Search results for: health awareness education

Authors: Aline V. Arroteia, Gustavo G. Do Amaral, Simone Z. Kikuti, Norberto C. S. Moura, Silvio B. Melhado

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Despite the significant advances made by the construction industry in recent years, the crystalized absence of integration between the design and construction phases is still an evident and costly problem in building construction. Globally, the construction industry has sought to adopt collaborative practices through new technologies to mitigate impacts of this fragmented process and to optimize its production. In this new technological business environment, professionals are required to develop new methodologies based on the notion of collaboration and integration of information throughout the building lifecycle. This scenario also represents the industry’s reality in developing nations, and the increasing need for overall efficiency has demanded new educational alternatives at the undergraduate and post-graduate levels. In countries like Brazil, it is the common understanding that Architecture, Engineering and Building Construction educational programs are being required to review the traditional design pedagogical processes to promote a comprehensive notion about integration and simultaneity between the phases of the project. In this context, the coherent inclusion of computation design to all segments of the educational programs of construction related professionals represents a significant research topic that, in fact, can affect the industry practice. Thus, the main objective of the present study was to comparatively measure the effectiveness of the Building Information Modeling courses offered by the University of Sao Paulo, the most important academic institution in Brazil, at the Schools of Architecture and Civil Engineering and the courses offered in well recognized BIM research institutions, such as the School of Design in the College of Architecture of the Georgia Institute of Technology, USA, to evaluate the dissemination of BIM knowledge amongst students in post graduate level. The qualitative research methodology was developed based on the analysis of the program and activities proposed by two BIM courses offered in each of the above-mentioned institutions, which were used as case studies. The data collection instruments were a student questionnaire, semi-structured interviews, participatory evaluation and pedagogical practices. The found results have detected a broad heterogeneity of the students regarding their professional experience, hours dedicated to training, and especially in relation to their general knowledge of BIM technology and its applications. The research observed that BIM is mostly understood as an operational tool and not as methodological project development approach, relevant to the whole building life cycle. The present research offers in its conclusion an assessment about the importance of the incorporation of BIM, with efficiency and in its totality, as a teaching method in undergraduate and graduate courses in the Brazilian architecture, engineering and building construction schools.

Keywords: building information modeling (BIM), BIM education, BIM process, design teaching

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Authors: Kuei-Ling Sun, Emily Chia-Yu Su

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Allergy is a hypersensitive overreaction of the immune system to environmental stimuli, and a major health problem. These overreactions include rashes, sneezing, fever, food allergies, anaphylaxis, asthmatic, shock, or other abnormal conditions. Allergies can be caused by food, insect stings, pollen, animal wool, and other allergens. Their development of allergies is due to both genetic and environmental factors. Allergies involve immunoglobulin E antibodies, a part of the body’s immune system. Immunoglobulin E antibodies will bind to an allergen and then transfer to a receptor on mast cells or basophils triggering the release of inflammatory chemicals such as histamine. Based on the increasingly serious problem of environmental change, changes in lifestyle, air pollution problem, and other factors, in this study, we both collect allergens and non-allergens from several databases and use several machine learning methods for classification, including logistic regression (LR), stepwise regression, decision tree (DT) and neural networks (NN) to do the model comparison and determine the permutations of allergen amino acid’s sequence.

Keywords: allergy, classification, decision tree, logistic regression, machine learning

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Authors: Michelle S. Pereira, Analice C. Azevedo, Julliane D. Medeiros, Ana Claudia S. Martins, Didier S. Castellano-Filho, Claudio G. Diniz, Vania L. Silva

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Vaginal microbiota is a complex ecosystem, composed by aerobic and anaerobic bacteria, living in a dynamic equilibrium. Lactobacillus spp. are predominant in vaginal ecosystem, and factors such as immunity and hormonal variations may lead to disruptions, resulting in proliferation of opportunistic pathogens. Bacterial vaginosis (BV) is a polymicrobial syndrome, caused by an increasing of anaerobic bacteria replacing Lactobacillus spp. Microorganisms such as Gardnerella vaginalis, Mycoplasma hominis, Mobiluncus spp., and Atopobium vaginae can be found in BV, which may also be associated to other infections such as by Human Papillomavirus (HPV). HPV is highly prevalent in sexually active women, and is considered a risk factor for development of cervical cancer. As long as few data is available on vaginal microbiota of women with HPV-associated cervical lesions, our objectives were to evaluate the diversity in vaginal ecosystem in these women. To all patients, clinical and socio-demographic data were collected after gynecological examination. This study was approved by the Ethics Committee from Federal University of Juiz de Fora, Minas Gerais, Brazil. Vaginal secretion and cervical scraping were collected. Gram-stained smears were evaluated to establish Nugent score for BV determination. Viral and bacterial DNA obtained was used as template for HPV genotyping (PCR) and bacterial fingerprint (REP-PCR). In total 31 patients were included (mean age 35 and 93.6% sexually active). The Nugent score showed that 38.7% were BV. From the medical records, Pap smear tests showed that 32.3% had low grade squamous epithelial lesion (LSIL), 29% had high grade squamous epithelial lesion (HSIL), 25.8% had atypical squamous cells of undetermined significance (ASC-US) and 12.9% with atypical squamous cells that would not exclude high-grade lesion (ASC-H). All participants were HPV+. HPV-16 was the most frequent (87.1%), followed by HPV-18 (61.3%). HPV-31, HPV-52 and HPV-58 were also detected. Coinfection HPV-16/HPV-18 was observed in 75%. In the 18-30 age group, HPV-16 was detected in 40%, and HPV-16/HPV-18 coinfection in 35%. HPV-16 was associated to 30% of ASC-H and 20% of HSIL patients. BV was observed in 50% of HPV-16+ participants and in 45% of HPV-16/HPV-18+. Fingerprints of bacterial communities showed clusters with low similarity suggesting high heterogeneity in vaginal microbiota within the sampled group. Overall, the data is worrisome once cervical-cancer highly risk-associated HPV-types were identified. The high microbial diversity observed may be related to the different levels of cellular lesions, and different physiological conditions of the participants (age, social behavior, education). Further prospective studies are needed to better address correlations and BV and microbial imbalance in vaginal ecosystems which would be related to the different cellular lesions in women with HPV infections. Supported by FAPEMIG, CNPq, CAPES, PPGCBIO/UFJF.

Keywords: human papillomavirus, bacterial vaginosis, bacterial diversity, cervical cancer

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Authors: K. Jahani, J. Razavi

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Nowadays, to decrease the number of downtimes in the industries such as metal mining, petroleum and chemical industries, predictive maintenance is crucial. In order to have efficient predictive maintenance, knowing the performance of critical equipment of production line such as pumps and hydro-cyclones under variable operating parameters, selecting best indicators of this equipment health situations, best locations for instrumentation, and also measuring of these indicators are very important. In this paper, computer aided engineering (CAE) tools are implemented to study some important elements of copper process line, namely slurry pumps and cyclone to predict the performance of these components under different working conditions. These modeling and simulations can be used in predicting, for example, the damage tolerance of the main shaft of the slurry pump or wear rate and location of cyclone wall or pump case and impeller. Also, the simulations can suggest best-measuring parameters, measuring intervals, and their locations.

Keywords: computer aided engineering, predictive maintenance, fault detection, mining process line, slurry pump, hydrocyclone

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Authors: Zumra Mehmedovic, Susan Luhrmann

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Treatment-resistant depression (TRD) is a debilitating mental health disorder for which there are very few available treatment options. Current research suggests that ketamine may be a safe and effective option for the treatment of TRD. Research utilizing a review of the literature was conducted to determine if ketamine in conjunction with antidepressants is more effective than antidepressants alone in the treatment of TRD. The literature consists of ten journal articles which include quantitative studies based on primary research. A critique of the literature was done to determine whether the findings are reliable, critiquing elements influencing the believability and robustness of the research. The research was based on the neuroplasticity theory of depression, hypothesizing that ketamine, in conjunction with antidepressants, will be more effective than antidepressants alone as they have different mechanisms of action. All the studies except one found ketamine in conjunction with antidepressants to be a more effective treatment than antidepressants alone in the treatment of TRD. Results of the studies indicate that ketamine is effective in treating TRD at various doses, settings, and routes of administration. Further research is necessary, though, to further explore and confirm the findings. Several gaps in literature were identified, including the optimal dose of ketamine, its long-term efficacy and safety, and effects of ketamine in repeated doses. The research topic is highly significant to advanced practice nursing, as based on the findings, ketamine can be utilized as a safe and effective treatment for TRD.

Keywords: ketamine, major depressive disorder, treatment-resistant depression, treatment

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Authors: Erika Tatiana Paredes Prada, Diana Marina Camargo Lemos

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Introduction: Recreovía as a public health strategy contributes to encourage the practice and adherence to physical activity (PA) recommendations, by temporarily closing the roads to motorized vehicles. The determination of the PA requires the evaluation of the reliability of the measurement instruments, in order to sustain the continuity and relevance of Recreovía as a community intervention. Objective: Establish the inter-rater reliability of the App for the System for Observing Play and Recreation in Communities (iSOPARC®) in the Recreovía of Bucaramanga, Colombia. Methods: Five trained observers at two observation points on the 2.3 km of the Recreovía (14th Street and 32nd Street) used the App (iSOPARC®), between 08:00 a.m. and 12:00 m. in periods of 20 minutes during a regular Sunday. Reliability analysis was performed using the Intraclass Correlation Coefficient (ICC 2.1). Results: A total of 2682 users were observed (43.6 % women) in 7 observations. ICC showed a range between 0.96 and 0.99 for the PA level and ICC between 0.95 and 0.99 for age group for the two observation points. Conclusion: The reliability found for the iSOPARC® guarantees the consecutive measurement of the PA level at the Recreovía, which will allow measuring it is effectiveness in the medium and long term, as a community intervention strategy.

Keywords: environment, observation, physical activity, recreation, reliability

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Authors: Kankurize Josiane, Nizigama Mediatrice

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Introduction: Burundi records a still high infant mortality rate. Despite efforts to reduce it, prematurity is still the leading cause of death in the neonatal period. The objective of this study was to assess the quality of care for premature babies hospitalized in the neonatology unit of the Centre Hospitalier Universitaire de Kamenge. Method: This was a descriptive and evaluative prospective carried out in the neonatology unit of the CHUK (Centre Hospitalier Universitaire de Kamenge) from December 1, 2016, to May 31, 2017, including 70 premature babies, 65 mothers of premature babies and 15 providers including a pediatrician and 14 nurses. Using a tool developed by the World Health Organization and adapted to the local context by national experts, the quality of care for premature babies was assessed. Results: Prematurity accounted for 44.05% of hospitalizations in neonatology at the University Hospital of Kamenge. The assessment of the quality of care for premature babies was of low quality, with an average global score of 2/5 (50%), indicating that there is a considerable need for improvement to reach the standards. Conclusion: Efforts must be made to have infrastructures, materials, and human resources sufficient in quality and quantity so that the neonatology unit of the CHUK can be efficient and optimize the care of premature babies.

Keywords: quality of care, evaluation, premature, standards

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Authors: S. Krustev, V. Angelova, K. Ivanov, P. Zaprjanova

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Approximately a dozen trace elements are vital for the development of all plants and some other elements are significant for some species. Heavy metals do not belong to this group of elements that are essential to plants, but some of them such as copper and zinc, have a dual effect on their growth. Concentration levels of these elements in the different regions of the world vary considerably. Their high concentrations in some parts of Central and Eastern Europe cause concern for human health and degrade the quality of agricultural produce from these areas. This study aims to compare the prevalence and levels of the major trace elements in some rural areas of Central and Eastern Europe. Soil samples from different regions of the Czech Republic, Slovakia, Austria, Hungary, Serbia, Romania, Bulgaria and Greece far from large industrial centers have been studied. The main methods for their determination are the atomic spectral techniques – atomic absorption and plasma atomic emission. As a result of this study, data on microelements levels in soils of 17 points from the main grain-producing regions of Central and Eastern Europe are presented and systematized. The content of trace elements was in the range of 5.0-84.1 mg.kg⁻¹ for Cu, 0.3-1.4 mg.kg⁻¹ for Cd, 26.1-225.5 mg.kg⁻¹ for Zn, 235.5-788.6 mg.kg⁻¹ for Mn and 4.1-25.8 mg.kg⁻¹ for Pb.

Keywords: trace elements, heavy metals, agricultural soils, Central and Eastern Europe

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Authors: Aarti Singh, Anees Ahmad

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Carotenoids comprise a group of isoprenoid pigments. Carotenes, xanthophylls and their derivatives have been found to play an important role in all living beings through foods, neutraceuticals and pharmaceuticals. α-carotene, β-carotene and β-cryptoxanthin play a vital role in humans to provide vitamin A source for the growth, development and proper functioning of immune system and vision. They are very crucial for plants and humans as they protect from photooxidative damage and are excellent antioxidants quenching singlet molecular oxygen and peroxyl radicals. Diet including more intake of carotenoids results in reduced threat of various chronic diseases such as cancer (lung, breast, prostrate, colorectal and ovarian cancers) and coronary heart diseases. The blue light filtering efficiency of the carotenoids in liposomes have been reported to be maximum in lutein followed by zeaxanthin, β-carotene and lycopene. Lycopene plays a vital role for the protection from CVD. Lycopene in serum is directly related to reduced risk of osteoporosis in postmenopausal women. Carotenoids have major role in the treatment of skin disorders. There is need to identify and isolate novel carotenoids from diverse natural sources for human health benefits.

Keywords: antioxidants, carotenoids, neutraceuticals, osteoporosis, pharmaceuticals

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

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In this work, we explored the use of Augmented Reality (AR) to support students in laboratory lectures in Distance Learning (DL), designing an application that proved to be ready for use next semester. AR could help students in the understanding of complex concepts as well as increase their motivation in the learning process. However, despite many prototypes in the literature, it is still less used in schools and universities. This is mainly due to the perceived limited advantages to the investment costs, especially regarding changes needed in the teaching modalities. However, with the spread of epidemiological emergency due to SARS-CoV-2, schools and universities were forced to a very rapid redefinition of consolidated processes towards forms of Distance Learning. Despite its many advantages, it suffers from the impossibility to carry out practical activities that are of crucial importance in STEM ("Science, Technology, Engineering e Math") didactics. In this context, AR perceived advantages increased a lot since teachers are more prepared for new teaching modalities, exploiting AR that allows students to carry on practical activities on their own instead of being physically present in laboratories. In this work, we designed an AR application for the support of engineering students in the understanding of assembly drawings of complex machines. Traditionally, this skill is acquired in the first years of the bachelor's degree in industrial engineering, through laboratory activities where the teacher shows the corresponding components (e.g., bearings, screws, shafts) in a real machine and their representation in the assembly drawing. This research aims to explore the effectiveness of AR to allow students to acquire this skill on their own without physically being in the laboratory. In a preliminary phase, we interviewed students to understand the main issues in the learning of this subject. This survey revealed that students had difficulty identifying machine components in an assembly drawing, matching between the 2D representation of a component and its real shape, and understanding the functionality of a component within the machine. We developed a mobile application using Unity3D, aiming to solve the mentioned issues. We designed the application in collaboration with the course professors. Natural feature tracking was used to associate the 2D printed assembly drawing with the corresponding 3D virtual model. The application can be displayed on students’ tablets or smartphones. Users could interact with selecting a component from a part list on the device. Then, 3D representations of components appear on the printed drawing, coupled with 3D virtual labels for their location and identification. Users could also interact with watching a 3D animation to learn how components are assembled. Students evaluated the application through a questionnaire based on the System Usability Scale (SUS). The survey was provided to 15 students selected among those we participated in the preliminary interview. The mean SUS score was 83 (SD 12.9) over a maximum of 100, allowing teachers to use the AR application in their courses. Another important finding is that almost all the students revealed that this application would provide significant power for comprehension on their own.

Keywords: augmented reality, distance learning, STEM didactics, technology in education

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Authors: Vincent Kheswa

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X-rays are ionizing electromagnetic radiation that is used in various industries such as computed tomography scans, dental X-rays, and screening freight trains. However, they pose health risks to humans if they are not shielded properly. In recent years, many researchers around the globe have been searching for nontoxic best possible glass materials for shielding X-rays. In this work, the x-ray shielding properties of 45Na₂O + 10 Bi₂O₃ + (5 - x)TiO₂+ (x) Nb₂O₅ + 40 P₂O₅, were x = 0, 1, 3, 5 mol%, glass materials were studied. The results revealed that the glass sample with the highest TiO2 content has the highest mass and linear attenuation coefficients and lowest half-value thickness, tenth-value thickness and mean-free path in the 20 to 80 keV energy region. The sample with 3 mol% of Nb₂O₅ has the highest mass and linear attenuation coefficients and the lowest half-value thickness, tenth-value thickness, and mean-free path at 15 keV and photon energies between 80 to 300 keV. It was, therefore, concluded that 45Na₂O + 10 Bi₂O₃ + 5 TiO₂ + 40 P₂O₅ glass is best for shielding x-rays of energies between 20 and 80 keV, while 45Na₂O + 10 Bi₂O₃ + 2 TiO₂ + 3 Nb₂O₅ + 40 P₂O₅ is best for shielding 15 keV x-rays and x-rays of energies between 80 keV and 300 keV.

Keywords: bismuth-titanium-phosphate glass, x-ray shielding, LAC, MAC, radiation shielding

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Authors: Ramandeep Kaur, Kamaljit Kaur, Preeti Ahluwalia, Poonam A. Sachdev

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Bread is an ideal vehicle to impart bioactive compounds to the consumers in a convenient manner. This study evaluated bread enriched with red sweet pepper powder (RSP) at 2, 4, 6, 8, 10% and compared to control bread (without RSP). The bread crumbs were assayed for bioactive, physical, nutritional, textural, color, and sensory properties. Bread supplemented with RSP improved its color, nutritional, and bioactive properties. The low moisture content and increased hardness were observed at higher levels of RSP. Color intensity (expressed as L*, a*, b* values) of bread with 2 and 4% RSP were lower than those of high levels, and the same trend was observed for protein, fibre and ash content of bread. Significant (p < 0.05) increases were recorded for bioactive compounds such as total phenols (0.145 to 235 mg GAE/g), antioxidant activity (56% to 78%) and flavonoids (0.112 to 0.379 mg/g) as the level of powder increased. Bread enriched with 8% RSP showed improved sensory profile as compared to control, whereas a further increase in RSP decreased the sensory and textural properties. Thus, RSP act as a natural colorant and functional food that enhanced the functional and nutritional properties of bread and can be used to customize bread for specific health needs.

Keywords: breads, bioactive compounds, red sweet pepper powder, sensory scores

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Authors: George Kassar, Phillip A. Cartwright

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Based on data collected from The Jones Learning Center (JLC), University of the Ozarks, Arkansas, U.S., this study explores the impact of inclusive classroom practices on neuro-diverse college students’ and their consequent academic performance having participated in integrative therapies designed to support students who are intellectually capable of obtaining a college degree, but who require support for learning challenges owing to disabilities, AD/HD, or ASD. The purpose of this study is two-fold. The first objective is to explore the general process, special techniques, and practices of the (JLC) inclusive program. The second objective is to identify and analyze the effectiveness of the processes, techniques, and practices in supporting the academic performance of enrolled college students with learning disabilities following integration into mainstream university learning. Integrity, transparency, and confidentiality are vital in the research. All questions were shared in advance and confirmed by the concerned management at the JLC. While administering the questionnaire as well as conducted the interviews, the purpose of the study, its scope, aims, and objectives were clearly explained to all participants prior starting the questionnaire / interview. Confidentiality of all participants assured and guaranteed by using encrypted identification of individuals, thus limiting access to data to only the researcher, and storing data in a secure location. Respondents were also informed that their participation in this research is voluntary, and they may withdraw from it at any time prior to submission if they wish. Ethical consent was obtained from the participants before proceeding with videorecording of the interviews. This research uses a mixed methods approach. The research design involves collecting, analyzing, and “mixing” quantitative and qualitative methods and data to enable a research inquiry. The research process is organized based on a five-pillar approach. The first three pillars are focused on testing the first hypothesis (H1) directed toward determining the extent to the academic performance of JLC students did improve after involvement with comprehensive JLC special program. The other two pillars relate to the second hypothesis (H2), which is directed toward determining the extent to which collective and applied knowledge at JLC is distinctive from typical practices in the field. The data collected for research were obtained from three sources: 1) a set of secondary data in the form of Grade Point Average (GPA) received from the registrar, 2) a set of primary data collected throughout structured questionnaire administered to students and alumni at JLC, and 3) another set of primary data collected throughout interviews conducted with staff and educators at JLC. The significance of this study is two folds. First, it validates the effectiveness of the special program at JLC for college-level students who learn differently. Second, it identifies the distinctiveness of the mix of techniques, methods, and practices, including the special individualized and personalized one-on-one approach at JLC.

Keywords: education, neuro-diverse students, program effectiveness, Jones learning center

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Authors: Ece Kaya

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Urban waterfront re-development is a well-established phenomenon internationally since 1960s. In cities throughout the world, old industrial waterfront land is being redeveloped into luxury housing, offices, tourist attractions, cultural amenities and shopping centres. These developments are intended to attract high-income residents, tourists and investors to the city. As urban waterfronts are iconic places for the cities and catalyst for further development. They are often referred as flagship project. In Sydney, the re-development of industrial waterfront has been exposed since 1980s with Darling Harbour Project. Darling Harbour waterfront used to be the main arrival and landing place for commercial and industrial shipping until 1970s. Its urban development has continued since the establishment of the city. It was developed as a major industrial and goods-handling precinct in 1812. This use was continued by the mid-1970s. After becoming a redundant industrial waterfront, the area was ripe for re-development in 1984. Darling Harbour is now one of the world’s fascinating waterfront leisure and entertainment destinations and its transformation has been considered as a success story. It is a contradictory statement for this paper. Data collection was carried out using an extensive archival document analysis. The data was obtained from Australian Institute of Architects, City of Sydney Council Archive, Parramatta Heritage Office, Historic Houses Trust, National Trust, and University of Sydney libraries, State Archive, State Library and Sydney Harbour Foreshore Authority Archives. Public documents, primarily newspaper articles and design plans, were analysed to identify possible differences in motives and to determine the process of implementation of the waterfront redevelopments. It was also important to obtain historical photographs and descriptions to understand how the waterfront had been altered. Sites maps in different time periods have been identified to understand what kind of changes happened on the urban landscape and how the developments affected areas. Newspaper articles and editorials have been examined in order to discover what aspects of the projects reflected the history and heritage. The thematic analysis of the archival data helped determine Darling Harbour is a historically important place as it had represented a focal point for Sydney's industrial growth and the cradle of industrial development in European Australia. It has been found that the development area was designated in order to be transformed to a place for tourist, education, recreational, entertainment, cultural and commercial activities and as a result little evidence remained of its industrial past. This paper aims to discuss the industrial significance of Darling Harbour and to explain the changes on its industrial landscape. What is absent now is the layer of its history that creates the layers of meaning to the place so its historic industrial identity is effectively lost.

Keywords: historical significance, industrial heritage, industrial waterfront, re-development

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Authors: Richard Ren

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Air pollution is a serious danger to international well-being and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.Air pollution is a serious danger to international wellbeing and economies - it will kill an estimated 7 million people every year, costing world economies $2.6 trillion by 2060 due to sick days, healthcare costs, and reduced productivity. In the United States alone, 60,000 premature deaths are caused by poor air quality. For this reason, there is a crucial need to develop effective methods to forecast air quality, which can mitigate air pollution’s detrimental public health effects and associated costs by helping people plan ahead and avoid exposure. The goal of this study is to propose an artificial intelligence framework for predicting future air quality based on timing variables (i.e. season, weekday/weekend), future weather forecasts, as well as past pollutant and air quality measurements. The proposed framework utilizes multiple machine learning algorithms (logistic regression, random forest, neural network) with different specifications and averages the results of the three top-performing models to eliminate inaccuracies, weaknesses, and biases from any one individual model. Over time, the proposed framework uses new data to self-adjust model parameters and increase prediction accuracy. To demonstrate its applicability, a prototype of this framework was created to forecast air quality in Los Angeles, California using datasets from the RP4 weather data repository and EPA pollutant measurement data. The results showed good agreement between the framework’s predictions and real-life observations, with an overall 92% model accuracy. The combined model is able to predict more accurately than any of the individual models, and it is able to reliably forecast season-based variations in air quality levels. Top air quality predictor variables were identified through the measurement of mean decrease in accuracy. This study proposed and demonstrated the efficacy of a comprehensive air quality prediction framework leveraging multiple machine learning algorithms to overcome individual algorithm shortcomings. Future enhancements should focus on expanding and testing a greater variety of modeling techniques within the proposed framework, testing the framework in different locations, and developing a platform to automatically publish future predictions in the form of a web or mobile application. Accurate predictions from this artificial intelligence framework can in turn be used to save and improve lives by allowing individuals to protect their health and allowing governments to implement effective pollution control measures.

Keywords: air quality prediction, air pollution, artificial intelligence, machine learning algorithms

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Authors: Obinna Benedict Duru

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This study focuses on the elderly and the challenges that confront them. The elderly are that particular segment of our population who by virtue of the aging process have attained the stage in most cases where they are confronted with the challenges of economic dependency and social marginality. These challenges are as a result of the physical and biological decline occasioned by social myths and realities which portray the elderly as a dependent population whose members could not and should not work and who need social assistance that the younger population is obliged to provide. From the moment of birth to the moment of death, our bodies are constantly changing. We are all enmeshed in the process of growing old, a transition from youthfulness to elderliness. In youth-oriented modern societies like ours, we tend to attach positive importance and significance to the biological changes that occur early in life and define later physical changes in negative terms. Children growing up and young adults receive more attention, greater responsibilities and more legal rights to reward them on their way. But few people are congratulated on getting old. We commiserate with people who are getting old and make jokes about their supposedly physical, mental and biological decline. Wrinkles, loss of weight and vitality are all parts of the aging process. In almost all parts of the world, earlier researches have shown that about fifty percent of the elderly who suffer from stroke, arthritis, senility and other age related diseases are the disengaged and neglected elderly. Rapid technological changes render the knowledge and skills of the elderly obsolete; education is geared toward the young and the generational competition for jobs leads to pressures on the elderly to retire. Control of initial resources are shifted to the middle-aged and older workers are pushed into positions of economic dependency. This study therefore, among other things tend to discover how some government policies have affected the elderly particularly in Africa. To discover the prospects and possibilities of the elderly for a better living. To make a comparison of the advances in healthcare giving made in the advanced western societies to the practice in Sub Saharan Africa etc. The hypotheses of this study include: that the elderly in Sub Saharan Africa are more vulnerable than their counterparts in Europe and America. The elderly are more prone to social isolation, and that the elderly are mostly affected by age-related sickness etc. With a survey method as the research design, and sample size of about 500 respondents,probability sampling technique was used. Data which were analyzed using chi-square and tables were collected through primary and secondary sources. The findings made include: that the elderly suffer pains of old age especially when disengaged from work or social activity. That loss of income condemn the elderly to a life of vegetable existence, and that those who do not have other means of re-integration usually see old age with regret and despair. It is therefore, recommended among other things that social welfare scheme and the process of re-integration at old age be introduced for the non pensionable elderly in Africa.

Keywords: elderly, social isolation, dependency, re-integration

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Authors: E. Pretorius, A. M. Viljoen, M. van der Bank

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Introduction: The phytochemistry of Agathosma crenulata and A. betulina has been studied extensively, while their molecular analysis through DNA barcoding remains virtually unexplored. This technique can confirm the identity of plant species included in a herbal product, thereby ensuring the efficacy of the herbal product and the accuracy of its label. Materials and methods: Authentic Agathosma reference material of A. betulina (n=16) and A. crenulata (n=10) were obtained. Thirteen commercial products were purchased from various health shops around Johannesburg, South Africa, using the search term “Agathosma” or “Buchu.” The plastid regions matK and ycf1 were used to barcode the Buchu products, and BRONX analysis confirmed the taxonomic identity of the samples. UPLC-MS analyses were also performed. Results: Only (30/60) 60% of the traded samples tested from 13 suppliers contained A. betulina in their herbal products. Similar results were also obtained for the UPLC-MS analysis. Conclusion: In this study, we demonstrate the application of DNA barcoding in combination with phytochemical analysis to authenticate herbal products claiming to contain Agathosma plants as an ingredient in their products. This supports manufacturing efforts to ensure that herbal products that are safe for the consumer.

Keywords: Buchu, substitution, barcoding, BRONX algorithm, matK, ycf1, UPLC-MS

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Authors: Kim Ji-Hyun, Jeon Hye-Seon, Kwon Oh-Yun, Park Eun-Young, Hwang Ui-Jae, Gwak Gyeong-Tae, Yoon Hyeo-Bin

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Stress urinary incontinence (SUI), a common women health problem, is an involuntary leakage of urine while sneezing, coughing, or physical exertion caused by insufficient strength of the pelvic floor and sphincter muscles. SUI also leads to decrease in quality of life and limits sexual activities. SUI is related to the increased bladder neck angle, bladder neck movement, funneling index, urethral width, and decreased urethral length. Various pelvic floor muscle electrical stimulation (ES) interventions have been applied to improve the symptoms of the people with SUI. ES activates afferent fibers of pudendal nerve and smoothly induces contractions of the pelvic floor muscles such as striated periurethral muscles and striated pelvic floor muscles. ES via intravaginal electrodes are the most frequently used types of the pelvic floor muscle ES for the female SUI. However, inserted electrode is uncomfortable and it increases the risks of infection. The purpose of this preliminary study was to determine if the 8-week transcutaneous pelvic floor ES would be effective to improve the symptoms and satisfaction of the females with SUI. Easy-K, specially designed ES equipment for the people with SUI, was used in this study. The oval shape stimulator can be placed on a toilet seat, and the surface has invaded electrode fit to contact with the entire vulva area while users are sitting on the stimulator. Five women with SUI were included in this experiment. Prior to the participation, subjects were instructed about procedures and precautions in using the ES. They have used the stimulator once a day for 20 minutes for each session at home. Outcome data was collected 3 times at the baseline, 4 weeks and 8 weeks after the intervention. Intravaginal sonography was used to measure the bladder neck angle, bladder neck movement, funneling index, thickness of an anterior rhabdosphincter and a posterior rhabdosphincter, urethral length, and urethral width. Leavator ani muscle (LAM) contraction strength was assessed by manual palpation according to the oxford scoring system. In addition, incontinence quality of life (IQOL) and female sexual function index (FSFI) questionnaires were used to obtain addition subjective information. Friedman test, a nonparametric statistical test, was used to determine the effectiveness of the ES. The Wilcoxon test was used for the post-hoc analysis and the significance level was set at .05. The bladder neck angle, funneling index and urethral width were significantly decreased after 8-weeks of intervention (p<.05). LAM contraction score, urethral length and anterior and posterior rhabdosphicter thickness were statistically increased by the intervention (p<.05). However, no significant change was found in the bladder neck movement. Although total score of the IQOL did not improve, the score of the ‘avoidance’ subscale of IQOL had significant improved (p<.05). FSFI had statistical difference in FSFI total score and ‘desire’ subscale (p<.05). In conclusion, 8-week use of a transcutaneous ES on peri-vulva area improved dynamic mechanical structures of the pelvic floor musculature as well as IQOL and conjugal relationship.

Keywords: electrical stimulation, Pelvic floor muscle, sonography, stress urinary incontinence, women health

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Authors: Elsayed Ahmed Elsayed, Azza Noor El-Deen, Mohamed A. Farid, Mohamed A. Wadaan

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Recently, a great attention has been paid to the use of dietary carbohydrates as prebiotic functional foods. Among the new commercially available products, fructooligosaccharides (FOS), which are microbial produced from sucrose, have attracted special interest due to their valuable properties and, thus, have a great economic potential for the sugar industrial branch. They are non-cariogenic sweeteners of low caloric value, as they are not hydrolyzed by the gastro-intestinal enzymes, promoting selectively the growth of the bifidobacteria in the colon, helping to eliminate the harmful microbial species to human and animal health and preventing colon cancer. FOS has been also found to reduce cholesterol, phospholipids and triglyceride levels in blood. FOS has been mainly produced by microbial fructosyltransferase (FTase) enzymes. The present work outlines bioprocess optimization for different cultivation parameters affecting the production of FTase by Penicillium aurantiogriseum AUMC 5605. The optimization involves both traditional as well as fractional factorial design approaches. Additionally, the production process will be compared under batch and fed-batch conditions. Finally, the optimized process conditions will be applied to 5-L stirred tank bioreactor cultivations.

Keywords: prebiotics, fructooligosaccharides, optimization, cultivation

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Authors: Arlene Villarama, Micol Grace Guanzon, Zenaida Ramos

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This paper provides insights into teaching English as a Foreign Language in the Philippines. The authors reviewed relevant theories and literature, and provide an analysis of the issues in teaching English in the Philippine setting in the light of these theories. The authors made an investigation in Bagong Barrio National High School (BBNHS) - a public school in Caloocan City. The institution has a population of nearly 3,000 students. The performances of randomly chosen 365 respondents were scrutinised. The study regarding the success of teaching English as a foreign language to Filipino children were highlighted. This includes the respondents’ family background, surroundings, way of living, and their behavior and understanding regarding education. The results show that there is a significant relationship between demonstrative, communal, and logical areas that touch the efficacy of introducing English as a foreign Dialectal. Filipino children, by nature, are adventurous and naturally joyful even for little things. They are born with natural skills and capabilities to discover new things. They highly consider activities and work that ignite their curiosity. They love to be recognised and are inspired the most when given the assurance of acceptance and belongingness. Fun is the appealing influence to ignite and motivate learning. The magic word is excitement. The study reveals the many facets of the accumulation and transmission of erudition, in introduction and administration of English as a foreign phonological; it runs and passes through different channels of diffusion. Along the way, there are particles that act as obstructions in protocols where knowledge are to be gathered. Data gained from the respondents conceals a reality that is beyond one’s imagination. One significant factor that touches the inefficacy of understanding and using English as a foreign language is an erroneous outset gained from an old belief handed down from generation to generation. This accepted perception about the power and influence of the use of language, gives the novices either a negative or a positive notion. The investigation shows that a higher number of dislikes in the use of English can be tracked down from the belief of the story on how the English language came into existence. The belief that only the great and the influential have the right to use English as a means of communication kills the joy of acceptance. A significant notation has to be examined so as to provide a solution or if not eradicate the misconceptions that lie behind the substance of the matter. The result of the authors’ research depicts a substantial correlation between the emotional (demonstrative), social (communal), and intellectual (logical). The focus of this paper is to bring out the right notation and disclose the misconceptions with regards to teaching English as a foreign language. This will concentrate on the emotional, social, and intellectual areas of the Filipino learners and how these areas affect the transmittance and accumulation of learning. The authors’ aim is to formulate logical ways and techniques that would open up new beginnings in understanding and acceptance of the subject matter.

Keywords: accumulation, behaviour, facets, misconceptions, transmittance

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Authors: Angad Arora

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In production operations/manufacturing, a cell or line is typically a bunch of similar machines (computer numerical control (CNCs), advanced cutting, 3D printing or special purpose machines. For qualifying a typical manufacturing line /cell / new process, Ideally, we need a sample of parts that can be flown through the process and then we make a judgment on the health of the line/cell. However, with huge volumes and mass production scope, such as in the mobile phone industry, for example, the actual cells or lines can go in thousands and to qualify each one of them with statistical confidence means utilizing samples that are very large and eventually add to product /manufacturing cost + huge waste if the parts are not intended to be customer shipped. To solve this, we come up with 2 steps statistical approach. We start with a small sample size and then objectively evaluate whether the process needs additional samples or not. For example, if a process is producing bad parts and we saw those samples early, then there is a high chance that the process will not meet the desired yield and there is no point in keeping adding more samples. We used this hypothesis and came up with 2 steps binomial testing approach. Further, we also prove through results that we can achieve an 18-25% reduction in samples while keeping the same statistical confidence.

Keywords: statistics, data science, manufacturing process qualification, production planning

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Authors: Carmen García Sánchez

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The UN's 17 Sustainable Development Goals – specifically the nº 3 and nº 11- urgently call for new architectural design solutions at different design scales to increase human contact with nature in the health and wellbeing promotion of primarily urban communities. The discipline of Interior Design offers an important alternative to large-scale nature-inclusive actions which are not always possible due to space limitations. These circumstances provide an immense opportunity to integrate biophilic design, a complex emerging and under-developed approach that pursues sustainable design strategies for increasing the human-nature connection through the experience of the built environment. Biophilic design explores the diverse ways humans are inherently inclined to affiliate with nature, attach meaning to and derive benefit from the natural world. It represents a biological understanding of architecture which categorization is still in progress. The internationally renowned Danish domestic architecture built in the 1950´s and early 1960´s - a golden age of Danish modern architecture - left a leading legacy that has greatly influenced the domestic sphere and has further led the world in terms of good design and welfare. This study examines how four existing post-war domestic buildings establish a dialogue with nature and her variations over time. The case-studies unveil both memorable and unique biophilic resources through sophisticated and original design expressions, where transformative processes connect the users to the natural setting and reflect fundamental ways in which they attach meaning to the place. In addition, fascinating analogies in terms of this nature interaction with particular traditional Japanese architecture inform the research. They embody prevailing lessons for our time today. The research methodology is based on a thorough literature review combined with a phenomenological analysis into how these case-studies contribute to the connection between humans and nature, after conducting fieldwork throughout varying seasons to document understanding in nature transformations multi-sensory perception (via sight, touch, sound, smell, time and movement) as a core research strategy. The cases´ most outstanding features have been studied attending the following key parameters: 1. Space: 1.1. Relationships (itineraries); 1.2. Measures/scale; 2. Context: Context: Landscape reading in different weather/seasonal conditions; 3. Tectonic: 3.1. Constructive joints, elements assembly; 3.2. Structural order; 4. Materiality: 4.1. Finishes, 4.2. Colors; 4.3. Tactile qualities; 5. Daylight interplay. Departing from an artistic-scientific exploration this groundbreaking study provides sustainable practical design strategies, perspectives, and inspiration to boost humans´ contact with nature through the experience of the interior built environment. Some strategies are associated with access to outdoor space or require ample space, while others can thrive in a dense urban context without direct access to the natural environment. The objective is not only to produce knowledge, but to phase in biophilic design in the built environment, expanding its theory and practice into a new dimension. Its long-term vision is to efficiently enhance the health and well-being of urban communities through daily interaction with Nature.

Keywords: sustainability, biophilic design, architectural design, interior design, nature, Danish architecture, Japanese architecture

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Authors: Lowanika Victor Tibane, David Mamba

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Human body, animals, and plants depend on certain essential metals in permissible quantities for their survival. Excessive metal concentration may cause severe malfunctioning of the organisms and even fatal in extreme cases. Because of gold mining in the Witwatersrand basin in South Africa, enormous untreated mine dumps comprise elevated concentration of essential trace elements. Elevated quantities of trace metal have direct negative impact on the quality of soil for different land use types, reduce soil efficiency for plant growth, and affect the health human and animals. A total of 21 subsoil samples were examined using inductively coupled plasma optical emission spectrometry and X-ray fluorescence methods and the results elevated men concentration of Fe (36,433.39) > S (5,071.83) > Cu (1,717,28) > Mn (612.81) > Cr (74.52) > Zn (68.67) > Ni (40.44) > Co (9.63) > P (3.49) > Mo > (2.74), reported in mg/kg. Using various contamination indices, it was discovered that the sites surveyed are on average moderately contaminated with Co, Cr, Cu, Mn, Ni, S, and Zn. The ecological risk assessment revealed a low ecological risk for Cr, Ni and Zn, whereas Cu poses a very high ecological risk.

Keywords: essential trace elements, soil contamination, contamination indices, toxicity, descriptive statistics, ecological risk evaluation

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Authors: Kidus Dawit Gedamu

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Addis Ababa City Road Authority is responsible for managing and setting performance evaluation of the city’s road network using the International Roughness Index (IRI). This helps the authority to conduct pavement condition assessments of asphalt roads each year to determine the health status or Level of service (LOS) of the roadway network and plan program improvements such as maintenance, resurfacing and rehabilitation. For a lower IRI limit economical and acceptable maintenance strategy may be selected among a number of maintenance alternatives. The Highway Development and Management (HDM-4) tool can do such measures to help decide which option is the best by evaluating the economic and structural conditions. This paper specifically addresses flexible pavement, including two principal arterial streets under the administration of the Addis Ababa City Roads Authority. The roads include the road from Megenagna Interchange to Ayat Square and from Ayat Square to Tafo RA. First, it was assessed the procedures followed by the city's road authority to develop the appropriate road maintenance strategies. Questionnaire surveys and interviews are used to collect information from the city's road maintenance departments. Second, the project analysis was performed for functional and economic comparison of different maintenance alternatives using HDM-4.

Keywords: appropriate maintenance strategy, cost stream, road deterioration, maintenance alternative

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Authors: Edson Ephraim Sanga

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This paper stems to explore possible places used for recreation in unplanned settlements in order to avail knowledge on how to create and shape urban spaces essential for recreation and leisure. The context of unplanned settlements is spatially characterized compactness and congestions of buildings developed by residents without professional inputs. These characteristics surpass greenery landscapes such as parks and squares essential for health, happiness and wellbeing. The lack of recreational greenery landscape arises a question on how possible can recreation take places in the settlements? This study used qualitative methods mainly observation and in-depth interview to explore the recreational situation in Manzese informal settlements as an instrumental case and found that ordinary spaces are re-configured into recreational spaces and used as ‘parks’ and ‘squares’ in the settlements. The spaces are diverse and complex as they possess different spatial characteristics based on their physical attributes and the way they are used and interpreted by respective users. This paper argues that the re-configuration processes of ordinary spaces should not be taken for granted because they portray the appropriation of spaces from quotidian dimensions in a particular context.

Keywords: ordinary spaces, recreation, unplanned settlement, urban spaces

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Authors: Yasaman Mohammadi

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Emotion regulation is a complex process that allows individuals to manage and modulate their emotional responses in order to adaptively respond to environmental demands. As individuals age, emotion regulation abilities may decline, leading to an increased vulnerability to mood disorders and other negative health outcomes. Advances in neuroimaging techniques have greatly enhanced our understanding of the neural substrates underlying emotion regulation and age-related changes in these neural systems. Additionally, genetic research has identified several candidate genes that may influence age-related changes in emotion regulation. In this paper, we review recent findings from neuroimaging and genetic research on age-related changes in the neural substrates of emotion regulation, highlighting the mechanisms and consequences of these changes. We also discuss potential interventions, including cognitive and behavioral approaches, that may be effective in mitigating age-related declines in emotion regulation. We propose that a better understanding of the mechanisms underlying age-related changes in emotion regulation may lead to the development of more targeted interventions aimed at promoting healthy emotional functioning in older adults. Overall, this paper highlights the importance of studying age-related changes in emotion regulation and provides a roadmap for future research in this field.

Keywords: emotion regulation, aging, neural substrates, neuroimaging, emotional functioning, healthy aging

Procedia PDF Downloads 90

Authors: Chandu Rathnayake, Isuri Anuradha

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Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

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Authors: Eniola Akande

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Introduction: English vocabulary and reading comprehension are core to academic achievement in many school subjects. Deficiency in both accounts for dismal performance in internal and external examinations among primary school pupils in Ibadan Metropolis, Nigeria. Previous studies largely focused on factors influencing pupils’ achievement in English vocabulary and reading comprehension. In spite of what literature has shown, the problem still persists, implying the need for other kinds of intervention. This study was therefore carried out to determine the effect of two transactional strategies Picture Walk (PW) and Know-Want to Learn-Learnt (KWL) on primary four pupils’ achievement in English vocabulary and reading comprehension in Ibadan Metropolis. The moderating effects of gender and learning style were also examined. Methodology: The study was anchored on Rosenblatt’s Transactional Reading and Piaget’s Cognitive Development theories; pretest-posttest control group quasi-experimental design with 3x2x3 factorial matrix was adopted. Six public primary schools were purposively selected based on the availability of qualified English language teachers in Primary Education Studies. Six intact classes (one per school) with a total of 101 primary four pupils (48 males and 53 females) participated. The intact classes were randomly assigned to PW (27), KWL (44) and conventional (30) groups. Instruments used were English Vocabulary (r=0.83), Reading Comprehension (r=0.84) achievement tests, Pupils’ Learning Style Preference Scale (r=0.93) and instructional guides. Treatment lasted six weeks. Data were analysed using the Descriptive statistics, Analysis of Covariance and Bonferroni post-hoc test at 0.05 level of significance. The mean age was 8.86±0.84 years. Result: Treatment had a significant main effect on pupils’ reading comprehension (F(2,82)=3.17), but not on English vocabulary. Participants in KWL obtained the highest post achievement means score in reading comprehension (8.93), followed by PW (8.06) and control (7.21) groups. Pupils’ learning style had a significant main effect on pupils’ achievement in reading comprehension (F(2,82)=4.41), but not on English vocabulary. Pupils with preference for tactile learning style had the highest post achievement mean score in reading comprehension (9.40), followed by the auditory (7.43) and the visual learning style (7.37) groups. Gender had no significant main effect on English vocabulary and reading comprehension. There was no significant two-way interaction effect of treatment and gender on pupils’ achievement in English vocabulary and reading comprehension. The two-way interaction effect of treatment and learning style on pupils’ achievement in reading comprehension was significant (F(4,82)=3.37), in favour of pupils with tactile learning style in PW group. There was no significant two-way interaction effect of gender and learning style on pupils’ achievement in English vocabulary and reading comprehension. The three-way interaction effects were not significant on English vocabulary and reading comprehension. Conclusion: Picture Walk and Know-Want to learn-Learnt instructional strategies were effective in enhancing pupils’ achievement in reading comprehension but not on English vocabulary. Learning style contributed considerably to achievement in reading comprehension but not to English vocabulary. Primary school, English language teachers, should put into consideration pupils’ learning style when adopting both strategies in teaching reading comprehension for improved achievement in the subject.

Keywords: comprehension-based intervention, know-want to learn-learnt, learning style, picture walk, primary school pupils

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Authors: Oktia Woro Kasmini Handayani, Sri Ratna Rahayu, Efa Nugroho, Berta Kalswahermawati

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Diabetes occurs 10 years faster in the Southeast Asian region than the European region, which occurs in the most productive periods. Cultural differences as well as cultural transitions can be determinant factors of health cases in urban and rural areas. The purpose of this research is to analyze the effect of the cultural environment, behavior and the occurrence of diabetes mellitus in urban areas of Semarang, Indonesia. The research was conducted in the area of Semarang Regency, using a quantitative approach and supported by qualitative data, the population is DM type 2 patients, sample size of 200 people, with a purposive sampling technique. The independent variable consists of cultural environment, behavior, and the dependent variable is DM. The data is analyzed with regression test method. Cultural environment affects behavior positively, with t value of 4,690 and p (sig.) 0.000, this means sig <0.05, while the effect of behavior on Diabetes Mellitus obtained t value 2.950 with p-value (sig.) 0.003 this means that sig <0.05, thus it can be interpreted that the behavior has a significant effect on Diabetes Mellitus. The cultural environment directly affects the incidence of DM. It can also shape a person's behavior or lifestyle or habit, whether healthy or unhealthy one, which in turn causes symptoms of DM.

Keywords: Behavior, Cultural Environment, Diebetes Millitus, Urban

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Authors: A. M. Andriano, M. Lombardi, A. Lopolito, M. Prosperi, A. Stasi, E. Iannuzzi

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In according to the scientific debate on the definition of Social Innovation (SI), the present paper identifies SI as new ideas (products, services, and models) that simultaneously meet social needs and create new social relationships or collaborations. This concept offers important tools to unravel the difficult condition for the agricultural sector in marginalized areas, characterized by the abandonment of activities, low level of farmer education, and low generational renewal, hampering new territorial strategies addressed at and integrated and sustainable development. Models of SI in agriculture, starting from bottom up approach or from the community, are considered to represent the driving force of an ecological and digital revolution. A system based on SI may be able to grasp and satisfy individual and social needs and to promote new forms of entrepreneurship. In this context, Vazapp ('Go Hoeing') is an emerging SI model in southern Italy that promotes solutions for satisfying needs of farmers and facilitates their relationships (creation of network). The Vazapp’s initiative, considered in this study, is the Contadinners ('Farmer’s dinners'), a dinner held at farmer’s house where stakeholders living in the surrounding area know each other and are able to build a network for possible future professional collaborations. The aim of the paper is to identify the evolution of farmers’ relationships, both quantitatively and qualitatively, because of the Contadinner’s initiative organized by Vazapp. To this end, the study adopts the Social Network Analysis (SNA) methodology by using UCINET (Version 6.667) software to analyze the relational structure. Data collection was realized through a questionnaire distributed to 387 participants in the twenty 'Contadinners', held from February 2016 to June 2018. The response rate to the survey was about 50% of farmers. The elaboration data was focused on different aspects, such as: a) the measurement of relational reciprocity among the farmers using the symmetrize method of answers; b) the measurement of the answer reliability using the dichotomize method; c) the description of evolution of social capital using the cohesion method; d) the clustering of the Contadinners' participants in followers and not-followers of Vazapp to evaluate its impact on the local social capital. The results concern the effectiveness of this initiative in generating trustworthy relationships within the rural area of southern Italy, typically affected by individualism and mistrust. The number of relationships represents the quantitative indicator to define the dimension of the network development; while the typologies of relationships (from simple friendship to formal collaborations, for branding new cooperation initiatives) represents the qualitative indicator that offers a diversified perspective of the network impact. From the analysis carried out, Vazapp’s initiative represents surely a virtuous SI model to catalyze the relationships within the rural areas and to develop entrepreneurship based on the real needs of the community.

Keywords:

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