Search results for: environmental sanitation parameters

Authors: Milenko Košutić, Jelena Filipović, Zvonko Nježić

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Extrusion technology is thermal processing that is applied to improve the nutritional, hygienic, and physical-chemical characteristics of the raw material. Overall, the extrusion process is an efficient method for the production of a wide range of food products. It combines heat, pressure, and shear to transform raw materials into finished goods with desired textures, shapes, and nutritional profiles. The extruded products’ quality is remarkably dependent upon feed material composition, barrel temperature profile, feed moisture content, screw speed, and other extrusion system parameters. Given consumer expectations for snack foods, a high expansion index and low bulk density, in addition to crunchy texture and uniform microstructure, are desired. This paper investigates the effects of simultaneous different types of corn (white corn, yellow corn, red corn, and black corn) addition and different screw speed (350, 500, 650 rpm) on the physical, technological, and functional properties of flakes products. Black corn flour and screw speed at 350 rpm positively influenced physical, technological characteristics, mineral composition, and antioxidant properties of flake products with the best total score analysis of 0,59. Overall, the combination of Tukey's HSD test and PCA enables a comprehensive analysis of the observed corn products, allowing researchers to identify them. This research aims to analyze the influence of different types of corn flour (white corn, yellow corn, red corn, and black corn) on the nutritive and sensory properties of the product (quality, texture, and color), as well as the acceptance of the new product by consumers on the territory of Novi Sad. The presented data point that investigated corn flakes from black corn flour at 350 rpm is a product with good physical-technological and functional properties due to a higher level of antioxidant activity.

Keywords: corn types, flakes product, nutritive quality, acceptability

Procedia PDF Downloads 41

Authors: Rameh Chauhan

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Tunnel construction in Himalayan rock is a challenging task due to fragile nature of the strata. Tunnel excavation carried out from lower Himalayas to high Himalayas in different metamorphic rock. Therefore application of engineering geology plays a vital role during various stage of the tunneling projects. Engineering geology is defined as application of geology to construction of civil structures through engineering practice. It is applied to the design, construction and performance aspects of engineering structure on the surface or sub-surface like dam, underground and surface power house, cut slopes, tunnels and underground storage cavern for nuclear material. But this paper emphasized mostly on underground structures like big caverns of Power house, desilting chambers, and tunnels of various sizes. Construction of these structures in the fragile rock conditions of Himalayan geology from Western Himalayas to Eastern Himalayas necessitated the application of the engineering geology on the micro-scale base for the stability, performance, and longevity of the civil structures. Number of hydropower projects have been constructed, some of them are under construction and under investigation stage. These projects are located in various parts of Himalayas under various seismic-tectonic zones. Tunneling works are involved in these projects. This paper represents the various engineering geological practices adopted in investigation and construction stage of various projects based on experiences gained during past construction histories in Himalayan geology of young mountains in very fragile geological conditions. Highlighting and sharing of use of these techniques on various platforms will definitely enhance the knowledge for carrying out the construction of various projects for the development of society. Construction of the tunnels, surface, and sub-surface caverns, dams, highway, metro, highway tunnels are all based on engineering geological parameters in combinations with other engineering considerations.

Keywords: cavern-power house, desilting chambers and tunnels, seismic-tectonic-zones, earthquake-prone zones based on intensities

Procedia PDF Downloads 211

Authors: Sylvia Szabo, Thilini Navaratne, Indrajit Pal, Seree Park

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Deltaic and coastal regions are often strategically important both from local and regional perspectives. While deltas are known to be bread baskets of the world, delta inhabitants often face the risk of food and nutritional insecurity. These risks are highly exacerbated by the impacts of climate and environmental change. While numerous regional studies examined the prevalence and the determinants of food security in specific delta and coastal regions, there is still a lack of a systematic analysis of the most widely used scientific food security indicators. In order to fill this gap, a systematic review was carried out using Covidence, a Cochrane-adopted systematic review processing software. Papers included in the review were selected from the SCOPUS, Thomson Reuters Web of Science, Science Direct, ProQuest, and Google Scholar databases. Both scientific papers and grey literature (e.g., reports by international organizations) were considered. The results were analyzed by food security components (access, availability, quality, and strategy) and by world regions. Suggestions for further food security, nutrition, and health research, as well as policy-related implications, are also discussed.

Keywords: delta regions, coastal, food security, indicators, systematic review

Procedia PDF Downloads 227

Authors: Win Zaw Hein, Khin Sandar Linn, Su Su Yi Mon, Yoshitaka Goto

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The Earth ionosphere is located at the altitude of about 70 km to several 100 km from the ground, and it is composed of ions and electrons called plasma. In the ionosphere, these plasma makes delay in GPS (Global Positioning System) signals and reflect in radio waves. The delay along the signal path from the satellite to the receiver is directly proportional to the total electron content (TEC) of plasma, and this delay is the largest error factor in satellite positioning and navigation. Sounding observation from the top and bottom of the ionosphere was popular to investigate such ionospheric plasma for a long time. Recently, continuous monitoring of the TEC using networks of GNSS (Global Navigation Satellite System) observation stations, which are basically built for land survey, has been conducted in several countries. However, in these stations, multi-frequency support receivers are installed to estimate the effect of plasma delay using their frequency dependence and the cost of multi-frequency support receivers are much higher than single frequency support GPS receiver. In this research, single frequency GPS receiver was used instead of expensive multi-frequency GNSS receivers to measure the ionospheric plasma variation such as vertical TEC distribution. In this measurement, single-frequency support ublox GPS receiver was used to probe ionospheric TEC. The location of observation was assigned at Mandalay Technological University in Myanmar. In the method, the ionospheric TEC distribution is represented by polynomial functions for latitude and longitude, and parameters of the functions are determined by least-squares fitting on pseudorange data obtained at a known location under an assumption of thin layer ionosphere. The validity of the method was evaluated by measurements obtained by the Japanese GNSS observation network called GEONET. The performance of measurement results using single-frequency of GPS receiver was compared with the results by dual-frequency measurement.

Keywords: ionosphere, global positioning system, GPS, ionospheric delay, total electron content, TEC

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Authors: Hossein Gitinavard, Mohammad Hossein Fazel Zarandi

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In the last decades, concerns about the environmental issues lead to professional and academic efforts on green supplier selection problems. In this sake, one of the main issues in evaluating the green supplier selection problems, which could increase the uncertainty, is the preferences of the experts' judgments about the candidate green suppliers. Therefore, preparing an expert system to evaluate the problem based on the historical data and the experts' knowledge can be sensible. This study provides an expert evaluation system to assess the candidate green suppliers under selected criteria in a multi-period approach. In addition, a ranking approach under interval-valued hesitant fuzzy set (IVHFS) environment is proposed to select the most appropriate green supplier in planning horizon. In the proposed ranking approach, the IVHFS and the last aggregation approach are considered to margin the errors and to prevent data loss, respectively. Hence, a comparative analysis is provided based on an illustrative example to show the feasibility of the proposed approach.

Keywords: green supplier selection, expert system, ranking approach, interval-valued hesitant fuzzy setting

Procedia PDF Downloads 314

Authors: Raquel Bayon, Ainara Lopez-Ortega, Elena Rodriguez, Amaya Igartua

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Corrosion is one of the most concerning phenomenon that accelerates material degradation in offshore applications. In order to avoid the premature failure of metallic materials in marine environments, organic coatings have widely been used, due to their elevated corrosion resistance. Thermally-sprayed metals have recently been used in offshore applications, whereas ceramic materials are usually less employed, due to their high cost. The protectiveness of the coatings can be evaluated and categorized in corrosivity categories in accordance with the ISO 12944-6 Standard. According to this standard, for coatings that are supposed to work in marine environments, a C5-M category is required for components working out of the water or partially immersed in the splash zone, and an Im2 category for totally immersed components. C5-M/Im-2 high category would correspond to a durability of more than 20 years without maintenance in accordance with ISO 12944 and NORSOK M501 standards. In this work, the corrosion behavior of three potential coatings used in offshore applications has been evaluated. For this aim, the materials have been subjected to different environmental conditions in several climatic chambers (humidostatic, climatic, immersion, UV and salt-fog). The category of the coatings to each condition has been selected, in accordance with the previously mentioned standard.

Keywords: cabinet, coatings, corrosion, offshore

Procedia PDF Downloads 408

Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Alejandro Tellez-Jurado, Juan C. Seck-Tuoh-Mora, Eva S. Hernandez-Gress, Norberto Hernandez-Romero, Iaina P. Medina-Serna

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Trichoderma harzianum is a fungus that has been utilized as a low-cost fungicide for biological control of pests, and it is important to determine the optimal conditions to produce the highest amount of conidiospores of Trichoderma harzianum. In this work, the conidiospore production of Trichoderma harzianum is modeled and optimized by using Artificial Neural Networks (AANs). In order to gather data of this process, 30 experiments were carried out taking into account the number of hours of culture (10 distributed values from 48 to 136 hours) and the culture humidity (70, 75 and 80 percent), obtained as a response the number of conidiospores per gram of dry mass. The experimental results were used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers, and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The ANN with the best performance was chosen in order to simulate the process and be able to maximize the conidiospores production. The obtained ANN with the highest performance has 2 inputs and 1 output, three hidden layers with 3, 10 and 10 neurons in each layer, respectively. The ANN performance shows an R2 value of 0.9900, and the Root Mean Squared Error is 1.2020. This ANN predicted that 644175467 conidiospores per gram of dry mass are the maximum amount obtained in 117 hours of culture and 77% of culture humidity. In summary, the ANN approach is suitable to represent the conidiospores production of Trichoderma harzianum because the R2 value denotes a good fitting of experimental results, and the obtained ANN model was used to find the parameters to produce the biggest amount of conidiospores per gram of dry mass.

Keywords: Trichoderma harzianum, modeling, optimization, artificial neural network

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Authors: Efe Ogidiaka-Obende, Gabriel C. C. Ndinwa, John Atadiose, Ewoma O. Oduma

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Water hyacinth (Eichhornia crassipes), which is a native of South America, is believed to have found its way into Nigeria waters through Pot-Novo creek, Benin Republic, in September 1984. This study attempts to review the impacts, challenges, and prospects of water hyacinths in Nigeria's coastal waters. Water hyacinth possesses a very high proliferation rate, and its infestation in Nigeria's coastal waters poses severe problems to the fishing, recreational, transportation, and health sector, amongst other activities. The weed has been reported to disrupt aquatic ecosystems, clog waterways, and create associated problems with water supply, irrigation, and drainage. To curb this menace, a huge amount of money is used yearly for its management, which is not sustainable. There is, however, a positive twist to this plant as it has the potential to be used as fertilizers, feed for fish, craft materials, biogas, and many more. Due to its high population and related economic importance and implications in Nigeria's coastal waters, it is highly recommended that more research works be carried out on the of making optimal use of this plant.

Keywords: waste to wealth, environmental pollution, water hyacinth, biogas, sustainable development goals

Procedia PDF Downloads 74

Authors: You-Lin Wu, Yi-Hsing Sung, Shih-Hung Lin, Jing-Jenn Lin

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Performance improvement in optoelectronic devices such as solar cells and photodetectors has been reported when a polymer/ZnO nanorods stack is used. Resistance switching of polymer/ZnO nanocrystals (or nanorods) hybrid has also gained a lot of research interests recently. It has been reported that high- and low-resistance states of a metal/insulator/metal (MIM) structure diode with a polystyrene (PS) and ZnO hybrid as the insulator layer can be switched by applied bias after a high-voltage forming process, while the same device structure merely with a PS layer does not show any forming behavior. In this work, we investigated the current-voltage (I-V) characteristics of an MIM device with a PS/ZnO nanorods stack deposited on fluorine-doped tin oxide (FTO) glass substrate. The ZnO nanorods were grown by a hydrothermal method using a mixture of zinc nitrate, hexamethylenetetramine, and DI water. Following that, a PS layer was deposited by spin coating. Finally, the device with a structure of Ti/ PS/ZnO nanorods/FTO was completed by e-gun evaporated Ti layer on top of the PS layer. Semiconductor parameters analyzer Agilent 4156C was then used to measure the I-V characteristics of the device by applying linear ramp sweep voltage with sweep sequence of 0V → 4V → 0V → 3V → 0V → 2V → 0V → 1V → 0V in both positive and negative directions. It is interesting to find that the I-V characteristics are bias dependent and hysteretic, indicating that the device Ti/PS/ZnO nanorods/FTO structure has ferroelectricity. Our results also show that the maximum hysteresis loop height of the I-V characteristics as well as the voltage at which the maximum hysteresis loop height of each scan occurs increase with increasing maximum sweep voltage. It should be noticed that, although ferroelectricity has been found in ZnO at its melting temperature (1975℃) and in Li- or Co-doped ZnO, neither PS nor ZnO has ferroelectricity at room temperature. Using the same structure but with a PS or ZnO layer only as the insulator does not give and hysteretic I-V characteristics. It is believed that a charge polarization layer is induced near the PS/ZnO nanorods stack interface and thus causes the ferroelectricity in the device with Ti/PS/ZnO nanorods/FTO structure. Our results show that the PS/ZnO stack can find a potential application in a resistive switching memory device with MIM structure.

Keywords: ferroelectricity, hysteresis, polystyrene, resistance switching, ZnO nanorods

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Authors: M. C. A. Leite, B. Chen-Charpentier, F. Agusto

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A long-term goal of sustainable forest management is a relatively stable source of wood and a stable forest age-class structure has become the goal of many forest management practices. In the absence of disturbances, this forest management goal could easily be achieved. However, in the face of recurring insect outbreaks and other disruptive processes forest planning becomes more difficult, requiring knowledge of the effects on the forest of a wide variety of environmental factors (e.g., habitat heterogeneity, fire size and frequency, harvesting, insect outbreaks, and age distributions). The association between distinct forest disturbances and the potential effect on forest dynamics is a complex matter, particularly when evaluated over time and at large scale, and is not well understood. However, gaining knowledge in this area is crucial for a sustainable forest management. Mathematical modeling is a tool that can be used to broader the understanding in this area. In this talk we will introduce mathematical models formulation incorporating the effect of insect outbreaks either as a single disturbance in the forest population dynamics or coupled with other disturbances: either wildfire or harvesting. The results and ecological insights will be discussed.

Keywords: age-structured forest population, disturbances interaction, harvesting insects outbreak dynamics, mathematical modeling

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Authors: Mahmoud Hassan Onsa, Saadelnour Abdueljabbar Adam

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Wastes from slaughterhouses in most towns in Sudan are often poorly managed and sometimes discharged into adjoining streams due to poor implementation of standards, thus causing environmental and public health hazards and also there is a large amount of manure from dairy farms. This paper presents solution of organic waste from cow dairy farms and slaughterhouse the anaerobic digestion and biogas production. The paper presents the findings of experimental investigation of biogas production with and without pasteurization using cow manure, blood and rumen content were mixed at two proportions, 72.3% manure, 21.7%, rumen content and 6% blood for bio digester1with 62% dry matter at the beginning and without pasteurization and 72.3% manure, 21.7%, rumen content and 6% blood for bio-digester2 with 10% dry matter and pasteurization. The paper analyses the quantitative and qualitative composition of biogas: gas content, the concentration of methane. The highest biogas output 2.9 mL/g dry matter/day (from bio-digester2) together with a high quality biogas of 87.4% methane content which is useful for combustion and energy production and healthy bio-fertilizer but biodigester1 gave 1.68 mL/g dry matter/day with methane content 85% which is useful for combustion, energy production and can be considered as new technology of dryer bio-digesters.

Keywords: anaerobic digestion, bio-digester, blood, cow manure, rumen content

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Authors: Pelin Yilmaz, Gizemnur Yildiz Uysal, Elcin Demirhan, Belma Ozbek

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The edible fig plant, Ficus carica Linn, belongs to the Moraceae family, and the leaves are mainly considered agricultural waste after harvesting. It has been demonstrated in the literature that fig leaves contain appealing properties such as high vitamins, fiber, amino acids, organic acids, and phenolic or flavonoid content. The extraction of these valuable products has gained importance. Microwave-assisted extraction (MAE) is a method using microwave energy to heat the solvents, thereby transferring the bioactive compounds from the sample to the solvent. The main advantage of the MAE is the rapid extraction of bioactive compounds. In the present study, the MAE was applied to extract the bioactive compounds from Ficus carica L. leaves, and the effect of microwave power (180-900 W), extraction time (60-180 s), and solvent to sample amount (mL/g) (10-30) on the antioxidant property of the leaves. Then, the volatile organic component profile was determined at the specified extraction point. Additionally, antimicrobial studies were carried out to determine the minimum inhibitory concentration of the microwave-extracted leaves. As a result, according to the data obtained from the experimental studies, the highest antimicrobial properties were obtained under the process parameters such as 540 W, 180 s, and 20 mL/g concentration. The volatile organic compound profile showed that isobergapten, which belongs to the furanocoumarins family exhibiting anticancer, antioxidant, and antimicrobial activity besides promoting bone health, was the main compound. Acknowledgments: This work has been supported by Yildiz Technical University Scientific Research Projects Coordination Unit under project number FBA-2021-4409. The authors would like to acknowledge the financial support from Tubitak 1515 - Frontier R&D Laboratory Support Programme.

Keywords: Ficus carica Linn leaves, volatile organic component, GC-MS, microwave extraction, isobergapten, antimicrobial

Procedia PDF Downloads 58

Authors: B. J. Babalola, M. B. Shongwe

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Spark Plasma Sintering technique is a novel processing method that produces limited grain growth and highly dense variety of materials; alloys, superalloys, and carbides just to mention a few. However, initial particle size and spark plasma sintering parameters are factors which influence the grain growth and mechanical properties of sintered materials. Ni-Cr alloys are regarded as the most promising alloys for aerospace turbine blades, owing to the fact that they meet the basic requirements of desirable mechanical strength at high temperatures and good resistance to oxidation. The conventional method of producing this alloy often results in excessive grain growth and porosity levels that are detrimental to its mechanical properties. The effect of sintering temperature was evaluated on the microstructure and mechanical properties of the nanostructured Ni-17Cr alloy. Nickel and chromium powder were milled using high energy ball milling independently for 30 hours, milling speed of 400 revs/min and ball to powder ratio (BPR) of 10:1. The milled powders were mixed in the composition of Nickel having 83 wt % and chromium, 17 wt %. This was sintered at varied temperatures from 800°C, 900°C, 1000°C, 1100°C and 1200°C. The structural characteristics such as porosity, grain size, fracture surface and hardness were analyzed by scan electron microscopy and X-ray diffraction, Archimedes densitometry, micro-hardness tester. The corresponding results indicated an increase in the densification and hardness property of the alloy as the temperature increases. The residual porosity of the alloy reduces with respect to the sintering temperature and in contrast, the grain size was enhanced. The study of the mechanical properties, including hardness, densification shows that optimum properties were obtained for the sintering temperature of 1100°C. The advantages of high sinterability of Ni-17Cr alloy using milled powders and microstructural details were discussed.

Keywords: densification, grain growth, milling, nanostructured materials, sintering temperature

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Authors: Mapatsakon Sarapat, Mongkol Ketwongsa, Somchat Sonasang, Preecha Yupapin

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The designed and performed preliminary tests on a space-time control circuit using a two-level system circuit with a 4-5 cm diameter microstrip for realistic teleportation have been demonstrated. It begins by calculating the parameters that allow a circuit that uses the alternative current (AC) at a specified frequency as the input signal. A method that causes electrons to move along the circuit perimeter starting at the speed of light, which found satisfaction based on the wave-particle duality. It is able to establish the supersonic speed (faster than light) for the electron cloud in the middle of the circuit, creating a timeline and propulsive force as well. The timeline is formed by the stretching and shrinking time cancellation in the relativistic regime, in which the absolute time has vanished. In fact, both black holes and white holes are created from time signals at the beginning, where the speed of electrons travels close to the speed of light. They entangle together like a capsule until they reach the point where they collapse and cancel each other out, which is controlled by the frequency of the circuit. Therefore, we can apply this method to large-scale circuits such as potassium, from which the same method can be applied to form the system to teleport living things. In fact, the black hole is a hibernation system environment that allows living things to live and travel to the destination of teleportation, which can be controlled from position and time relative to the speed of light. When the capsule reaches its destination, it increases the frequency of the black holes and white holes canceling each other out to a balanced environment. Therefore, life can safely teleport to the destination. Therefore, there must be the same system at the origin and destination, which could be a network. Moreover, it can also be applied to space travel as well. The design system will be tested on a small system using a microstrip circuit system that we can create in the laboratory on a limited budget that can be used in both wired and wireless systems.

Keywords: quantum teleportation, black-white hole, time, timeline, relativistic electronics

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Authors: Gholamreza Namavar, Ali Bayati

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Nowadays according to increasing the population all around the world, consuming of fossil fuels increased dramatically. Many believe that most of the atmospheric pollution comes by using fossil fuels. The process of natural sources entering cities show one of the large challenges in consumption sources management. Nowadays, everyone considered about the consumption of fossil fuels and also reduction of consumption civil energy in megacities that play a key role in solving serious problems such as air pollution, producing greenhouse gasses, global warming and damage ozone layer. In construction industry we should use the materials with the lowest need to energy for making and carrying them, and also the materials which need the lowest energy and expenses to recycling. In this way, the kind of usage material, the way of processing, regional materials and the adaption with environment is critical. Otherwise, the isolation should be use and mention in long term. Accordingly, in this article we investigates the new ways in order to reduce environmental pollution and save more energy by using materials that are not harmful to the environment, fully insulated materials in buildings, sustainable and diversified buildings, suitable urban design and using solar energy more efficiently in order to reduce energy consumption.

Keywords: architectural design, insulation, sustainable construction, reducing energy consumption

Procedia PDF Downloads 238

Authors: Siamak Yaghoubi, Vahideh Rashtchi, Marzieh Khezri, Hamid Kayalha, Monadi Hamidfar

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Background and objectives: Effective postoperative pain management in abdominal surgeries, which are painful procedures, plays an important role in reducing postoperative complications and increasing patient’s satisfaction. There are many techniques for pain control, one of which is Patient-Controlled Analgesia (PCA). The aim of this study was to compare the analgesic effects of morphine, paracetamol and ketorolac in the patients undergoing open cholecystectomy, using PCA method. Material and Methods: This randomized controlled trial was performed on 330 ASA (American Society of Anesthesiology) I-II patients ( three equal groups, n=110) who were scheduled for elective open cholecystectomy in Shahid Rjaee hospital of Qazvin, Iran from August 2013 until September 2015. All patients were managed by general anesthesia with TIVA (Total Intra Venous Anesthesia) technique. The control group received morphine with maximum dose of 0.02mg/kg/h, the paracetamol group received paracetamol with maximum dose of 1mg/kg/h, and the ketorolac group received ketorolac with maximum daily dose of 60mg using IV-PCA method. The parameters of pain, nausea, hemodynamic variables (BP and HR), pruritus, arterial oxygen desaturation, patient’s satisfaction and pain score were measured every two hours for 8 hours following operation in all groups. Results: There were no significant differences in demographic data between the three groups. there was a statistically significant difference with regard to the mean pain score at all times between morphine and paracetamol, morphine and ketorolac, and paracetamol and ketorolac groups (P<0.001). Results indicated a reduction with time in the mean level of postoperative pain in all three groups. At all times the mean level of pain in ketorolac group was less than that in the other two groups (p<0.001). Conclusion: According to the results of this study ketorolac is more effective than morphine and paracetamol in postoperative pain control in the patients undergoing open cholecystectomy, using PCA method.

Keywords: analgesia, cholecystectomy, ketorolac, morphine, paracetamol

Procedia PDF Downloads 184

Authors: Öznur Saribaş, Si̇bel Kahraman Çeti̇ntaş

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It is aimed to compare target volume and critical organ doses by using CyberKnife (CK) in accelerated partial breast irradiation (APBI) in patients with early stage breast cancer. Three different virtual plans were made for Iris, fixed and multi-leaf collimator (MLC) for 5 patients who received radiotherapy in the CyberKnife system. CyberKnife virtual plans were created, with 6 Gy per day totaling 30 Gy. Dosimetric parameters for the three collimators were analyzed according to the restrictions in the NSABP-39/RTOG 0413 protocol. The plans ensured critical organs were protected and GTV received 95 % of the prescribed dose. The prescribed dose was defined by the isodose curve of a minimum of 80. Homogeneity index (HI), conformity index (CI), treatment time (min), monitor unit (MU) and doses taken by critical organs were compared. As a result of the comparison of the plans, a significant difference was found for the duration of treatment, MU. However, no significant difference was found for HI, CI. V30 and V15 values of the ipsi-lateral breast were found in the lowest MLC. There was no significant difference between Dmax values for lung and heart. However, the mean MU and duration of treatment were found in the lowest MLC. As a result, the target volume received the desired dose in each collimator. The contralateral breast and contralateral lung doses were the lowest in the Iris. Fixed collimator was found to be more suitable for cardiac doses. But these values did not make a significant difference. The use of fixed collimators may cause difficulties in clinical applications due to the long treatment time. The choice of collimator in breast SBRT applications with CyberKnife may vary depending on tumor size, proximity to critical organs and tumor localization.

Keywords: APBI, CyberKnife, early stage breast cancer, radiotherapy.

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Authors: Ainara Lopez-Ortega, Raquel Bayon, Elena Rodriguez, Amaya Igartua

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The materials used in offshore structural applications are continuously subjected to aggressive environmental conditions that accelerate their degradation, thus shortening their useful life. Wear, corrosion and the effect of marine microorganisms are the main processes taking place in marine environments, and whenever they occur simultaneously the durability of materials is strongly reduced. In the present work, the tribocorrosion behaviour of a High-Strength Low-Alloy (HSLA) steel and three coatings commonly used for protecting offshore components has been studied by means of unidirectional tribological tests in synthetic seawater. The coatings were found to enhance the tribological response of the uncoated steel and provide the system with improved corrosion resistance, in terms of smaller material losses and reduction of friction coefficients. The tests were repeated after ageing the materials in a salt-fog cabinet, and the aging process was found to slightly affect the performance of two of the coatings, in terms of higher material losses, meanwhile the third coating was not affected.

Keywords: coatings, corrosion, high-strength low-alloy steel, seawater, tribocorrosion

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Authors: Sachin Kamble, Raghothama Anekal, Shivakumar Bhavi

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Thermal management of electronic components packaged inside an IP65 rated enclosure is of prime importance in industrial applications. Electrical enclosure protects the multiple board configurations such as inverter, power, controller board components, busbars, and various power dissipating components from harsh environments. Industrial environments often experience relatively warm ambient conditions, and the electronic components housed in the enclosure dissipate heat, due to which the enclosures and the components require thermal management as well as reduction of internal ambient temperatures. Design of Experiments based thermal simulation approach with MOSFET arrangement, Heat sink design, Enclosure Volume, Copper and Aluminum Spreader, Power density, and Printed Circuit Board (PCB) type were considered to optimize air temperature inside the IP65 enclosure to ensure conducive operating temperature for controller board and electronic components through the different modes of heat transfer viz. conduction, natural convection and radiation using Ansys ICEPAK. MOSFET’s with the parallel arrangement, IP65 enclosure molded heat sink with rectangular fins on both enclosures, specific enclosure volume to satisfy the power density, Copper spreader to conduct heat to the enclosure, optimized power density value and selecting Aluminum clad PCB which improves the heat transfer were the contributors towards achieving a conducive operating temperature inside the IP-65 rated Motor Inverter enclosure. A reduction of 52 ℃ was achieved in internal ambient temperature inside the IP65 enclosure between baseline and final design parameters, which met the operative temperature requirements of the electronic components inside the IP-65 rated Motor Inverter.

Keywords: Ansys ICEPAK, aluminium clad PCB, IP 65 enclosure, motor inverter, thermal simulation

Procedia PDF Downloads 109

Authors: Sitaram Dahal

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Among many strategic and practical needs in overcoming the threats and challenges being experienced in the global environment, constitutional provision for Rights to live in clean and healthy environment is one and so is the school curriculum incorporating information on such rights. Government of Nepal has also introduced information on rights to live in clean and healthy environment, as provisioned in its interim constitution of 2007, in the secondary level curriculum of formal education. As the predetermined specific objective of such curriculum is to prepare students who are conscious of citizens’ rights and responsibilities and are able to adopt functions, duties and rights of the rights holders and duty bearers; the study was designed to assess the effectiveness of such curriculum. The study was conducted in one private school and a community school to assess the effectiveness of such curriculum. The study shows that such curriculum has been able to make students responsible duty bearers as they were aware of their habits towards environment. Whereas only very few students are aware enough as being rights holders. Students of community schools were aware rights holders as they complain if they are not satisfied with the environment of the school itself. But private school is far behind in this case. It can be said that only curriculum with very few portion of information on such rights might not be capable enough to meet its objective.

Keywords: curriculum, environmental rights, constitution, effectiveness

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Authors: Enea Danut Nicolae, Osman (Defta) Aurelia, Vidu Livia, Marginean Gheorghe, Defta Nicoleta, Moise Andrada

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Today, as a result of population growth, there is an increase in demand for animal products; milk and dairy products are an important part of this category. Maintaining production at maximum levels for as long as possible is one of the main objectives of dairy farmers. Over the course of lactation, a cow's milk production is not uniform. During the initial stage of lactation, the cow's milk production follows an upward slope, a plateau, and then a downward slope, which is a reflection of the lactation curve. The evolution of the lactation curve is influenced by numerous factors, which are genetic, exploitation, physiological, environmental and technological. The aim of this study was to observe the lactation curve of Holstein cows in Romania and determine the extent to which they conform to the expected pattern. In addition, there has been an analysis of the factors which have an influence on this curve and the extent of this influence. In order to be able to carry out the present study, data were collected from three farms located in three different geographical areas. To highlight the findings, the data collected was then statistically processed and graphically interpreted. All the farms have only Holstein cows, which are kept in free stalls.

Keywords: lactation curve, Holstein, milk production, influencing factors

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Authors: Ali M. Zaid, Muftah Mayouf, Yahya Said Farouj

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The effect of post emergence herbicides on soil micro-flora and nitrogen fixing bacteria was studied in pea field. Pea (Pisum sativum) was grown and treated with one or a mixture of two of several herbicides 2 weeks after sowing. Soil samples were collected 2 weeks after herbicides application. Average number of colony forming units per gram of soil of bacteria, actinomycetes and fungi were determined. Average number of nodules per plant was obtained at the end of the growing season. The results of the study showed MCPB, Bentazon, MCPB+Fluozifop-p-butyl, Bentazon+Fluozifop-p-butyl, Metribuzin, Flouzifop-p-butyl+Metribuzin, Cycloxydin, and Sethoxydin increased the population of soil fungi, with 4 to 10 times compared with the control. The herbicides used showed no significant effects on nitrogen fixing bacteria. The effects of herbicides on soil bacteria and actinomycetes were different. The study showed the use of herbicides could influence the biological balance of soil microflora, which has an important role in soil fertility and microbial ecosystem.

Keywords: herbicides, post emergence, nitrogen fixing bacteria, environmental systems

Procedia PDF Downloads 382

Authors: Michael Zaidman, Naum Simanovsky

Abstract:

Introduction. Symptomatic tarsal coalition with rigid flat foot often demands operative solution. An isolated coalition resection does not guarantee pain relief; correction of co-existing foot deformity may be required. The objective of the study was to analyze the results of combination of tarsal coalition resection and arthroereisis. Patients and methods. We retrospectively reviewed medical records and radiographs of children operatively treated in our institution for symptomatic calcaneonavicular or talocalcaneal coalition between the years 2019 and 2022. Eight patients (twelve feet), 4 boys and 4 girls with mean age 11.2 years, were included in the study. In six patients (10 feet) calcaneonavicular coalition was diagnosed, two patients (two feet) sustained talonavicular coalition. To quantify degrees of foot deformity, we used calcaneal pitch angle, lateral talar-first metatarsal (Meary's) angle, and talonavicular coverage angle. The clinical results were assessed using the American Orthopaedic Foot and Ankle Society (AOFAS) Ankle Hindfoot Score. Results. The mean follow-up was 28 month. The preoperative mean talonavicular coverage angle was 17,75º as compared with postoperative mean angle of 5.4º. The calcaneal pitch angle improved from mean 6,8º to 16,4º. The mean preoperative Meary’s angle of -11.3º improved to mean 2.8º. The preoperative mean AOFAS score improved from 54.7 to 93.1 points post-operatively. In nine of twelve feet, overall clinical outcome judged by AOFAS scale was excellent (90-100 points), in three feet was good (80-90 points). Six patients (ten feet) obviously improved their subtalar range of motion. Conclusion. For symptomatic stiff or rigid flat feet associated with tarsal coalition, the combination of coalition resection and arthroereisis leads to normalization of radiographic parameters, clinical and functional improvement with good patient’s satisfaction and likely to be more effective than the isolated procedures.

Keywords: rigid flat foot, tarsal coalition resection, arthroereisis, outcome

Procedia PDF Downloads 52

Authors: Richard Ren

Abstract:

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

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

Procedia PDF Downloads 106

Authors: Belayneh Matebie, Michael Melese

Abstract:

The study focuses on addressing the challenges in classifying and ensuring the quality of Eragrostis Teff, a small and round grain that is the smallest cereal grain. Employing a traditional classification method is challenging because of its small size and the similarity of its environmental characteristics. To overcome this, this study employs a machine learning approach to develop a source and quality classification system for Teff cereal. Data is collected from various production areas in the Amhara regions, considering two types of cereal (high and low quality) across eight classes. A total of 5,920 images are collected, with 740 images for each class. Image enhancement techniques, including scaling, data augmentation, histogram equalization, and noise removal, are applied to preprocess the data. Convolutional Neural Network (CNN) is then used to extract relevant features and reduce dimensionality. The dataset is split into 80% for training and 20% for testing. Different classifiers, including FVGG16, FINCV3, QSCTC, EMQSCTC, SVM, and RF, are employed for classification, achieving accuracy rates ranging from 86.91% to 97.72%. The ensemble of FVGG16, FINCV3, and QSCTC using the Max-Voting approach outperforms individual algorithms.

Keywords: Teff, ensemble learning, max-voting, CNN, SVM, RF

Procedia PDF Downloads 29

Authors: Mohammadreza Azarnoush, Ali Bayati, Jamileh Azarnoush

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Nowadays according to increasing the population all around the world, consuming of fossil fuels increased dramatically. Many believe that most of the atmospheric pollution comes by using fossil fuels. The process of natural sources entering cities shows one of the large challenges in consumption sources management. Nowadays, everyone considers the consumption of fossil fuels and also reduction of consumption civil energy in megacities as playing a key role in solving serious problems such as air pollution, producing greenhouse gasses, global warming, and damage ozone layer. In the construction industry, we should use the materials with the lowest need to energy for making and carrying them, and also the materials which need the lowest energy and expenses to recycling. In this way, the kind of usage material, the way of processing, regional materials, and the adoption to the environment is critical. Otherwise, the isolation should be use and mention in the long term. Accordingly, in this article, we investigate the new ways in order to reduce environmental pollution and save more energy by using materials that are not harmful to the environment, fully insulated materials in buildings, sustainable and diversified buildings, suitable urban design and using solar energy more efficiently in order to reduce energy consumption.

Keywords: building design, construction masonry, insulation, sustainable construction

Procedia PDF Downloads 397

Authors: Sheikh Omar Sillah

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Introduction: Monitoring is an important means of ensuring the smooth implementation and quality of clinical trials. For many years, traditional site monitoring approaches have been critical in detecting data errors but not optimal in identifying fabricated and implanted data as well as non-random data distributions that may significantly invalidate study results. The objective of this paper was to provide recommendations based on best statistical monitoring practices for detecting data-integrity issues suggestive of fabrication and implantation early in the study conduct to allow implementation of meaningful corrective and preventive actions. Methodology: Electronic bibliographic databases (Medline, Embase, PubMed, Scopus, and Web of Science) were used for the literature search, and both qualitative and quantitative studies were sought. Search results were uploaded into Eppi-Reviewer Software, and only publications written in the English language from 2012 were included in the review. Gray literature not considered to present reproducible methods was excluded. Results: A total of 18 peer-reviewed publications were included in the review. The publications demonstrated that traditional site monitoring techniques are not efficient in detecting data anomalies. By specifying project-specific parameters such as laboratory reference range values, visit schedules, etc., with appropriate interactive data monitoring, statistical monitoring can offer early signals of data anomalies to study teams. The review further revealed that statistical monitoring is useful to identify unusual data patterns that might be revealing issues that could impact data integrity or may potentially impact study participants' safety. However, subjective measures may not be good candidates for statistical monitoring. Conclusion: The statistical monitoring approach requires a combination of education, training, and experience sufficient to implement its principles in detecting data anomalies for the statistical aspects of a clinical trial.

Keywords: statistical monitoring, data anomalies, clinical trials, traditional monitoring

Procedia PDF Downloads 56

Authors: Hamed Nafar, Sajad Rezaei, Hamid Behbahani

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Safety analysis of the roads through the accident rates which is one of the widely used tools has been resulted from the direct exposure method which is based on the ratio of the vehicle-kilometers traveled and vehicle-travel time. However, due to some fundamental flaws in its theories and difficulties in gaining access to the data required such as traffic volume, distance and duration of the trip, and various problems in determining the exposure in a specific time, place, and individual categories, there is a need for an algorithm for prioritizing the road safety so that with a new exposure method, the problems of the previous approaches would be resolved. In this way, an efficient application may lead to have more realistic comparisons and the new method would be applicable to a wider range of time, place, and individual categories. Therefore, an algorithm was introduced to prioritize the safety of roads using the quasi-induced exposure method and utilizing the analytical hierarchy process. For this research, 11 provinces of Iran were chosen as case study locations. A rural accidents database was created for these provinces, the validity of quasi-induced exposure method for Iran’s accidents database was explored, and the involvement ratio for different characteristics of the drivers and the vehicles was measured. Results showed that the quasi-induced exposure method was valid in determining the real exposure in the provinces under study. Results also showed a significant difference in the prioritization based on the new and traditional approaches. This difference mostly would stem from the perspective of the quasi-induced exposure method in determining the exposure, opinion of experts, and the quantity of accidents data. Overall, the results for this research showed that prioritization based on the new approach is more comprehensive and reliable compared to the prioritization in the traditional approach which is dependent on various parameters including the driver-vehicle characteristics.

Keywords: road safety, prioritizing, Quasi-induced exposure, Analytical Hierarchy Process

Procedia PDF Downloads 322

Authors: Rebekah Granger Ellis, Pat J. Austin, Marc P. Bonis, Richard B. Speaker, Jr.

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Using two psychometric instruments, this study examined social and emotional intelligence and moral judgment levels of more than 300 gifted and talented high school students enrolled in arts-integrated, academic acceleration, and creative arts charter schools in an ethnically diverse large city in the southeastern United States. Gifted and talented individuals possess distinguishable characteristics; these frequently appear as strengths, but often serious problems accompany them. Although many gifted adolescents thrive in their environments, some struggle in their school and community due to emotional intensity, motivation and achievement issues, lack of peers and isolation, identification problems, sensitivity to expectations and feelings, perfectionism, and other difficulties. These gifted students endure and survive in school rather than flourish. Gifted adolescents face special intrapersonal, interpersonal, and environmental problems. Furthermore, they experience greater levels of stress, disaffection, and isolation than non-gifted individuals due to their advanced cognitive abilities. Therefore, it is important to examine the long-term effects of participation in various gifted and talented programs on the socio-affective development of these adolescents. Numerous studies have researched moral, social, and emotional development in the areas of cognitive-developmental, psychoanalytic, and behavioral learning; however, in almost all cases, these three facets have been studied separately leading to many divergent theories. Additionally, various frameworks and models purporting to encourage the different socio-affective branches of development have been debated in curriculum theory, yet research is inconclusive on the effectiveness of these programs. Most often studied is the socio-affective domain, which includes development and regulation of emotions; empathy development; interpersonal relations and social behaviors; personal and gender identity construction; and moral development, thinking, and judgment. Examining development in these domains can provide insight into why some gifted and talented adolescents are not always successful in adulthood despite advanced IQ scores. Particularly whether emotional, social and moral capabilities of gifted and talented individuals are as advanced as their intellectual abilities and how these are related to each other. This mixed methods longitudinal study examined students in urban gifted and talented charter schools for (1) socio-affective development levels and (2) whether a particular environment encourages developmental growth. Research questions guiding the study: (1) How do academically and artistically gifted 10th and 11th grade students perform on psychological scales of social and emotional intelligence and moral judgment? Do they differ from the normative sample? Do gender differences exist among gifted students? (2) Do adolescents who attend distinctive gifted charter schools differ in developmental profiles? Students’ performances on psychometric instruments were compared over time and by program type. Assessing moral judgment (DIT-2) and socio-emotional intelligence (BarOn EQ-I: YV), participants took pre-, mid-, and post-tests during one academic school year. Quantitative differences in growth on these psychological scales (individuals and school-wide) were examined. If a school showed change, qualitative artifacts (culture, curricula, instructional methodology, stakeholder interviews) provided insight for environmental correlation.

Keywords: gifted and talented programs, moral judgment, social and emotional intelligence, socio-affective education

Procedia PDF Downloads 176

Authors: Pooja Kumari, Anandkumar Tengli

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Aurora kinase enzyme, a protein on overexpression, leads to metastasis and is extremely important for women’s health in terms of prevention or treatment. While creating a targeted technique, the aim of the work is to design purine molecules that inhibit in aurora kinase enzyme and helps to suppress breast cancer. Purine molecules attached to an amino acid in DNA block protein synthesis or halt the replication and metastasis caused by the aurora kinase enzyme. Various protein related to the overexpression of aurora protein was docked with purine molecule using Biovia Drug Discovery, the perpetual software. Various parameters like X-ray crystallographic structure, presence of ligand, Ramachandran plot, resolution, etc., were taken into consideration for selecting the target protein. A higher negative binding scored molecule has been taken for simulation studies. According to the available research and computational analyses, purine compounds may be powerful enough to demonstrate a greater affinity for the aurora target. Despite being clinically effective now, purines were originally meant to fight breast cancer by inhibiting the aurora kinase enzyme. In in-silico studies, it is observed that purine compounds have a moderate to high potency compared to other molecules, and our research into the literature revealed that purine molecules have a lower risk of side effects. The research involves the design, synthesis, and identification of active purine molecules against breast cancer. Purines are structurally similar to the normal metabolites of adenine and guanine; hence interfere/compete with protein synthesis and suppress the abnormal proliferation of cells/tissues. As a result, purine target metastasis cells and stop the growth of kinase; purine derivatives bind with DNA and aurora protein which may stop the growth of protein or inhibits replication and stop metastasis of overexpressed aurora kinase enzyme.

Keywords: aurora kinases, in silico studies, medicinal chemistry, combination therapies, chronic cancer, clinical translation

Procedia PDF Downloads 72