Search results for: electrical distribution network

Authors: Tacho Rubby Kong

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Community health workers’ performances are known to influence members’ behaviours and practices while translating policies into service delivery. However, little remains known about the extent to which this remains true within interventions aimed at addressing malaria burden in low-resource settings like Cameroon. The objective of this study was to examine the health workers’ performance and their influence on the adoption of strategies to address the malaria burden at a subnational level health system in Cameroon. A qualitative exploratory design was adopted on a purposively selected sample of 18 key informants. The study was conducted in Konye health district among sub-national health systems, managers, health facility in-charges, and frontline community health workers. Data was collected using semi-structured interview guides in a face-to-face interview with respondents. The analysis adopted a thematic approach utilising journals, credible authors, and peer review articles for data management. Participants acknowledged that workplace networks were influential during the implementation of policies to address malaria. The influence exerted was in form of linkage with other services, caution, and advice regarding strict adherence to policy recommendations, perhaps reflective of the level of trust in providers’ ability to adhere to policy provisions. At the district health management level and among non-state actors, support in perceived areas of weak performance in policy implementation was observed. In addition, timely initiation of contact and subsequent referral was another aspect where community health workers exerted influence while translating policies to address the malaria burden. While the level of support from among network peers was observed to influence community health workers’ adoption and implementation of strategies to address the malaria burden, different mechanisms triggered subsequent response and level of adherence to recommended policy aspects. Drawing from the elicited responses, it was infer that community health workers’ performance influence the direction and extent of success in policy implementation to address the malaria burden at the subnational level.

Keywords: subnational, community, malaria, strategy

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Authors: Bashair Al Riyami

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Background: Acylation stimulating protein (ASP) is a small basic protein that was isolated based on its function as a potent lipogenic factor. The role of ASP in lipid metabolism has been described in numerous studies. Several association studies suggest that ASP may play a prominent role in female fat metabolism and distribution. Progesterone is established as a female lipogenic hormone, however the mechanisms by which progesterone exert its effects are not fully understood. AIM: Since ASP is an established potent lipogenic factor with a known mechanism of action, in this study we aim to investigate acute effects of different hormone treatments on ASP levels in vivo after a fat load. Methods: This is a longitudinal study including 24 female wister rats that were randomly divided into 4 groups including controls (n=6). The rats were ovariectomized, and fourteen days later the fasting rats were injected subcutaneously with a single dose of different hormone treatments (progesterone, estrogen and testosterone). An hour later, olive was administered by oral gavage, and plasma blood samples were collected at several time points after oil administration for ASP and triglyceride measurements. Area under the curve (TG-AUC) was calculated to represent TG clearance Results: RM-ANCOVA and post-analysis showed that only the progesterone treated group had a significant postprandial ASP increase at two hours compared to basal levels and to the controls (439.8± 62.4 vs 253.45± 59.03 ug/ml), P= 0.04. Interestingly, increased postprandial ASP levels coordinated negatively with corresponding TG levels and TG-AUC across the postprandial period most apparent in the progesterone and testosterone treated groups that behaved in an opposite manner. ASP levels were 3-fold higher in the progesterone compared to the testosterone treated group, whereas TG-AUC was significantly lower in the progesterone treated group compared to the testosterone treated group. Conclusion: These findings suggest that progesterone treatment enhances ASP production and TG clearance in a simultaneous manner. The strong association of postprandial ASP levels and TG clearance in the progesterone treated group support the notion of a stimulatory role for progesterone on ASP mediated TG clearance. This is the first functional study to demonstrate a cause-effect relationship between hormone treatment and ASP levels in vivo. These findings are promising and may contribute to further understanding the mechanism of progesterone function as a female lipogenic hormone through enhancing ASP production and plasma levels.

Keywords: ASP, lipids, sex hormones, wister rats

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Authors: Nji Queenta Ngum, Mwanza Mulunda

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Introduction Most African research reports on the frequent aflatoxin contamination of various foodstuffs, with researchers rarely specifying which of the Aspergillus species are present in these commodities. Numerous research works provide evidence of the ability of fungi to grow, thrive, and interact with other crop species and focus on the fact that these processes are largely affected by climatic variables. South Africa is a water-stressed country with high spatio-temporal rainfall variability; moreover, temperatures have been projected to rise at a rate twice the global rate. This weather pattern change may lead to crop stress encouraging mold contamination with subsequent mycotoxin production. In this study, the biodiversity and distribution of Aspergillus species with their corresponding toxins in maize from six distinct maize producing regions with different weather patterns in South Africa were investigated. Materials And Methods By applying cultural and molecular methods, a total of 1028 maize samples from six distinct agro-climatic regions were examined for contamination by the Aspergillus species while the high performance liquid chromatography (HPLC) method was applied to analyse the level of contamination by aflatoxins. Results About 30% of the overall maize samples were contaminated by at least one Aspergillus species. Less than 30% (28.95%) of the 228 isolates subjected to the aflatoxigenic test was found to possess at least one of the aflatoxin biosynthetic genes. Furthermore, almost 20% were found to be contaminated with aflatoxins, with mean total aflatoxin concentration levels of 64.17 ppb. Amongst the contaminated samples, 59.02% had mean total aflatoxin concentration levels above the SA regulatory limit of 20ppb for animals and 10 for human consumption. Conclusion In this study, climate variables (rainfall reduction) were found to significantly (p<0.001) influence the occurrence of the Aspergillus species (especially Aspergillus fumigatus) and the production of aflatoxin in South Africa commercial maize by maize variety, year of cultivation as well as the agro-climatic region in which the maize is cultivated. This included, amongst others, a reduction in the average annual rainfall of the preceding year to about 21.27 mm, and, as opposed to other regions whose average maximum rainfall ranged between 37.24 – 44.1 mm, resulted in a significant increase in the aflatoxin contamination of maize.

Keywords: aspergillus species, aflatoxins, diversity, drought, food safety, HPLC and PCR techniques

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Authors: María Teresa Baquero, Ester Higueras

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One of the challenges facing 21st century cities, is their adaptation to the phenomenon of an ageing population. International policies have been developed, such as the "Global Network for Age-friendly Cities and Communities". These cities must recognize the diversity of the elderly population, and facilitate an active, healthy, satisfied aging and promote inclusion. In order to promote active and healthy aging, older people should be encouraged to engage in physical activity, sunbathe, socialize and enjoy the public open spaces in the city. Some studies recognize thermal comfort as one of the factors that most influence the use of public open spaces. However, although some studies have shown vulnerability to thermal extremes and environmental conditions in older people, there is little research on thermal comfort for older adults, because it is usually analyzed based on the characteristics of the ¨average young person¨ without considering the physiological, physical and psychological differences that characterize the elderly. This study analyzes the relationship between the microclimate parameters as air temperature, relative humidity, wind speed and sky view factor (SVF) with the personal thermal perception of older adults in three public spaces in Madrid, through a mixed methodology that combines weather measurements with interviews, made during the year 2018. Statistical test like Chi-square, Spearman, and analysis of variance were used to analyze the relationship between preference votes and thermal sensation votes with environmental and personal parameters. The results show that there is a significant correlation between thermal sensation and thermal preference with the measured air temperature, age, level of clothing, the color of clothing, season, time of the day and kind of space while no influence of gender or other environmental variables was detected. These data would contribute to the design of comfortable public spaces that improve the welfare of the elderly contributing to "active and healthy aging" as one of the 21st century challenges cities face.

Keywords: healthy ageing, older adults, outdoor public space, thermal perception

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Authors: A. O. Abulibdeh

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The aim of this study is to investigate and compare the changes in the Land Surface Temperature (LST) as a function of urbanization, particularly land use/land cover changes, in three cities in the UAE, mainly Abu Dhabi, Dubai, and Al Ain. The scale of this assessment will be at the macro- and micro-levels. At the macro-level, a comparative assessment will take place to compare between the four cities in the UAE. At the micro-level, the study will compare between the effects of different land use/land cover on the LST. This will provide a clear and quantitative city-specific information related to the relationship between urbanization and local spatial intra-urban LST variation in three cities in the UAE. The main objectives of this study are 1) to investigate the development of LST on the macro- and micro-level between and in three cities in the UAE over two decades time period, 2) to examine the impact of different types of land use/land cover on the spatial distribution of LST. Because these three cities are facing harsh arid climate, it is hypothesized that (1) urbanization is affecting and connected to the spatial changes in LST; (2) different land use/land cover have different impact on the LST; and (3) changes in spatial configuration of land use and vegetation concentration over time would control urban microclimate on a city scale and control macroclimate on the country scale. This study will be carried out over a 20-year period (1996-2016) and throughout the whole year. The study will compare between two distinct periods with different thermal characteristics which are the cool/cold period from November to March and warm/hot period between April and October. The best practice research method for this topic is to use remote sensing data to target different aspects of natural and anthropogenic systems impacts. The project will follow classical remote sensing and mapping techniques to investigate the impact of urbanization, mainly changes in land use/land cover, on LST. The investigation in this study will be performed in two stages. Stage one remote sensing data will be used to investigate the impact of urbanization on LST on a macroclimate level where the LST and Urban Heat Island (UHI) will be compared in the three cities using data from the past two decades. Stage two will investigate the impact on microclimate scale by investigating the LST and UHI using a particular land use/land cover type. In both stages, an LST and urban land cover maps will be generated over the study area. The outcome of this study should represent an important contribution to recent urban climate studies, particularly in the UAE. Based on the aim and objectives of this study, the expected outcomes are as follow: i) to determine the increase or decrease of LST as a result of urbanization in these four cities, ii) to determine the effect of different land uses/land covers on increasing or decreasing the LST.

Keywords: land use/land cover, global warming, land surface temperature, remote sensing

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Authors: Lakdar Sadi-Haddad

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The past few years study of very high speed electrical drives have seen a resurgence of interest. An inventory of the number of scientific papers and patents dealing with the subject makes it relevant. In fact democratization of magnetic bearing technology is at the origin of recent developments in high speed applications. These machines have as main advantage a much higher power density than the state of the art. Nevertheless particular attention should be paid to the design of the inverter as well as control and command. Surface mounted permanent magnet synchronous machine is the most appropriate technology to address high speed issues. However, it has the drawback of using a carbon sleeve to contain magnets that could tear because of the centrifugal forces generated in rotor periphery. Carbon fiber is well known for its mechanical properties but it has poor heat conduction. It results in a very bad evacuation of eddy current losses induce in the magnets by time and space stator harmonics. The three-phase inverter is the main harmonic source causing eddy currents in the magnets. In high speed applications such harmonics are harmful because on the one hand the characteristic impedance is very low and on the other hand the ratio between the switching frequency and that of the fundamental is much lower than that of the state of the art. To minimize the impact of these harmonics a first lever is to use strategy of modulation producing low harmonic distortion while the second is to introduce a sinus filter between the inverter and the machine to smooth voltage and current waveforms applied to the machine. Nevertheless, in very high speed machine the interaction of the processes mentioned above may introduce particular harmonics that can irreversibly damage the system: harmonics at the resonant frequency, harmonics at the shaft mode frequency, subharmonics etc. Some studies address these issues but treat these phenomena with separate solutions (specific strategy of modulation, active damping methods ...). The purpose of this paper is to present a complete new active harmonic compensation algorithm based on an improvement of the standard vector control as a global solution to all these issues. This presentation will be based on a complete theoretical analysis of the processes leading to the generation of such undesired harmonics. Then a state of the art of available solutions will be provided before developing the content of a new active harmonic compensation algorithm. The study will be completed by a validation study using simulations and practical case on a high speed machine.

Keywords: active harmonic compensation, eddy current losses, high speed machine

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Authors: Matt S. Van Deren, Michael Papenfus

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Seattle is one of the hundreds of cities in the United States that relies on a combined sewer system to collect and convey municipal wastewater. By design, these systems convey all wastewater, including industrial and commercial wastewater, human sewage, and stormwater runoff, through a single network of pipes. Serious problems arise for combined sewer systems during heavy precipitation events when treatment plants and storage facilities are unable to accommodate the influx of wastewater needing treatment, causing the sewer system to overflow into local waterways through sewer outfalls. CSOs (Combined Sewer Overflows) pose a serious threat to human and environmental health. Principal pollutants found in CSO discharge include microbial pathogens, comprising of bacteria, viruses, parasites, oxygen-depleting substances, suspended solids, chemicals or chemical mixtures, and excess nutrients, primarily nitrogen and phosphorus. While concentrations of these pollutants can vary between overflow events, CSOs have the potential to spread disease and waterborne illnesses, contaminate drinking water supplies, disrupt aquatic life, and effect a waterbody’s designated use. This paper estimates the economic impact of CSOs on residential property values. Using residential property sales data from Seattle, Washington, this paper employs a hedonic valuation model that controls for housing and neighborhood characteristics, as well as spatial and temporal effects, to predict a consumer’s willingness to pay for improved water quality near their homes. Initial results indicate that a 100,000-gallon decrease in the average annual overflow discharged from a sewer outfall within 300 meters of a home is associated with a 0.053% increase in the property’s sale price. For the average home in the sample, the price increase is estimated to be $18,860.23. These findings reveal some of the important economic benefits of improving water quality by reducing the frequency and severity of combined sewer overflows.

Keywords: benefits, hedonic, Seattle, sewer

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Authors: Martín Pratto Burgos

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The Engineering School of the University of the Republic in Uruguay offers an Introductory Mathematical Course from the second semester of 2019. This course has been designed to assist students in preparing themselves for math courses that are essential for Engineering Degrees, namely Math1, Math2, and Math3 in this research. The research proposes to build a model that can accurately predict the student's activity and academic progress based on their performance in the three essential Mathematical courses. Additionally, there is a need for a model that can forecast the incidence of the Introductory Mathematical Course in the three essential courses approval during the first academic year. The techniques used are Principal Component Analysis and predictive modelling using the Generalised Linear Model. The dataset includes information from 5135 engineering students and 12 different characteristics based on activity and course performance. Two models are created for a type of data that follows a binomial distribution using the R programming language. Model 1 is based on a variable's p-value being less than 0.05, and Model 2 uses the stepAIC function to remove variables and get the lowest AIC score. After using Principal Component Analysis, the main components represented in the y-axis are the approval of the Introductory Mathematical Course, and the x-axis is the approval of Math1 and Math2 courses as well as student activity three years after taking the Introductory Mathematical Course. Model 2, which considered student’s activity, performed the best with an AUC of 0.81 and an accuracy of 84%. According to Model 2, the student's engagement in school activities will continue for three years after the approval of the Introductory Mathematical Course. This is because they have successfully completed the Math1 and Math2 courses. Passing the Math3 course does not have any effect on the student’s activity. Concerning academic progress, the best fit is Model 1. It has an AUC of 0.56 and an accuracy rate of 91%. The model says that if the student passes the three first-year courses, they will progress according to the timeline set by the curriculum. Both models show that the Introductory Mathematical Course does not directly affect the student’s activity and academic progress. The best model to explain the impact of the Introductory Mathematical Course on the three first-year courses was Model 1. It has an AUC of 0.76 and 98% accuracy. The model shows that if students pass the Introductory Mathematical Course, it will help them to pass Math1 and Math2 courses without affecting their performance on the Math3 course. Matching the three predictive models, if students pass Math1 and Math2 courses, they will stay active for three years after taking the Introductory Mathematical Course, and also, they will continue following the recommended engineering curriculum. Additionally, the Introductory Mathematical Course helps students to pass Math1 and Math2 when they start Engineering School. Models obtained in the research don't consider the time students took to pass the three Math courses, but they can successfully assess courses in the university curriculum.

Keywords: machine-learning, engineering, university, education, computational models

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Authors: Mehrdad Shafiei Dizaji, Hoda Azari

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The research explores the pioneering integration of Physics-Informed Neural Networks (PINNs) into the domain of Ground-Penetrating Radar (GPR) data prediction, akin to advancements in medical imaging for tracking tumor progression in the human body. This research presents a detailed development framework for a specialized PINN model proficient at interpreting and forecasting GPR data, much like how medical imaging models predict tumor behavior. By harnessing the synergy between deep learning algorithms and the physical laws governing subsurface structures—or, in medical terms, human tissues—the model effectively embeds the physics of electromagnetic wave propagation into its architecture. This ensures that predictions not only align with fundamental physical principles but also mirror the precision needed in medical diagnostics for detecting and monitoring tumors. The suggested deep learning structure comprises three components: a CNN, a spatial feature channel attention (SFCA) mechanism, and ConvLSTM, along with temporal feature frame attention (TFFA) modules. The attention mechanism computes channel attention and temporal attention weights using self-adaptation, thereby fine-tuning the visual and temporal feature responses to extract the most pertinent and significant visual and temporal features. By integrating physics directly into the neural network, our model has shown enhanced accuracy in forecasting GPR data. This improvement is vital for conducting effective assessments of bridge deck conditions and other evaluations related to civil infrastructure. The use of Physics-Informed Neural Networks (PINNs) has demonstrated the potential to transform the field of Non-Destructive Evaluation (NDE) by enhancing the precision of infrastructure deterioration predictions. Moreover, it offers a deeper insight into the fundamental mechanisms of deterioration, viewed through the prism of physics-based models.

Keywords: physics-informed neural networks, deep learning, ground-penetrating radar (GPR), NDE, ConvLSTM, physics, data driven

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Authors: Mokgadi Miranda Hlongwane, Ntebogeng Sharon Mokgalaka, Felix Dapare Dakora

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Lessertia (L.) frutescens (syn. Sutherlandia frutescens) is a leguminous medicinal plant indigenous to South Africa. Traditionally, L. frutescens has been used to treat cancer, diabetes, epilepsy, fever, HIV, stomach problems, wounds and other ailments. This legume is endemic to the Cape fynbos, with large populations occurring wild and cultivated in the Cape Florist Region. Its widespread distribution in the Western Cape, Northern Cape, Eastern Cape and Kwazulu-Natal is linked to its increased use as a phytomedicine in the treatment of various diseases by traditional healers. The frequent harvesting of field plants for use as a medicine has made it necessary to undertake studies towards the conservation of Lessertia frutescens. As a legume, this species can form root nodules and fix atmospheric N₂ when in symbiosis with soil bacteria called rhizobia. So far, however, few studies (if any) have been done on the efficacy and diversity of native bacterial symbionts nodulating L. frutescens in South Africa. The aim of this project was to isolate and characterize L. frutescens-nodulating bacteria from five different locations in the Western Cape Province. This was done by trapping soil rhizobia using rhizosphere soil suspension to inoculate L. frutescens seedlings growing in sterilized sand and receiving sterile N-free Hoagland nutrient solution under glasshouse conditions. At 60 days after planting, root nodules were harvested from L. frutescens plants, surface-sterilized, macerated, and streaked on yeast mannitol agar (YMA) plates and incubated at 28 ˚C for observation of bacterial growth. The majority of isolates were slow-growers that took 6-14 days to appear on YMA plates. However, seven isolates were fast-growers, taking 2-4 days to appear on YMA plates. Single-colony cultures of the isolates were assessed for their ability to nodulate L. frutescens as a homologous host under glasshouse conditions. Of the 92 bacterial isolates tested, 63 elicited nodule formation on L. frutescens. Symbiotic effectiveness varied markedly between and among test isolates. There were also significant (p≤0.005) differences in nodulation, shoot biomass, photosynthetic rates, leaf transpiration and stomatal conductance of L. frutescens plants inoculated with the test isolates, which is an indication of their functional diversity.

Keywords: lessertia frutescens, nodulating, rhizobia, symbiotic effectiveness

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Authors: Ivana Prochazkova

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Cognitive linguistics offers biblical scholarship a specific methodological tool for analysis and interpretation of metaphorical expressions. Its methodology makes it possible to study processes involved in constructing the meaning of individual metaphorical expressions and whole conceptual metaphors; to analyze their function in the text; to follow the semantic development of concepts and conceptual domains, and to trace semantic changes and their motivation. The legal language in the Hebrew canon is extremely specific and formalized. Especially in the preambles to the collections of laws in the Pentateuch, more general considerations of the motif of keeping and breaking the law are encountered. This is also true in the psalms and wisdom literature. Legal theory and the philosophy of law deal with these motifs today. Metaphors play an important role in texts that reflect on more general issues. The purpose of this conference contribution is to write all over the central metaphorical concept, conceptual metaphor ךרד תורה (TORAH/LAW IS A JOURNEY), its function in the Torah and principal trends of the further development in the Prophets and the Writings. The conceptual metaphor תורה ךרד (TORAH/LAW IS A JOURNEY) constitutes a coherent system in conjunction with other metaphors that include e.g., conceptual metaphors נחה תורה (TORAH/LAW LEADS); its variant רעה תורה (TORAH IS A SHEPHERD/GUIDE); מקור תורה (TORAH/LAW IS A FOUNTAIN/A SOURCE OF LIFE). Some conceptual metaphors are well known, and their using are conventional (עשׁר תורה TORAH/LAW IS RICHES, שׂשׂון תורה TORAH/LAW IS DELIGHT, דבשׁ תורה TORAH/LAW IS HONEY, שׁמשׁ תורה TORAH/LAW IS SUN ). But some conceptual metaphors are by its occurrence innovative and unique (e.g., שׁריון תורה TORAH /LAW IS BODY ARMOR, כובע תורה TORAH /LAW IS A HELMET, בגד תורה TORAH/LAW IS A GARMENT, etc.). There will be given examples. Conceptual metaphors will be described by means of some 'metaphorical vehicles,' which are Hebrew expressions in the source domain that are repeatedly used in metaphorical conceptualizations of the target domain(s). Conceptual metaphors will be further described by means of 'generic narrative structures,' which are the particular aspects of a conceptual metaphor that emerge during the metaphorical structuring of concepts. They are the units of the metaphorical vehicles – the Hebrew expressions in the source domain – that structure concepts in much the same way that the conceptual metaphor in the target domain does. And finally, they will be described by means of the network of correspondences that exist between metaphorical vehicles – or generic metaphorical structures – and the Hebrew expressions in the target domain.

Keywords: cognitive theology, conceptual metaphor in the Old Testament, conceptual metaphors of the Torah, conceptual domain of law, righteousness, and justice

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Authors: Habib Abida, Noura Dahri

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Flash floods are among the most serious natural hazards that have disastrous environmental and human impacts. They are associated with exceptional rain events, characterized by short durations, very high intensities, rapid flows and small spatial extent. Flash floods happen very suddenly and are difficult to forecast. They generally cause damage to agricultural crops and property, infrastructures, and may even result in the loss of human lives. The city of Gabes (South-eastern Tunisia) has been exposed to numerous damaging floods because of its mild topography, clay soil, high urbanization rate and erratic rainfall distribution. The risks associated with this situation are expected to increase further in the future because of climate change, deemed responsible for the increase of the frequency and the severity of this natural hazard. Recently, exceptional events hit Gabes City causing death and major property losses. A major flooding event hit the region on June 2nd, 2014, causing human deaths and major material losses. It resulted in the stagnation of storm water in the numerous low zones of the study area, endangering thereby human health and causing disastrous environmental impacts. The characterization of flood risk in Gabes Watershed (South-eastern Tunisia) is considered an important step for flood management. Analytical Hierarchy Process (AHP) method coupled with Monte Carlo simulation and geographic information system were applied to delineate and characterize flood areas. A spatial database was developed based on geological map, digital elevation model, land use, and rainfall data in order to evaluate the different factors susceptible to affect flood analysis. Results obtained were validated by remote sensing data for the zones that showed very high flood hazard during the extreme rainfall event of June 2014 that hit the study basin. Moreover, a survey was conducted from different areas of the city in order to understand and explore the different causes of this disaster, its extent and its consequences.

Keywords: analytical hierarchy process, flash floods, Gabes, remote sensing, Tunisia

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Authors: Lawrence Gumbe

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Kenya Vision 2030 is the country's programme for transformation covering the period 2008 to 2030. Its objective is to help transform Kenya into a newly industrializing, middle-income, exceeding US$10000, country providing a high quality of life to all its citizens by 2030, in a clean and secure environment. Increased agricultural and production and productivity is crucial for the realization of Vision 2030. Mechanization of agriculture in order to achieve greater yields is the only way to achieve these objectives. There are contending groups and views on the strategy for agricultural mechanization. The first group are those who oppose the widespread adoption of advanced technologies (mostly internal combustion engines and tractors) in agricultural mechanization as entirely inappropriate in most situations in developing countries. This group argues that mechanically powered -agricultural mechanization often leads to displacement of labour and hence increased unemployment, and this results in a host of other socio-economic problems, amongst them, rural-urban migration, inequitable distribution of wealth and in many cases an increase in absolute poverty, balance of payments due to the need to import machinery, fuel and sometimes technical assistance to manage them. The second group comprises of those who view the use of the improved hand tools and animal powered technology as transitional step between the most rudimentary step in technological development (characterized by entire reliance on human muscle power) and the advanced technologies (characterized 'by reliance on tractors and other machinery). The third group comprises those who regard these intermediate technologies (ie. improved hand tools and draught animal technology in agriculture) as a ‘delaying’ tactic and they advocate the use of mechanical technologies as-the most appropriate. This group argues that alternatives to the mechanical technologies do not just exist as a practical matter, or, if they are available, they are inefficient and they cannot be compared to the mechanical technologies in terms of economics and productivity. The fourth group advocates a compromise between groups two and third above. This group views the improved hand tools and draught animal technology as more of an 18th century technology and the modem tractor and combine harvester as too advanced for developing countries. This group has been busy designing an ‘intermediate’, ‘appropriate’, ‘mini’, ‘micro’ tractor for use by farmers in developing countries. This paper analyses and concludes on the different agricultural mechanization strategies available to Kenya and other third world countries

Keywords: agriculture, mechanazation, transformation, industrialization

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Authors: Josef Novák, Alena Kohoutková

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The performance of concrete structures in fire depends on several factors which include, among others, the change in material properties due to the fire. Today, fiber reinforced concrete (FRC) belongs to materials which have been widely used for various structures and elements. While the knowledge and experience with FRC behavior under ambient temperature is well-known, the effect of elevated temperature on its behavior has to be deeply investigated. This paper deals with an experimental investigation and stress‑strain relations for hybrid fiber reinforced concrete (HFRC) which contains siliceous aggregates, polypropylene and steel fibers. The main objective of the experimental investigation is to enhance a database of mechanical properties of concrete composites with addition of fibers subject to elevated temperature as well as to validate existing stress-strain relations for HFRC. Within the investigation, a unique heat transport test, compressive test and splitting tensile test were performed on 150 mm cubes heated up to 200, 400, and 600 °C with the aim to determine a time period for uniform heat distribution in test specimens and the mechanical properties of the investigated concrete composite, respectively. Both findings obtained from the presented experimental test as well as experimental data collected from scientific papers so far served for validating the computational accuracy of investigated stress-strain relations for HFRC which have been developed during last few years. Owing to the presence of steel and polypropylene fibers, HFRC becomes a unique material whose structural performance differs from conventional plain concrete when exposed to elevated temperature. Polypropylene fibers in HFRC lower the risk of concrete spalling as the fibers burn out shortly with increasing temperature due to low ignition point and as a consequence pore pressure decreases. On the contrary, the increase in the concrete porosity might affect the mechanical properties of the material. To validate this thought requires enhancing the existing result database which is very limited and does not contain enough data. As a result of the poor database, only few stress-strain relations have been developed so far to describe the structural performance of HFRC at elevated temperature. Moreover, many of them are inconsistent and need to be refined. Most of them also do not take into account the effect of both a fiber type and fiber content. Such approach might be vague especially when high amount of polypropylene fibers are used. Therefore, the existing relations should be validated in detail based on other experimental results.

Keywords: elevated temperature, fiber reinforced concrete, mechanical properties, stress strain relation

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Authors: Muhammad Tanveer Altaf, Mehmet Bedir, Waqas Liaqat, Gönül Cömertpay, Volkan Çatalkaya, Celaluddin Barutçular, Nergiz Çoban, Ibrahim Cerit, Muhammad Azhar Nadeem, Tolga Karaköy, Faheem Shehzad Baloch

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Food production needs to be almost double by 2050 in order to feed around 9 billion people around the Globe. Plant production mostly relies on fertilizers, which also have one of the main roles in environmental pollution. In addition to this, climatic conditions are unpredictable, and the earth is expected to face severe drought conditions in the future. Therefore, water and fertilizers, especially nitrogen are considered as main constraints for future food security. To face these challenges, developing integrative approaches for germplasm characterization and selecting the resilient genotypes performing under limiting conditions is very crucial for effective breeding to meet the food requirement under climatic change scenarios. This study is part of the European Research Area Network (ERANET) project for the characterization of the diversity panel of 172 sorghum accessions and six hybrids as control cultivars under limiting (+N/-H2O, -N/+H2O) and non-limiting conditions (+N+H2O). This study was planned to characterize the sorghum diversity in relation to resource Use Efficiency (RUE), with special attention on harnessing the interaction between genotype and environment (GxE) from a physiological and agronomic perspective. Experiments were conducted at Adana, a Mediterranean climate, with augmented design, and data on various agronomic and physiological parameters were recorded. Plentiful diversity was observed in the sorghum diversity panel and significant variations were seen among the limiting water and nitrogen conditions in comparison with the control experiment. Potential genotypes with the best performance are identified under limiting conditions. Whole genome resequencing was performed for whole germplasm under investigation for diversity analysis. GWAS analysis will be performed using genotypic and phenotypic data and linked markers will be identified. The results of this study will show the adaptation and improvement of sorghum under climate change conditions for future food security.

Keywords: germplasm, sorghum, drought, nitrogen, resources use efficiency, sequencing

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Authors: Mercia I. Van Der Walt, Suzan Sayegh, Izzeldin E. L. J. Ibrahim, Mohamed G. Al-Kuwari, Manaf Kamil

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Background: Increased physical activity is associated with improvements in health conditions. Walking is recognized as an easy form of physical activity and a strategy used in health promotion. Step into Health (SIH), a national community program, was established in Qatar to support physical activity promotion through the monitoring of step counts. This study aims to assess the physical activity levels of the adult population in Qatar through a pedometer-based community program over a three-year-period. Methodology: This cross-sectional longitudinal study was conducted between from January 2013 and December 2015 based on daily step counts. A total of 15,947 adults (8,551 males and 7,396 females), from different nationalities enrolled in the program and aged 18 to 64, are included. The program involves free distribution of pedometers to members who voluntarily choose to register. It is also supported by a self-monitoring online account and linked to a web-database. All members are informed about the 10,000 steps/day target and automated emails as well as text messages are sent as reminders to upload data. Daily step counts were measured through the Omron HJ-324U pedometer (Omron Healthcare Co., Ltd., Japan). Analyses are done on the data extracted from the web-database. Results: Daily average step count for the overall community increased from 4,830 steps/day (2013) to 6,124 steps /day (2015). This increase was also observed within the three age categories (18–30), (31-45) and (>45) years. Average steps per day were found to be more among males compared with females in each of the aforementioned age groups. Moreover, males and females in the age group (>45 years) show the highest average step count with 7,010 steps/day and 5,564 steps/day respectively. The 21% increase in overall step count throughout the study period is associated with well-resourced program and ongoing impact in smaller communities such as workplaces and universities, a step in the right direction. However, the average step count of 6,124 steps/day in the third year is still classified as the low active category. Although the program showed an increase step count we found, 33% of the study population are low active, 35 % are sedentary with only 32% being active. Conclusion: This study indicates that the pedometer-based intervention was effective in increasing the daily physical activity of participants. However, alternative approaches need to be incorporated within the program to educate and encourage the community to meet the physical activity recommendations in relation to step count.

Keywords: pedometer, physical activity, Qatar, step count

Procedia PDF Downloads 247

Authors: Iva Blazkova, Amitava Moulick, Vedran Milosavljevic, Pavel Kopel, Marketa Vaculovicova, Vojtech Adam, Rene Kizek

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Doxorubicin is one of the most commonly used and the most effective chemotherapeutic drugs. This antracycline drug isolated from the bacteria Streptomyces peuceticus var. caesius is sold under the trade name Adriamycin (hydroxydaunomycin, hydroxydaunorubicin). Doxorubicin is used in single therapy to treat hematological malignancies (blood cancers, leukaemia, lymphoma), many types of carcinoma (solid tumors) and soft tissue sarcomas. It has many serious side effects like nausea and vomiting, hair lost, myelosupression, oral mucositis, skin reactions and redness, but the most serious one is the cardiotoxicity. Because of the risk of heart attack and congestive heart failure, the total dose administered to patients has to be accurately monitored. With the aim to lower the side effects and to targeted delivery of doxorubicin into the tumor tissue, the different nanoparticles are studied. The drug can be bound on a surface of nanoparticle, encapsulated in the inner cavity, or incorporated into the structure of nanoparticle. Among others, carbon nanoparticles (graphene, carbon nanotubes, fullerenes) are highly studied. Besides the number of inorganic nanoparticles, a great potential exhibit also organic ones mainly lipid-based and polymeric nanoparticle. The aim of this work was to perform a toxicity study of free doxorubicin compared to doxorubicin conjugated with various nanotransporters. The effect of liposomes, fullerenes, graphene, and carbon nanotubes on the toxicity was analyzed. As a first step, the binding efficacy of between doxorubicin and the nanotransporter was determined. The highest efficacy was detected in case of liposomes (85% of applied drug was encapsulated) followed by graphene, carbon nanotubes and fullerenes. For the toxicological studies, the chicken embryos incubated under controlled conditions (37.5 °C, 45% rH, rotation every 2 hours) were used. In 7th developmental day of chicken embryos doxorubicin or doxorubicin-nanotransporter complex was applied on the chorioallantoic membrane of the eggs and the viability was analyzed every day till the 17th developmental day. Then the embryos were extracted from the shell and the distribution of doxorubicin in the body was analyzed by measurement of organs extracts using laser induce fluorescence detection. The chicken embryo mortality caused by free doxorubicin (30%) was significantly lowered by using the conjugation with nanomaterials. The highest accumulation of doxorubicin and doxorubicin nanotransporter complexes was observed in the liver tissue

Keywords: doxorubicin, chicken embryos, nanotransporters, toxicity

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Authors: Markus Remm, Sebastian Dienert

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Vehicle interiors are not only changing in terms of design and functionality but also due to new driving situations in which, for example, autonomous operating modes are possible. Flexible seating positions are changing the requirements for passive safety system behavior and location in the interior of a vehicle. With fully autonomous driving, the driver can, for example, leave the position behind the steering wheel and take a seated position facing backward. Since autonomous and non-autonomous vehicles will share the same road network for the foreseeable future, accidents cannot be avoided, which makes the use of passive safety systems indispensable. With JENOPTIK-VOTAN® A technology, the trend towards flexible predetermined airbag weakening lines is enabled. With the help of laser beams, the predetermined weakening lines are introduced from the backside of the components so that they are absolutely invisible. This machining process is sensor-controlled and guarantees that a small residual wall thickness remains for the best quality and reliability for airbag weakening lines. Due to the wide processing range of the laser, the processing of almost all materials is possible. A CO₂ laser is used for many plastics, natural fiber materials, foams, foils and material composites. A femtosecond laser is used for natural materials and textiles that are very heat-sensitive. This laser type has extremely short laser pulses with very high energy densities. Supported by a high-precision and fast movement of the laser beam by a laser scanner system, the so-called cold ablation is enabled to predetermine weakening lines layer by layer until the desired residual wall thickness remains. In that way, for example, genuine leather can be processed in a material-friendly and process-reliable manner without design implications to the components A-Side. Passive safety in the vehicle is increased through the interaction of modern airbag technology and high-precision laser airbag weakening. The JENOPTIK-VOTAN® A product family has been representing this for more than 25 years and is pointing the way to the future with new and innovative technologies.

Keywords: design freedom, interior material processing, laser technology, passive safety

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Authors: Dino Carpentras, Alejandro Dinkelberg, Michael Quayle

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Opinion dynamics models use an agent-based modeling approach to model people’s opinions. Model's properties are usually explored by testing the two 'degrees of freedom': the interaction rule and the network topology. The latter defines the connection, and thus the possible interaction, among agents. The interaction rule, instead, determines how agents select each other and update their own opinion. Here we show the existence of the third degree of freedom. This can be used for turning one model into each other or to change the model’s output up to 100% of its initial value. Opinion dynamics models represent the evolution of real-world opinions parsimoniously. Thus, it is fundamental to know how real-world opinion (e.g., supporting a candidate) could be turned into a number. Specifically, we want to know if, by choosing a different opinion-to-number transformation, the model’s dynamics would be preserved. This transformation is typically not addressed in opinion dynamics literature. However, it has already been studied in psychometrics, a branch of psychology. In this field, real-world opinions are converted into numbers using abstract objects called 'scales.' These scales can be converted one into the other, in the same way as we convert meters to feet. Thus, in our work, we analyze how this scale transformation may affect opinion dynamics models. We perform our analysis both using mathematical modeling and validating it via agent-based simulations. To distinguish between scale transformation and measurement error, we first analyze the case of perfect scales (i.e., no error or noise). Here we show that a scale transformation may change the model’s dynamics up to a qualitative level. Meaning that a researcher may reach a totally different conclusion, even using the same dataset just by slightly changing the way data are pre-processed. Indeed, we quantify that this effect may alter the model’s output by 100%. By using two models from the standard literature, we show that a scale transformation can transform one model into the other. This transformation is exact, and it holds for every result. Lastly, we also test the case of using real-world data (i.e., finite precision). We perform this test using a 7-points Likert scale, showing how even a small scale change may result in different predictions or a number of opinion clusters. Because of this, we think that scale transformation should be considered as a third-degree of freedom for opinion dynamics. Indeed, its properties have a strong impact both on theoretical models and for their application to real-world data.

Keywords: degrees of freedom, empirical validation, opinion scale, opinion dynamics

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Authors: Olga S. Volodko, Lidiya A. Kompaniets, Ludmila V. Gavrilova

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The method of empirical orthogonal functions is the method of data analysis with a complex spatial-temporal structure. This method allows us to decompose the data into a finite number of modes determined by empirically finding the eigenfunctions of data correlation matrix. The modes have different scales and can be associated with various physical processes. The empirical orthogonal function method has been widely used for the analysis of hydrophysical characteristics, for example, the analysis of sea surface temperatures in the Western North Atlantic, ocean surface currents in the North Carolina, the study of tropical wave disturbances etc. The method used in this study has been applied to the analysis of temperature and velocity measurements in saline Lake Shira (Southern Siberia, Russia). Shira is a shallow lake with the maximum depth of 25 m. The lake Shira can be considered as a closed water site because of it has one small river providing inflow and but it has no outflows. The main factor that causes the motion of fluid is variable wind flows. In summer the lake is strongly stratified by temperature and saline. Long-term measurements of the temperatures and currents were conducted at several points during summer 2014-2015. The temperature has been measured with an accuracy of 0.1 ºC. The data were analyzed using the empirical orthogonal function method in the real version. The first empirical eigenmode accounts for 70-80 % of the energy and can be interpreted as temperature distribution with a thermocline. A thermocline is a thermal layer where the temperature decreases rapidly from the mixed upper layer of the lake to much colder deep water. The higher order modes can be interpreted as oscillations induced by internal waves. The currents measurements were recorded using Acoustic Doppler Current Profilers 600 kHz and 1200 kHz. The data were analyzed using the empirical orthogonal function method in the complex version. The first empirical eigenmode accounts for about 40 % of the energy and corresponds to the Ekman spiral occurring in the case of a stationary homogeneous fluid. Other modes describe the effects associated with the stratification of fluids. The second and next empirical eigenmodes were associated with dynamical modes. These modes were obtained for a simplified model of inhomogeneous three-level fluid at a water site with a flat bottom.

Keywords: Ekman spiral, empirical orthogonal functions, data analysis, stratified fluid, thermocline

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Authors: Amandeep Kaur, Ns Atri, Munruchi Kaur

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Mushrooms have shaped our environment in ways that we are only beginning to understand. The weather patterns, topography, flora and fauna of Punjab state in India create favorable growing conditions for thousands of species of mushrooms, but the complete region was unexplored when it comes to coprophilous mushrooms growing on herbivorous dung. Coprophilous mushrooms are the most specialized fungi ecologically, which germinate and grow directly on different types of animal dung or on manured soil. In the present work, the diversity of coprophilous mushrooms' of Family Psathyrellaceae of the order Agaricales is explored, their relationship to the human world is sketched out, and their supreme significance to life on this planet is revealed. During the investigation, different dung localities from 16 districts of Punjab state have been explored for the collection of material. The macroscopic features of the collected mushrooms were documented on the Field key. The hand cut sections of the various parts of carpophore, such as pileus, gills, stipe and the basidiospores details, were studied microscopically under different magnification. Various authentic publications were consulted for the identification of the investigated taxa. The classification, authentic names and synonyms of the investigated taxa are as per the latest version of Dictionary of Fungi and the MycoBank. The present work deals with the taxonomy of 81 collections belonging to 39 species spread over 05 coprophilous genera, namely Psathyrella, Panaeolus, Parasola, Coprinopsis, and Coprinellus of family Psathyrellaceae. In the text, the investigated taxa have been arranged as they appear in the key to the genera and species investigated. In this work, have been thoroughly examined for their macroscopic, microscopic, ecological, and chemical reaction details. The authors dig deeper to give indication of their ecology and the dung type where they can be obtained. Each taxon is accompanied by a detailed listing of its prominent features and an illustration with habitat photographs and line drawings of morphological and anatomical features. Taxa are organized as per their status in the keys, which allow easy recognition. All the taxa are compared with similar taxa. The study has shown that dung is an important substrate which serves as a favorable niche for the growth of a variety of mushrooms. This paper shows an insight what short-lived coprophilous mushrooms can teach us about sustaining life on earth!

Keywords: abundance, basidiomycota, biodiversity, seasonal availability, systematics

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Authors: S. Curteanu, F. Leon, M. Gavrilescu, S. A. Floria

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Optimization algorithms inspired from human behavior were applied in this approach, associated with neural networks models. The algorithms belong to human behaviors of learning and cooperation and human competitive behavior classes. For the first class, the main strategies include: random learning, individual learning, and social learning, and the selected algorithms are: simplified human learning optimization (SHLO), social learning optimization (SLO), and teaching-learning based optimization (TLBO). For the second class, the concept of learning is associated with competitiveness, and the selected algorithms are sports-inspired algorithms (with Football Game Algorithm, FGA and Volleyball Premier League, VPL) and Imperialist Competitive Algorithm (ICA). A real process, the synthesis of polyacrylamide-based multicomponent hydrogels, where some parameters are difficult to obtain experimentally, is considered as a case study. Reaction yield and swelling degree are predicted as a function of reaction conditions (acrylamide concentration, initiator concentration, crosslinking agent concentration, temperature, reaction time, and amount of inclusion polymer, which could be starch, poly(vinyl alcohol) or gelatin). The experimental results contain 175 data. Artificial neural networks are obtained in optimal form with biologically inspired algorithm; the optimization being perform at two level: structural and parametric. Feedforward neural networks with one or two hidden layers and no more than 25 neurons in intermediate layers were obtained with values of correlation coefficient in the validation phase over 0.90. The best results were obtained with TLBO algorithm, correlation coefficient being 0.94 for an MLP(6:9:20:2) – a feedforward neural network with two hidden layers and 9 and 20, respectively, intermediate neurons. Good results obtained prove the efficiency of the optimization algorithms. More than the good results, what is important in this approach is the simulation methodology, including neural networks and optimization biologically inspired algorithms, which provide satisfactory results. In addition, the methodology developed in this approach is general and has flexibility so that it can be easily adapted to other processes in association with different types of models.

Keywords: artificial neural networks, human behaviors of learning and cooperation, human competitive behavior, optimization algorithms

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Authors: Thayse Marques Passos, Brid Quilty, Mary Pryce

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The interest in developing alternative techniques to obtain safe water, free from pathogens and hazardous substances, is growing in recent times. The photodynamic inactivation of microorganisms (PDI) is a promising ecologically-friendly and multi-target approach for water disinfection. It uses visible light as an energy source combined with a photosensitiser (PS) to transfer energy/electrons to a substrate or molecular oxygen generating reactive oxygen species, which cause cidal effects towards cells. PDI has mainly been used in clinical studies and investigations on its application to disinfect water is relatively recent. The majority of studies use planktonic cells. However, in their natural environments, bacteria quite often do not occur as freely suspended cells (planktonic) but in cell aggregates that are either freely floating or attached to surfaces as biofilms. Microbes can form aggregates and biofilms as a strategy to protect them from environmental stress. As aggregates, bacteria have a better metabolic function, they communicate more efficiently, and they are more resistant to biocide compounds than their planktonic forms. Among the bacteria that are able to form aggregates are members of the genus Pseudomonas, they are a very diverse group widely distributed in the environment. Pseudomonas species can form aggregates/biofilms in water and can cause particular problems in water distribution systems. The aim of this study was to evaluate the effectiveness of photodynamic inactivation in killing a range of planktonic cells including Escherichia coli DSM 1103, Staphylococcus aureus DSM 799, Shigella sonnei DSM 5570, Salmonella enterica and Pseudomonas putida DSM 6125, and aggregating cells of Pseudomonas fluorescens DSM 50090, Pseudomonas aeruginosa PAO1. The experiments were performed in glass Petri dishes, containing the bacterial suspension and the photosensitiser, irradiated with a multi-LED (wavelengths 430nm and 660nm) for different time intervals. The responses of the cells were monitored using the pour plate technique and confocal microscopy. The study showed that bacteria belonging to Pseudomonads group tend to be more tolerant to PDI. While E. coli, S. aureus, S. sonnei and S. enterica required a dosage ranging from 39.47 J/cm2 to 59.21 J/cm2 for a 5 log reduction, Pseudomonads needed a dosage ranging from 78.94 to 118.42 J/cm2, a higher dose being required when the cells aggregated.

Keywords: bacterial aggregation, photoinactivation, Pseudomonads, water disinfection

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Authors: Madhawa Basnayaka, Jouni Paltakari

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Fully passive backscattering chipless RFID tags are an emerging wireless technology with low cost, higher reading distance, and fast automatic identification without human interference, unlike already available technologies like optical barcodes. The design optimization of chipless RFID tags is crucial as it requires replacing integrated chips found in conventional RFID tags with printed geometric designs. These designs enable data encoding and decoding through backscattered electromagnetic (EM) signatures. The applications of chipless RFID tags have been limited due to the constraints of data encoding capacity and the ability to design accurate yet efficient configurations. The traditional approach to accomplishing design parameters for a desired EM response involves iterative adjustment of design parameters and simulating until the desired EM spectrum is achieved. However, traditional numerical simulation methods encounter limitations in optimizing design parameters efficiently due to the speed and resource consumption. In this work, a deep learning neural network (DNN) is utilized to establish a correlation between the EM spectrum and the dimensional parameters of nested centric rings, specifically square and octagonal. The proposed bi-directional DNN has two simultaneously running neural networks, namely spectrum prediction and design parameters prediction. First, spectrum prediction DNN was trained to minimize mean square error (MSE). After the training process was completed, the spectrum prediction DNN was able to accurately predict the EM spectrum according to the input design parameters within a few seconds. Then, the trained spectrum prediction DNN was connected to the design parameters prediction DNN and trained two networks simultaneously. For the first time in chipless tag design, design parameters were predicted accurately after training bi-directional DNN for a desired EM spectrum. The model was evaluated using a randomly generated spectrum and the tag was manufactured using the predicted geometrical parameters. The manufactured tags were successfully tested in the laboratory. The amount of iterative computer simulations has been significantly decreased by this approach. Therefore, highly efficient but ultrafast bi-directional DNN models allow rapid and complicated chipless RFID tag designs.

Keywords: artificial intelligence, chipless RFID, deep learning, machine learning

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

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

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

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Authors: Bander Mohayya Alotaibi

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The valuable partnerships between parents and teachers may develop positive and effective interactions between home and school. This will help these stakeholders share information and resources regarding student academics during ongoing interactions. Thus, partnerships will build a solid foundation for both families and schools to help children succeed in school. Parental involvement can be seen as an effective tool that can change homes and communities and not just schools’ systems. Seeking parents and stakeholders’ attitudes toward learning and learners can help schools design a curriculum. Subsequently, this information can be used to find ways to help improve the academic performance of students, especially in low performing schools. There may be some conflicts when designing curriculum. In addition, designing curriculum might bring more educational expectations to all the sides. There is a lack of research that targets the specific attitude of parents toward specific concepts on curriculum contents. More research is needed to study the perspective that parents of children with learning disabilities (LD) have regarding early reading curriculum. Parents and stakeholders’ perspectives on early reading intervention implemented as a curriculum for children with LD was studied through an advanced quantitative research. The purpose of this study seeks to understand stakeholders and parents’ perspectives of key concepts and essential early reading skills that impact the design of curriculum that will serve as an intervention for early struggler readers who have LD. Those concepts or stages include phonics, phonological awareness, and reading fluency as well as strategies used in house by parents. A survey instrument was used to gather the data. Participants were recruited through 29 schools and districts of the metropolitan area of the northern part of Saudi Arabia. Participants were stakeholders including parents of children with learning disability. Data were collected using distribution of paper and pen survey to schools. Psychometric properties of the instrument were evaluated for the validity and reliability of the survey; face validity, content validity, and construct validity including an Exploratory Factor Analysis were used to shape and reevaluate the structure of the instrument. Multivariate analysis of variance (MANOVA) used to find differences between the variables. The study reported the results of the perspectives of stakeholders toward reading strategies, phonics, phonological awareness, and reading fluency. Also, suggestions and limitations are discussed.

Keywords: stakeholders, learning disability, early reading, perspectives, parents, intervention, curriculum

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Authors: Jennifer Walinga, Samantha Heron

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The goal of the study was to inform the design of effective leadership and mentorship development programming for sport science leaders within the network of Canadian sport institutes and centers. The LEAD (Learn, Engage, Accelerate, Develop) program was implemented to equip sport science leaders with the leadership knowledge, skills, and practice to foster a high - performance culture, enhance the daily training environment, and contribute to optimal performance in sport. After two years of delivery, this analysis of LEAD’s effect on individual and organizational health and performance factors informs the quality of future deliveries and identifies best practice for leadership development across the Canadian sport system and beyond. A larger goal for this project was to inform the public sector more broadly and position sport as a source of best practice for human and social health, development, and performance. The objectives of this study were to review and refine the LEAD program in collaboration with Canadian Sport Institute and Centre leaders, 40-50 participants from three cohorts, and the LEAD program advisory committee, and to trace the effects of the LEAD leadership development program on key leadership mentorship and organizational health indicators across the Canadian sport institutes and centers so as to capture best practice. The study followed a participatory action research framework (PAR) using semi structured interviews with sport scientist participants, program and institute leaders inquiring into impact on specific individual and organizational health and performance factors. Findings included a strong increase in self-reported leadership knowledge, skill, language and confidence, enhancement of human and organizational health factors, and the opportunity to explore more deeply issues of diversity and inclusion, psychological safety, team dynamics, and performance management. The study was significant in building sport leadership and mentorship development strategies for managing change efforts, addressing inequalities, and building personal and operational resilience amidst challenges of uncertainty, pressure, and constraint in real time.

Keywords: sport leadership, sport science leader, leadership development, professional development, sport education, mentorship

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Authors: Vidya Yadav

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India’s youth bulge is now sharpest at the critical 15-24 age group, even as its youngest, and oldest age groups begin to narrow. As the ‘single year, age data’ for the 2011 Census releases the data on the number of people at each year of age in the population. The data shows that India’s working age population (15-64 years) is now 63.4 percent of the total, as against just short of 60 percent in 2001. The numbers also show that the ‘dependency ratio’ the ratio of children (0-14) and the elderly (65 above) to those in the working age has shrunk further to 0.55. “Even as the western world is in ageing situation, these new numbers show that India’s population is still very young”. As the fertility falls faster in urban areas, rural India is younger than urban India; while 51.73 percent of rural Indians are under the age of 24 and 45.9 percent of urban Indians are under 24. The percentage of the population under the age of 24 has dropped, but many demographers say that it should not be interpreted as a sign of the youth bulge is shrinking. Rather it is because of “declining fertility, the number of infants and children reduces first, and this is what we see with the number of under age 24. Indeed the figure shows that the proportion of children in the 0-4 and 5-9 age groups has fallen in 2011 compared to 2001. For the first time, the percentage of children in the 10-14 age group has also fallen, as the effect of families reducing the number of children they have begins to be felt. The present paper key issue is to examine that “whether this growing youth bulge has the right skills for the workforce or not”. The study seeks to examine the youth population structure and employment distribution among them in India during 2001-2011 in different industrial category. It also tries to analyze the workforce participation rate as main and marginal workers both for male and female workers in rural and urban India by utilizing an abundant source of census data from 2001-2011. Result shows that an unconscionable number of adolescents are working when they should study. In rural areas, large numbers of youths are working as an agricultural labourer. Study shows that most of the youths working are in the 15-19 age groups. In fact, this is the age of entry into higher education, but due to economic compulsion forces them to take up jobs, killing their dreams of higher skills or education. Youths are primarily engaged in low paying irregular jobs which are clearly revealed by census data on marginal workers. That is those who get work for less than six months in a year. Large proportions of youths are involved in the cultivation and household industries works.

Keywords: main, marginal, youth, work

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Authors: Josée Charette

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The academic and educational success of immigrant students is a current issue in education, especially in western societies such in the province of Quebec, in Canada. For people who immigrate with school-age children, the success of the family’s migratory project is often measured by the benefits drawn by children from the educational institutions of their host society. In order to support the academic achievement of their children, immigrant parents try to develop practices that derive from their representations of school and related challenges inspired by the socio-cultural context of their country of origin. These findings lead us to the following question: How does strategies implemented by immigrant parents to manage the representational distance between school of their country of origin and school of the host society support or not the academic and educational success of their child? In the context of a qualitative exploratory approach, we have made interviews in the French-, English- and Spanish-languages with 32 newly immigrated parents and 10 of their children. Parents were invited to complete a network of free associations about «School in Quebec» as a premise for the interview. The objective of this communication is to present strategies implemented by immigrant parents to manage the distance between their representations of schools in their country of origin and in the host society, and to explore the influence of this management on their child’s academic and educational trajectories. Data analysis led us to develop various types of strategies, such as continuity, adaptation, resources mobilization, compensation and "return to basics" strategies. These strategies seem to be part of a continuum from oppositional-conflict scenario, in which parental strategies act as a risk factor, to conciliator-integrator scenario, in which parental strategies act as a protective factor for immigrant students’ academic and educational success. In conclusion, we believe that our research helps in providing a more efficient support to immigrant parents and contributes to develop a wider portrait of immigrant students’ academic achievement. In addition, we think that by improving the experience of immigrant families in Quebec schools, a greater number of migratory projects will be effective.

Keywords: immigrant students, family’s migratory project, school of origin and school of host society, immigrants parental strategies

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Authors: M. A. C. S. Sampath Fernando, James M. Curran, Renate Meyer

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Forensic DNA analysis has received much attention over the last three decades, due to its incredible usefulness in human identification. The statistical interpretation of DNA evidence is recognised as one of the most mature fields in forensic science. Peak heights in an Electropherogram (EPG) are approximately proportional to the amount of template DNA in the original sample being tested. A stutter is a minor peak in an EPG, which is not masking as an allele of a potential contributor, and considered as an artefact that is presumed to be arisen due to miscopying or slippage during the PCR. Stutter peaks are mostly analysed in terms of stutter ratio that is calculated relative to the corresponding parent allele height. Analysis of mixture profiles has always been problematic in evidence interpretation, especially with the presence of PCR artefacts like stutters. Unlike binary and semi-continuous models; continuous models assign a probability (as a continuous weight) for each possible genotype combination, and significantly enhances the use of continuous peak height information resulting in more efficient reliable interpretations. Therefore, the presence of a sound methodology to distinguish between stutters and real alleles is essential for the accuracy of the interpretation. Sensibly, any such method has to be able to focus on modelling stutter peaks. Bayesian nonparametric methods provide increased flexibility in applied statistical modelling. Mixture models are frequently employed as fundamental data analysis tools in clustering and classification of data and assume unidentified heterogeneous sources for data. In model-based clustering, each unknown source is reflected by a cluster, and the clusters are modelled using parametric models. Specifying the number of components in finite mixture models, however, is practically difficult even though the calculations are relatively simple. Infinite mixture models, in contrast, do not require the user to specify the number of components. Instead, a Dirichlet process, which is an infinite-dimensional generalization of the Dirichlet distribution, is used to deal with the problem of a number of components. Chinese restaurant process (CRP), Stick-breaking process and Pólya urn scheme are frequently used as Dirichlet priors in Bayesian mixture models. In this study, we illustrate an infinite mixture of simple linear regression models for modelling stutter ratio and introduce some modifications to overcome weaknesses associated with CRP.

Keywords: Chinese restaurant process, Dirichlet prior, infinite mixture model, PCR stutter

Procedia PDF Downloads 324