Search results for: physiological data extraction

Authors: Najafi S., Heidai R., Jamei R., Tofigh F.

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In order to study the effects of magnetic field on the root system and growth of Phaseolus vulgaris, an experiment was conducted in 2012. The possible involvement of magnetic field (MF) pretreatment in physiological factors of Phaseolus vulgaris was investigated. Seeds were subjected to 10 days with 1.8 mT of magnetic field for 1h per day. MF pretreatment decreased the plant height, fresh and dry weight, length of root and length of shoot, Chlorophyll a, Chlorophyll b and carotenoid in 10 days old seedling. In addition, activity of enzymes such as Catalase and Guaiacol peroxidase was decreased due to MF exposure. Also, the total Protein and DPPH content of the treated by magnetic field was not significantly changed in compare to control groups, while the flavonoid, Phenol and prolin content of the treated of the treated by magnetic field was significantly changed in compare to control groups. Lateral branches of roots and secondary roots increased with MF. The results suggest that pretreatment of this MF plays important roles in changes in crop productivity. In all cases there was observed a slight stimulating effect of the factors examined. The growth dynamics were weakened. The plants were shorter. Moreover, the effect of a magnetic field on the crop of Phaseolus vulgaris and its structure was small.

Keywords: carotenoid, Chlorophyll a, Chlorophyll b, DPPH, enzymes, flavonoid, germination, growth, phenol, proline, protein, magnetic field, phaseolus vulgaris

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Authors: Taner Ersoz, Filiz Ersoz

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This study was designed enable application of multivariate technique in the interpretation of categorical data for measuring health care services satisfaction in Turkey. The data was collected from a total of 17726 respondents. The establishment of the sample group and collection of the data were carried out by a joint team from The Ministry of Health and Turkish Statistical Institute (Turk Stat) of Turkey. The multiple correspondence analysis (MCA) was used on the data of 2882 respondents who answered the questionnaire in full. The multiple correspondence analysis indicated that, in the evaluation of health services females, public employees, younger and more highly educated individuals were more concerned and complainant than males, private sector employees, older and less educated individuals. Overall 53 % of the respondents were pleased with the improvements in health care services in the past three years. This study demonstrates the public consciousness in health services and health care satisfaction in Turkey. It was found that most the respondents were pleased with the improvements in health care services over the past three years. Awareness of health service quality increases with education levels. Older individuals and males would appear to have lower expectancies in health services.

Keywords: multiple correspondence analysis, multivariate categorical data, health care services, health satisfaction survey

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Authors: Juliana Bastos dos Santos, Francisca Dantas Mendes, Abdul Jabbar Mohammad Khatri, Adam Abdul Jabbar Khatri

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This research aims to describe the experimentation of color extraction from household waste, for the application of the natural vegetable dyeing technique, as a more sustainable option for the upcycling process. Based on the research of the case study, this article intends to record the process of collecting the materials, extracting the colors and their applicability. The study aims to deepen the knowledge about possible alternatives that generate less impact on the environment throughout the process of plant stamping and, also, to spread the concepts of sustainability in fashion. Therefore, this content becomes relevant for valuing an artisanal production process, reconnecting with ancestral knowledge. This article also intends to serve as a record of ancestral artisanal processes, based on the indigenous and African matrices that are pillars of Brazilian culture.

Keywords: natural dyeing, sustainability, organic residue, fashion, reuse

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Authors: Mehri Sadat Alavinasab Ashgezari, Gholam Reza Nabi Bidhendi, Fatemeh Sadat Alavinasab Ashkezari

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Atmospheric aerosol loading (AAL) from anthropogenic sources is an evidence in industrial development. The accelerated trends in material consumption at the global scale in recent years demonstrate consumption paradigms sensible to the planetary boundaries (PB). This paper is a statistical approach on recognizing the path of climate-relevant bulk materials production (CBMP) of steel, cement and plastics to AAL via an updated and validated spatiotemporal distribution. The methodology of statistical analysis used the most updated regional or global databases or instrumental technologies. This corresponded to a selection of processes and areas capable for tracking AAL within the last decade, analyzing the most validated data while leading to explore the behavior functions or models. The results also represented a correlation within socio economic metabolism idea between the materials specified as macronutrients of society and AAL as a PB with an unknown threshold. The selected country contributors of China, India, US and the sample country of Iran show comparable cumulative AAL values vs to the bulk materials domestic extraction and production rate in the study period of 2012 to 2022. Generally, there is a tendency towards gradual descend in the worldwide and regional aerosol concentration after 2015. As of our evaluation, a considerable share of human role, equivalent 20% from CBMP, is for the main anthropogenic species of aerosols, including sulfate, black carbon and organic particulate matters too. This study, in an innovative approach, also explores the potential role of AAL control mechanisms from the economy sectors where ordered and smoothing loading trends are accredited through the disordered phenomena of CBMP and aerosol precursor emissions. The equilibrium states envisioned is an approval to the well-established theory of Spin Glasses applicable in physical system like the Earth and here to AAL.

Keywords: atmospheric aeroso loading, material flows, climate bulk materials, industrial ecology

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Authors: Fatima Bello, Ibrahim Sani

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Medicinal plants are the most important sources of life saving drugs for the majority of world’s population. People of all continents have used hundreds to thousands of indigenous plants in curing and management of many diseases. Sesame (Sesamum indicum L.) is one of the most widely cultivated species for its nutritious and medicinal seeds and oil. This research was carried out to determine the flavonoid content and antioxidant potential of two varieties of sesame seeds oil. Oil extraction was done using Soxhlet apparatus. The percentage oil yield for white and brown seeds were 47.85% and 20.72%, respectively. Flavonoid was present in both seeds with concentration of 480 mg/g and 360 mg/g in white and brown sesame seeds, respectively. The antioxidant potential was determined at different oil volume; 1.00, 0.75, 0.50 and 0.25ml. The results for the white and brown sesame seed oils were 96.8 and 70.7, 91.0 and 65.2, 83.1 and 55.4, 77.9 and 50.2, respectively. The white seed oil has higher oil yield than the brown seed oil. Likewise, the white seed oil has more flavonoid content than the brown seed oil and also better reducing power than the brown seed oil.

Keywords: antioxidant potential, brown sesame seeds, flavonoid content, sesame seed oil, Sesamum indicum L., white sesame seeds

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Authors: Muhammad Al Rizqi Dharma Fauzi, Dwi Yulian Fahruddin Shah, Andre Pratama, Ari Hasna Widyapuspa, Ganden Supriyanto

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Diabetes mellitus is still known as one of diseases which give a big amount of death in the world. From 2012 to 2014, diabetes is estimated to have resulted in 1.5 to 4.9 million deaths each year. In this paper, we present our research in the analysis and dose determination of Tenebrio molitor (Mealworm) extract as an anti-diabetic agent which is believed by Indonesian people as a traditional treatment to prevent and treat diabetes. We found that Tenebrio molitor extract has a potential as an anti-diabetic agent by in vitro test to Mus musculus which were divided into six group of treatment. Our dose determination analysis gave a conclusion that at 2,5 g/mL of concentration of the extract would give the optimal result in healing a wound given to Mus musculus which were induced by aloxane monohydrate. These results show that Tenebrio molitor extract is potential to be used as an Anti-Diabetic agent.

Keywords: diabetes, extraction, Tenebrio molitor, traditional medicine

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Authors: Paul Dallyn, Ashraf El-Hamalawi, Alessandro Palmeri, Bob Knight

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In order to better understand the long term implications of the grout wear failure mode in large-diameter plain-sided grouted connections, a numerical model has been developed and calibrated that can take advantage of existing operational plant data to predict the wear accumulation for the actual load conditions experienced over a given period, thus limiting the need for expensive monitoring systems. This model has been derived and calibrated based on site structural condition monitoring (SCM) data and supervisory control and data acquisition systems (SCADA) data for two operational wind turbine generator substructures afflicted with this challenge, along with experimentally derived wear rates.

Keywords: grouted connection, numerical model, offshore structure, wear, wind energy

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Authors: Valdrina Ajeti, Icko Gjorgoski

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Stress can be a reason for some physiological and biological disorders in the body. The antioxidative defense system is necessary for the maintenance of redox homeostasis in organisms. Because of its antioxidant effect, alkaline water (AW) is the focus of scientific interest. Adding AW and co-treatment with sodium ascorbate (SA) is expected for the organism to act preventively to hyperthermic stress. To investigate the effect of AW and SA on glucose and cortisol levels during acute hyperthermic stress, white female Wistar laboratory rats, divided into three groups of 10 individuals, were exposed to heat for 80 min, for 21 days. Acute hyperthermic exposure at 41˚C was a cause for oxidative stress. The first group is the control group, the second group is treated with AW, and the third group with AW and SA. Plasma glucose levels were determined by colorimetric method and cortisol was measured using the enzyme-linked immunosorbent assay method. The comparison of the means was made using the Tukey test. Differences were considered significant at a level of p < 0.05. Our results show that levels of glucose and cortisol have been increased in the group treated with AW on the 21st day after treatment (p < 0.0001), but not on the 7th and 14th day as compared to the control group. Also, co-treatment of animals with AW and SA significantly increased the levels of glucose and cortisol on the 21st day after treatment showing a synergistic effect. The individual action of AW, as well as synergism with SA, caused a high protective effect on oxidative damage.

Keywords: alkaline water, sodium ascorbate, hyperthermic stress, glucose, cortisol

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Authors: Ons Slimene, Aroua Taamallah, Maha Khemaja

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In recent years, human activity recognition (HAR) has been a key area of research due to its diverse applications. It has garnered increasing attention in the field of computer vision. HAR plays an important role in people’s daily lives as it has the ability to learn advanced knowledge about human activities from data. In HAR, activities are usually represented by exploiting different types of sensors, such as embedded sensors or visual sensors. However, these sensors have limitations, such as local obstacles, image-related obstacles, sensor unreliability, and consumer concerns. Recently, several deep learning-based approaches have been proposed for HAR and these approaches are classified into two categories based on the type of data used: vision-based approaches and sensor-based approaches. This research paper highlights the importance of multimodal data fusion from skeleton data obtained from videos and data generated by embedded sensors using deep neural networks for achieving HAR. We propose a deep multimodal fusion network based on a twostream architecture. These two streams use the Convolutional Neural Network combined with the Bidirectional LSTM (CNN BILSTM) to process skeleton data and data generated by embedded sensors and the fusion at the feature level is considered. The proposed model was evaluated on a public OPPORTUNITY++ dataset and produced a accuracy of 96.77%.

Keywords: human activity recognition, action recognition, sensors, vision, human-centric sensing, deep learning, context-awareness

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Authors: Lubna Azmi, Ila Shukla, Shyam Sundar Gupta, Padam Kant, C. V. Rao

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Elvitegravir is the mainstay of anti-HIV combination therapy in most endemic countries presently. However, it cannot be used alone owing to its long onset time of action. 2-(3,4-dihydroxyphenyl)-3,5,7-trihydroxychromen-4-one (Quercetin: QU) is a polyphenolic compound obtained from Argeria speciosa Linn (Family: Convolvulaceae), an anti-HIV candidate. In the present study, a sensitive, simple and rapid high-performance liquid chromatography coupled with positive ion electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) method was developed for the simultaneous determination elvitegravir and Quercetin, in rat plasma. The method was linear over a range of 0.2–500 ng/ml. All validation parameters met the acceptance criteria according to regulatory guidelines. LC–MS/MS method for determination of Elvitegravir and Quercetin was developed and validated. Results show the potential of drug–drug interaction upon co-administration this marketed drugs and plant derived secondary metabolite.

Keywords: anti-HIV resistance, extraction, HPLC-ESI-MS-MS, validation

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Authors: Lauren E. Church

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Background: Extravehicular activities (EVAs) are a critical aspect of missions aboard the International Space Station (ISS). It has long been noted that the spaceflight environment and the physical demands of EVA cause physiological and metabolic changes in humans; this review aims to combine these findings with nutritional studies in analogues of the spaceflight and EVA environments to make nutritional recommendations for astronauts scheduled for and immediately returning from EVAs. Results: Energy demands increase during orbital spaceflight and see further increases during EVA. Another critical element of EVA nutrition is adequate hydration. Orbital EVA appears to provide adequate hydration under current protocol, but during lunar surface EVA (LEVA) and in a 10km lunar walk-back test astronauts have stated that up to 20% more water was needed. Previous attempts for in-suit edible sustenance have not been adequately taken up by astronauts to be economically viable. In elite endurance athletes, a mixture of glucose and fructose is used in gels, improving performance. Discussion: A combination of non-caffeinated energy drink and simple water should be available for astronauts during EVA, allowing more autonomy. There should also be provision of gels or a similar product containing appropriate sodium levels to maintain hydration, but not so much as to hyperhydrate through renal water reabsorption. It is also suggested that short breaks be built into the schedule of EVAs for these gels to be consumed, as it is speculated that reason for low uptake of in-suit sustenance is the lack of time available in which to consume it.

Keywords: astronaut, nutrition, space, sport

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Authors: Adrien Chatel, Ehsan Askari Mahvelati, Laurent Fitschy

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Once-Through-Steam-Generators are commonly used in the oil-sand industry in the heavy fuel oil extraction process. They are composed of three main parts: the burner, the radiant and convective sections. Natural gas is burned through staged diffusive flames stabilized by the burner. The heat generated by the combustion is transferred to the water flowing through the piping system in the radiant and convective sections. The steam produced within the pipes is then directed to the ground to reduce the oil viscosity and allow its pumping. With the rapid development of the oil-sand industry, the number of OTSG in operation has increased as well as the associated emissions of environmental pollutants, especially the Nitrous Oxides (NOₓ). To limit the environmental degradation, various international environmental agencies have established regulations on the pollutant discharge and pushed to reduce the NOₓ release. To meet these constraints, OTSG constructors have to rely on more and more advanced tools to study and predict the NOₓ emission. With the increase of the computational resources, Computational Fluid Dynamics (CFD) has emerged as a flexible tool to analyze the combustion and pollutant formation process. Moreover, to optimize the burner operating condition regarding the NOx emission, field characterization and measurements are usually accomplished. However, these kinds of experimental campaigns are particularly time-consuming and sometimes even impossible for industrial plants with strict operation schedule constraints. Therefore, the application of CFD seems to be more adequate in order to provide guidelines on the NOₓ emission and reduction problem. In the present work, two different software are employed to simulate the combustion process in an OTSG, namely the commercial software ANSYS Fluent and the open source software OpenFOAM. RANS (Reynolds-Averaged Navier–Stokes) equations combined with the Eddy Dissipation Concept to model the combustion and closed by the k-epsilon model are solved. A mesh sensitivity analysis is performed to assess the independence of the solution on the mesh. In the first part, the results given by the two software are compared and confronted with experimental data as a mean to assess the numerical modelling. Flame temperatures and chemical composition are used as reference fields to perform this validation. Results show a fair agreement between experimental and numerical data. In the last part, OpenFOAM is employed to simulate several operating conditions, and an Emission Characteristic Map of the combustion system is generated. The sources of high NOₓ production inside the OTSG are pointed and correlated to the physics of the flow. CFD is, therefore, a useful tool for providing an insight into the NOₓ emission phenomena in OTSG. Sources of high NOₓ production can be identified, and operating conditions can be adjusted accordingly. With the help of RANS simulations, an Emission Characteristics Map can be produced and then be used as a guide for a field tune-up.

Keywords: combustion, computational fluid dynamics, nitrous oxides emission, once-through-steam-generators

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Authors: Edjere Oghenekohwiroro, Asibor Irabor Godwin, Uwem Bassey

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This paper determines the presence and levels of phthalates in sachet and borehole water source in some parts of Delta State, Nigeria. Sachet and borehole water samples were collected from seven different water packaging facilities and level of phthalates determined using GC-MS instrumentation. Phthalates concentration in borehole samples varied from 0.00-0.01 (DMP), 0.06-0.20 (DEP), 0.10-0.98 (DBP), 0.21-0.36 (BEHP), 0.01-0.03 (DnOP) µg/L and (BBP) was not detectable; while sachet water varied from 0.03-0.95 (DMP), 0.16-12.45 (DEP), 0.57-3.38 (DBP), 0.00-0.03 (BBP), 0.08-0.31 (BEHP) and 0-0.03 (DnOP) µg/L. Phthalates concentration in the sachet water was higher than that of the corresponding boreholes sources and also showed significant difference (p < 0.05) between the two. Sources of these phthalate esters were the interaction between water molecules and plastic storage facilities. Although concentration of all phthalate esters analyzed were lower than the threshold limit value(TLV), over time storage of water samples in this medium can lead to substantial increase with negative effects on individuals consuming them.

Keywords: phthalate esters, borehole, sachet water, sample extraction, gas chromatography, GC-MS

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Authors: Chandra Mukherjee

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The prevalent knowledge of the biological systems is based on the standard scientific perception of natural equilibrium, determination and predictability. Recently, a rethinking of concepts was presented and a new scientific perspective emerged that involves complexity theory with deterministic chaos theory, nonlinear dynamics and theory of fractals. The unpredictability of the chaotic processes probably would change our understanding of diseases and their management. The mathematical definition of chaos is defined by deterministic behavior with irregular patterns that obey mathematical equations which are critically dependent on initial conditions. The chaos theory is the branch of sciences with an interest in nonlinear dynamics, fractals, bifurcations, periodic oscillations and complexity. Recently, the biomedical interest for this scientific field made these mathematical concepts available to medical researchers and practitioners. Any biological network system is considered to have a nominal state, which is recognized as a homeostatic state. In reality, the different physiological systems are not under normal conditions in a stable state of homeostatic balance, but they are in a dynamically stable state with a chaotic behavior and complexity. Biological systems like heart rhythm and brain electrical activity are dynamical systems that can be classified as chaotic systems with sensitive dependence on initial conditions. In biological systems, the state of a disease is characterized by a loss of the complexity and chaotic behavior, and by the presence of pathological periodicity and regulatory behavior. The failure or the collapse of nonlinear dynamics is an indication of disease rather than a characteristic of health.

Keywords: HRV, HRVI, LF, HF, DII

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Authors: Burcu Guvenek, Duygu Baysal Kurt

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The impact of foreign trade on economic growth has been discussed since the Classical Economists. Today, foreign trade has become more important for the country's economy with the increasing globalization. When it comes to foreign trade, policies which may vary from country to country and from time to time as protectionism or free trade are implemented. In general, the positive effect of foreign trade on economic growth is alleged. However, as studies supporting this general acceptance take place in the economics literature, there are also studies in the opposite direction. In this paper, the impact of foreign trade on economic growth will be investigated with the help of panel data analysis. For this research, 24 OECD countries’ GDP and foreign trade data, including the period of 1990 and 2010, will be used.

Keywords: foreign trade, economic growth, OECD countries, panel data analysis

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Authors: Emanuel Koseos

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Data-Driven Decision Making (DDDM) refers to making decisions that are based on historical data in order to inform practice, develop strategies and implement policies that benefit organizational settings. In educational technology, DDDM facilitates the implementation of differential educational learning approaches such as Educational Data Mining (EDM) and Competency-Based Education (CBE), which commonly target university classrooms. There is a current need for DDDM models applied to middle and secondary schools from a concern for assessing the needs, progress and performance of students and educators with respect to regional standards, policies and evolution of curriculums. To address these concerns, we propose a DDDM reference model developed using educational key process initiatives as inputs to a machine learning framework implemented with statistical software (SAS, R) to provide a best-practices, complex-free and automated approach for educators at their regional level. We assessed the efficiency of the model over a six-year period using data from 45 schools and grades K-12 in the Langley, BC, Canada regional school district. We concluded that the model has wider appeal, such as business learning systems.

Keywords: competency-based learning, data-driven decision making, machine learning, secondary schools

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Authors: Enerit Sacdanaku, Idriz Haxhiu

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This study was conducted in the area of Vlora Bay, Albania. Data about Sea Turtles Caretta caretta and Chelonia mydas, belonging to two periods of time (1984–1991; 2008–2014) are given. All data gathered were analyzed using recent methodologies. For all turtles captured (as by catch), the Curve Carapace Length (CCL) and Curved Carapace Width (CCW) were measured. These data were statistically analyzed, where the mean was 67.11 cm for CCL and 57.57 cm for CCW of all individuals studied (n=13). All untagged individuals of marine turtles were tagged using metallic tags (Stockbrand’s titanium tag) with an Albanian address. Sex was determined and resulted that 45.4% of individuals were females, 27.3% males and 27.3% juveniles. All turtles were studied for the presence of the epibionts. The area of Vlora Bay is used from marine turtles (Caretta caretta) as a migratory corridor to pass from the Mediterranean to the northern part of the Adriatic Sea.

Keywords: Caretta caretta, Chelonia mydas, CCL, CCW, tagging, Vlora Bay

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Authors: Farhat Imtiaz, Umar Farooq

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In this work, we developed a computational model to predict ply level failure in impacted composite laminates. Data obtained from physical testing from flat and round nose impacts of 8-, 16-, 24-ply laminates were considered. Routine inspections of the tested laminates were carried out to approximate ply by ply inflicted damage incurred. Plots consisting of load–time, load–deflection, and energy–time history were drawn to approximate the inflicted damages. Impact test generated unwanted data logged due to restrictions on testing and logging systems were also filtered. Conventional filters (built-in, statistical, and numerical) reliably predicted load thresholds for relatively thin laminates such as eight and sixteen ply panels. However, for relatively thick laminates such as twenty-four ply laminates impacted by flat nose impact generated clipped data which can just be de-noised using oscillatory algorithms. The literature search reveals that modern oscillatory data filtering and extrapolation algorithms have scarcely been utilized. This investigation reports applications of filtering and extrapolation of the clipped data utilising fast Fourier Convolution algorithm to predict load thresholds. Some of the results were related to the impact-induced damage areas identified with Ultrasonic C-scans and found to be in acceptable agreement. Based on consistent findings, utilizing of modern data filtering and extrapolation algorithms to data logged by the existing machines has efficiently enhanced data interpretations without resorting to extra resources. The algorithms could be useful for impact-induced damage approximations of similar cases.

Keywords: fibre reinforced laminates, fast Fourier algorithms, mechanical testing, data filtering and extrapolation

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Authors: Liliana Crăc, Nicolae Giorgi, Gheorghe Fometescu

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In Romania, billions of tonnes of wastes are generated yearly, an important amount being stored within industrial dumps that covers high soil areas and affects the environment quality, especially of ground and surface waters. Landfill represents in Romania the most important way for wastes removal, over 75% being generated every year, the costs with the dumps construction being considerable. In most of the cases, the wastes generated mainly by the energy industry, oil exploitation and metallurgy, are still considered wastes with NO-use, and their removal and neutralization represent for transport, handling and storing, high non-productive expenses which raise the cost of the useful products obtained. The paper presents a recycling idea of three types of wastes in order to use them for building materials manufacturing, by promoting ECOWASTES LIFE+ project, whose aim is to demonstrate that the recycling of waste from energy industry (coal combustion waste), petroleum extraction (drilling mud) and metallurgy (steelmaking slag) is technically feasible.

Keywords: fly ash, drilled solid wastes, metallurgical slag, recycling, building materials

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Authors: Nadine Sammy, Mark Wilson, Samuel Vine

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The Theory of Challenge and Threat States in Athletes (TCTSA) states that self-efficacy is an antecedent of challenge and threat. These states result from conscious and unconscious evaluations of situational demands and personal resources and are represented by both cognitive and physiological markers. Challenge is considered a more adaptive stress response as it is associated with a more efficient cardiovascular profile, as well as better performance and attention effects compared with threat. Self-efficacy is proposed to influence challenge/threat because an individual’s belief that they have the skills necessary to execute the courses of action required to succeed contributes to a perception that they can cope with the demands of the situation. This study experimentally examined the effects of self-efficacy on cardiovascular responses (challenge and threat), demand and resource evaluations, performance and attention under pressurised conditions. Forty-five university students were randomly assigned to either a control (n=15), low self-efficacy (n=15) or high self-efficacy (n=15) group and completed baseline and pressurised golf putting tasks. Self-efficacy was manipulated using false feedback adapted from previous studies. Measures of self-efficacy, cardiovascular reactivity, demand and resource evaluations, task performance and attention were recorded. The high self-efficacy group displayed more favourable cardiovascular reactivity, indicative of a challenge state, compared with the low self-efficacy group. The former group also reported high resource evaluations, but no task performance or attention effects were detected. These findings demonstrate that levels of self-efficacy influence cardiovascular reactivity and perceptions of resources under pressurised conditions.

Keywords: cardiovascular, challenge, performance, threat

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Authors: Chandra Sekhar Singh, P. Chakrapani, B. Arun Jyothi, A. Roja Rani

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The green synthesis of metallic nanoparticles (NPs) involves biocompatible ingredients under physiological conditions of temperature and pressure. Moreover, the biologically active molecules involved in the green synthesis of NPs act as functionalizing ligands, making these NPs more suitable for biomedical applications. Among the most important bioreductants are plant extracts, which are relatively easy to handle, readily available, low cost, and have been well explored for the green synthesis of other nanomaterials. Various types of metallic NPs have already been synthesized using plant extracts. They have wide applicability in various areas such as electronics, catalysis, chemistry, energy, and medicine. Metallic nanoparticles are traditionally synthesized by wet chemical techniques, where the chemicals used are quite often toxic and flammable. In our study, we were described a cost effective and environment friendly technique for green synthesis of silver nanoparticles from 1mM AgNO3 solution through the aqueous extract of Erythrina indica as reducing as well as capping agent. Nanoparticles were characterized using UV–Vis absorption spectroscopy, FTIR, XRD, X-ray diffraction, SEM and TEM analysis showed the average particle size of 30 nm as well as revealed their spherical structure. Further these biologically synthesized nanoparticles were found to be highly toxic against different human pathogens viz. two Gram positive namely Klebsiella pneumonia and Bacillus subtilis bacteria and two were Gram negative bacteria namely Staphylococcus aureus and Escherichia coli (E. coli). This is for the first time reporting that Erythrina indica plant extract was used for the synthesis of nanoparticles.

Keywords: silver nanoparticles, green synthesis, antibacterial activity, FTIR, TEM, SEM

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Authors: Inna V. Krotova

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The study pays special attention to the definition of the psychological potential of a specialist-defectologist, which determines his desire to increase the level of his or her professional competence. The group included participants of the educational environment – an additional professional program 'Technologies of psychological and pedagogical assistance for children with complex developmental disabilities' implemented by the department of defectology and clinical psychology of the KFU jointly with the Support Fund for the Deafblind people 'Co-Unity'. The purpose of our study was to identify the psychological aspects of the readiness of the specialist-defectologist to his or her professional development. The study assessed the indicators of psychological preparedness, and its four components were taken into account: motivational, cognitive, emotional and volitional. We used valid and standardized tests during the study. As a result of the factor analysis of data received (from Extraction Method: Principal Component Analysis, Rotation Method: Varimax with Kaiser Normalization, Rotation converged in 12 iterations), there were identified three factors with maximum factor load from 24 indices, and their correlation coefficients with other indicators were taken into account at the level of reliability p ≤ 0.001 and p ≤ 0.01. Thus the system making factor was determined – it’s a 'motivation to achieve success'; it formed a correlation galaxy with two other factors: 'general internality' and 'internality in the field of achievements', as well as with such psychological indicators as 'internality in the field of family relations', 'internality in the field of interpersonal relations 'and 'low self-control-high self-control' (the names of the scales used is the same as names in the analysis methods. In conclusion of the article, we present some proposals to take into account the psychological model of readiness of specialists-defectologists for their professional development, to stimulate the growth of their professional competence. The study has practical value for all providers of special education and organizations that have their own specialists-defectologists, teachers-defectologists, teachers for correctional and ergotherapeutic activities, specialists working in the field of correctional-pedagogical activity (speech therapists) to people with special needs who need true professional support.

Keywords: psychological readiness, defectologist, professional development, psychological factors, special education, professional competence, innovative educational environment

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Authors: Amon Olimov, Umarov Jamshid, Dae-Ho Kim, Chol-U Lee, Ryum-Duck Oh

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This paper proposes IoT virtualization platform based incident information system. IoT information based environment is the platform that was developed for the purpose of collecting a variety of data by managing regionally scattered IoT devices easily and conveniently in addition to analyzing data collected from roads. Moreover, this paper configured the platform for the purpose of providing incident information based on sensed data. It also provides the same input/output interface as UNIX and Linux by means of matching IoT devices with the directory of file system and also the files. In addition, it has a variety of approaches as to the devices. Thus, it can be applied to not only incident information but also other platforms. This paper proposes the incident information system that identifies and provides various data in real time as to urgent matters on roads based on the existing USN/M2M and IoT visualization platform.

Keywords: incident information system, IoT, virtualization platform, USN, M2M

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Authors: Mina Kargozari, Isabel Revilla Martin, Ángel A. Carbonell-Barrachina, Antoni Szumny

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The profiles of volatile compounds of differently formulated sausages including CH (camel meat-hump), CB (camel meat-beef fat), BH (beef-hump) and BB (beef-beef fat) were analyzed by gas chromatography/mass spectrometry (GC-MS) using a solid phase micro-extraction (SPME) in order to investigate the role of meat and fat type in aroma compounds release. A total of 47 compounds identified, were consisted of 3 acids, 1 ester, 3 alcohols, 7 aldehydes, 5 sulphur compounds, and 27 terpenes. The significant differences were observed in the aroma compounds among four batches. The CH sucuk samples containing the highest (p<0.05) fat amount among the others showed higher amounts of volatiles in consequence. The sausages prepared with hump showed higher amounts of aldehydes and lower amounts of terpenes compared to the sausages made with beef fat (p<0.05). It seemed that meat type had an inconsiderable effect on the volatile profile of the sausages.

Keywords: aromatic compounds, camel meat, hump, SPME

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Authors: Sean McCarthy, Patrice M. Ludwig, Will Watson

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This exploratory case study explores the deployment of Social Network Analysis (SNA) in mapping community assets in an interdisciplinary, undergraduate, team-taught course focused on income insecure populations in a rural area in the US. Specifically, it analyzes how students were taught to collect data on community assets and to visualize the connections between those assets using Kumu, an SNA data visualization tool. Further, the case study shows how social network data was also collected about student teams via their written communications in Slack, an enterprise messaging tool, which enabled instructors to manage and guide student research activity throughout the semester. The discussion presents how SNA methods can simultaneously inform both community-based research and social innovation pedagogy through the use of data visualization and collaboration-focused communication technologies.

Keywords: social innovation, social network analysis, pedagogy, problem-based learning, data visualization, information communication technologies

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Authors: Taju Mohammednur, Tesfaye Megersa, Karta Kaske, Tekeste Kifle

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Coffee is economically important in Ethiopia. However, the conditions under which coffee seeds are dried and processed significantly affect the seedling quality and productivity. The objective of this study was to evaluate the effect of pre-sowing treatments and drying methods on the physiological quality of coffee seeds and seedlings. The study was conducted at the Jimma Agricultural Research Center seed laboratory and nursery site. Two coffee varieties, 74110 and 75227, were used. Fully ripe red cherries were harvested, and the seeds were dried under two conditions: a shade drying room and direct open sun. Pre-sowing seed soaking treatments of 6, 8, 18, and 24 hours, including a control, were applied. A factorial design in a Complete Randomized Design was used. The highest germination percentage (91.48%), emergence rate (90.19%), and seedling vigor index (2236.30) were recorded for seeds dried in the shade drying room. In contrast, the lowest values (70.47%, 68.36%, and 1378.22, respectively) were observed for seeds dried in direct sunlight. There was a significant difference in seed germination based on soaking time, with the highest germination percentage (83.25%) recorded for seeds soaked for 6 hours, followed by 24 hours (83.13%), while the lowest (76.88%) was recorded for un-soaked seeds. The results indicated that drying seeds under shade is better for seed quality. Moreover, further investigation into seed treatment methods and preservation techniques is necessary to improve coffee seed quality.

Keywords: coffee, seed drying, germination, seed, seed longevity, seed priming

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Authors: Farouk Lawan Gambo

Abstract:

Data compression shrinks files into fewer bits then their original presentation. It has more advantage on internet because the smaller a file, the faster it can be transferred but learning most of the concepts in data compression are abstract in nature therefore making them difficult to digest by some students (Engineers in particular). To determine the best approach toward learning data compression technique, this paper first study the learning preference of engineering students who tend to have strong active, sensing, visual and sequential learning preferences, the paper also study the advantage that mobility of learning have experienced; Learning at the point of interest, efficiency, connection, and many more. A survey is carried out with some reasonable number of students, through random sampling to see whether considering the learning preference and advantages in mobility of learning will give a promising improvement over the traditional way of learning. Evidence from data analysis using Ms-Excel as a point of concern for error-free findings shows that there is significance different in the students after using learning content provided on smart phone, also the result of the findings presented in, bar charts and pie charts interpret that mobile learning has to be promising feature of learning.

Keywords: data analysis, compression techniques, learning content, traditional learning approach

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Authors: S. Abera, T. Gidey, W. Terefe

Abstract:

Introduction: Testing for HIV is the key entry point to HIV prevention, treatment, and care and support services. Hence, predictive data mining techniques can greatly benefit to analyze and discover new patterns from huge datasets like that of EDHS 2011 data. Objectives: The objective of this study is to build a predictive modeling for HIV testing and identify determinants of HIV testing for adults with age above fourteen years using data mining techniques. Methods: Cross-Industry Standard Process for Data Mining (CRISP-DM) was used to predict the model for HIV testing and explore association rules between HIV testing and the selected attributes among adult Ethiopians. Decision tree, Naïve-Bayes, logistic regression and artificial neural networks of data mining techniques were used to build the predictive models. Results: The target dataset contained 30,625 study participants; of which 16, 515 (53.9%) were women. Nearly two-fifth; 17,719 (58%), have never been tested for HIV while the rest 12,906 (42%) had been tested. Ethiopians with higher wealth index, higher educational level, belonging 20 to 29 years old, having no stigmatizing attitude towards HIV positive person, urban residents, having HIV related knowledge, information about family planning on mass media and knowing a place where to get testing for HIV showed an increased patterns with respect to HIV testing. Conclusion and Recommendation: Public health interventions should consider the identified determinants to promote people to get testing for HIV.

Keywords: data mining, HIV, testing, ethiopia

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Authors: Fatemehsadat Mortazavizadeh, Amin Dehghani, Majid Mirzaei, Nurulhuda Binti Mohammad Ramli, Adnan Dehghani

Abstract:

Flood is Malaysia's most common and serious natural disaster. Kelantan River Basin is a tropical basin that experiences a rainy season during North-East Monsoon from November to March. It is also one of the hardest hit areas in Peninsular Malaysia during the heavy monsoon rainfall. Considering the consequences of the flood events, it is essential to develop the flood inundation map as part of the mitigation approach. In this study, the delineation of flood inundation zone in the area of Kelantan River basin using a hydrodynamic model is done by HEC-RAS, QGIS and ArcMap. The streamflow data has been generated with the weather generator based on the observation data. Then, the data is statistically analyzed with the Extreme Value (EV1) method for 2-, 5-, 25-, 50- and 100-year return periods. The minimum depth, maximum depth, mean depth, and the standard deviation of all the scenarios, including the OBS, are observed and analyzed. Based on the results, generally, the value of the data increases with the return period for all the scenarios. However, there are certain scenarios that have different results, which not all the data obtained are increasing with the return period. Besides, OBS data resulted in the middle range within Scenario 1 to Scenario 40.

Keywords: flood inundation, kelantan river basin, hydrodynamic model, extreme value analysis

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Authors: Cleiton Pons Ferreira, Diana Francisca Adamatti

Abstract:

Advancements in computers technology have allowed to obtain information for research in biology and neuroscience. In order to transform the data from these surveys, networks have long been used to represent important biological processes, changing the use of this tools from purely illustrative and didactic to more analytic, even including interaction analysis and hypothesis formulation. Many studies have involved this application, but not directly for interpretation of data obtained from brain functions, asking for new perspectives of development in neuroinformatics using existent models of tools already disseminated by the bioinformatics. This study includes an analysis of neurological data through electroencephalogram (EEG) signals, using the Cytoscape, an open source software tool for visualizing complex networks in biological databases. The data were obtained from a comparative case study developed in a research from the University of Rio Grande (FURG), using the EEG signals from a Brain Computer Interface (BCI) with 32 eletrodes prepared in the brain of a blind and a sighted individuals during the execution of an activity that stimulated the spatial ability. This study intends to present results that lead to better ways for use and adapt techniques that support the data treatment of brain signals for elevate the understanding and learning in neuroscience.

Keywords: neuroinformatics, bioinformatics, network tools, brain mapping

Procedia PDF Downloads 167