operators with the continuous growth of data and moving from long term evolution (LTE) to 5G. So, there is an urgent need for effective Big data analytics to predict future demands, traffic, and network performance to full fill the requirements of the fifth generation of mobile network technology. In this paper, we introduce data science techniques using machine learning and deep learning algorithms: the autoregressive integrated moving average (ARIMA), Bayesian-based curve fitting, and recurrent neural network (RNN) are employed for a data-driven application to mobile network operators. The main framework included in models are identification parameters of each model, estimation, prediction, and final data-driven application of this prediction from business and network performance applications. These models are applied to Telecom Italia Big Data challenge call detail records (CDRs) datasets. The performance of these models is found out using a specific well-known evaluation criteria shows that ARIMA (machine learning-based model) is more accurate as a predictive model in such a dataset than the RNN (deep learning model).

Keywords: big data analytics, machine learning, CDRs, 5G

Procedia PDF Downloads 125

Authors: Iyabode A. Kehinde, Joshua O. Oyekanmi, Jumoke T. Abimbola, Olajumoke E. Ayanda

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African yam bean (AYB), (Sphenostylis stenocarpa) is a leguminous crop that provides nutritionally rich seeds, tubers and leaves for human consumption. AYB potentials as an important food security crop is yet to be realized and thus classified as underutilized crop. Underutilization of the crop has been partly associated with scarce information on the incidence and characterization of fungal endophytes infecting vascular parts of AYB. Accurate and robust detection of these endophytic fungi is essential for diagnosis, modeling, surveillance and protection of germplasm (seed) health. This work aimed at isolating and identifying fungal endophytes associated with leaves, stems and roots of AYB in Ogun State, Nigeria. This study investigated both cultural and molecular properties of endophytic fungi in AYB for its characterization and diversity. Fungal endophytes were isolated and culturally identified. DNA extraction, PCR amplification using ITS primers and analyses of nucleotide sequences of ribosomal DNA fragments were conducted on selected isolates. BLAST analysis was conducted on consensus nucleotide sequences of 28 out of 30 isolates and results showed similar homology with genera of Rhizopus, Cunninghamella, Fusarium, Aspergillus, Penicillium, Alternaria, Diaporthe, Nigrospora, Purpureocillium, Corynespora, Magnaporthe, Macrophomina, Curvularia, Acrocalymma, Talaromyces and Simplicillium. Slight similarity was found with endophytes associated with soybean. Phylogenetic analysis by maximum likelihood method showed high diversity among the general. These organisms have high economic importance in crop improvement. For an instance, Purpureocillium lilacinum showed high potential in control of root rot caused by nematodes in tomatoes. Though some can be pathogens, but many of the fungal endophytes have beneficial attributes to plant in host health, uptake of nutrients, disease suppression, and host immunity.

Keywords: molecular characterization, African Yam Bean, fungal endophyte, plant parts

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Authors: Milica Karadzic, Lidija Jevric, Sanja Podunavac-Kuzmanovic, Strahinja Kovacevic, Anamarija Mandic, Katarina Penov Gasi, Marija Sakac, Aleksandar Okljesa, Andrea Nikolic

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The present paper deals with chromatographic lipophilicity prediction of newly synthesized steroid derivatives. The prediction was achieved using in silico generated molecular descriptors and quantitative structure-retention relationship (QSRR) methodology with the artificial neural networks (ANN) approach. Chromatographic lipophilicity of the investigated compounds was expressed as retention factor value logk. For QSRR modeling, a feedforward back-propagation ANN with gradient descent learning algorithm was applied. Using the novel sum of ranking differences (SRD) method generated ANN models were ranked. The aim was to distinguish the most consistent QSRR model that can be found, and similarity or dissimilarity between the models that could be noticed. In this study, SRD was performed with average values of retention factor value logk as reference values. An excellent correlation between experimentally observed retention factor value logk and values predicted by the ANN was obtained with a correlation coefficient higher than 0.9890. Statistical results show that the established ANN models can be applied for required purpose. This article is based upon work from COST Action (TD1305), supported by COST (European Cooperation in Science and Technology).

Keywords: artificial neural networks, liquid chromatography, molecular descriptors, steroids, sum of ranking differences

Procedia PDF Downloads 303

Authors: Sinead Impey, Damon Berry, Selma Furtado, Miriam Galvin, Loretto Grogan, Orla Hardiman, Lucy Hederman, Mark Heverin, Vincent Wade, Linda Douris, Declan O'Sullivan, Gaye Stephens

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Healthcare is a knowledge-rich environment. This knowledge, while valuable, is not always accessible outside the borders of individual clinics. This research aims to address part of this problem (at a study site) by constructing a maximal data set (knowledge artefact) for motor neurone disease (MND). This data set is proposed as an initial knowledge base for a concurrent project to develop an MND patient data platform. It represents the domain knowledge at the study site for the duration of the research (12 months). A knowledge elicitation method was also developed from the lessons learned during this process - the WICKED method. WICKED is an anagram of the words: eliciting and confirming data, information, knowledge, wisdom. But it is also a reference to the concept of wicked problems, which are complex and challenging, as is eliciting expert knowledge. The method was evaluated at a second site, and benefits and limitations were noted. Benefits include that the method provided a systematic way to manage data, information, knowledge and wisdom (DIKW) from various sources, including healthcare specialists and existing data sets. Limitations surrounded the time required and how the data set produced only represents DIKW known during the research period. Future work is underway to address these limitations.

Keywords: healthcare, knowledge acquisition, maximal data sets, action design science

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Authors: Mário Silva, Filipa Gomes, Filipa Oliveira, Simone Morais, Cristina Delerue-Matos

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Brown seaweeds are abundant in Portuguese coastline and represent an almost unexploited marine economic resource. One of the most common species, easily available for harvesting in the northwest coast, is Saccorhiza polyschides grows in the lowest shore and costal rocky reefs. It is almost exclusively used by local farmers as natural fertilizer, but contains a substantial amount of valuable compounds, particularly alginates, natural biopolymers of high interest for many industrial applications. Alginates are natural polysaccharides present in cell walls of brown seaweed, highly biocompatible, with particular properties that make them of high interest for the food, biotechnology, cosmetics and pharmaceutical industries. Conventional extraction processes are based on thermal treatment. They are lengthy and consume high amounts of energy and solvents. In recent years, microwave-assisted extraction (MAE) has shown enormous potential to overcome major drawbacks that outcome from conventional plant material extraction (thermal and/or solvent based) techniques, being also successfully applied to the extraction of agar, fucoidans and alginates. In the present study, acid pretreatment of brown seaweed Saccorhiza polyschides for subsequent microwave-assisted extraction (MAE) of alginate was optimized. Seaweeds were collected in Northwest Portuguese coastal waters of the Atlantic Ocean between May and August, 2014. Experimental design was used to assess the effect of temperature and acid pretreatment time in alginate extraction. Response surface methodology allowed the determination of the optimum MAE conditions: 40 mL of HCl 0.1 M per g of dried seaweed with constant stirring at 20ºC during 14h. Optimal acid pretreatment conditions have enhanced significantly MAE of alginates from Saccorhiza polyschides, thus contributing for the development of a viable, more environmental friendly alternative to conventional processes.

Keywords: acid pretreatment, alginate, brown seaweed, microwave-assisted extraction, response surface methodology

Procedia PDF Downloads 358

Authors: Emmanuel Dele Balogun

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This paper analyzes, using descriptive statistics and econometrics data which span the period 1981 to 2014 to gauge the effects of trade policy incentives on economic growth in Nigeria. It argues that the provided incentives penalize economic growth during pre-trade liberalization eras, but stimulated a rapid increase in total factor productivity during the post-liberalization period of 2000 to 2014. The trend analysis shows that Nigeria maintained high tariff walls in economic regulation eras which became low in post liberalization era. The protections were in favor of infant industries, which were mainly appendages of multinationals but against imports of competing food and finished consumer products. The trade openness index confirms the undue exposure of Nigeria’s economy to the vagaries of international market shocks; while banking sector recapitalization and new listing of telecommunications companies deepened the financial markets in post-liberalization era. The structure of economic incentives was biased in favor of construction, trade and services, but against the real sector despite protectionist policies. Total Factor Productivity (TFP) estimates show that the Nigerian economy suffered stagnation in pre-liberalization eras, but experienced rapid growth rates in post-liberalization eras. The regression results relating trade policy incentives to TFP growth rate yielded a significant but negative intercept suggesting that a non-interventionist policy could be detrimental to economic progress, while protective tariff which limits imports of competing products could spur productivity gains in domestic import substitutes beyond factor growth with market liberalization. The main constraint to the effectiveness of trade policy incentives is the failure of benefiting industries to leverage on the domestic factor endowments of the nation. This paper concludes that there is the need to review the current economic transformation strategies urgently with a view to provide policymakers with a better understanding of the most viable options that could make for rapid success.

Keywords: economic growth, macroeconomic incentives, total factor productivity, trade policies

Procedia PDF Downloads 307