Search results for: vector density

Authors: Magdalena B. Kaziuk, Waldemar Kosiba

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Background: In the XXI century we have to deal with the epidemic of obesity which is important risk factor for the cardiovascular and kidney diseases. Lipo proteins are directly involved in the atherosclerotic process. Non-high-density lipo protein (non-HDL) began following widespread recognition of its superiority over LDL as a measurement of vascular event risk. Non-HDL includes residual risk which persists in patients after achieved recommended level of LDL. Materials and Methods: The study covered 111 patients (52 females, 59 males, age 51,91±14 years), hospitalized on the intern department. Body composition was assessed using the bioimpendance method and anthropometric measurements. Physical activity data were collected during the interview. The nutritional status and the obesity type were determined with the Waist to Height Ratio and the Waist to Hip Ratio. A function of the kidney was evaluated by calculating the estimated glomerular filtration rate (eGFR) using MDRD formula. Non-HDL was calculated as a difference between concentration of the Total and HDL cholesterol. Results: 10% of patients were found to be underweight; 23.9 % had correct body weight; 15,08 % had overweight, while the remaining group had obesity: 51,02 %. People with the android shape have higher non-HDL cholesterol versus with the gynoid shape (p=0.003). The higher was non-HDL, the lower eGFR had studied subjects (p < 0.001). Significant correlation was found between high non-HDL and incorrect dietary habits in patients avoiding eating vegetables, fruits and having low physical activity (p < 0.005). Conclusions: Android type of figure raises the residual risk of the heart disease associated with higher levels of non-HDL. Increasing physical activity in these patients reduces the level of non-HDL. Non-HDL seems to be the best predictor among all cholesterol measures for the cardiovascular events and worsening eGFR.

Keywords: obesity, non-HDL cholesterol, glomerular filtration rate, lifestyle

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Authors: Bernardo C. P. Albuquerque, Darym J. F. Campos

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Increasing our ability to solve complex engineering problems is directly related to the processing capacity of computers. By means of such equipments, one is able to fast and accurately run numerical algorithms. Besides the increasing interest in numerical simulations, probabilistic approaches are also of great importance. This way, statistical tools have shown their relevance to the modelling of practical engineering problems. In general, statistical approaches to such problems consider that the random variables involved follow a normal distribution. This assumption tends to provide incorrect results when skew data is present since normal distributions are symmetric about their means. Thus, in order to visualize and quantify this aspect, 9 statistical distributions (symmetric and skew) have been considered to model a hypothetical slope stability problem. The data modeled is the friction angle of a superficial soil in Brasilia, Brazil. Despite the apparent universality, the normal distribution did not qualify as the best fit. In the present effort, data obtained in consolidated-drained triaxial tests and saturated direct shear tests have been modeled and used to analytically derive the probability density function (PDF) of the safety factor of a hypothetical slope based on Mohr-Coulomb rupture criterion. Therefore, based on this analysis, it is possible to explicitly derive the failure probability considering the friction angle as a random variable. Furthermore, it is possible to compare the stability analysis when the friction angle is modelled as a Dagum distribution (distribution that presented the best fit to the histogram) and as a Normal distribution. This comparison leads to relevant differences when analyzed in light of the risk management.

Keywords: statistical slope stability analysis, skew distributions, probability of failure, functions of random variables

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Authors: Semayat Fanta, P.M. Mohite, C.S. Upadhyay

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Damage meso-model for laminates is one of the most widely applicable approaches for the analysis of damage induced in laminated fiber-reinforced polymeric composites. Damage meso-model for laminates has been developed over the last three decades by many researchers in experimental, theoretical, and analytical methods that have been carried out in micromechanics as well as meso-mechanics analysis approaches. It has been fundamentally developed based on the micromechanical description that aims to predict the damage initiation and evolution until the failure of structure in various loading conditions. The current damage meso-model for laminates aimed to act as a bridge between micromechanics and macro-mechanics of the laminated composite structure. This model considers two meso-constituents for the analysis of damage in ply and interface that imparted from low-velocity impact. The damages considered in this study include fiber breakage, matrix cracking, and diffused damage of the lamina, and delamination of the interface. The damage initiation and evolution in laminae can be modeled in terms of damaged strain energy density using damage parameters and the thermodynamic irreversible forces. Interface damage can be modeled with a new concept of spherical micro-void in the resin-rich zone of interface material. The damage evolution is controlled by the damage parameter (d) and the radius of micro-void (r) from the point of damage nucleation to its saturation. The constitutive martial model for meso-constituents is defined in a user material subroutine VUMAT and implemented in ABAQUS/Explicit finite element modeling tool. The model predicts the damages in the meso-constituents level very accurately and is considered the most effective technique of modeling low-velocity impact simulation for laminated composite structures.

Keywords: mesomodel, laminate, low-energy impact, micromechanics

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Authors: Suvorov Vasyl, Filipchuk Viktor

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Developmental Dysplasia of the Hip (DDH) is a frequent pathology in pediatric orthopedist’s practice. Neglected or residual cases of DDH in walking patients are usually treated using pelvic osteotomies. Plastic changes take place in hinge points due to acetabulum reorientation during surgery. Classically described hinge points and a traditional division of pelvic osteotomies on reshaping and reorientation are currently debated. The purpose of this article was to evaluate biomechanical changes during the most commonly used pelvic osteotomies (Salter, Dega, Pemberton) for DDH treatment in pediatric patients. Methods: virtual pelvic models of 2- and 6-years old patients were created, material properties were assigned, pelvic osteotomies were simulated and biomechanical changes were evaluated using finite element analysis (FEA). Results: it was revealed that the patient's age has an impact on pelvic bones and cartilages density (in younger patients the pelvic elements are more pliable - p<0.05). Stress distribution after each of the abovementioned pelvic osteotomy was assessed in 2- and 6-years old patients’ pelvic models; hinge points were evaluated. The new term "restriction point" was introduced, which means a place where restriction of acetabular deformity correction occurs. Pelvic ligaments attachment points were mainly these restriction points. Conclusions: it was found out that there are no purely reshaping and reorientation pelvic osteotomies as previously believed; the pelvic ring acts as a unit in carrying out the applied load. Biomechanical overload of triradiate cartilage during Salter osteotomy in 2-years old patient and in 2- and 6-years old patients during Pemberton osteotomy was revealed; overload of the posterior cortical layer in the greater sciatic notch in 2-years old patient during Dega osteotomy was revealed. Level of Evidence – Level IV, prognostic.

Keywords: developmental dysplasia of the hip, pelvic osteotomy, finite element analysis, hinge point, biomechanics

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Authors: Yubo Bi, Xiao Chen, Shouxiang Lu

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A kind of gas-fueled burner, named Burning Rate Emulator, was proposed for the purpose of the emulation of condensed fuel recently. The gaseous fuel can be pure combustible fuel gas or blends of gaseous fuel or inert gas. However, this concept was recently proposed without detailed study on the combustion characteristic of fuel blends. In this study, two kinds of common gaseous fuels were selected, propane and acetylene, to provide the combustion heat as well as a large amount of smoke, which widely exists in liquid and solid fuel burning process. A set of experiments were carried out using a gas-fueled burner with a diameter of 8 cm. The total volume flow rate of propane and acetylene was kept at 3 liters per minute. The volume fraction of propane varied from 0% to 100% at interval of 10%. It is found that the flame height increases with propane volume fraction, which may be caused by the increase of heat release rate, as the energy density of propane is larger than that of acetylene. The dimensionless flame height is correlated against dimensionless heat release rate, which shows a power function relationship. The radiation fraction of the flame does not show a monotonic relationship with propane volume fraction. With the increase of propane volume fraction from 0% to 100%, the value of radiation fraction increases first and reach a maximum value around 0.46 at a propane volume fraction of 10%, and then decreases continuously to a value of 0.25 at the propane volume fraction of 100%. The flame radiation is related to the soot in the flame. The trend of the radiation fraction reflects that there may be a synergistic effect of soot formation between propane and acetylene which can be guessed from the significantly high radiation fraction at a propane volume fraction of 10%. This work provides data for combustion of gaseous fuel blends pool fire and also give reference on the design of Burning Rate Emulator.

Keywords: Burning Rate Emulator, fuel blends pool fire, flame height, radiation fraction

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Authors: Kiatnarong Supapanmanee, Ekkarin Phongphinittana, Pongsak Nimdum

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Natural fibers are readily available raw materials that are widely used as composite materials. The most common problem facing many researchers with composites made from this fiber is the adhesion between the natural fiber contact surface and the matrix material. Part of the problem is due to the hydrophilic properties of natural fibers and the hydrophobic properties of the matrix material. Based on the aforementioned problems, this research selected bamboo fiber, which is a strong natural fiber in the research study. The first step was to study the effect of the mechanical properties of the pure bamboo strip by testing the tensile strength of different measurement lengths. The bamboo strip was modified surface with sodium hydroxide (NaOH) at 6wt% concentrations for different soaking periods. After surface modification, the physical and mechanical properties of the pure bamboo strip fibers were studied. The modified and unmodified bamboo strips were molded into a composite material using epoxy as a matrix to compare the mechanical properties and adhesion between the fiber surface and the material with tensile and bending tests. In addition, the results of these tests were compared with the finite element method (FEM). The results showed that the length of the bamboo strip affects the strength of the fibers, with shorter fibers causing higher tensile stress. Effects of surface modification of bamboo strip with NaOH, this chemical eliminates lignin and hemicellulose, resulting in the smaller dimension of the bamboo strip and increased density. From the pretreatment results above, it was found that the treated bamboo strip and composite material had better Ultimate tensile stress and Young's modulus. Moreover, that results in better adhesion between bamboo fiber and matrix material.

Keywords: bamboo fiber, bamboo strip, composite material, bamboo composite, pure bamboo, surface modification, mechanical properties of bamboo, bamboo finite element method

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Authors: Tris Kee

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This research investigates social sustainability factors in transitional housing projects and their impact on fostering healthy living environments that promote physical activity and social interaction for residents. Social sustainability is integral to individual health and well-being, as emphasized by Goal 11 of the 2030 Agenda for Sustainable Development, which highlights the importance of safe, affordable, and accessible transport systems, green spaces, and public spaces catering to vulnerable populations' needs. Communal spaces in urban environments are essential for fostering social sustainability, as they serve as settings for physical activities and social interactions among diverse socio-economic groups. Factors such as neighborhood social atmosphere, historical context, social disparity, and mobility can influence the relationship between existing and transitional communities. Mental health effects can be measured through housing segregation, mobility and accessibility, and housing tenure. A significant research gap exists in understanding the living environment of transitional housing in Hong Kong and the social sustainability factors affecting residents' mental and physical health. To address this gap, our study employs a mixed-methods approach combining survey questionnaires and interviews to gather both quantitative and qualitative data. This methodology will provide comprehensive insights into residents' experiences and perceptions. Our research's main contribution is identifying key social sustainability factors in transitional housing and their impact on residents' well-being, informing policy-making and the creation of inclusive, healthy living environments. By addressing this research gap, we aim to provide valuable insights for future housing projects, ultimately promoting the development of socially sustainable transitional communities.

Keywords: social sustainablity, affordable housing, transitional housing, high density housing

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Authors: Dafna Knani, Sarit S. Sivan

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Aggrecan, one of the main components of the intervertebral disc (IVD), belongs to the family of proteoglycans (PGs) that are composed of glycosaminoglycan (GAG) chains covalently attached to a core protein. Its primary function is to maintain tissue hydration and hence disc height under the high loads imposed by muscle activity and body weight. Significant PG loss is one of the first indications of disc degeneration. A possible solution to recover disc functions is by injecting a synthetic hydrogel into the joint cavity, hence mimicking the role of PGs. One of the hydrogels proposed is GAG-analogues, based on sulfate-containing polymers, which are responsible for hydration in disc tissue. In the present work, we used molecular dynamics (MD) to study the effect of the hydrogel crosslinking (type and degree) on the swelling behavior of the suggested GAG-analogue biomimetics by calculation of cohesive energy density (CED), solubility parameter, enthalpy of mixing (ΔEmix) and the interactions between the molecules at the pure form and as a mixture with water. The simulation results showed that hydrophobicity plays an important role in the swelling of the hydrogel, as indicated by the linear correlation observed between solubility parameter values of the copolymers and crosslinker weight ratio (w/w); this correlation was found useful in predicting the amount of PEGDA needed for the desirable hydration behavior of (CS)₄-peptide. Enthalpy of mixing calculations showed that all the GAG analogs, (CS)₄ and (CS)₄-peptide are water-soluble; radial distribution function analysis revealed that they form interactions with water molecules, which is important for the hydration process. To conclude, our simulation results, beyond supporting the experimental data, can be used as a useful predictive tool in the future development of biomaterials, such as disc replacement.

Keywords: molecular dynamics, proteoglycans, enthalpy of mixing, swelling

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Authors: Hong Beom Hur

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Politics in America is polarized. The best illustration of this is the 2016 presidential election result map. States with megacities like California, New York, Illinois, Virginia, and others are marked blue to signify the color of the Democratic party. States located in inland and south like Texas, Florida, Tennesse, Kansas and others are marked red to signify the color of the Republican party. Such a stark difference between two colors, red and blue, combined with geolocations of each state with their borderline remarks one central message; America is divided into two colors between urban Democrats and rural Republicans. This paper seeks to defy the visualization by pointing out its limitations and search for alternative ways to visualize the 2016 election result. One such limitation is that geolocations of each state and state borderlines limit the visualization of population density. As a result, the election result map does not convey the fact that Clinton won the popular vote and only accentuates the voting patterns of urban and rural states. The paper seeks whether an alternative narrative can be observed by factoring in the population number into the size of each state and manipulating the state borderline according to the normalization. Yet another alternative narrative may be reached by factoring the size of each state by the number of the electoral college of each state by voting and visualize the number. Other alternatives will be discussed but are not implemented in visualization. Such methods include dividing the land of America into about 120 million cubes each representing a voter or by the number of whole population 300 million cubes. By exploring these alternative methods to visualize the politics of the 2016 election map, the public may be able to question whether it is possible to be free from the narrative of the divide-conquer when interpreting the election map and to look at both parties as a story of the United States of America.

Keywords: 2016 U.S. presidential election, data visualization, population scale, geo-political

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Authors: Arkadiusz Zurek

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The potential of using drones is visible in many areas of logistics, especially in terms of their use for monitoring and control of many processes. The technologies implemented in the last decade concern new possibilities for companies that until now have not even considered them, such as warehouse inventories. Unmanned aerial vehicles are no longer seen as a revolutionary tool for Industry 4.0, but rather as tools in the daily work of factories and logistics operators. The research problem is to develop a method for measuring the weight of goods in a selected link of the clothing supply chain by drones. However, the purpose of this article is to analyze the causes of errors in traditional measurements, and then to identify adverse events related to the use of drones for the inventory of a heap of textiles intended for production purposes. On this basis, it will be possible to develop guidelines to eliminate the causes of these events in the measurement process using drones. In a real environment, work was carried out to determine the volume and weight of textiles, including, among others, weighing a textile sample to determine the average density of the assortment, establishing a local geodetic network, terrestrial laser scanning and photogrammetric raid using an unmanned aerial vehicle. As a result of the analysis of measurement data obtained in the facility, the volume and weight of the assortment and the accuracy of their determination were determined. In this article, this work presents how such heaps are currently being tested, what adverse events occur, indicate and describes the current use of photogrammetric techniques of this type of measurements so far performed by external drones for the inventory of wind farms or construction of the station and compare them with the measurement system of the aforementioned textile heap inside a large-format facility.

Keywords: drones, unmanned aerial system, UAS, indoor system, security, process automation, cost optimization, photogrammetry, risk elimination, industry 4.0

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Authors: Amanda Gregorim Fernandes, Lorena Cardoso Cintra, Rosalia Santos Amorim Jesuino, Fabricia Paula De Faria, Marcio José Poças Fonseca

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Bioethanol is one of the most promising biofuels and able to replace fossil fuels and reduce its different environmental impacts and can be generated from various agroindustrial waste. The Brazil is in first place in bioethanol production to be the largest producer of sugarcane. The bagasse sugarcane (SCB) has lignocellulose which is composed of three major components: cellulose, hemicellulose and lignin. Cellulose is a homopolymer of glucose units connected by glycosidic linkages. Among all species of Penicillium, Penicillium echinulatum has been the focus of attention because they produce high quantities of cellulase and the mutant strain 9A02S1 produces higher enzyme levels compared to the wild. Among the cellulases, the cellobiohydrolases enzymes are the main components of the cellulolytic system of fungi, and are also responsible for most of the potential hydrolytic in enzyme cocktails for the industrial processing of plant biomass and several cellobiohydrolases Penicillium had higher specific activity against cellulose compared to CBH I from Trichoderma reesei. This fact makes it an interesting pattern for higher yields in the enzymatic hydrolysis, and also they are important enzymes in the hydrolysis of crystalline regions of cellulose. Therefore, finding new and more active enzymes become necessary. Meanwhile, β-glycosidases act on soluble substrates and are highly dependent on cellobiohydrolases and endoglucanases action to provide the substrate in the hydrolysis of the biomass, but the cellobiohydrolases and endoglucanases are highly dependent β-glucosidases to maintain efficient hydrolysis. Thus, there is a need to understand the structure-function relationships that govern the catalytic activity of cellulolytic enzymes to elucidate its mechanism of action and optimize its potential as industrial biocatalysts. To evaluate the enzyme β-glucosidase of Penicillium echinulatum (PeBGL1) the gene was synthesized from the assembly sequence from a library in induction conditions and then the PeBGL1 gene was cloned in the vector pPICZαA and transformed into P. pastoris GS115. After processing, the producers of PeBGL1 were analyzed for enzyme activity and protein profile where a band of approximately 100 kDa was viewed. It was also carried out the zymogram. In partial characterization it was determined optimum temperature of 50°C and optimum pH of 6,5. In addition, to increase the secreted recombinant PeBGL1 production by Pichia pastoris, three parameters of P. pastoris culture medium were analysed: methanol, nitrogen source concentrations and the inoculum size. A 23 factorial design was effective in achieving the optimum condition. Altogether, these results point to the potential application of this P. echinulatum β-glucosidase in hydrolysis of cellulose for the production of bioethanol.

Keywords: bioethanol, biotechnology, beta-glucosidase, penicillium echinulatum

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Authors: Alexandru-Ion Marinescu

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There exist a plethora of methods in the scientific literature which tackle the well-established task of credit score evaluation. In its most abstract form, a credit scoring algorithm takes as input several credit applicant properties, such as age, marital status, employment status, loan duration, etc. and must output a binary response variable (i.e. “GOOD” or “BAD”) stating whether the client is susceptible to payment return delays. Data imbalance is a common occurrence among financial institution databases, with the majority being classified as “GOOD” clients (clients that respect the loan return calendar) alongside a small percentage of “BAD” clients. But it is the “BAD” clients we are interested in since accurately predicting their behavior is crucial in preventing unwanted loss for loan providers. We add to this whole context the constraint that the algorithm must yield an actual, tractable mathematical formula, which is friendlier towards financial analysts. To this end, we have turned to genetic algorithms and genetic programming, aiming to evolve actual mathematical expressions using specially tailored mutation and crossover operators. As far as data representation is concerned, we employ a very flexible mechanism – LINQ expression trees, readily available in the C# programming language, enabling us to construct executable pieces of code at runtime. As the title implies, they model trees, with intermediate nodes being operators (addition, subtraction, multiplication, division) or mathematical functions (sin, cos, abs, round, etc.) and leaf nodes storing either constants or variables. There is a one-to-one correspondence between the client properties and the formula variables. The mutation and crossover operators work on a flattened version of the tree, obtained via a pre-order traversal. A consequence of our chosen technique is that we can identify and discard client properties which do not take part in the final score evaluation, effectively acting as a dimensionality reduction scheme. We compare ourselves with state of the art approaches, such as support vector machines, Bayesian networks, and extreme learning machines, to name a few. The data sets we benchmark against amount to a total of 8, of which we mention the well-known Australian credit and German credit data sets, and the performance indicators are the following: percentage correctly classified, area under curve, partial Gini index, H-measure, Brier score and Kolmogorov-Smirnov statistic, respectively. Finally, we obtain encouraging results, which, although placing us in the lower half of the hierarchy, drive us to further refine the algorithm.

Keywords: expression trees, financial credit scoring, genetic algorithm, genetic programming, symbolic evolution

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Authors: Mylena McCoggle, Shyra Wilson, Andrea Rivera, Rocio Alba-Flores

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This work introduces the use of EMGs (electromyography) from muscle sensors to develop an Artificial Neural Network (ANN) for pattern recognition to control a small unmanned aerial vehicle. The objective of this endeavor exhibits interfacing drone applications beyond manual control directly. MyoWare Muscle sensor contains three EMG electrodes (dual and single type) used to collect signals from the posterior (extensor) and anterior (flexor) forearm and the bicep. Collection of raw voltages from each sensor were connected to an Arduino Uno and a data processing algorithm was developed with the purpose of interpreting the voltage signals given when performing flexing, resting, and motion of the arm. Each sensor collected eight values over a two-second period for the duration of one minute, per assessment. During each two-second interval, the movements were alternating between a resting reference class and an active motion class, resulting in controlling the motion of the drone with left and right movements. This paper further investigated adding up to three sensors to differentiate between hand gestures to control the principal motions of the drone (left, right, up, and land). The hand gestures chosen to execute these movements were: a resting position, a thumbs up, a hand swipe right motion, and a flexing position. The MATLAB software was utilized to collect, process, and analyze the signals from the sensors. The protocol (machine learning tool) was used to classify the hand gestures. To generate the input vector to the ANN, the mean, root means squared, and standard deviation was processed for every two-second interval of the hand gestures. The neuromuscular information was then trained using an artificial neural network with one hidden layer of 10 neurons to categorize the four targets, one for each hand gesture. Once the machine learning training was completed, the resulting network interpreted the processed inputs and returned the probabilities of each class. Based on the resultant probability of the application process, once an output was greater or equal to 80% of matching a specific target class, the drone would perform the motion expected. Afterward, each movement was sent from the computer to the drone through a Wi-Fi network connection. These procedures have been successfully tested and integrated into trial flights, where the drone has responded successfully in real-time to predefined command inputs with the machine learning algorithm through the MyoWare sensor interface. The full paper will describe in detail the database of the hand gestures, the details of the ANN architecture, and confusion matrices results.

Keywords: artificial neural network, biosensors, electromyography, machine learning, MyoWare muscle sensors, Arduino

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Authors: Jerzy Smardzewski

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Structures with negative Poisson's ratios are called auxetic. They are characterized by better mechanical properties than conventional structures, especially shear strength, the ability to better absorb energy and increase strength during bending, especially in sandwich panels. Commonly used paper cores of cellular boards are made of hexagonal cells. With isotropic facings, these cells provide isotropic properties of the entire furniture board. Shelves made of such panels with a thickness similar to standard chipboards do not provide adequate stiffness and strength of the furniture. However, it is possible to transform the shape of hexagonal cells into polyhedral auxetic cells that improve the mechanical properties of the core. The work aimed to transform the hexagonal cells of the paper core into auxetic cells and determine their basic mechanical properties. Using numerical methods, it was decided to design the most favorable proportions of cells distinguished by the lowest Poisson's ratio and the highest modulus of linear elasticity. Standard cores for cellular boards commonly used to produce 34 mm thick furniture boards were used for the tests. Poisson's ratios, bending strength, and linear elasticity moduli were determined for such cores and boards. Then, the cells were transformed into auxetic structures, and analogous cellular boards were made for which mechanical properties were determined. The results of numerical simulations for which the variable parameters were the dimensions of the cell walls, wall inclination angles, and relative cell density were presented in the further part of the paper. Experimental tests and numerical simulations showed the beneficial effect of auxeticization on the mechanical quality of furniture panels. They allowed for the selection of the optimal shape of auxetic core cells.

Keywords: auxetics, honeycomb, panels, simulation, experiment

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Authors: Donald Wright

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The ultimate goal of this study is to reinvigorate the philosophical underpinnings the study of urbanization with scientific data with the goal of circumventing what seems an inevitable future clash between rural and urban populations. To that end urban infrastructure must be sustainable economically, politically and ecologically over the course of several generations as cities continue to grow with the incorporation of climate refugees. Our research will provide data concerning the projected increase in population over the coming two decades in Morocco, and the population will shift from rural areas to urban centers during that period of time. As a result, urban infrastructure will need to be adapted, developed or built to fit the demand of future internal migrations from rural to urban centers in Morocco. This paper will also examine how past experiences of internally displaced people give insight into the challenges faced by future migrants and, beyond the gathering of data, how people react to internal migration. This study employs four different sets of research tools. First, a large part of this study is archival, which involves compiling the relevant literature on the topic and its complex history. This step also includes gathering data bout migrations in Morocco from public data sources. Once the datasets are collected, the next part of the project involves populating the attribute fields and preprocessing the data to make it understandable and usable by machine learning algorithms. In tandem with the mathematical interpretation of data and projected migrations, this study benefits from a theoretical understanding of the critical apparatus existing around urban development of the 20th and 21st centuries that give us insight into past infrastructure development and the rationale behind it. Once the data is ready to be analyzed, different machine learning algorithms will be experimented (k-clustering, support vector regression, random forest analysis) and the results compared for visualization of the data. The final computational part of this study involves analyzing the data and determining what we can learn from it. This paper helps us to understand future trends of population movements within and between regions of North Africa, which will have an impact on various sectors such as urban development, food distribution and water purification, not to mention the creation of public policy in the countries of this region. One of the strengths of this project is the multi-pronged and cross-disciplinary methodology to the research question, which enables an interchange of knowledge and experiences to facilitate innovative solutions to this complex problem. Multiple and diverse intersecting viewpoints allow an exchange of methodological models that provide fresh and informed interpretations of otherwise objective data.

Keywords: climate change, machine learning, migration, Morocco, urban development

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Authors: Samson Mil'shtein, Dhawal Asthana, Benjamin Sullivan

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The wide energy gap of GaN is the major parameter justifying the design and fabrication of high-power electronic components made of this material. However, the existence of a piezo-electrics in nature sheet charge at the AlGaN/GaN interface complicates the control of carrier injection into the intrinsic channel of GaN HEMTs (High Electron Mobility Transistors). As a result, most of the transistors created as R&D prototypes and all of the designs used for mass production are D-mode devices which introduce challenges in the design of integrated circuits. This research presents the design and modeling of an E-mode GaN HEMT with a very low turn-on voltage. The proposed device includes two critical elements allowing the transistor to achieve zero conductance across the channel when Vg = 0V. This is accomplished through the inclusion of an extremely thin, 2.5nm intrinsic Ga₀.₇₄Al₀.₂₆N spacer layer. The added spacer layer does not create piezoelectric strain but rather elastically follows the variations of the crystal structure of the adjacent GaN channel. The second important factor is the design of a gate metal with a high work function. The use of a metal gate with a work function (Ni in this research) greater than 5.3eV positioned on top of n-type doped (Nd=10¹⁷cm⁻³) Ga₀.₇₄Al₀.₂₆N creates the necessary built-in potential, which controls the injection of electrons into the intrinsic channel as the gate voltage is increased. The 5µm long transistor with a 0.18µm long gate and a channel width of 30µm operate at Vd=10V. At Vg =1V, the device reaches the maximum drain current of 0.6mA, which indicates a high current density. The presented device is operational at frequencies greater than 10GHz and exhibits a stable transconductance over the full range of operational gate voltages.

Keywords: compound semiconductors, device modeling, enhancement mode HEMT, gallium nitride

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Authors: Anna V. Zaporozhchenko, Dmytro Kutnyakhov, Katherina Medjanik, Christian Tusche, Hans-Joachim Elmers, Olena Fedchenko, Sergey Chernov, Martin Ellguth, Sergej A. Nepijko, Gerd Schoenhense

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Graphene reveals a unique electronic structure that predetermines many intriguing properties such as massless charge carriers, optical transparency and high velocity of fermions at the Fermi level, opening a wide horizon of future applications. Hence, a detailed investigation of the electronic structure of graphene is crucial. The method of choice is angular resolved photoelectron spectroscopy ARPES. Here we present experiments using time-of-flight (ToF) momentum microscopy, being an alternative way of ARPES using full-field imaging of the whole Brillouin zone (BZ) and simultaneous acquisition of up to several 100 energy slices. Unlike conventional ARPES, k-microscopy is not limited in simultaneous k-space access. We have recorded the whole first BZ of graphene on Ir(111) including all six Dirac cones. As excitation source we used synchrotron radiation from BESSY II (Berlin) at the U125-2 NIM, providing linearly polarized (both polarizations p- and s-) VUV radiation. The instrument uses a delay-line detector for single-particle detection up the 5 Mcps range and parallel energy detection via ToF recording. In this way, we gather a 3D data stack I(E,kx,ky) of the full valence electronic structure in approx. 20 mins. Band dispersion stacks were measured in the energy range of 14 eV up to 23 eV with steps of 1 eV. The linearly-dispersing graphene bands for all six K and K’ points were simultaneously recorded. We find clear features of hybridization with the substrate, in particular in the linear dichroism in the angular distribution (LDAD). Recording of the whole Brillouin zone of graphene/Ir(111) revealed new features. First, the intensity differences (i.e. the LDAD) are very sensitive to the interaction of graphene bands with substrate bands. Second, the dark corridors are investigated in detail for both, p- and s- polarized radiation. They appear as local distortions of photoelectron current distribution and are induced by quantum mechanical interference of graphene sublattices. The dark corridors are located in different areas of the 6 Dirac cones and show chirality behaviour with a mirror plane along vertical axis. Moreover, two out of six show an oval shape while the rest are more circular. It clearly indicates orientation dependence with respect to E vector of incident light. Third, a pattern of faint but very sharp lines is visible at energies around 22eV that strongly remind on Kikuchi lines in diffraction. In conclusion, the simultaneous study of all six Dirac cones is crucial for a complete understanding of dichroism phenomena and the dark corridor.

Keywords: band structure, graphene, momentum microscopy, LDAD

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Authors: Alireza Vahid, Santu Rana, Sunil Gupta, Pratibha Vellanki, Svetha Venkatesh, Thomas Dorin

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Aluminum is the preferred material for lightweight applications and its alloys are constantly improving. The high strength 7xxx alloys have been extensively used for structural components in aerospace and automobile industries for the past 50 years. In the next decade, a great number of airplanes will be retired, providing an obvious source of valuable used metals and great demand for cost-effective methods to re-use these alloys. The design of proper aerospace alloys is primarily based on optimizing strength and ductility, both of which can be improved by controlling the additional alloying elements as well as heat treatment conditions. In this project, we explore the design of high-performance alloys with 7xxx as a base material. These designed alloys have to be optimized and improved to compare with modern 7xxx-series alloys and to remain competitive for aircraft manufacturing. Aerospace alloys are extremely complex with multiple alloying elements and numerous processing steps making optimization often intensive and costly. In the present study, we used Bayesian optimization algorithm, a well-known adaptive design strategy, to optimize this multi-variable system. An Al alloy was proposed and the relevant heat treatment schedules were optimized, using the tensile yield strength as the output to maximize. The designed alloy has a maximum yield strength and ultimate tensile strength of more than 730 and 760 MPa, respectively, and is thus comparable to the modern high strength 7xxx-series alloys. The microstructure of this alloy is characterized by electron microscopy, indicating that the increased strength of the alloy is due to the presence of a high number density of refined precipitates.

Keywords: aluminum alloys, Bayesian optimization, heat treatment, tensile properties

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Authors: Awad Khireldin, Colin Law

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Runways are the major infrastructure of airports around the world. Efficient operations of runways are key to ensure that airports are running smoothly with minimal delays. There are many factors that affect the efficiency of runway operations, such as the aircraft wake separation, runways system configuration, the fleet mix, and the runways separation distance. This paper aims to address how to maximize runway operations using a Discrete Event Simulation model. A case study of Cairo International Airport (CIA) is developed to maximize the utilizing of three parallel runways using a simulation model. Different scenarios have been designed where every runway could be assigned for arrival, departure, or mixed operations. A benchmarking study was also included to compare the actual to the proposed results to spot the potential improvements. The simulation model shows that there is a significant difference in utilization and delays between the actual and the proposed ones, there are several recommendations that can be provided to airport management, in the short and long term, to increase the efficiency and to reduce the delays. By including the recommendation with different operations scenarios, such as upgrading the airport slot Coordination from Level 1 to Level 2 in the short term. In the long run, discuss the possibilities to increase the International Air Transport association (IATA) slot coordination to Level 3 as more flights are expected to be handled by the airport. Technological advancements such as radar in the approach full airside simulation model could improve the airport performance where the airport is recommended to review the standard operations procedures with the appropriate authorities. Also, the airport can adopt a future operational plan to accommodate the forecasted additional traffic density in case of adding a fourth terminal building to increase the airport capacity.

Keywords: airport performance, runway, discrete event simulation, capacity, airside

Procedia PDF Downloads 131

Authors: Jingcheng Ma, Patricia B. Weisensee, Young H. Shin, Yujin Chang, Junjiao Tian, William P. King, Nenad Miljkovic

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Water droplet impact on surfaces is a ubiquitous phenomenon in both nature and industry. The transfer of mass, momentum and energy can be influenced by the time of contact between droplet and surface. In order to reduce the contact time, we study the influence of substrate motion prior to impact on the dynamics of droplet recoil. Using optical high speed imaging, we investigated the impact dynamics of macroscopic water droplets (~ 2mm) on rigid nanostructured superhydrophobic surfaces vibrating at 60 – 300 Hz and amplitudes of 0 – 3 mm. In addition, we studied the influence of the phase of the substrate at the moment of impact on total contact time. We demonstrate that substrate vibration can alter droplet dynamics, and decrease total contact time by as much as 50% compared to impact on stationary rigid superhydrophobic surfaces. Impact analysis revealed that the vibration frequency mainly affected the maximum contact time, while the amplitude of vibration had little direct effect on the contact time. Through mathematical modeling, we show that the oscillation amplitude influences the possibility density function of droplet impact at a given phase, and thus indirectly influences the average contact time. We also observed more vigorous droplet splashing and breakup during impact at larger amplitudes. Through semi-empirical mathematical modeling, we describe the relationship between contact time and vibration frequency, phase, and amplitude of the substrate. We also show that the maximum acceleration during the impact process is better suited as a threshold parameter for the onset of splashing than a Weber-number criterion. This study not only provides new insights into droplet impact physics on vibrating surfaces, but develops guidelines for the rational design of surfaces to achieve controllable droplet wetting in applications utilizing vibration.

Keywords: contact time, impact dynamics, oscillation, pear-shape droplet

Procedia PDF Downloads 454

Authors: Donatella Giuliani

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In this research, we propose an unsupervised grayscale image segmentation method based on a combination of the Firefly Algorithm and the Gaussian Mixture Model. Firstly, the Firefly Algorithm has been applied in a histogram-based research of cluster means. The Firefly Algorithm is a stochastic global optimization technique, centered on the flashing characteristics of fireflies. In this context it has been performed to determine the number of clusters and the related cluster means in a histogram-based segmentation approach. Successively these means are used in the initialization step for the parameter estimation of a Gaussian Mixture Model. The parametric probability density function of a Gaussian Mixture Model is represented as a weighted sum of Gaussian component densities, whose parameters are evaluated applying the iterative Expectation-Maximization technique. The coefficients of the linear super-position of Gaussians can be thought as prior probabilities of each component. Applying the Bayes rule, the posterior probabilities of the grayscale intensities have been evaluated, therefore their maxima are used to assign each pixel to the clusters, according to their gray-level values. The proposed approach appears fairly solid and reliable when applied even to complex grayscale images. The validation has been performed by using different standard measures, more precisely: the Root Mean Square Error (RMSE), the Structural Content (SC), the Normalized Correlation Coefficient (NK) and the Davies-Bouldin (DB) index. The achieved results have strongly confirmed the robustness of this gray scale segmentation method based on a metaheuristic algorithm. Another noteworthy advantage of this methodology is due to the use of maxima of responsibilities for the pixel assignment that implies a consistent reduction of the computational costs.

Keywords: clustering images, firefly algorithm, Gaussian mixture model, meta heuristic algorithm, image segmentation

Procedia PDF Downloads 217

Authors: Piyachat Chuysinuan, Nitirat Chimnoi, Arthit Makarasen, Nanthawan Reuk-Ngam, Pitt Supaphol, Supanna Techasakul

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In this work, biomaterial wound dressings was developed based on gelatin containing herbal substances (essential oil), a substance from the plant Eupatorium adenophorum Spreng (Crofton weed) that used as traditional wound healers. Gelatin hydrogel was prepared from a 10 wt-% gelatin solution. The oil in water (o/w) emulsion Eupatorium adenophorum of essential oil were prepared and used Pluronic F68 as a surfactant. The 10, 20, and 30 % v/v emulsion were mixed with gelatin solution and cast into film. These hydrogels were tested for their gel fraction, swelling and weight loss behavior. With an increase in the emulsion concentration the emulsion-loaded in hydrogels, the gel fraction were decreased due to the crosslink density, while the swelling and weight loss behavior were increased with an increasing in the emulsion content. The potential to use the emulsion-containing gelatin hydrogels as wound dressing was assessed on investigation the release characteristics of the as-loaded hydrogels. The E. adenophorum essential oil was first identified the chemical composition by using GC-MS analysis. The principal components of the oil were p-cymene (16.23%), bornyl acetate (11.84%), and amorpha-4, 7(11)-diene (10.51%). The hydrogel wound dressing containing essential oil was then characterized for their antibacterial activity against Gram-positive and Gram-negative in order to elucidate their potential for use as antibacterial wound dressings by using agar disk diffusion methods. The result showed that E. adenophorum essential oil and the emulsion-loaded gelatin hydrogel inhibited the growth of the test pathogens, Staphylococcus aureus and Staphylococcus epidermidis and increased with increasing the initial amount of essential oil in the hydrogels which confirmed their application as antibacterial wound dressings. Furthermore, the potential use of these wound dressings was further assessed in terms of the indirect cytotoxicity, in vitro attachment and proliferation of dermal human fibroblasts cultured in the hydrogel wound dressings.

Keywords: hydrogel, antibacterial wound dressing, Eupatorium adenophorum essential oil, gelatin

Procedia PDF Downloads 356

Authors: Nataliya Apanovich, Mark Wright

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Uganda is among the poorest but fastest growing populations in the world. Its annual population growth of 3% puts additional stress through land fragmentation, agricultural intensification, and deforestation on already highly weathered tropical (Ferralsol) soils. All of these factors lead to decreased agricultural yields and consequently diminished food security. The central region of Uganda, Buganda Kingdom, is especially vulnerable in terms of food security as its high population density coupled with mismanagement of natural resources led to gradual loss of its soil and even changes in microclimate. These changes are negatively affecting livelihoods of smallholder farmers who comprise 80% of all population in Uganda. This research focuses on biochar for soil remediation in Masaka District, Uganda. If produced on a small scale from locally sourced materials, biochar can increase the quality of soil in a cost and time effective manner. To assess biochar potential, 151 smallholder farmers were interviewed on the types of crops grown, agricultural residues produced and their use, as well as on attitudes towards biochar use and its production on a small scale. The interviews were conducted in 7 sub-counties, 32 parishes, and 92 villages. The total farmland covered by the study was 606.2 kilometers. Additional information on the state of agricultural development and environmental degradation in the district was solicited from four local government officials via informal interviews. This project has been conducted in collaboration with the international agricultural research institution, Makerere University in Kampala, Uganda. The results of this research can have implications on the way farmers perceive the value of their agricultural residues and what they decide to do with them. The underlying objective is to help smallholders in degraded soils increase their agricultural yields through the use of biochar without diverting the already established uses of agricultural residues to a new soil management practice.

Keywords: agricultural residues, biochar, central Uganda, food security, soil erosion, soil remediation

Procedia PDF Downloads 284

Authors: Hao Yang, Lei Chen, Ting Mei, Jianbang Zheng

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Currently, the uncooled PbSe photodetectors in the mid-infrared range (2-5μm) with sensitization technology extract more photoelectric response than traditional ones, and enable the room temperature (300K) photo-detection with high detectivity, which have attracted wide attentions in many fields. This technology generally contains the film fabrication with vapor phase deposition (VPD) and a sensitizing process with doping of oxygen and iodine. Many works presented in the recent years almost provide and high temperature activation method with oxygen/iodine vapor diffusion, which reveals that oxygen or iodine plays an important role in the sensitization of PbSe material. In this paper, we provide our latest experimental results and discussions in the stoichiometry of oxygen and iodine and its influence on the polycrystalline structure and photo-response. The experimental results revealed that crystal orientation was transformed from (200) to (420) by sensitization, and the responsivity of 5.42 A/W was gained by the optimal stoichiometry of oxygen and iodine with molecular density of I2 of ~1.51×1012 mm-3 and oxygen pressure of ~1Mpa. We verified that I2 plays a role in transporting oxygen into the lattice of crystal, which is actually not its major role. It is revealed that samples sensitized with iodine transform atomic proportion of Pb from 34.5% to 25.0% compared with samples without iodine from XPS data, which result in the proportion of about 1:1 between Pb and Se atoms by sublimation of PbI2 during sensitization process, and Pb/Se atomic proportion is controlled by I/O atomic proportion in the polycrystalline grains, which is very an important factor for improving responsivity of uncooled PbSe photodetector. Moreover, a novel sensitization and dopant activation method is proposed using oxygen ion implantation with low ion energy of < 500eV and beam current of ~120μA/cm2. These results may be helpful to understanding the sensitization mechanism of polycrystalline lead salt materials.

Keywords: polycrystalline PbSe, sensitization, transport, stoichiometry

Procedia PDF Downloads 349

Authors: Quin Emparan, Razif Harun, Dayang R. A. Biak, Rozita Omar, Michael K. Danquah

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Cultivation of immobilized microalgae cells is on the rise for biotechnological applications. In this study, cultivation of Chlorella vulgaris was carried out in the form of suspended free-cell and immobilized cells system. NaCS-PDMDAAC capsules were used to immobilize C. vulgaris. Initially, the synthesized NaCS with C. vulgaris culture were prepared at various concentration of 5- 20% (w/v) using a 6% hardening solution (PDMDAAC) to investigate the capsules' gel stability and suitability for microalgae cells growth. Then, the capsules produced from 15% NaCS with C. vulgaris culture were furthered investigated using 5%, 10%, and 15% (w/v) of PDMDAAC solution. The capsules' gel stability was evaluated through dissolution time and loss of uniform spherical shape of capsules, while suitability for microalgae cells growth was evaluated through the optical density of microalgae. In this study, the 15% NaCS-10% PDMDAAC capsules were found to be the most suitable to sustain the capsules' gel stability and microalgae cells growth in MLA. For that reason, the C. vulgaris immobilized in the 15% NaCS-10% PDMDAAC capsules were further characterized using physicochemical analysis in terms of morphological, carbon (C), hydrogen (H) and nitrogen (N), Fourier transform-infrared (FT-IR), scanning electron microscopy-energy dispersive X-ray (SEM-EDX), zeta potential and Brunauer-Emmet-Teller (BET) analyses. The results revealed that the presence of sulfonates in the synthesized NaCS and NaCS-PDMDAAC capsules without and with C. vulgaris proves that cellulose alcohol group was successfully bonded by sulfo group. Besides that, immobilized microalgae cells have a smaller cell size of 6.29 ± 1.09 µm and zeta potential of -11.93 ± 0.91 mV than suspended free-cells microalgae culture. It can be summarized that immobilization of C. vulgaris in the 15% NaCS-10% PDMDAAC capsules are relevant as a bioremediator for wastewater treatment purposes due to its suitable size of pore and capsules as well as structural and compositional properties.

Keywords: biological capsules, immobilized cultivation, microalgae, physico-chemical analysis

Procedia PDF Downloads 172

Authors: Jaypalsinh Parmar, Pintu Nakrani, Bhaumik Shah

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Digital Elevation Model (DEM) is elevation data of the virtual grid on the ground. DEM can be used in application in GIS such as hydrological modelling, flood forecasting, morphometrical analysis and surveying etc.. For morphometrical analysis the stream flow network plays a very important role. DEM lacks accuracy and cannot match field data as it should for accurate results of morphometrical analysis. The present study focuses on comparing the Agree method and the conventional Shortest path method for finding out morphometric parameters in the flat region of the Lower Tapi Basin which is located in the western India. For the present study, open source SRTM (Shuttle Radar Topography Mission with 1 arc resolution) and toposheets issued by Survey of India (SOI) were used to determine the morphometric linear aspect such as stream order, number of stream, stream length, bifurcation ratio, mean stream length, mean bifurcation ratio, stream length ratio, length of overland flow, constant of channel maintenance and aerial aspect such as drainage density, stream frequency, drainage texture, form factor, circularity ratio, elongation ratio, shape factor and relief aspect such as relief ratio, gradient ratio and basin relief for 53 catchments of Lower Tapi Basin. Stream network was digitized from the available toposheets. Agree DEM was created by using the SRTM and stream network from the toposheets. The results obtained were used to demonstrate a comparison between the two methods in the flat areas.

Keywords: agree method, morphometric analysis, lower Tapi basin, shortest path method

Procedia PDF Downloads 239

Authors: Eric Muñoz de la Torre, Julián González Trinidad, Efrén González Ramírez

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Rain varies greatly in its duration, intensity, and spatial coverage, it is important to have sub-daily rainfall data for various applications, including risk prevention. However, the ground measurements are limited by the low and irregular density of rain gauges. An alternative to this problem are the Satellite Precipitation Products (SPPs) that use passive microwave and infrared sensors to estimate rainfall, as IMERG, however, these SPPs have to be validated before their application. The aim of this study is to evaluate the performance of the IMERG: Integrated Multi-satellitE Retrievals for Global Precipitation Measurament final run V06B SPP in a semi-arid region of Mexico, using 4 automatic rain gauges (pluviographs) sub-daily data of October 2019 and June to September 2021, using the Minimum inter-event Time (MIT) criterion to separate unique rain events with a dry period of 10 hrs. for the purpose of evaluating the rainfall properties (depth, duration and intensity). Point to pixel analysis, continuous, categorical, and volumetric statistical metrics were used. Results show that IMERG is capable to estimate the rainfall depth with a slight overestimation but is unable to identify the real duration and intensity of the rain events, showing large overestimations and underestimations, respectively. The study zone presented 80 to 85 % of convective rain events, the rest were stratiform rain events, classified by the depth magnitude variation of IMERG pixels and pluviographs. IMERG showed poorer performance at detecting the first ones but had a good performance at estimating stratiform rain events that are originated by Cold Fronts.

Keywords: IMERG, rainfall, rain gauge, remote sensing, statistical evaluation

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Authors: Darwin Castillo Huamaní, Francisco A. M. Gomes

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The aim of the multi-material topology optimization (MTO) is to obtain the optimal topology of structures composed by many materials, according to a given set of constraints and cost criteria. In this work, we seek the optimal distribution of materials in a domain, such that the flexibility of the structure is minimized, under certain boundary conditions and the intervention of external forces. In the case we have only one material, each point of the discretized domain is represented by two values from a function, where the value of the function is 1 if the element belongs to the structure or 0 if the element is empty. A common way to avoid the high computational cost of solving integer variable optimization problems is to adopt the Solid Isotropic Material with Penalization (SIMP) method. This method relies on the continuous interpolation function, power function, where the base variable represents a pseudo density at each point of domain. For proper exponent values, the SIMP method reduces intermediate densities, since values other than 0 or 1 usually does not have a physical meaning for the problem. Several extension of the SIMP method were proposed for the multi-material case. The one that we explore here is the ordered SIMP method, that has the advantage of not being based on the addition of variables to represent material selection, so the computational cost is independent of the number of materials considered. Although the number of variables is not increased by this algorithm, the optimization subproblems that are generated at each iteration cannot be solved by methods that rely on second derivatives, due to the cost of calculating the second derivatives. To overcome this, we apply a globally convergent version of the sequential linear programming method, which solves a linear approximation sequence of optimization problems.

Keywords: globally convergence, multi-material design ordered simp, sequential linear programming, topology optimization

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Authors: Ella Sèdé Maforikan

Abstract:

Sustained water management requires quantitative information and the knowledge of spatiotemporal dynamics of hydrological system within the basin. This can be achieved through the research. Several studies have investigated both surface water and groundwater in Beterou catchment. However, there are few published papers on the application of the SWAT modeling in Beterou catchment. The objective of this study was to evaluate the performance of SWAT to simulate the water balance within the watershed. The inputs data consist of digital elevation model, land use maps, soil map, climatic data and discharge records. The model was calibrated and validated using the Sequential Uncertainty Fitting (SUFI2) approach. The calibrated started from 1989 to 2006 with four years warming up period (1985-1988); and validation was from 2007 to 2020. The goodness of the model was assessed using five indices, i.e., Nash–Sutcliffe efficiency (NSE), the ratio of the root means square error to the standard deviation of measured data (RSR), percent bias (PBIAS), the coefficient of determination (R²), and Kling Gupta efficiency (KGE). Results showed that SWAT model successfully simulated river flow in Beterou catchment with NSE = 0.79, R2 = 0.80 and KGE= 0.83 for the calibration process against validation process that provides NSE = 0.78, R2 = 0.78 and KGE= 0.85 using site-based streamflow data. The relative error (PBIAS) ranges from -12.2% to 3.1%. The parameters runoff curve number (CN2), Moist Bulk Density (SOL_BD), Base Flow Alpha Factor (ALPHA_BF), and the available water capacity of the soil layer (SOL_AWC) were the most sensitive parameter. The study provides further research with uncertainty analysis and recommendations for model improvement and provision of an efficient means to improve rainfall and discharges measurement data.

Keywords: watershed, water balance, SWAT modeling, Beterou

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Authors: Charles Chijioke Dike, Hugh Clifford Chima Maduka, Chinwe A. Isibor

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Fish is among the products consumed at a very high rate. In most countries of the world, fish are used as part of the daily meal. The high cost of commercial fish feeds in Africa has made it necessary the development of an alternative source of fish feed processing from organic waste. The objective of this research is to investigate the efficacy of fish feeds processed from various animal wastes in order to know whether those feeds shall be alternatives to commercial feeds. This work shall be carried out at the Research Laboratory Unit of the Department of Human Biochemistry, Faculty of Basic Medical Sciences, College of Health Sciences, Nnamdi Azikiwe University (NAU), Nnewi Campus, Anambra State. The fingerlings to be used shall be gotten from the Agricultural Department of NAU, Awka, Anambra State, and allowed to acclimatize for 14 d. Animal and food wastes shall be gotten from Nnewi. The fish shall be grouped into 1-13 (Chicken manure only, cow dung only, pig manure only, chicken manure + yeast, cow dung + yeast, pig manure + yeast, chicken manure + other wastes + yeast, cow dung + other wastes + yeast, and pig manure + other wastes + yeast. Feed assessment shall be carried out by determining bulk density, feed water absorption, feed hardness, feed oil absorption, and feed water stability. The nutritional analysis shall be carried out on the feeds processed. The risk assessment shall be done on the fish by determining methylmercury (MeHg), polycyclic aromatic hydrocarbons (PAHs), and dichloro-diphenyl-trichloroethane (DDT) in the fish. The results from this study shall be analyzed statistically using SPSS statistical software, version 25. The hypothesis is that fish feeds processed from animal wastes are efficient in raising catfish. The outcome of this study shall provide the basis for the formulation of fish feeds from organic wastes.

Keywords: assessment, feeds, health risk, wastes

Procedia PDF Downloads 104