Search results for: hybrid energy resources

Authors: Kirolos Gerges Yakoub Gerges

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Self-sustaining agricultural machines act in stochastic surroundings and therefore, should be capable of perceive the surroundings in real time. This notion can be done using image sensors blended with superior device learning, mainly Deep mastering. Deep convolutional neural networks excel in labeling and perceiving colour pix and since the fee of RGB-cameras is low, the hardware cost of accurate notion relies upon heavily on memory and computation power. This paper investigates the opportunity of designing lightweight convolutional neural networks for semantic segmentation (pixel clever class) with reduced hardware requirements, to allow for embedded usage in self-reliant agricultural machines. The usage of compression techniques, a lightweight convolutional neural community is designed to carry out actual-time semantic segmentation on an embedded platform. The community is skilled on two big datasets, ImageNet and Pascal Context, to apprehend as much as four hundred man or woman instructions. The 400 training are remapped into agricultural superclasses (e.g. human, animal, sky, road, area, shelterbelt and impediment) and the capacity to provide correct actual-time perception of agricultural environment is studied. The network is carried out to the case of self-sufficient grass mowing the usage of the NVIDIA Tegra X1 embedded platform. Feeding case-unique pics to the community consequences in a fully segmented map of the superclasses within the picture. As the network remains being designed and optimized, handiest a qualitative analysis of the technique is entire on the abstract submission deadline. intending this cut-off date, the finalized layout is quantitatively evaluated on 20 annotated grass mowing pictures. Light-weight convolutional neural networks for semantic segmentation can be implemented on an embedded platform and show aggressive performance on the subject of accuracy and speed. It’s miles viable to offer value-efficient perceptive capabilities related to semantic segmentation for autonomous agricultural machines.

Keywords: centrifuge pump, hydraulic energy, agricultural applications, irrigationaxial flux machines, axial flux applications, coreless machines, PM machinesautonomous agricultural machines, deep learning, safety, visual perception

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Authors: S. Lertsakulpasuk, S. Athichanagorn

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As depletion-drive gas reservoirs are abandoned when there is insufficient production rate due to pressure depletion, waterflooding has been proposed to increase the reservoir pressure in order to prolong gas production. Due to high cost, water injection may not be economically feasible. Water dumpflood into gas reservoirs is a new promising approach to increase gas recovery by maintaining reservoir pressure with much cheaper costs than conventional waterflooding. Thus, a simulation study of water dumpflood into multiple nearly abandoned or already abandoned thin-bedded gas reservoirs commonly found in the Gulf of Thailand was conducted to demonstrate the advantage of the proposed method and to determine the most suitable operational parameters for reservoirs having different system parameters. A reservoir simulation model consisting of several thin-layered depletion-drive gas reservoirs and an overlying aquifer was constructed in order to investigate the performance of the proposed method. Two producers were initially used to produce gas from the reservoirs. One of them was later converted to a dumpflood well after gas production rate started to decline due to continuous reduction in reservoir pressure. The dumpflood well was used to flow water from the aquifer to increase pressure of the gas reservoir in order to drive gas towards producer. Two main operational parameters which are wellhead pressure of producer and the time to start water dumpflood were investigated to optimize gas recovery for various systems having different gas reservoir dip angles, well spacings, aquifer sizes, and aquifer depths. This simulation study found that water dumpflood can increase gas recovery up to 12% of OGIP depending on operational conditions and system parameters. For the systems having a large aquifer and large distance between wells, it is best to start water dumpflood when the gas rate is still high since the long distance between the gas producer and dumpflood well helps delay water breakthrough at producer. As long as there is no early water breakthrough, the earlier the energy is supplied to the gas reservoirs, the better the gas recovery. On the other hand, for the systems having a small or moderate aquifer size and short distance between the two wells, performing water dumpflood when the rate is close to the economic rate is better because water is more likely to cause an early breakthrough when the distance is short. Water dumpflood into multiple nearly-depleted or depleted gas reservoirs is a novel study. The idea of using water dumpflood to increase gas recovery has been mentioned in the literature but has never been investigated. This detailed study will help a practicing engineer to understand the benefits of such method and can implement it with minimum cost and risk.

Keywords: dumpflood, increase gas recovery, low-pressure gas reservoir, multiple gas reservoirs

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Authors: Nur Azilina Abdul Aziz, Tuti Katrina Abdullah, Ahmad Azmin Mohamad

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Lithium-transition metals and some of their oxides, such as LiCoO2, LiMn2O2, LiFePO4, and LiNiO2 have been used as cathode materials in high performance lithium-ion rechargeable batteries. Among the cathode materials, LiCoO2 has potential to been widely used as a lithium-ion battery because of its layered crystalline structure, good capacity, high cell voltage, high specific energy density, high power rate, low self-discharge, and excellent cycle life. This cathode material has been widely used in commercial lithium-ion batteries due to its low irreversible capacity loss and good cycling performance. However, there are several problems that interfere with the production of material that has good electrochemical properties, including the crystallinity, the average particle size and particle size distribution. In recent years, synthesis of nanoparticles has been intensively investigated. Powders prepared by the traditional solid-state reaction have a large particle size and broad size distribution. On the other hand, solution method can reduce the particle size to nanometer range and control the particle size distribution. In this study, LiCoO2 was synthesized using the sol–gel preparation method, which Lithium acetate and Cobalt acetate were used as reactants. The stoichiometric amounts of the reactants were dissolved in deionized water. The solutions were stirred for 30 hours using magnetic stirrer, followed by heating at 80°C under vigorous stirring until a viscous gel was formed. The as-formed gel was calcined at 700°C for 7 h under a room atmosphere. The structural and morphological analysis of LiCoO2 was characterized using X-ray diffraction and Scanning electron microscopy. The diffraction pattern of material can be indexed based on the α-NaFeO2 structure. The clear splitting of the hexagonal doublet of (006)/(102) and (108)/(110) in this patterns indicates materials are formed in a well-ordered hexagonal structure. No impurity phase can be seen in this range probably due to the homogeneous mixing of the cations in the precursor. Furthermore, SEM micrograph of the LiCoO2 shows the particle size distribution is almost uniform while particle size is between 0.3-0.5 microns. In conclusion, LiCoO2 powder was successfully synthesized using the sol–gel method. LiCoO2 showed a hexagonal crystal structure. The sample has been prepared clearly indicate the pure phase of LiCoO2. Meanwhile, the morphology of the sample showed that the particle size and size distribution of particles is almost uniform.

Keywords: cathode material, LiCoO2, lithium-ion rechargeable batteries, Sol-Gel method

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Authors: Zeinab Jafari A., Ali Sharifnezhad B., Mohammad Razi C., Mohammad Haghpanahi D., Arash Maghsoudi

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Background and Objective: Sports-related rupture of the anterior cruciate ligament (ACL) and following injuries have been associated with various disorders, such as long-lasting changes in muscle activation patterns in athletes, which might last after ACL reconstruction (ACLR). The rupture of the ACL might result in abnormal patterns of movement execution, extending the treatment period and delaying athletes’ return to sports (RTS). As ACL injury is especially prevalent among athletes, the lengthy treatment process and athletes’ absence from sports are of great concern to athletes and coaches. Thus, estimating safe time of RTS is of crucial importance. Therefore, using a deep neural network (DNN) to classify the health levels of ACL in injured athletes, this study aimed to estimate the safe time for athletes to return to competitions. Methods: Ten athletes with ACLR and fourteen healthy controls participated in this study. Three health levels of ACL were defined: healthy, six-month post-ACLR surgery and nine-month post-ACLR surgery. Athletes with ACLR were tested six and nine months after the ACLR surgery. During the course of this study, surface electromyography (sEMG) signals were recorded from five knee muscles, namely Rectus Femoris (RF), Vastus Lateralis (VL), Vastus Medialis (VM), Biceps Femoris (BF), Semitendinosus (ST), during single-leg drop landing (SLDL) and forward hopping (SLFH) tasks. The Pseudo-Wigner-Ville distribution (PWVD) was used to produce three-dimensional (3-D) images of the energy distribution patterns of sEMG signals. Then, these 3-D images were converted to two-dimensional (2-D) images implementing the heat mapping technique, which were then fed to a deep convolutional neural network (DCNN). Results: In this study, we estimated the safe time of RTS by designing a DCNN classifier with an accuracy of 90 %, which could classify ACL into three health levels. Discussion: The findings of this study demonstrate the potential of the DCNN classification technique using sEMG signals in estimating RTS time, which will assist in evaluating the recovery process of ACLR in athletes.

Keywords: anterior cruciate ligament reconstruction, return to sports, surface electromyography, deep convolutional neural network

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Authors: Camila Lemos Pinto, Juliana Alves Carneiro, Patrícia Borges Botelho, João Felipe Mota

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Sarcopenia, a syndrome characterized by progressive and generalized loss of skeletal muscle mass and strength, currently affects over 50 million people and increases the risk of adverse outcomes such as physical disability, poor quality of life and death. The aim of this study was to examine the efficacy of creatine supplementation associated with resistance training on muscle mass in the elderly. A 12-week, double blind, randomized, parallel group, placebo controlled trial was conducted. Participants were randomly allocated into one of the following groups: placebo with resistance training (PL+RT, n=14) and creatine supplementation with resistance training (CR + RT, n=13). The subjects from CR+RT group received 5 g/day of creatine monohydrate and the subjects from the PL+RT group were given the same dose of maltodextrin. Participants were instructed to ingest the supplement on non-training days immediately after lunch and on training days immediately after resistance training sessions dissolved in a beverage comprising 100 g of maltodextrin lemon flavored. Participants of both groups undertook a supervised exercise training program for 12 weeks (3 times per week). The subjects were assessed at baseline and after 12 weeks. The primary outcome was muscle mass, assessed by dual energy X-ray absorptiometry (DXA). The secondary outcome included diagnose participants with one of the three stages of sarcopenia (presarcopenia, sarcopenia and severe sarcopenia) by skeletal muscle mass index (SMI), handgrip strength and gait speed. CR+RT group had a significant increase in SMI and muscle (p<0.0001), a significant decrease in android and gynoid fat (p = 0.028 and p=0.035, respectively) and a tendency of decreasing in body fat (p=0.053) after the intervention. PL+RT only had a significant increase in SMI (p=0.007). The main finding of this clinical trial indicated that creatine supplementation combined with resistance training was capable of increasing muscle mass in our elderly cohort (p=0.02). In addition, the number of subjects diagnosed with one of the three stages of sarcopenia at baseline decreased in the creatine supplemented group in comparison with the placebo group (CR+RT, n=-3; PL+RT, n=0). In summary, 12 weeks of creatine supplementation associated with resistance training resulted in increases in muscle mass. This is the first research with elderly of both sexes that show the same increase in muscle mass with a minor quantity of creatine supplementation in a short period. Future long-term research should investigate the effects of these interventions in sarcopenic elderly.

Keywords: creatine, dietetic supplement, elderly, resistance training

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Authors: I. Stathopoulos, V. Syrgiamiotis, E. Karavasilis, A. Ploussi, I. Nikas, C. Hatzigiorgi, K. Platoni, E. P. Efstathopoulos

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Introduction: Brain and central nervous system (CNS) tumors form the second most common group of cancer in children, accounting for 30% of all childhood cancers. MRI is the key imaging technique used for the visualization and management of pediatric brain tumors. Initial characterization of tumors from MRI scans is usually performed via a radiologist’s visual assessment. However, different brain tumor types do not always demonstrate clear differences in visual appearance. Using only conventional MRI to provide a definite diagnosis could potentially lead to inaccurate results, and so histopathological examination of biopsy samples is currently considered to be the gold standard for obtaining definite diagnoses. Machine learning is defined as the study of computational algorithms that can use, complex or not, mathematical relationships and patterns from empirical and scientific data to make reliable decisions. Concerning the above, machine learning techniques could provide effective and accurate ways to automate and speed up the analysis and diagnosis for medical images. Machine learning applications in radiology are or could potentially be useful in practice for medical image segmentation and registration, computer-aided detection and diagnosis systems for CT, MR or radiography images and functional MR (fMRI) images for brain activity analysis and neurological disease diagnosis. Purpose: The objective of this study is to provide an automated tool, which may assist in the imaging evaluation and classification of brain neoplasms in pediatric patients by determining the glioma type, grade and differentiating between different brain tissue types. Moreover, a future purpose is to present an alternative way of quick and accurate diagnosis in order to save time and resources in the daily medical workflow. Materials and Methods: A cohort, of 80 pediatric patients with a diagnosis of posterior fossa tumor, was used: 20 ependymomas, 20 astrocytomas, 20 medulloblastomas and 20 healthy children. The MR sequences used, for every single patient, were the following: axial T1-weighted (T1), axial T2-weighted (T2), FluidAttenuated Inversion Recovery (FLAIR), axial diffusion weighted images (DWI), axial contrast-enhanced T1-weighted (T1ce). From every sequence only a principal slice was used that manually traced by two expert radiologists. Image acquisition was carried out on a GE HDxt 1.5-T scanner. The images were preprocessed following a number of steps including noise reduction, bias-field correction, thresholding, coregistration of all sequences (T1, T2, T1ce, FLAIR, DWI), skull stripping, and histogram matching. A large number of features for investigation were chosen, which included age, tumor shape characteristics, image intensity characteristics and texture features. After selecting the features for achieving the highest accuracy using the least number of variables, four machine learning classification algorithms were used: k-Nearest Neighbour, Support-Vector Machines, C4.5 Decision Tree and Convolutional Neural Network. The machine learning schemes and the image analysis are implemented in the WEKA platform and MatLab platform respectively. Results-Conclusions: The results and the accuracy of images classification for each type of glioma by the four different algorithms are still on process.

Keywords: image classification, machine learning algorithms, pediatric MRI, pediatric oncology

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Authors: Shoba Rathilal

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High unemployment rates and a shortage of experienced and qualified employees appear to be a paradox that currently plagues most countries worldwide. In a developing country like South Africa, the rate of unemployment is reported to be approximately 35%, the highest recorded globally. At the same time, a countrywide deficit in experienced and qualified potential employees is reported in South Africa, which is causing fierce rivalry among firms. Employers have reported that graduates are very rarely able to meet the demands of the job as there are gaps in their knowledge and conceptual understanding and other 21st-century competencies, attributes, and dispositions required to successfully negotiate the multiple responsibilities of employees in organizations. In addition, the rates of unemployment and suitability of graduates appear to be skewed by race and social class, the continued effects of a legacy of inequitable educational access. Higher Education in the current technologically advanced and dynamic world needs to serve as an agent of transformation, aspiring to develop graduates to be creative, flexible, critical, and with entrepreneurial acumen. This requires that higher education curricula and pedagogy require a re-envisioning of our selection, sequencing, and pacing of the learning, teaching, and assessment. At a particular Higher education Institution in South Africa, Design Thinking and Project Based learning are being adopted as two approaches that aim to enhance the student experience through the provision of a “distinctive education” that brings together disciplinary knowledge, professional engagement, technology, innovation, and entrepreneurship. Using these methodologies forces the students to solve real-time applied problems using various forms of knowledge and finding innovative solutions that can result in new products and services. The intention is to promote the development of skills for self-directed learning, facilitate the development of self-awareness, and contribute to students being active partners in the application and production of knowledge. These approaches emphasize active and collaborative learning, teamwork, conflict resolution, and problem-solving through effective integration of theory and practice. In principle, both these approaches are extremely impactful. However, at the institution in this study, the implementation of the PBL and DT was not as “smooth” as anticipated. This presentation reports on the analysis of the implementation of these two approaches within higher education curricula at a particular university in South Africa. The study adopts a qualitative case study design. Data were generated through the use of surveys, evaluation feedback at workshops, and content analysis of project reports. Data were analyzed using document analysis, content, and thematic analysis. Initial analysis shows that the forces constraining the implementation of PBL and DT range from the capacity to engage with DT and PBL, both from staff and students, educational contextual realities of higher education institutions, administrative processes, and resources. At the same time, the implementation of DT and PBL was enabled through the allocation of strategic funding and capacity development workshops. These factors, however, could not achieve maximum impact. In addition, the presentation will include recommendations on how DT and PBL could be adapted for differing contexts will be explored.

Keywords: design thinking, project based learning, innovative higher education pedagogy, student and staff capacity development

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Authors: Chabungbam Niranjit Khuman, Makarand Madhao Ghangrekar, Arunabha Mitra

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The cost of aeration is one of the limiting factors in the upscaling of microbial fuel cells (MFC) for field-scale applications. Wetland macrophytes have the ability to release oxygen into the water to maintain aerobic conditions in their root zone. In this experiment, the efficacy of rhizospheric oxygen release of wetland macrophytes as a source of oxygen in the cathodic chamber of MFC was conducted. The experiment was conducted in an MFC consisting of a three-liter anodic chamber made of ceramic cylinder and a 27 L cathodic chamber. Untreated carbon felts were used as electrodes (i.e., anode and cathode) and connected to an external load of 100 Ω using stainless steel wire. Wetland macrophytes (Canna indica) were grown in the cathodic chamber of the MFC in a hydroponic fashion using a styrofoam sheet (termed as macrophytes assisted-microbial fuel cell, M-MFC). The catholyte (i.e., water) in the M-MFC had negligible contact with atmospheric air due to the styrofoam sheet used for maintaining the hydroponic condition. There was no mixing of the catholyte in the M-MFC. Sucrose based synthetic wastewater having chemical oxygen demand (COD) of 3000 mg/L was fed into the anodic chamber of the MFC in fed-batch mode with a liquid retention time of four days. The C. indica thrived well throughout the duration of the experiment without much care. The average dissolved oxygen (DO) concentration and pH value in the M-MFC were 3.25 mg/L and 7.07, respectively, in the catholyte. Since the catholyte was not in contact with air, the DO in the catholyte might be considered as solely liberated from the rhizospheric oxygen release of C. indica. The maximum COD removal efficiency of M-MFC observed during the experiment was 76.9%. The inadequacy of terminal electron acceptor in the cathodic chamber in M-MFC might have hampered the electron transfer, which in turn, led to slower specific microbial activity, thereby resulting in lower COD removal efficiency than the traditional MFC with aerated catholyte. The average operating voltage (OV) and open-circuit voltage (OCV) of 294 mV and 594 mV, respectively, were observed in M-MFC. The maximum power density observed during polarization was 381 mW/m³, and the maximum sustainable power density observed during the experiment was 397 mW/m³ in M-MFC. The maximum normalized energy recovery and coulombic efficiency of 38.09 Wh/m³ and 1.27%, respectively, were observed. Therefore, it was evidenced that rhizospheric oxygen release of wetland macrophytes (C. indica) was capable of sustaining the cathodic reaction in MFC for field-scale applications.

Keywords: hydroponic, microbial fuel cell, rhizospheric oxygen release, wetland macrophytes

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Authors: Nikolai N. Bogolubov, Andrey V. Soldatov

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Terahertz radiation occupies a range of frequencies somewhere from 100 GHz to approximately 10 THz, just between microwaves and infrared waves. This range of frequencies holds promise for many useful applications in experimental applied physics and technology. At the same time, reliable, simple techniques for generation, amplification, and modulation of electromagnetic radiation in this range are far from been developed enough to meet the requirements of its practical usage, especially in comparison to the level of technological abilities already achieved for other domains of the electromagnetic spectrum. This situation of relative underdevelopment of this potentially very important range of electromagnetic spectrum is known under the name of the 'terahertz gap.' Among other things, technological progress in the terahertz area has been impeded by the lack of compact, low energy consumption, easily controlled and continuously radiating terahertz radiation sources. Therefore, development of new techniques serving this purpose as well as various devices based on them is of obvious necessity. No doubt, it would be highly advantageous to employ the simplest of suitable physical systems as major critical components in these techniques and devices. The purpose of the present research was to show by means of conventional methods of non-equilibrium statistical mechanics and the theory of open quantum systems, that a thoroughly studied two-level quantum system, also known as an one-electron two-level 'atom', being driven by external classical monochromatic high-frequency (e.g. laser) field, can radiate continuously at much lower (e.g. terahertz) frequency in the fluorescent regime if the transition dipole moment operator of this 'atom' possesses permanent non-equal diagonal matrix elements. This assumption contradicts conventional assumption routinely made in quantum optics that only the non-diagonal matrix elements persist. The conventional assumption is pertinent to natural atoms and molecules and stems from the property of spatial inversion symmetry of their eigenstates. At the same time, such an assumption is justified no more in regard to artificially manufactured quantum systems of reduced dimensionality, such as, for example, quantum dots, which are often nicknamed 'artificial atoms' due to striking similarity of their optical properties to those ones of the real atoms. Possible ways to experimental observation and practical implementation of the predicted effect are discussed too.

Keywords: terahertz gap, two-level atom, resonant fluorescence, quantum dot, resonant fluorescence, two-level atom

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Authors: Tausif A. Ishtiaque, Zarrin T. Tasin, Kazi S. Akter

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Current trend of urban expansion, especially in the developing countries has caused significant changes in land cover, which is generating great concern due to its widespread environmental degradation. Energy consumption of the cities is also increasing with the aggravated heat island effect. Distribution of land surface temperature (LST) is one of the most significant climatic parameters affected by urban land cover change. Recent increasing trend of LST is causing elevated temperature profile of the built up area with less vegetative cover. Gradual change in land cover, especially decrease in vegetative cover is enhancing the Urban Heat Island (UHI) effect in the developing cities around the world. Increase in the amount of urban vegetation cover can be a useful solution for the reduction of UHI intensity. LST and Normalized Difference Vegetation Index (NDVI) have widely been accepted as reliable indicators of UHI and vegetation abundance respectively. Chittagong, the second largest city of Bangladesh, has been a growth center due to rapid urbanization over the last several decades. This study assesses the intensity of UHI in Chittagong city by analyzing the relationship between LST and NDVI based on the type of land use/land cover (LULC) in the study area applying an integrated approach of Geographic Information System (GIS), remote sensing (RS), and regression analysis. Land cover map is prepared through an interactive supervised classification using remotely sensed data from Landsat ETM+ image along with NDVI differencing using ArcGIS. LST and NDVI values are extracted from the same image. The regression analysis between LST and NDVI indicates that within the study area, UHI is directly correlated with LST while negatively correlated with NDVI. It interprets that surface temperature reduces with increase in vegetation cover along with reduction in UHI intensity. Moreover, there are noticeable differences in the relationship between LST and NDVI based on the type of LULC. In other words, depending on the type of land usage, increase in vegetation cover has a varying impact on the UHI intensity. This analysis will contribute to the formulation of sustainable urban land use planning decisions as well as suggesting suitable actions for mitigation of UHI intensity within the study area.

Keywords: land cover change, land surface temperature, normalized difference vegetation index, urban heat island

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Authors: Zachary Blanks, Solomon Sonya

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Poaching presents a serious threat to endangered animal species, environment conservations, and human life. Additionally, some poaching activity has even been linked to supplying funds to support terrorist networks elsewhere around the world. Consequently, agencies dedicated to protecting wildlife habitats have a near intractable task of adequately patrolling an entire area (spanning several thousand kilometers) given limited resources, funds, and personnel at their disposal. Thus, agencies need predictive tools that are both high-performing and easily implementable by the user to help in learning how the significant features (e.g. animal population densities, topography, behavior patterns of the criminals within the area, etc) interact with each other in hopes of abating poaching. This research develops a classification model using machine learning algorithms to aid in forecasting future attacks that is both easy to train and performs well when compared to other models. In this research, we demonstrate how data imputation methods (specifically predictive mean matching, gradient boosting, and random forest multiple imputation) can be applied to analyze data and create significant predictions across a varied data set. Specifically, we apply these methods to improve the accuracy of adopted prediction models (Logistic Regression, Support Vector Machine, etc). Finally, we assess the performance of the model and the accuracy of our data imputation methods by learning on a real-world data set constituting four years of imputed data and testing on one year of non-imputed data. This paper provides three main contributions. First, we extend work done by the Teamcore and CREATE (Center for Risk and Economic Analysis of Terrorism Events) research group at the University of Southern California (USC) working in conjunction with the Department of Homeland Security to apply game theory and machine learning algorithms to develop more efficient ways of reducing poaching. This research introduces ensemble methods (Random Forests and Stochastic Gradient Boosting) and applies it to real-world poaching data gathered from the Ugandan rain forest park rangers. Next, we consider the effect of data imputation on both the performance of various algorithms and the general accuracy of the method itself when applied to a dependent variable where a large number of observations are missing. Third, we provide an alternate approach to predict the probability of observing poaching both by season and by month. The results from this research are very promising. We conclude that by using Stochastic Gradient Boosting to predict observations for non-commercial poaching by season, we are able to produce statistically equivalent results while being orders of magnitude faster in computation time and complexity. Additionally, when predicting potential poaching incidents by individual month vice entire seasons, boosting techniques produce a mean area under the curve increase of approximately 3% relative to previous prediction schedules by entire seasons.

Keywords: ensemble methods, imputation, machine learning, random forests, statistical analysis, stochastic gradient boosting, wildlife protection

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Authors: Karan Sharma, Ajay Kumar

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Epileptic seizure is a type of disease due to which electrical charge in the brain flows abruptly resulting in abnormal activity by the subject. One percent of total world population gets epileptic seizure attacks.Due to abrupt flow of charge, EEG (Electroencephalogram) waveforms change. On the display appear a lot of spikes and sharp waves in the EEG signals. Detection of epileptic seizure by using conventional methods is time-consuming. Many methods have been evolved that detect it automatically. The initial part of this paper provides the review of techniques used to detect epileptic seizure automatically. The automatic detection is based on the feature extraction and classification patterns. For better accuracy decomposition of the signal is required before feature extraction. A number of parameters are calculated by the researchers using different techniques e.g. approximate entropy, sample entropy, Fuzzy approximate entropy, intrinsic mode function, cross-correlation etc. to discriminate between a normal signal & an epileptic seizure signal.The main objective of this review paper is to present the variations in the EEG signals at both stages (i) Interictal (recording between the epileptic seizure attacks). (ii) Ictal (recording during the epileptic seizure), using most appropriate methods of analysis to provide better healthcare diagnosis. This research paper then investigates the effects of a noninvasive healing therapy on the subjects by studying the EEG signals using latest signal processing techniques. The study has been conducted with Reiki as a healing technique, beneficial for restoring balance in cases of body mind alterations associated with an epileptic seizure. Reiki is practiced around the world and is recommended for different health services as a treatment approach. Reiki is an energy medicine, specifically a biofield therapy developed in Japan in the early 20th century. It is a system involving the laying on of hands, to stimulate the body’s natural energetic system. Earlier studies have shown an apparent connection between Reiki and the autonomous nervous system. The Reiki sessions are applied by an experienced therapist. EEG signals are measured at baseline, during session and post intervention to bring about effective epileptic seizure control or its elimination altogether.

Keywords: EEG signal, Reiki, time consuming, epileptic seizure

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Authors: Fernando M. Soto, Gaetano Di Mino

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The design of an unmodified bituminous mixture and three rubber-aggregate mixtures containing rubber-aggregate by a dry process (RUMAC) was evaluated, using an empirical-analytical approach based on experimental findings obtained in the laboratory with the volumetric mix design by gyratory compaction. A reference dense-graded bituminous sub-ballast mixture (3% of air voids and a bitumen 4% over the total weight of the mix), and three rubberized mixtures by dry process (1,5 to 3% of rubber by total weight and 5-7% of binder) were used applying the Superpave mix-design for a level 3 (high-traffic) design rail lines. The railway trackbed section analyzed was a granular layer of 19 cm compacted, while for the sub-ballast a thickness of 12 cm has been used. In order to evaluate the effect of increasing the specimen density (as a percent of its theoretical maximum specific gravity), in this article, are illustrated the results obtained after different comparative analysis into the influence of varying the binder-rubber percentages under the sub-ballast layer mix-design. This work demonstrates that rubberized blends containing crumb and ground rubber in bituminous asphalt mixtures behave at least similar or better than conventional asphalt materials. By using the same methodology of volumetric compaction, the densification curves resulting from each mixture have been studied. The purpose is to obtain an optimum empirical parameter multiplier of the number of gyrations necessary to reach the same compaction energy as in conventional mixtures. It has provided some experimental parameters adopting an empirical-analytical method, evaluating the results obtained from the gyratory-compaction of bituminous mixtures with an HMA and rubber-aggregate blends. An extensive integrated research has been carried out to assess the suitability of rubber-modified hot mix asphalt mixtures as a sub-ballast layer in railway underlayment trackbed. Design optimization of the mixture was conducted for each mixture and the volumetric properties analyzed. Also, an improved and complete manufacturing process, compaction and curing of these blends are provided. By adopting this increase-parameters of compaction, called 'beta' factor, mixtures modified with rubber with uniform densification and workability are obtained that in the conventional mixtures. It is found that considering the usual bearing capacity requirements in rail track, the optimal rubber content is 2% (by weight) or 3.95% (by volumetric substitution) and a binder content of 6%.

Keywords: empirical approach, rubber-asphalt, sub-ballast, superpave mix-design

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Authors: Omaima A. Sharaf, Tarek A. Moussa, Said M. Badr El-Din, H. Moawad

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Background: Polycyclic aromatic hydrocarbons (PAHs) pose great environmental and human health concerns for their widespread occurrence, persistence, and carcinogenic properties. PAHs releases due to anthropogenic activities to the wider environment have led to higher concentrations of these contaminants than would be expected from natural processes alone. This may result in a wide range of environmental problems that can accumulate in agricultural ecosystems, which threatened to become a negative impact on sustainable agricultural development. Thus, this study aimed to evaluate the physico-chemical, and microbial properties of the compost leachate (CL) to assess its role as nutrient and microbial source (biostimulation/bioaugmentation) for developing a cost-effective bioremediation technology for PAHs contaminated sites. Material and Methods: PAHs-degrading bacteria were isolated from CL that was collected from a composting site located in central Scotland, UK. Isolation was carried out by enrichment using phenanthrene (PHR), pyrene (PYR) and benzo(a)pyrene (BaP) as the sole source of carbon and energy. The isolates were characterized using a variety of phenotypic and molecular properties. Six different isolates were identified based on the difference in morphological and biochemical tests. The efficiency of these isolates in PAHs utilization was assessed. Further analysis was performed to define taxonomical status and phylogenic relation between the most potent PAHs-utilizing bacterial strains and other standard strains, using molecular approach by partial 16S rDNA gene sequence analysis. Results indicated that the 16S rDNA sequence analysis confirmed the results of biochemical identification, as both of biochemical and molecular identification of the isolates assigned them to Bacillus licheniformis, Pseudomonas aeruginosa, Alcaligenes faecalis, Serratia marcescens, Enterobacter cloacae and Providenicia which were identified as the prominent PAHs-utilizers isolated from CL. Conclusion: This study indicates that the CL samples contain a diverse population of PAHs-degrading bacteria and the use of CL may have a potential for bioremediation of PAHs contaminated sites.

Keywords: polycyclic aromatic hydrocarbons, physico-chemical analyses, compost leachate, microbial and biochemical analyses, phylogenic relations, 16S rDNA sequence analysis

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Authors: Marek Dosbaba

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Within the mining sector, SEM-based Automated Mineralogy (AM) has been the standard application for quickly and efficiently handling mineral processing tasks. Over the last decade, the trend has been to analyze larger numbers of samples, often with a higher level of detail. This has necessitated a shift from interactive sample analysis performed by an operator using a SEM, to an increased reliance on offline processing to analyze and report the data. In response to this trend, TESCAN TIMA Mineral Analyzer is designed to quickly create a virtual copy of the studied samples, thereby preserving all the necessary information. Depending on the selected data acquisition mode, TESCAN TIMA can perform hyperspectral mapping and save an X-ray spectrum for each pixel or segment, respectively. This approach allows the user to browse through elemental distribution maps of all elements detectable by means of energy dispersive spectroscopy. Re-evaluation of the existing data for the presence of previously unconsidered elements is possible without the need to repeat the analysis. Additional tiers of data such as a secondary electron or cathodoluminescence images can also be recorded. To take full advantage of these information-rich datasets, TIMA utilizes a new archiving tool introduced by TESCAN. The dataset size can be reduced for long-term storage and all information can be recovered on-demand in case of renewed interest. TESCAN TIMA is optimized for network storage of its datasets because of the larger data storage capacity of servers compared to local drives, which also allows multiple users to access the data remotely. This goes hand in hand with the support of remote control for the entire data acquisition process. TESCAN also brings a newly extended open-source data format that allows other applications to extract, process and report AM data. This offers the ability to link TIMA data to large databases feeding plant performance dashboards or geometallurgical models. The traditional tabular particle-by-particle or grain-by-grain export process is preserved and can be customized with scripts to include user-defined particle/grain properties.

Keywords: Tescan, electron microscopy, mineralogy, SEM, automated mineralogy, database, TESCAN TIMA, open format, archiving, big data

Procedia PDF Downloads 109

Authors: Michel Soto Chalhoub

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Building designers in the Mediterranean region and other parts of the world utilize natural stone panels on the exterior façades as skin cover. This type of finishing is not only intended for aesthetic reasons but also environmental. The stone, since the earliest ages of civilization, has been used in construction and to-date some of the most appealing buildings owe their beauty to stone finishing. The stone also provides warmth in winter and freshness in summer as it moderates heat transfer and absorbs radiation. However, as structural codes became increasingly stringent about the dynamic performance of buildings, it became essential to study the performance of stone panels under cyclic loading – a condition that arises under the building is subjected to wind or earthquakes. The present paper studies the performance of stone panels using mechanical connectors when subjected to load reversal. In this paper, we present a theoretical model that addresses modes of failure in the steel connectors, by yield, and modes of failure in the stone, by fracture. Then we provide an experimental set-up and test results for rectangular stone panels of varying thickness. When the building is subjected to an earthquake, its rectangular panels within the structural system are subjected to shear deformations, which in turn impart stress into the stone cover. Rectangular stone panels, which typically range from 40cmx80cm to 60cmx120cm, need to be designed to withstand transverse loading from the direct application of lateral loads, and to withstand simultaneously in-plane loading (membrane stress) caused by inter-story drift and overall building lateral deflection. Results show correlation between the theoretical model which we derive from solid mechanics fundamentals and the experimental results, and lead to practical design recommendations. We find that for panel thickness below a certain threshold, it is more advantageous to utilize structural adhesive materials to connect stone panels to the main structural system of the building. For larger panel thicknesses, it is recommended to utilize mechanical connectors with special detailing to ensure a minimum level of ductility and energy dissipation.

Keywords: solid mechanics, cyclic loading, mechanical connectors, natural stone, seismic, wind, building skin

Procedia PDF Downloads 255

Authors: Miaomiao Zhang, Sabrina Beckmann, Haluk Ertan, Rocky Chau, Mike Manefield

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Phenazines are a large class of nitrogen-containing aromatic heterocyclic compounds, which are almost exclusively produced by bacteria from diverse genera including Pseudomonas and Streptomyces. Phenazine-1-carboxylic acid (PCA) as one of 'core' phenazines are converted from chorismic acid before modified to other phenazine derivatives in different cells. Phenazines have attracted enormous interests because of their multiple roles on biocontrol, bacterial interaction, biofilm formation and fitness of their producers. However, in spite of ecological importance, degradation as a part of phenazines’ fate only have extremely limited attention now. Here, to isolate PCA-degrading bacteria, 200 mg L-1 PCA was supplied as sole carbon, nitrogen and energy source in minimal mineral medium. Quantitative PCR and Reverse-transcript PCR were employed to study abundance and activity of functional gene MFORT 16269 in PCA degradation, respectively. Intermediates and products of PCA degradation were identified with LC-MS/MS. After enrichment and isolation, a PCA-degrading strain was selected from soil and was designated as Rhodanobacter sp. PCA2 based on full 16S rRNA sequencing. As determined by HPLC, strain PCA2 consumed 200 mg L-1 (836 µM) PCA at a rate of 17.4 µM h-1, accompanying with significant cells yield from 1.92 × 105 to 3.11 × 106 cells per mL. Strain PCA2 was capable of degrading other phenazines as well, including phenazine (4.27 µM h-1), pyocyanin (2.72 µM h-1), neutral red (1.30 µM h-1) and 1-hydroxyphenazine (0.55 µM h-1). Moreover, during the incubation, transcript copies of MFORT 16269 gene increased significantly from 2.13 × 106 to 8.82 × 107 copies mL-1, which was 2.77 times faster than that of the corresponding gene copy number (2.20 × 106 to 3.32 × 107 copies mL-1), indicating that MFORT 16269 gene was activated and played roles on PCA degradation. As analyzed by LC-MS/MS, decarboxylation from the ring structure was determined as the first step of PCA degradation, followed by cleavage of nitrogen-containing ring by dioxygenase which catalyzed phenazine to nitrosobenzene. Subsequently, phenylhydroxylamine was detected after incubation for two days and was then transferred to aniline and catechol. Additionally, genomic and proteomic analyses were also carried out for strain PCA2. Overall, the findings presented here showed that a newly isolated strain Rhodanobacter sp. PCA2 was capable of degrading phenazines through decarboxylation and cleavage of nitrogen-containing ring, during which MFORT 16269 gene was activated and played important roles.

Keywords: decarboxylation, MFORT16269 gene, phenazine-1-carboxylic acid degradation, Rhodanobacter sp. PCA2

Procedia PDF Downloads 223

Authors: Milton Ixquiac, Erick Montenegro, Francisco Reynoso, Matthew Schmidt, Thomas Mazur, Tianyu Zhao, Hiram Gay, Geoffrey Hugo, Lauren Henke, Jeff Michael Michalski, Angel Velarde, Vicky de Falla, Franky Reyes, Osmar Hernandez, Edgar Aparicio Ruiz, Baozhou Sun

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Purpose: Radiotherapy departments in low- and middle-income countries (LMICs) like Guatemala have recently introduced intensity-modulated radiotherapy (IMRT). IMRT has become the standard of care in high-income countries (HIC) due to reduced toxicity and improved outcomes in some cancers. The purpose of this work is to show the agreement between the dosimetric results shown in the Dose Volume Histograms (DVH) to the objectives proposed in the adopted protocol. This is the initial experience with an O-ring Linac. Methods and Materials: An O-Linac Linac was installed at our clinic in Guatemala in 2019 and has been used to treat approximately 90 patients daily with IMRT. This Linac is a completely Image Guided Device since to deliver each radiotherapy session must take a Mega Voltage Cone Beam Computerized Tomography (MVCBCT). In each MVCBCT, the Linac deliver 9 UM, and they are taken into account while performing the planning. To start the standardization, the TG263 was employed in the nomenclature and adopted a hypofractionated protocol to treat ChestWall, including supraclavicular nodes achieving 40.05Gy in 15 fractions. The planning was developed using 4 semiarcs from 179-305 degrees. The planner must create optimization volumes for targets and Organs at Risk (OARs); the difficulty for the planner was the dose base due to the MVCBCT. To evaluate the planning modality, we used 30 chestwall cases. Results: The plans created manually achieve the protocol objectives. The protocol objectives are the same as the RTOG1005, and the DHV curves look clinically acceptable. Conclusions: Despite the O-ring Linac doesn´t have the capacity to obtain kv images, the cone beam CT was created using MV energy, the dose delivered by the daily image setup process still without affect the dosimetric quality of the plans, and the dose distribution is acceptable achieving the protocol objectives.

Keywords: hypofrationation, VMAT, chestwall, radiotherapy planning

Procedia PDF Downloads 118

Authors: Jorge Martínez-Rodríguez, Esther Pérez-Carrillo, Diana Laura Anchondo Álvarez, Julia Lucía Leal Villarreal, Mariana Juárez Dominguez, Luisa Fernanda Torres Hernández, Daniela Salinas Morales, Erick Heredia-Olea

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Maize tortillas are a staple food in Mexico which are mostly made by nixtamalization, which includes the cooking and steeping of maize kernels in alkaline conditions. The cooking step in nixtamalization demands a lot of energy and also generates nejayote, a water pollutant, at the end of the process. The aim of this study was to reduce the cooking time by adding a maize soaking step before nixtamalization while maintaining the quality properties of masa and tortillas. Maize kernels were soaked for 36 h to increase moisture up to 36%. Then, the effect of different cooking times (0, 5, 10, 15, 20, 20, 25, 30, 35, 45-control and 50 minutes) was evaluated on viscosity profile (RVA) of masa to select the treatments with a profile similar or equal to control. All treatments were left steeping overnight and had the same milling conditions. Treatments selected were 20- and 25-min cooking times which had similar values for pasting temperature (79.23°C and 80.23°C), Maximum Viscosity (105.88 Cp and 96.25 Cp) and Final Viscosity (188.5 Cp and 174 Cp) to those of 45 min-control (77.65 °C, 110.08 Cp, and 186.70 Cp, respectively). Afterward, tortillas were produced with the chosen treatments (20 and 25 min) and for control, then were analyzed for texture, damage starch, colorimetry, thickness, and average diameter. Colorimetric analysis of tortillas only showed significant differences for yellow/blue coordinates (b* parameter) at 20 min (0.885), unlike the 25-minute treatment (1.122). Luminosity (L*) and red/green coordinates (a*) showed no significant differences from treatments with respect control (69.912 and 1.072, respectively); however, 25 minutes was closer in both parameters (73.390 and 1.122) than 20 minutes (74.08 and 0.884). For the color difference, (E), the 25 min value (3.84) was the most similar to the control. However, for tortilla thickness and diameter, the 20-minute with 1.57 mm and 13.12 cm respectively was closer to those of the control (1.69 mm and 13.86 cm) although smaller to it. On the other hand, the 25 min treatment tortilla was smaller than both 20 min and control with 1.51 mm thickness and 13.590 cm diameter. According to texture analyses, there was no difference in terms of stretchability (8.803-10.308 gf) and distance for the break (95.70-126.46 mm) among all treatments. However, for the breaking point, all treatments (317.1 gf and 276.5 gf for 25 and 20- min treatment, respectively) were significantly different from the control tortilla (392.2 gf). Results suggest that by adding a soaking step and reducing cooking time by 25 minutes, masa and tortillas obtained had similar functional and textural properties to the traditional nixtamalization process.

Keywords: tortilla, nixtamalization, corn, lime cooking, RVA, colorimetry, texture, masa rheology

Procedia PDF Downloads 177

Authors: A. Dean, M. Pitcher, L. Storer, K. Shanahan, I. Rio, B. Mann

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Purpose: Breast cancer survivors are at risk of specific physical and psycho-social issues, such as arm swelling, fatigue, and depression. Firstly, we investigate symptoms reported by Australia breast cancer survivors upon completion of definitive treatment. Secondly, we evaluate the appropriateness and effectiveness of a multi-centre pilot program nurse-led clinic to identify these issues and make timely referrals to available services. Methods: Patients post-definitive treatment (excluding ongoing hormonal therapy) for early breast cancer or ductal carcinoma in situ were invited to participate. An hour long appointment with a breast care nurse (BCN) was scheduled. In preparation, patients completed validated quality-of-life surveys (FACT-B, Menopause Rating Scale, Distress Thermometer). During the appointment, issues identified in the surveys were addressed and referrals to appropriate services arranged. Results: 183 of 274 (67%) eligible patients attended a nurse-led clinic. Mean age 56.8 years (range 29-87 years), 181/183 women, 105/183 post-menopausal. 96 (55%) participants reported significant level of distress; 31 (18%) participants reported extreme distress or depression. Distress stemmed from a lack of energy (56/175); poor quality of sleep (50/176); inability to work or participate in household activities (35/172) and problems with sex life (28/89). 166 referrals were offered; 94% of patients accepted the referrals. 65% responded to a follow-up survey: the majority of women either strongly agreed or agreed that the BCN was overwhelmingly supportive, helpful in making referrals, and compassionate towards them. 39% reported making lifestyle changes as a result of the BCN. Conclusion: Breast cancer survivors experience a unique set of challenges, including low mood, difficulty sleeping, problems with sex life and fear of disease recurrence. The nurse-led clinic model is an appropriate and effective method to ensure physical and psycho-social issues are identified and managed in a timely manner. This model empowers breast cancer survivors with information about their diagnosis and available services.

Keywords: early breast cancer, survivorship, breast care nursing, oncology nursing and cancer care

Procedia PDF Downloads 399

Authors: Nikoloz Jalabadze, Roin Chedia, Lili Nadaraia, Levan Khundadze

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Nanocrystalline materials in powder condition can be manufactured by a number of different methods, however manufacture of composite materials product in the same nanocrystalline state is still a problem because the processes of compaction and synthesis of nanocrystalline powders go with intensive growth of particles – the process which promotes formation of pieces in an ordinary crystalline state instead of being crystallized in the desirable nanocrystalline state. To date spark plasma sintering (SPS) has been considered as the most promising and energy efficient method for producing dense bodies of composite materials. An advantage of the SPS method in comparison with other methods is mainly low temperature and short time of the sintering procedure. That finally gives an opportunity to obtain dense material with nanocrystalline structure. Graphene has recently garnered significant interest as a reinforcing phase in composite materials because of its excellent electrical, thermal and mechanical properties. Graphene nanoplatelets (GNPs) in particular have attracted much interest as reinforcements for ceramic matrix composites (mostly in Al2O3, Si3N4, TiO2, ZrB2 a. c.). SPS has been shown to fully densify a variety of ceramic systems effectively including Al2O3 and often with improvements in mechanical and functional behavior. Alumina consolidated by SPS has been shown to have superior hardness, fracture toughness, plasticity and optical translucency compared to conventionally processed alumina. Knowledge of how GNPs influence sintering behavior is important to effectively process and manufacture process. In this study, the effects of GNPs on the SPS processing of Al2O3 are investigated by systematically varying sintering temperature, holding time and pressure. Our experiments showed that SPS process is also appropriate for the synthesis of nanocrystalline powders of alumina-graphene composites. Depending on the size of the molds, it is possible to obtain different amount of nanopowders. Investigation of the structure, physical-chemical, mechanical and performance properties of the elaborated composite materials was performed. The results of this study provide a fundamental understanding of the effects of GNP on sintering behavior, thereby providing a foundation for future optimization of the processing of these promising nanocomposite systems.

Keywords: alumina oxide, ceramic matrix composites, graphene nanoplatelets, spark-plasma sintering

Procedia PDF Downloads 376

Authors: Krupali Mehta, Sandip Bhatt, Umesh Trivedi, Bhavesh Bharatiya, Mukesh Ranjan, Atindra D. Shukla

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Owing to the dominating surface forces and large-scale surface interactions, the nano-scale particles face difficulties in getting suspended in various media. Magnetic nanoparticles of iron oxide offer a great deal of promise due to their ease of preparation, reasonable magnetic properties, low cost and environmental compatibility. We intend to modify the surface of magnetic Fe₂O₃ nanoparticles with selected surface modifying agents using simple and effective single-step chemical reactions in order to enhance dispersibility of magnetic nanoparticles in non-polar media. Magnetic particles were prepared by hydrolysis of Fe²⁺/Fe³⁺ chlorides and their subsequent oxidation in aqueous medium. The dried particles were then treated with Octadecyl quaternary ammonium silane (Terrasil™), stearic acid and gallic acid ester of stearyl alcohol in ethanol separately to yield S-2 to S-4 respectively. The untreated Fe₂O₃ was designated as S-1. The surface modified nanoparticles were then analysed with Dynamic Light Scattering (DLS), Fourier Transform Infrared spectroscopy (FTIR), X-Ray Diffraction (XRD), Thermogravimetric Gravimetric Analysis (TGA) and Scanning Electron Microscopy and Energy dispersive X-Ray analysis (SEM-EDAX). Characterization reveals the particle size averaging 20-50 nm with and without modification. However, the crystallite size in all cases remained ~7.0 nm with the diffractogram matching to Fe₂O₃ crystal structure. FT-IR suggested the presence of surfactants on nanoparticles’ surface, also confirmed by SEM-EDAX where mapping of elements proved their presence. TGA indicated the weight losses in S-2 to S-4 at 300°C onwards suggesting the presence of organic moiety. Hydrophobic character of modified surfaces was confirmed with contact angle analysis, all modified nanoparticles showed super hydrophobic behaviour with average contact angles ~129° for S-2, ~139.5° for S-3 and ~151° for S-4. This indicated that surface modified particles are super hydrophobic and they are easily dispersible in non-polar media. These modified particles could be ideal candidates to be suspended in oil-based fluids, polymer matrices, etc. We are pursuing elaborate suspension/sedimentation studies of these particles in various oils to establish this conjecture.

Keywords: iron nanoparticles, modification, hydrophobic, dispersion

Procedia PDF Downloads 141

Authors: Zahra Jandaghian, Mehdi Ghobadi, Michal Bartko, Alex Hayes, Marianne Armstrong, Alexandra Thompson, Michael Lacasse

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The Intergovernmental Panel on Climate Change (IPCC) report stated the urgent need to cut greenhouse gas emissions to avoid the adverse impacts of climatic changes. The United Nations has forecasted that nearly 70 percent of people will live in urban areas by 2050 resulting in a doubling of the global building stock. Given that buildings are currently recognised as emitting 40 percent of global carbon emissions, there is thus an urgent incentive to decarbonize existing buildings and to build net-zero carbon buildings. To attain net zero carbon emissions in communities in the future requires action in two directions: I) reduction of emissions; and II) removal of on-going emissions from the atmosphere once de-carbonization measures have been implemented. Nature-based solutions (NBS) have a significant role to play in achieving net zero carbon communities, spanning both emission reductions and removal of on-going emissions. NBS for the decarbonisation of buildings can be achieved by using green roofs and green walls – increasing vertical and horizontal vegetation on the building envelopes – and using nature-based materials that either emit less heat to the atmosphere thus decreasing photochemical reaction rates, or store substantial amount of carbon during the whole building service life within their structure. The NBS approach can also mitigate urban flooding and overheating, improve urban climate and air quality, and provide better living conditions for the urban population. For existing buildings, de-carbonization mostly requires retrofitting existing envelopes efficiently to use NBS techniques whereas for future construction, de-carbonization involves designing new buildings with low carbon materials as well as having the integrity and system capacity to effectively employ NBS. This paper presents the opportunities and challenges in respect to the de-carbonization of buildings using NBS for both building retrofits and new construction. This review documents the effectiveness of NBS to de-carbonize Canadian buildings, identifies the missing links to implement these techniques in cold climatic conditions, and determine a road map and immediate approaches to mitigate the adverse impacts of climate change such as urban heat islanding. Recommendations are drafted for possible inclusion in the Canadian building and energy codes.

Keywords: decarbonization, nature-based solutions, GHG emissions, greenery enhancement, buildings

Procedia PDF Downloads 93

Authors: Z. Zaman Asam, M. Ajmal, R. Saeed, H. Miraj, M. Muhammad Ahtisham, B. Hameed, A. -Sattar Nizami

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In Pakistan, environmental degradation and consequent human health deterioration has rapidly accelerated in the past decade due to solid waste mismanagement. As the situation worsens with time, establishment of proper waste management practices is urgently needed especially in semi urban and rural areas of Pakistan. This study uses a concept of Waste Bank, which involves a transfer station for collection of sorted waste fractions and its delivery to the targeted market such as recycling industries, biogas plants, composting facilities etc. The management efficiency and effectiveness of Waste Bank depend strongly on the proficient sorting and collection of solid waste fractions at household level. However, the social attitude towards such a solution in semi urban/rural areas of Pakistan demands certain prerequisites to make it workable. Considering these factors the objectives of this study are to: [A] Obtain reliable data about quantity and characteristics of generated waste to define feasibility of business and design factors, such as required storage area, retention time, transportation frequency of the system etc. [B] Analyze the effects of various social factors on waste generation to foresee future projections. [C] Quantify the improvement in waste sorting efficiency after awareness campaign. We selected Gujrat city of Central Punjab province of Pakistan as it is semi urban adjoined by rural areas. A total of 60 houses (20 from each of the three selected colonies), belonging to different social status were selected. Awareness sessions about waste segregation were given through brochures and individual lectures in each selected household. Sampling of waste, that households had attempted to sort, was then carried out in the three colored bags that were provided as part of the awareness campaign. Finally, refined waste sorting, weighing of various fractions and measurement of dry mass was performed in environmental laboratory using standard methods. It was calculated that sorting efficiency of waste improved from 0 to 52% as a result of the awareness campaign. The generation of waste (dry mass basis) on average from one household was 460 kg/year whereas per capita generation was 68 kg/year. Extrapolating these values for Gujrat Tehsil, the total waste generation per year is calculated to be 101921 tons dry mass (DM). Characteristics found in waste were (i) organic decomposable (29.2%, 29710 tons/year DM), (ii) recyclables (37.0%, 37726 tons/year DM) that included plastic, paper, metal and glass, and (iii) trash (33.8%, 34485 tons/year DM) that mainly comprised of polythene bags, medicine packaging, pampers and wrappers. Waste generation was more in colonies with comparatively higher income and better living standards. In future, data collection for all four seasons and improvements due to expansion of awareness campaign to educational institutes will be quantified. This waste management system can potentially fulfill vital sustainable development goals (e.g. clean water and sanitation), reduce the need to harvest fresh resources from the ecosystem, create business and job opportunities and consequently solve one of the most pressing environmental issues of the country.

Keywords: integrated solid waste management, waste segregation, waste bank, community development

Procedia PDF Downloads 141

Authors: Alexander Chinyere Nwankpa, Nneka Ngozi Nwankpa

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In Nigeria, the Federal government is trying to make sure that everyone has access to enough food that is nutritiously adequate and safe. But in the southwest of Nigeria, notably in Ondo State, the most valuable minerals such as oil and gas, bitumen, kaolin, limestone talc, columbite, tin, gold, coal, and phosphate are abundant. Therefore, some regions of Ondo State are now linked to large quantities of natural radioactivity as a result of the mineral presence. In this work, the baseline radioactivity levels in some of the most important food crops in Ondo State were analyzed, allowing for the prediction of probable radiological health impacts. To this effect, maize (Zea mays), yam (Dioscorea alata) and cassava (Manihot esculenta) tubers were collected from the farmlands in the State because they make up the majority of food's nutritional needs. Ondo State was divided into eight zones in order to provide comprehensive coverage of the research region. At room temperature, the maize (Zea mays), yam (Dioscorea alata), and cassava (Manihot esculenta) samples were dried until they reached a consistent weight. They were pulverized, homogenized, and 250 g packed in a 1-liter Marinelli beaker and kept for 28 days to achieve secular equilibrium. The activity concentrations of Radium-226 (Ra-226), Thorium-232 (Th-232), and Potassium-40 (K-40) were determined in the food samples using Gamma-ray spectrometry. Firstly, the Hyper Pure Germanium detector was calibrated using standard radioactive sources. The gamma counting, which lasted for 36000s for each sample, was carried out in the Centre for Energy Research and Development, Obafemi Awolowo University, Ile-Ife, Nigeria. The mean activity concentration of Ra-226, Th-232 and K-40 for yam were 1.91 ± 0.10 Bq/kg, 2.34 ± 0.21 Bq/kg and 48.84 ± 3.14 Bq/kg, respectively. The content of the radionuclides in maize gave a mean value of 2.83 ± 0.21 Bq/kg for Ra-226, 2.19 ± 0.07 Bq/kg for Th-232 and 41.11 ± 2.16 Bq/kg for K-40. The mean activity concentrations in cassava were 2.52 ± 0.31 Bq/kg for Ra-226, 1.94 ± 0.21 Bq/kg for Th-232 and 45.12 ± 3.31 Bq/kg for K-40. The average committed effective doses in zones 6-8 were 0.55 µSv/y for the consumption of yam, 0.39 µSv/y for maize, and 0.49 µSv/y for cassava. These values are higher than the annual dose guideline of 0.35 µSv/y for the general public. Therefore, the values obtained in this work show that there is radiological contamination of some foodstuffs consumed in some parts of Ondo State. However, we recommend that systematic and appropriate methods also need to be established for the measurement of gamma-emitting radionuclides since these constitute important contributors to the internal exposure of man through ingestion, inhalation, or wound on the body.

Keywords: contamination, environment, radioactivity, radionuclides

Procedia PDF Downloads 104

Authors: Tobias Huwer, Thomas Bobek, Gunter Spöcker

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Driving forces for enhancements in production are trends like digitalization and individualized production. Currently, such developments are restricted to assembly parts. Thus, complex freeform surfaces are not addressed in this context. The need for efficient use of resources and near-net-shape production will require individualized production of complex shaped workpieces. Due to variations between nominal model and actual geometry, this can lead to changes in operations in Computer-aided process planning (CAPP) to make CAPP manageable for an adaptive serial production. In this context, 3D CAD data can be a key to realizing that objective. Along with developments in the geometrical adaptation, a preceding inspection method based on CAD data is required to support the process planner by finding objective criteria to make decisions about the adaptive manufacturability of workpieces. Nowadays, this kind of decisions is depending on the experience-based knowledge of humans (e.g. process planners) and results in subjective decisions – leading to a variability of workpiece quality and potential failure in production. In this paper, we present an automatic part inspection method, based on design and measurement data, which evaluates actual geometries of single workpiece preforms. The aim is to automatically determine the suitability of the current shape for further machining, and to provide a basis for an objective decision about subsequent adaptive manufacturability. The proposed method is realized by a workflow-based approach, keeping in mind the requirements of industrial applications. Workflows are a well-known design method of standardized processes. Especially in applications like aerospace industry standardization and certification of processes are an important aspect. Function blocks, providing a standardized, event-driven abstraction to algorithms and data exchange, will be used for modeling and execution of inspection workflows. Each analysis step of the inspection, such as positioning of measurement data or checking of geometrical criteria, will be carried out by function blocks. One advantage of this approach is its flexibility to design workflows and to adapt algorithms specific to the application domain. In general, within the specified tolerance range it will be checked if a geometrical adaption is possible. The development of particular function blocks is predicated on workpiece specific information e.g. design data. Furthermore, for different product lifecycle phases, appropriate logics and decision criteria have to be considered. For example, tolerances for geometric deviations are different in type and size for new-part production compared to repair processes. In addition to function blocks, appropriate referencing systems are important. They need to support exact determination of position and orientation of the actual geometries to provide a basis for precise analysis. The presented approach provides an inspection methodology for adaptive and part-individual process chains. The analysis of each workpiece results in an inspection protocol and an objective decision about further manufacturability. A representative application domain is the product lifecycle of turbine blades containing a new-part production and a maintenance process. In both cases, a geometrical adaptation is required to calculate individual production data. In contrast to existing approaches, the proposed initial inspection method provides information to decide between different potential adaptive machining processes.

Keywords: adaptive, CAx, function blocks, turbomachinery

Procedia PDF Downloads 297

Authors: Xiquan Weng, Chaoge Wang, Guoqin Xu, Wentao Lin

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Objective: Cold exposure and exercise serve as two powerful physiological stimuli to launch the conversion of fat-accumulating white adipose tissue (WAT) into energy-dissipating brown adipose tissue (BAT). So far, it remains to be elucidated whether exercise plus cold exposure can produce an addictive effect on promoting WAT browning. Methods: 64 SD rats were subjected to high-fat and high-sugar diets for 9-week and successfully established an obesity model. They were randomly divided into 8 groups: normal control group (NC), normal exercise group (NE), continuous cold control group (CC), continuous cold exercise group (CE), intermittent cold control group (IC) and intermittent cold exercise group (IE). For continuous cold exposure, the rats stayed in a cold environment all day; For intermittent cold exposure, the rats were exposed to cold for only 4h per day. The protocol for treadmill exercises were as follows: 25m/min (speed), 0°C (slope), 30mins each time, an interval for 10 mins between two exercises, twice/two days, lasting for 5 weeks. Sampling were conducted on the 5th weekend. The body length and weight of the rats were measured, and the Lee's index was calculated. The visceral fat rate (VFR), subcutaneous fat rate (SFR), brown fat rate (BrFR) and body fat rate (BoFR) were measured by Micro-CT LCT200, and the expression of UCP1 protein in inguinal fat was examined by Western-blot. SPSS 22.0 was used for statistical analysis of the experimental results, and the ANOVA analysis was performed between groups (P < 0.05 was significant). Results: (1) Compared with the NC group, the weight of obese rats was significantly declined in the NE, CE and IE groups (P < 0.05), the Lee's index of obese rats significantly declined in the CE group (P < 0.05). Compared with the NE group, the weight of obese rats was significantly declined in the CE and IE groups (P < 0.05). (2)Compared with the NC group, the VFR and BoFR of the rats significantly declined in the NE, CE and IE groups (P < 0.05), the SFR of the rats significantly declined in the CE and IE groups (P < 0.05), and the BFR of the rats was significantly higher in the CC and IC groups (P < 0.05), respectively. Compared with the NE group, the VFR and BoFR of the rats significantly declined in the CE group (P < 0.05), the SFR of the rats was significantly higher in the CC and IS groups (P < 0.05), and the BrFR of the rats was significantly higher in the IC group (P < 0.05). (3)Compared with the NC group, the up-regulation of UCP1 protein expression in the inguinal fat of the rats was significant in the NE, CC, CE, IC and IE groups (P < 0.05). Compared with the NE group, the up-regulation of UCP1 protein expression in the inguinal fat of the rats was significant in the CC, CE and IE groups (P < 0.05). Conclusions: Exercise in the continuous and intermittent cold, especially in the former, can effectively decline the weight and body fat rate of obese rats. This is related to the effect of cold and exercise on the browning of white fat in rats.

Keywords: cold, browning of white fat, exercise, obesity

Procedia PDF Downloads 131

Authors: Nadia Miranda Lorick, Neela Badrie, Marsha Singh

Abstract:

Cassava (Manihot esculenta, Crantz) which is also known as ‘yucca’ or ‘manioc’ has been acknowledged as a millennium crop which has been utilized for food security purposes. The crop provides considerable amount of energy. The aim of the study was to assess consumer groups of both ‘fresh’ and ‘frozen’ in terms of their perceptions toward the quality and safety attributes of frozen cassava. The questionnaire included four sections: consumer demographics, consumer perceptions on quality attributes of ‘frozen’ cassava, consumer knowledge, awareness and attitudes toward food safety of ‘frozen’ cassava and consumer suggestions toward the improvement of frozen cassava. A face-to-face questionnaire was administered to 200 consumers of cassava between April and May 2016. The criteria for inclusion in the survey were that they must be 15 years and over and consumer of cassava. The sections of the questionnaire included demographics of respondents, consumer perception on quality and safety attributes of cassava and suggestions for the improvement of the value-added product. The data was analysed by descriptive and chi-square using SPSS as well as qualitative information was captured. Only 17% of respondents purchased frozen cassava and this was significantly (P<0.05) associated to income. Some (15%) of fresh cassava purchasers had never heard of frozen cassava products and 7.5% o perceived that these products were unhealthy for consumption. More than half (51.3%) of the consumers (all from the ‘fresh’ cassava group) believed that there were ‘no toxins’ within cassava. The ‘frozen’ cassava products were valued for convenience but purchasers were least satisfied with ‘value for money’ (50%), ‘product safety’ (50%) and ‘colour’ (52.9%). Cassava purchasers demonstrated highest dissatisfaction levels with the quality attribute: value for money (6.6%, 11.8%) respectively. The most predominant area outlined by respondents for frozen cassava improvement was promotion /advertising/education (23%). The ‘frozen’ cassava purchasers were ‘least satisfied’ thus most concern that clean knives and clean surface would not be used agro- processing. Fresh cassava purchasers were comparatively more knowledgeable on the potential existence of naturally occurring toxins in cassava, however with 1% respondents being able to specifically identify the toxin as ‘cyanide’. Dangerous preservatives (31%), poor hygiene (30%) and chemicals from the packaging (11%) were identified as some sources of contamination of ‘frozen’ cassava. Purchasers of frozen cassava indicated that the information on packaging label was unclear (P<0.01) when compared to ‘fresh’ cassava consumers.

Keywords: consumer satisfaction, convenience, cyanide toxin, product safety, price, label

Procedia PDF Downloads 402

Authors: Elif Doğru, Bülent Kızılduman, Huriye İcil

Abstract:

Throughout history, Cyprus has been involved in various commercial and cultural relationships with different civilizations, owing to its strategic location. Particularly during the Late Bronze Age, Cyprus emerged as a significant region engaged in interactions with the Mycenaeans and other Mediterranean civilizations. Presently, findings from archaeological excavations provide valuable insights into Cyprus' cultural history and its connections with other civilizations. Painted Mycenaean ceramics discovered during the excavations at Kaleburnu-Kral Tepesi (Galinaporni-Vasili), dated to the Late Bronze Age in Cyprus, are considered significant archaeological findings that carry traces of the art and culture of that era, reflecting the island's commercial and cultural connections. Considering these findings, there is a need for archaeometric studies to aid in the understanding of the commercial and cultural ties at Kaleburnu-Kral Tepesi. In line with this need, analytical studies have been initiated concerning the provenance and production techniques of the Mycenaean ceramics discovered in the excavations at Kaleburnu-Kral Tepesi, dated to the Late Bronze Age. In the context of origin analysis studies, it is advocated that understanding the techniques and materials used for the figures and designs applied on Mycenaean ceramics would significantly contribute to a better comprehension of historical contexts. Hence, the adopted approach involves not only the analysis of the ceramic raw material but also the characterization of the pigments on the ceramics as a whole. In light of this, in addition to the studies aimed at determining the provenance and production techniques of the Mycenaean ceramic bodies, the characterization of the pigments used in the decorations of the relevant ceramics has been included in the research scope. Accordingly, this study aims to characterize the pigments used in the decorations of Mycenaean ceramics discovered at Kaleburnu-Kral Tepesi, dated to the Late Bronze Age. The X-Ray diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), and Scanning Electron Microscopy with Energy Dispersive X-ray Spectroscopy (SEM-EDX) methods have been employed to determine the surface morphology and chemical properties of the Mycenaean pigments. The characterization has been conducted through the combination of multiple analytical methods. The characterization of the pigments of Mycenaean ceramics aims to enhance the scientific perspective adopted for understanding the contributions of Mycenaean ceramics found in Cyprus to the island's culture, by providing scientific data on the types and origins of pigments used during the Late Bronze Age.

Keywords: mycenaean, ceramic, provenance, pigment

Procedia PDF Downloads 74

Authors: Rizwan Ahmed Bhutto, Noor ul ain Hira Bhutto, Mingwei Wang, Shahid Iqbal, Jiang Yi

Abstract:

Curcumin, a natural polyphenolic compound, boasts numerous health benefits; however, its industrial applications are hindered by instabilities and poor solubility. Encapsulating curcumin in Pickering emulsion presents a promising strategy to enhance its bioavailability. Yet, the development of an efficient and straightforward method to fabricate a natural emulsifier for Pickering emulsion poses a significant challenge. Chitosan has garnered attention due to its non-toxicity and excellent emulsifying properties. This study aimed to prepare four distinct types of self-aggregated chitosan particles using a pH-responsive self-assembling approach. The properties of the aggregated particles were adjusted by pH, degree of deacetylation (DDA), and molecular weight (MW), thereby controlling surface charge, size (ranging from nano to micro and floc), and contact angle. Pickering emulsions were then formulated using these various aggregated particles. As MW and pH increased and DDA decreased, the networked structures of the aggregated particles formed, resulting in highly elastic gels that were more resistant to the breakdown of Pickering emulsion at ambient temperature. With elevated temperatures, the kinetic energy of the aggregated particles increased, disrupting hydrogen bonds and potentially transforming the systems from fluids to gels. The Pickering emulsion based on aggregated particles served as a carrier for curcumin encapsulation. It was observed that DDA and MW played crucial roles in regulating drug loading, encapsulation efficiency, and release profile. This research sheds light on selecting suitable chitosan for controlling the release of bioactive compounds in Pickering emulsions, considering factors such as adjustable rheological properties, microstructure, and macrostructure. Furthermore, this study introduces an environmentally friendly and cost-effective synthesis of pH-responsive aggregate particles without the need for high-pressure homogenizers. It underscores the potential of aggregate particles with various MWs and DDAs for encapsulating other bioactive compounds, offering valuable applications in industries including food, flavor/fragrance, cosmetics, and medicine.

Keywords: chitosan, molecular weight, rheological properties, curcumin encapsulation

Procedia PDF Downloads 65