Search results for: mode prediction

Authors: Amir Nazemi, Milad Ramezankhani, Marian Kӧrber, Abbas S. Milani

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The excellent strength to weight ratio of woven fabric composites, along with their high formability, is one of the primary design parameters defining their increased use in modern manufacturing processes, including those in aerospace and automotive. However, for emerging automated preform processes under the smart manufacturing paradigm, complex geometries of finished components continue to bring several challenges to the designers to cope with manufacturing defects on site. Wrinklinge. g. is a common defectoccurring during the forming process and handling of semi-finished textile composites. One of the main reasons for this defect is the weak bending stiffness of fibers in unconsolidated state, causing excessive relative motion between them. Further challenges are represented by the automated handling of large-area fiber blanks with specialized gripper systems. For fabric composites forming simulations, the finite element (FE)method is a longstanding tool usedfor prediction and mitigation of manufacturing defects. Such simulations are predominately meant, not only to predict the onset, growth, and shape of wrinkles but also to determine the best processing condition that can yield optimized positioning of the fibers upon forming (or robot handling in the automated processes case). However, the need for use of small-time steps via explicit FE codes, facing numerical instabilities, as well as large computational time, are among notable drawbacks of the current FEtools, hindering their extensive use as fast and yet efficient digital twins in industry. This paper presents a novel woven fabric simulation technique through the application of the material point method (MPM), which enables the use of much larger time steps, facing less numerical instabilities, hence the ability to run significantly faster and efficient simulationsfor fabric materials handling and forming processes. Therefore, this method has the ability to enhance the development of automated fiber handling and preform processes by calculating the physical interactions with the MPM fiber models and rigid tool components. This enables the designers to virtually develop, test, and optimize their processes based on either algorithmicor Machine Learning applications. As a preliminary case study, forming of a hemispherical plain weave is shown, and the results are compared to theFE simulations, as well as experiments.

Keywords: material point method, woven fabric composites, forming, material handling

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Authors: Saahith M. S., Sivakami R.

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In the realm of football analytics, particularly focusing on predicting football player performance, the ability to forecast player success accurately is of paramount importance for teams, managers, and fans. This study introduces an elaborate examination of predicting football player performance through the integration of data visualization methods and machine learning algorithms. The research entails the compilation of an extensive dataset comprising player attributes, conducting data preprocessing, feature selection, model selection, and model training to construct predictive models. The analysis within this study will involve delving into feature significance using methodologies like Select Best and Recursive Feature Elimination (RFE) to pinpoint pertinent attributes for predicting player performance. Various machine learning algorithms, including Random Forest, Decision Tree, Linear Regression, Support Vector Regression (SVR), and Artificial Neural Networks (ANN), will be explored to develop predictive models. The evaluation of each model's performance utilizing metrics such as Mean Squared Error (MSE) and R-squared will be executed to gauge their efficacy in predicting player performance. Furthermore, this investigation will encompass a top player analysis to recognize the top-performing players based on the anticipated overall performance scores. Nationality analysis will entail scrutinizing the player distribution based on nationality and investigating potential correlations between nationality and player performance. Positional analysis will concentrate on examining the player distribution across various positions and assessing the average performance of players in each position. Age analysis will evaluate the influence of age on player performance and identify any discernible trends or patterns associated with player age groups. The primary objective is to predict a football player's overall performance accurately based on their individual attributes, leveraging data-driven insights to enrich the comprehension of player success on the field. By amalgamating data visualization and machine learning methodologies, the aim is to furnish valuable tools for teams, managers, and fans to effectively analyze and forecast player performance. This research contributes to the progression of sports analytics by showcasing the potential of machine learning in predicting football player performance and offering actionable insights for diverse stakeholders in the football industry.

Keywords: football analytics, player performance prediction, data visualization, machine learning algorithms, random forest, decision tree, linear regression, support vector regression, artificial neural networks, model evaluation, top player analysis, nationality analysis, positional analysis

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Authors: William Creighton, Jan Smitheram

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Queer discourse has been tied to a middle-class, urban-centric, white approach to the discussion of queerness. In doing so, the multilayeredness of queer existence has been washed away in favour of palatable queer occupation. This paper uses design to explore a queer anti-urbanist approach to facilitate a more egalitarian architectural occupancy. Scott Herring’s work on queer anti-urbanism is key to this approach. Herring redeploys anti-urbanism from its historical understanding of open hostility, rejection and desire to destroy the city towards a mode of queer critique that counters normative ideals of homonormative metronormative gay lifestyles. He questions how queer identity has been closed down into a more diminutive frame where those who do not fit within this frame are subjected to persecution or silenced through their absence. We extend these ideas through design to ask how a queer anti-urbanist approach facilitates a more egalitarian architectural occupancy. Following a “design as research” methodology, the design outputs allow a vehicle to ask how we might live, otherwise, in architectural space. A design as research methodologically is a process of questioning, designing and reflecting – in a non-linear, iterative approach – establishes itself through three projects, each increasing in scale and complexity. Each of the three scales tackled a different body relationship. The project began exploring the relations between body to body, body to known others, and body to unknown others. Moving through increasing scales was not to privilege the objective, the public and the large scale; instead, ‘intra-scaling’ acts as a tool to re-think how scale reproduces normative ideas of the identity of space. There was a queering of scale. Through this approach, the results were an installation that brings two people together to co-author space where the installation distorts the sensory experience and forces a more intimate and interconnected experience challenging our socialized proxemics: knees might touch. To queer the home, the installation was used as a drawing device, a tool to study and challenge spatial perception, drawing convention, and as a way to process practical information about the site and existing house – the device became a tool to embrace the spontaneous. The final design proposal operates as a multi-scalar boundary-crossing through “private” and “public” to support kinship through communal labour, queer relationality and mooring. The resulting design works to set adrift bodies in a sea of sensations through a mix of pleasure programmes. To conclude, through three design proposals, this design research creates a relationship between queer anti-urbanism and design. It asserts that queering the design process and outcome allows a more inclusive way to consider place, space and belonging. The projects lend to a queer relationality and interdependence by making spaces that support the unsettled, out-of-place, but is it queer enough?

Keywords: queer, queer anti-urbanism, design as research, design

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Authors: Johan Buermans, Kristel Crombé, Niek Desmet, Laura Dittrich, Andrei Goriaev, Yurii Kovtun, Daniel López-Rodriguez, Sören Möller, Per Petersson, Maja Verstraeten

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The International Thermonuclear Experimental Reactor (ITER) will rely on three sources of external heating to produce and sustain a plasma; Neutral Beam Injection (NBI), Ion Cyclotron Resonance Heating (ICRH), and Electron Cyclotron Resonance Heating (ECRH). ECRH is a way to heat the electrons in a plasma by resonant absorption of electromagnetic waves. The energy of the electrons is transferred indirectly to the ions by collisions. The electron cyclotron heating system can be directed to deposit heat in particular regions in the plasma (https://www.iter.org/mach/Heating). Electron Cyclotron Resonance Heating (ECRH) at the fundamental resonance in X-mode is limited by a low cut-off density. Electromagnetic waves cannot propagate in the region between this cut-off and the Upper Hybrid Resonance (UHR) and cannot reach the Electron Cyclotron Resonance (ECR) position. Higher harmonic heating is hence preferred in heating scenarios nowadays to overcome this problem. Additional power deposition mechanisms can occur above this threshold to increase the plasma density. This includes collisional losses in the evanescent region, resonant power coupling at the UHR, tunneling of the X-wave with resonant coupling at the ECR, and conversion to the Electron Bernstein Wave (EBW) with resonant coupling at the ECR. A more profound knowledge of these deposition mechanisms can help determine the optimal plasma production scenarios. Several ECRH experiments are performed on the TOroidally MAgnetized System (TOMAS) to identify the conditions for Electron Bernstein Wave (EBW) heating. Density and temperature profiles are measured with movable Triple Langmuir Probes in the horizontal and vertical directions. Measurements of the forwarded and reflected power allow evaluation of the coupling efficiency. Optical emission spectroscopy and camera images also contribute to plasma characterization. The influence of the injected power, magnetic field, gas pressure, and wave polarization on the different deposition mechanisms is studied, and the contribution of the Electron Bernstein Wave is evaluated. The TOMATOR 1D hydrogen-helium plasma simulator numerically describes the evolution of current less magnetized Radio Frequency plasmas in a tokamak based on Braginskii’s legal continuity and heat balance equations. This code was initially benchmarked with experimental data from TCV to determine the transport coefficients. The code is used to model the plasma parameters and the power deposition profiles. The modeling is compared with the data from the experiments.

Keywords: electron Bernstein wave, Langmuir probe, plasma characterization, TOMAS

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Authors: Qiuhu Shao

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Community home-based care service system, which is based on the family pension, supported by community pension and supplied by institutions pension, is an effective pension system to solve the current situation of China's accelerated aging. However, due to the fundamental realities of our country, the government is not able to bear the unilateral supply of the old-age service of the community. Therefore, based on the theory of welfare pluralism, the participation of social organizations in the home-based care service center has become an important part of the diversified supply of the old-age service for the elderly. Meanwhile, the home-based care service industry is still in the early stage, the management is relatively rough, which resulted in a large number of social resources waste. Thus, scientific, objective and long-term implementation is needed for social organizations to participate in home-based care services to guide its performance management. In order to realize the design of the performance management system, the author has done a research work that clarifies the research status of social organization's participation in home-based care service. Relevant theories such as welfare pluralism, community care theory, and performance management theory have been used to demonstrate the feasibility of data envelopment analysis method in social organization performance research. This paper analyzes the characteristics of the operation mode of the home-based care service center, and hackles the national as well as local documents, standards and norms related to the development of the home-based care industry, particularly studies those documents in Nanjing. Based on this, the paper designed a set of performance management PDCA system for home-based care service center in Nanjing and clarified each step of the system in detail. Subsequently, the research methods of performance evaluation and performance management and feedback, which are two core steps of performance management have been compared and screened in order to establish the overall framework of the performance management system of the home-based care service center. Through a large number of research, the paper summarized and analyzed the characteristics of the home-based care service center. Based on the research results, combined with the practice of the industry development in Nanjing, the paper puts forward a targeted performance evaluation index system of home-based care service center in Nanjing. Finally, the paper evaluated and sub-filed the performance of 186 home-based care service centers in Nanjing and then designed the performance optimization direction and performance improvement path based on the results. This study constructs the index system of performance evaluation of home-based care service and makes the index detailed to the implementation level, and constructs the evaluation index system which can be applied directly. Meanwhile, the quantitative evaluation of social organizations participating in the home-based care service changed the subjective impression in the previous practice of evaluation.

Keywords: data envelopment analysis, home-based care, performance management, social organization

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Authors: Liliane Steiner

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Beyond the testimonial act, that sheds light on the feminine experience in the Holocaust, the survivors' writing voices first and foremost the abjection of the feminine self brutally inflicted by the Nazis in the Holocaust, and in the same movement redeems the self by the means of poetics, and brings it to an existential state of being a subject. This study aims to stress the poetics of this writing in order to promote the Holocaust literature from the margins to the mainstream and to contribute to the commemoration of the Holocaust in the next generations. Methodology: The study of the survivors' redeeming of self is based on Julia Kristeva's theory of the abject: the self-throws out everything that threatens its existence and Liliane Steiner's theory of the post- abjection of hell: the belated act of vomiting the abject experiences settles cores with the author of the abject to redeem the self. The research will focus on Ruth Sender's trilogy The Cage, To Life and The Holocaust Lady as a case study. Findings: The binary mode that characterizes this writing reflects the experience of Jewish women, who were subject(s), were treated violently as object(s), debased, defeminized and, eventually turned into abject by the Nazis. In a tour de force, this writing re-enacts the postponed resistance, that vomited the abject imposed on the feminine self by the very act of narration, which denounces the real abject, the perpetrators. The post-abjection of self is acted out in constructs of abject, relating the abject experience of the Holocaust as well as the rehabilitation of the surviving self (subject). The transcription of abject surfaces in deconstructing the abject through self- characterization, and in the elusive rendering of bad memories, having recourse to literary figures. The narrative 'I' selects, obstructs, mends and tells the past events from an active standpoint, as would a subject in control of its (narrative) fate. In a compensatory movement, the narrating I tells itself by reconstructing the subject and proving time and again that I is other. Moreover, in the belated endeavor to revenge, testify and narrate the abject, the narrative I defies itself, and represents itself as a dialectical I, splitting and multiplying itself in a deconstructing way. The dialectical I is never (one) I. It voices not only the unvoiced but also and mainly the other silenced 'I's. Drawing its nature and construct from traumatic memories, the dialectical I transgresses boundaries to narrate her story, and in the same breath, the story of Jewish women doomed to silence. In this narrative feat, the dialectical I stresses its essential dialectical existence with the past, never to be (one) again. Conclusion: The pattern of I is other generates patterns of subject(s) that defy, transgress and repudiate the abject and its repercussions on the feminine I. The feminine I writes itself as a survivor that defies the abject (Nazis) and takes revenge. The paradigm of metamorphosis that accompanies the journey of the Holocaust memoirist engenders life and surviving as well as a narration that defies stagnation and death.

Keywords: abject, feminine writing, holocaust, post-abjection

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Authors: Amelia Frickey, Timothy (TJ) Sheridan, Angelica Rossi, Bahar Aliakbarian

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The growth of large food supply chains demanded improved end-to-end traceability of food products, which has led to companies being increasingly interested in using smart technologies such as Radio Frequency Identification (RFID)-enabled packaging to track items. As technology is being widely used, there are several technological or economic issues that should be overcome to facilitate the adoption of this track-and-trace technology. One of the technological challenges of RFID technology is its sensitivity to different environmental form factors, including packaging materials and the content of the packaging. Although researchers have assessed the performance loss due to the proximity of water and aqueous solutions, there is still the need to further investigate the impacts of food products on the reading range of RFID tags. However, to the best of our knowledge, there are not enough studies to determine the correlation between RFID tag performance and food beverages properties. The goal of this project was to investigate the effect of the solution properties (pH and conductivity) and different packaging materials filled with food-like water-based solutions on the performance of an RFID tag. Three commercially available ultra high-frequency RFID tags were placed on three different bottles and filled with different concentrations of water-based solutions, including sodium chloride, citric acid, sucrose, and ethanol. Transparent glass, Polyethylneterephtalate (PET), and Tetrapak® were used as the packaging materials commonly used in the beverage industries. Tag readability (Theoretical Read Range, TRR) and sensitivity (Power on Tag Forward, PoF) were determined using an anechoic chamber. First, the best place to attach the tag for each packaging material was investigated using empty and water-filled bottles. Then, the bottles were filled with the food-like solutions and tested with the three different tags and the PoF and TRR at the fixed frequency of 915MHz. In parallel, the pH and conductivity of solutions were measured. The best-performing tag was then selected to test the bottles filled with wine, orange, and apple juice. Despite various solutions altering the performance of each tag, the change in tag performance had no correlation with the pH or conductivity of the solution. Additionally, packaging material played a significant role in tag performance. Each tag tested performed optimally under different conditions. This study is the first part of comprehensive research to determine the regression model for the prediction of tag performance behavior based on the packaging material and the content. More investigations, including more tags and food products, are needed to be able to develop a robust regression model. The results of this study can be used by RFID tag manufacturers to design suitable tags for specific products with similar properties.

Keywords: smart food packaging, supply chain management, food waste, radio frequency identification

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Authors: Sara R. Knigge, Sugat R. Tuladhar, Hans-Klaus HöFfler, Tobias Schilling, Tim Kaufeld, Axel Haverich

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Tissue engineered (TE) heart valves based on degradable electrospun fiber scaffold represent a promising approach to overcome the known limitations of mechanical or biological prostheses. But the mechanical stress in the high-pressure system of the human circulation is a severe challenge for the delicate materials. Hence, the prediction of the scaffolds` in vivo degradation kinetics must be as accurate as possible to prevent fatal events in future animal or even clinical trials. Therefore, this study investigates whether long-term testing in full blood provides more meaningful results regarding the degradation behavior than conventional tests in simulated body fluids (SBF) or Phosphate Buffered Saline (PBS). Fiber mats were produced from a polycaprolactone (PCL)/tetrafluoroethylene solution by electrospinning. The morphology of the fiber mats was characterized via scanning electron microscopy (SEM). A maximum physiological degradation environment utilizing a test set-up with porcine full blood was established. The set-up consists of a reaction vessel, an oxygenator unit, and a roller pump. The blood parameters (pO2, pCO2, temperature, and pH) were monitored with an online test system. All tests were also carried out in the test circuit with SBF and PBS to compare conventional degradation media with the novel full blood setting. The polymer's degradation is quantified by SEM picture analysis, differential scanning calorimetry (DSC), and Raman spectroscopy. Tensile and cyclic loading tests were performed to evaluate the mechanical integrity of the scaffold. Preliminary results indicate that PCL degraded slower in full blood than in SBF and PBS. The uptake of water is more pronounced in the full blood group. Also, PCL preserved its mechanical integrity longer when degraded in full blood. Protein absorption increased during the degradation process. Red blood cells, platelets, and their aggregates adhered on the PCL. Presumably, the degradation led to a more hydrophilic polymeric surface which promoted the protein adsorption and the blood cell adhesion. Testing degradable implants in full blood allows for developing more reliable scaffold materials in the future. Material tests in small and large animal trials thereby can be focused on testing candidates that have proven to function well in an in-vivo-like setting.

Keywords: Electrospun scaffold, full blood degradation test, long-term polymer degradation, tissue engineered aortic heart valve

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Authors: Vibha Devi, Shabina Khanam

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Hemp (Cannabis sativa) possesses a rich content of ω-6 linoleic and ω-3 linolenic essential fatty acid in the ratio of 3:1, which is a rare and most desired ratio that enhances the quality of hemp oil. These components are beneficial for the development of cell and body growth, strengthen the immune system, possess anti-inflammatory action, lowering the risk of heart problem owing to its anti-clotting property and a remedy for arthritis and various disorders. The present study employs supercritical fluid extraction (SFE) approach on hemp seed at various conditions of parameters; temperature (40 - 80) °C, pressure (200 - 350) bar, flow rate (5 - 15) g/min, particle size (0.430 - 1.015) mm and amount of co-solvent (0 - 10) % of solvent flow rate through central composite design (CCD). CCD suggested 32 sets of experiments, which was carried out. As SFE process includes large number of variables, the present study recommends the application of resampling techniques for cross-validation of the obtained data. Cross-validation refits the model on each data to achieve the information regarding the error, variability, deviation etc. Bootstrap and jackknife are the most popular resampling techniques, which create a large number of data through resampling from the original dataset and analyze these data to check the validity of the obtained data. Jackknife resampling is based on the eliminating one observation from the original sample of size N without replacement. For jackknife resampling, the sample size is 31 (eliminating one observation), which is repeated by 32 times. Bootstrap is the frequently used statistical approach for estimating the sampling distribution of an estimator by resampling with replacement from the original sample. For bootstrap resampling, the sample size is 32, which was repeated by 100 times. Estimands for these resampling techniques are considered as mean, standard deviation, variation coefficient and standard error of the mean. For ω-6 linoleic acid concentration, mean value was approx. 58.5 for both resampling methods, which is the average (central value) of the sample mean of all data points. Similarly, for ω-3 linoleic acid concentration, mean was observed as 22.5 through both resampling. Variance exhibits the spread out of the data from its mean. Greater value of variance exhibits the large range of output data, which is 18 for ω-6 linoleic acid (ranging from 48.85 to 63.66 %) and 6 for ω-3 linoleic acid (ranging from 16.71 to 26.2 %). Further, low value of standard deviation (approx. 1 %), low standard error of the mean (< 0.8) and low variance coefficient (< 0.2) reflect the accuracy of the sample for prediction. All the estimator value of variance coefficients, standard deviation and standard error of the mean are found within the 95 % of confidence interval.

Keywords: resampling, supercritical fluid extraction, hemp oil, cross-validation

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Authors: Farnaz Farhangi

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Many people in New Zealand believe that the access to water is inexhaustible, and it comes from a history of virtually unrestricted access to it. For the region like Hamilton which is one of New Zealand’s fastest growing cities, it is crucial for policy makers to know about the future water consumption and implementation of rules and regulation such as universal water metering. Hamilton residents use water freely and they do not have any idea about how much water they use. Hence, one of proposed objectives of this research is focusing on forecasting water consumption using different methods. Residential water consumption time series exhibits seasonal and trend variations. Seasonality is the pattern caused by repeating events such as weather conditions in summer and winter, public holidays, etc. The problem with this seasonal fluctuation is that, it dominates other time series components and makes difficulties in determining other variations (such as educational campaign’s effect, regulation, etc.) in time series. Apart from seasonality, a stochastic trend is also combined with seasonality and makes different effects on results of forecasting. According to the forecasting literature, preprocessing (de-trending and de-seasonalization) is essential to have more performed forecasting results, while some other researchers mention that seasonally non-adjusted data should be used. Hence, I answer the question that is pre-processing essential? A wide range of forecasting methods exists with different pros and cons. In this research, I apply double seasonal ARIMA and Artificial Neural Network (ANN), considering diverse elements such as seasonality and calendar effects (public and school holidays) and combine their results to find the best predicted values. My hypothesis is the examination the results of combined method (hybrid model) and individual methods and comparing the accuracy and robustness. In order to use ARIMA, the data should be stationary. Also, ANN has successful forecasting applications in terms of forecasting seasonal and trend time series. Using a hybrid model is a way to improve the accuracy of the methods. Due to the fact that water demand is dominated by different seasonality, in order to find their sensitivity to weather conditions or calendar effects or other seasonal patterns, I combine different methods. The advantage of this combination is reduction of errors by averaging of each individual model. It is also useful when we are not sure about the accuracy of each forecasting model and it can ease the problem of model selection. Using daily residential water consumption data from January 2000 to July 2015 in Hamilton, I indicate how prediction by different methods varies. ANN has more accurate forecasting results than other method and preprocessing is essential when we use seasonal time series. Using hybrid model reduces forecasting average errors and increases the performance.

Keywords: artificial neural network (ANN), double seasonal ARIMA, forecasting, hybrid model

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Authors: Jéssica Bernegossi, Lívia Nordi Dovigo, Marlus Chorilli

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Mucoadhesive liquid crystalline systems are emerging how delivery systems for oral cavity. These systems are interesting since they facilitate the targeting of medicines and change the release enabling a reduction in the number of applications made by the patient. The buccal mucosa is permeable besides present a great blood supply and absence of first pass metabolism, it is a good route of administration. It was developed two systems liquid crystals utilizing as surfactant the ethyl alcohol ethoxylated and propoxylated (30%) as oil phase the oleic acid (60%), and the aqueous phase (10%) dispersion of polymer polyethylenimine (0.5%) or dispersion of polymer poloxamer 407 (16%), with the intention of applying the buccal mucosa. Initially, was performed for characterization of systems the conference by polarized light microscopy and rheological analysis. For the preparation of the systems the components described was added above in glass vials and shaken. Then, 30 and 100% artificial saliva were added to each prepared formulation so as to simulate the environment of the oral cavity. For the verification of the system structure, aliquots of the formulations were observed in glass slide and covered with a coverslip, examined in polarized light microscope (PLM) Axioskop - Zeizz® in 40x magnifier. The formulations were also evaluated for their rheological profile Rheometer TA Instruments®, which were obtained rheograms the selected systems employing fluency mode (flow) in temperature of 37ºC (98.6ºF). In PLM, it was observed that in formulations containing polyethylenimine and poloxamer 407 without the addition of artificial saliva was observed dark-field being indicative of microemulsion, this was also observed with the formulation that was increased with 30% of the artificial saliva. In the formulation that was increased with 100% simulated saliva was shown to be a system structure since it presented anisotropy with the presence of striae being indicative of hexagonal liquid crystalline mesophase system. Upon observation of rheograms, both systems without the addition of artificial saliva showed a Newtonian profile, after addition of 30% artificial saliva have been given a non-Newtonian behavior of the pseudoplastic-thixotropic type and after adding 100% of the saliva artificial proved plastic-thixotropic. Furthermore, it is clearly seen that the formulations containing poloxamer 407 have significantly larger (15-800 Pa) shear stress compared to those containing polyethyleneimine (5-50 Pa), indicating a greater plasticity of these. Thus, it is possible to observe that the addition of saliva was of interest to the system structure, starting from a microemulsion for a liquid crystal system, thereby also changing thereby its rheological behavior. The systems have promising characteristics as controlled release systems to the oral cavity, as it features good fluidity during its possible application and greater structuring of the system when it comes into contact with environmental saliva.

Keywords: liquid crystal system, poloxamer 407, polyethylenimine, rheology

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Authors: Alan N. A. Heberle, Salatiel W. Da Silva, Valentin Perez-Herranz, Andrea M. Bernardes

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Contaminants of emerging concern are substances widely used, such as pharmaceutical products. These compounds represent risk for both wild and human life since they are not completely removed from wastewater by conventional wastewater treatment plants. In the environment, they can be harm even in low concentration (µ or ng/L), causing bacterial resistance, endocrine disruption, cancer, among other harmful effects. One of the most common taken medicine to treat cardiocirculatory diseases is the Atenolol (ATL), a β-Blocker, which is toxic to aquatic life. In this way, it is necessary to implement a methodology, which is capable to promote the degradation of the ATL, to avoid the environmental detriment. A very promising technology is the advanced electrochemical oxidation (AEO), which mechanisms are based on the electrogeneration of reactive radicals (mediated oxidation) and/or on the direct substance discharge by electron transfer from contaminant to electrode surface (direct oxidation). The hydroxyl (HO•) and sulfate (SO₄•⁻) radicals can be generated, depending on the reactional medium. Besides that, at some condition, the peroxydisulfate (S₂O₈²⁻) ion is also generated from the SO₄• reaction in pairs. Both radicals, ion, and the direct contaminant discharge can break down the molecule, resulting in the degradation and/or mineralization. However, ATL molecule and byproducts can still remain in the treated solution. On this wise, some efforts can be done to implement the AEO process, being one of them the use of a cationic membrane to separate the cathodic (reduction) from the anodic (oxidation) reactor compartment. The aim of this study is investigate the influence of the implementation of a cationic membrane (Nafion®-117) to separate both cathodic and anodic, AEO reactor compartments. The studied reactor was a filter-press, with bath recirculation mode, flow 60 L/h. The anode was an Nb/BDD2500 and the cathode a stainless steel, both bidimensional, geometric surface area 100 cm². The solution feeding the anodic compartment was prepared with ATL 100 mg/L using Na₂SO₄ 4 g/L as support electrolyte. In the cathodic compartment, it was used a solution containing Na₂SO₄ 71 g/L. Between both solutions was placed the membrane. The applied currents densities (iₐₚₚ) of 5, 20 and 40 mA/cm² were studied over 240 minutes treatment time. Besides that, the ATL decay was analyzed by ultraviolet spectroscopy (UV/Vis). The mineralization was determined performing total organic carbon (TOC) in TOC-L CPH Shimadzu. In the cases without membrane, the iₐₚₚ 5, 20 and 40 mA/cm² resulted in 55, 87 and 98 % ATL degradation at the end of treatment time, respectively. However, with membrane, the degradation, for the same iₐₚₚ, was 90, 100 and 100 %, spending 240, 120, 40 min for the maximum degradation, respectively. The mineralization, without membrane, for the same studied iₐₚₚ, was 40, 55 and 72 %, respectively at 240 min, but with membrane, all tested iₐₚₚ reached 80 % of mineralization, differing only in the time spent, 240, 150 and 120 min, for the maximum mineralization, respectively. The membrane increased the ATL oxidation, probably due to avoid oxidant ions (S₂O₈²⁻) reduction on the cathode surface.

Keywords: contaminants of emerging concern, advanced electrochemical oxidation, atenolol, cationic membrane, double compartment reactor

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Authors: Yasmeen Cheema, Parvinder Singh

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The evolution of Islamic State (acronym IS) has an ultimate goal of restoring the caliphate. IS threat to the global security is main concern of international community but has also raised a factual concern for India about the regular radicalization of IS ideology among Indian youth. The incident of joining Arif Ejaz Majeed, an Indian as ‘jihadist’ in IS has set strident alarm in law & enforcement agencies. On 07.03.2017, many people were injured in an Improvised Explosive Device (IED) blast on-board of Bhopal Ujjain Express. One perpetrator of this incident was killed in encounter with police. But, the biggest shock is that the conspiracy was pre-planned and the assailants who carried out the blast were influenced by the ideology perpetrated by the Islamic State. This is the first time name of IS has cropped up in a terror attack in India. It is a red indicator of violent presence of IS in India, which is spreading through social media. The IS have the capacity to influence the younger Muslim generation in India through its brutal and aggressive propaganda videos, social media apps and hatred speeches. It is a well known fact that India is on the radar of IS, as well on its ‘Caliphate Map’. IS uses Twitter, Facebook and other social media platforms constantly. Islamic State has used enticing videos, graphics, and articles on social media and try to influence persons from India & globally that their jihad is worthy. According to arrested perpetrator of IS in different cases in India, the most of Indian youths are victims to the daydreams which are fondly shown by IS. The dreams that the Muslim empire as it was before 1920 can come back with all its power and also that the Caliph and its caliphate can be re-established are shown by the IS. Indian Muslim Youth gets attracted towards these euphemistic ideologies. Islamic State has used social media for disseminating its poisonous ideology, recruitment, operational activities and for future direction of attacks. IS through social media inspired its recruits & lone wolfs to continue to rely on local networks to identify targets and access weaponry and explosives. Recently, a pro-IS media group on its Telegram platform shows Taj Mahal as the target and suggested mode of attack as a Vehicle Born Improvised Explosive Attack (VBIED). Islamic State definitely has the potential to destroy the Indian national security & peace, if timely steps are not taken. No doubt, IS has used social media as a critical mechanism for recruitment, planning and executing of terror attacks. This paper will therefore examine the specific characteristics of social media that have made it such a successful weapon for Islamic State. The rise of IS in India should be viewed as a national crisis and handled at the central level with efficient use of modern technology.

Keywords: ideology, India, Islamic State, national security, recruitment, social media, terror attack

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Authors: A. Shakoor, M. Arshad

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The utilization of groundwater resources in irrigation has significantly increased during the last two decades due to constrained canal water supplies. More than 70% of the farmers in the Punjab, Pakistan, depend directly or indirectly on groundwater to meet their crop water demands and hence, an unchecked paradigm shift has resulted in aquifer depletion and deterioration. Therefore, a comprehensive research was carried at central Punjab-Pakistan, regarding spatiotemporal variation in groundwater level and quality. Processing MODFLOW for window (PMWIN) and MT3D (solute transport model) models were used for existing and future prediction of groundwater level and quality till 2030. The comprehensive data set of aquifer lithology, canal network, groundwater level, groundwater salinity, evapotranspiration, groundwater abstraction, recharge etc. were used in PMWIN model development. The model was thus, successfully calibrated and validated with respect to groundwater level for the periods of 2003 to 2007 and 2008 to 2012, respectively. The coefficient of determination (R2) and model efficiency (MEF) for calibration and validation period were calculated as 0.89 and 0.98, respectively, which argued a high level of correlation between the calculated and measured data. For solute transport model (MT3D), the values of advection and dispersion parameters were used. The model used for future scenario up to 2030, by assuming that there would be no uncertain change in climate and groundwater abstraction rate would increase gradually. The model predicted results revealed that the groundwater would decline from 0.0131 to 1.68m/year during 2013 to 2030 and the maximum decline would be on the lower side of the study area, where infrastructure of canal system is very less. This lowering of groundwater level might cause an increase in the tubewell installation and pumping cost. Similarly, the predicted total dissolved solids (TDS) of the groundwater would increase from 6.88 to 69.88mg/L/year during 2013 to 2030 and the maximum increase would be on lower side. It was found that in 2030, the good quality would reduce by 21.4%, while marginal and hazardous quality water increased by 19.28 and 2%, respectively. It was found from the simulated results that the salinity of the study area had increased due to the intrusion of salts. The deterioration of groundwater quality would cause soil salinity and ultimately the reduction in crop productivity. It was concluded from the predicted results of groundwater model that the groundwater deteriorated with the depth of water table i.e. TDS increased with declining groundwater level. It is recommended that agronomic and engineering practices i.e. land leveling, rainwater harvesting, skimming well, ASR (Aquifer Storage and Recovery Wells) etc. should be integrated to meliorate management of groundwater for higher crop production in salt affected soils.

Keywords: groundwater quality, groundwater management, PMWIN, MT3D model

Procedia PDF Downloads 378

Authors: Elvis Nyirenda

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This research study work was done to evaluate and propose an optimum measure to enhance the uptake of clean energy technologies such as solar photovoltaics, the study also aims at enhancing the country’s energy mix from the overdependence on hydro power which is susceptible to droughts and climate change challenges The country in the years 2015 - 2016 and 2018 - 2019 had received rainfall below average due to climate change and a shift in the weather pattern; this resulted in prolonged power outages and load shedding for more than 10 hours per day. ZESCO Limited, the utility company that owns infrastructure in the generation, transmission, and distribution of electricity (state-owned), is seeking alternative sources of energy in order to reduce the over-dependence on hydropower stations. One of the alternative sources of energy is Solar Energy from the sun. However, solar power is intermittent in nature and to smoothen the load curve, investment in robust energy storage facilities is of great importance to enhance security and reliability of electricity supply in the country. The methodology of the study looked at the historical performance of the Kafue gorge upper power station and utilised the hourly generation figures as input data for generation modelling in Homer software. The average yearly demand was derived from the available data on the system SCADA. The two dams were modelled as natural battery with the absolute state of charging and discharging determined by the available water resource and the peak electricity demand. The software Homer Energy System is used to simulate the scheme incorporating a pumped storage facility and Solar photovoltaic systems. The pumped hydro scheme works like a natural battery for the conservation of water, with the only losses being evaporation and water leakages from the dams and the turbines. To address the problem of intermittency on the solar resource and the non-availability of water for hydropower generation, the study concluded that utilising the existing Hydro power stations, Kafue Gorge upper and Kafue Gorge Lower to work conjunctively with Solar energy will reduce power deficits and increase the security of supply for the country. An optimum capacity of 350MW of solar PV can be integrated while operating Kafue Gorge power station in both generating and pumping mode to enable efficient utilisation of water at Kafue Gorge upper Dam and Kafue Gorge Lower dam.

Keywords: hydropower, solar power systems, energy storage, photovoltaics, solar irradiation, pumped hydro storage system, supervisory control and data acquisition, Homer energy

Procedia PDF Downloads 117

Authors: Antoine Lauvray, Fabien Poulhaon, Pierre Michaud, Pierre Joyot, Emmanuel Duc

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Additive Friction Stir Manufacturing (AFSM) is a new industrial process that follows the emergence of friction-based processes. The AFSM process is a solid-state additive process using the energy produced by the friction at the interface between a rotating non-consumable tool and a substrate. Friction depends on various parameters like axial force, rotation speed or friction coefficient. The feeder material is a metallic rod that flows through a hole in the tool. Unlike in Friction Stir Welding (FSW) where abundant literature exists and addresses many aspects going from process implementation to characterization and modeling, there are still few research works focusing on AFSM. Therefore, there is still a lack of understanding of the physical phenomena taking place during the process. This research work aims at a better AFSM process understanding and implementation, thanks to numerical simulation and experimental validation performed on a prototype effector. Such an approach is considered a promising way for studying the influence of the process parameters and to finally identify a process window that seems relevant. The deposition of material through the AFSM process takes place in several phases. In chronological order these phases are the docking phase, the dwell time phase, the deposition phase, and the removal phase. The present work focuses on the dwell time phase that enables the temperature rise of the system composed of the tool, the filler material, and the substrate and due to pure friction. Analytic modeling of heat generation based on friction considers as main parameters the rotational speed and the contact pressure. Another parameter considered influential is the friction coefficient assumed to be variable due to the self-lubrication of the system with the rise in temperature or the materials in contact roughness smoothing over time. This study proposes, through numerical modeling followed by experimental validation, to question the influence of the various input parameters on the dwell time phase. Rotation speed, temperature, spindle torque, and axial force are the main monitored parameters during experimentations and serve as reference data for the calibration of the numerical model. This research shows that the geometry of the tool as well as fluctuations of the input parameters like axial force and rotational speed are very influential on the temperature reached and/or the time required to reach the targeted temperature. The main outcome is the prediction of a process window which is a key result for a more efficient process implementation.

Keywords: numerical model, additive manufacturing, friction, process

Procedia PDF Downloads 147

Authors: Tamar Grdzelishvili, Zaza Sinauridze

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Introduction: Preeclampsia is a complication of the second trimester of pregnancy, which is characterized by high morbidity and multiorgan damage. Many complex pathogenic mechanisms are now implicated to be responsible for this disease (1). Preeclampsia is one of the leading causes of maternal mortality worldwide. Statistics are enough to convince you of the seriousness of this pathology: about 100,000 women die of preeclampsia every year. It occurs in 3-14% (varies significantly depending on racial origin or ethnicity and geographical region) of pregnant women, in 75% of cases - in a mild form, and in 25% - in a severe form. During severe pre-eclampsia-eclampsia, perinatal mortality increases by 5 times and stillbirth by 9.6 times. Considering that the only way to treat the disease is to end the pregnancy, the main thing is timely diagnosis and prevention of the disease. Identification of high-risk pregnant women for PE and giving prophylaxis would reduce the incidence of preterm PE. First-trimester screening model developed by the Fetal Medicine Foundation (FMF), which uses the Bayes-theorem to combine maternal characteristics and medical history together with measurements of mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor, has been proven to be effective and have superior screening performance to that of traditional risk factor-based approach for the prediction of PE (2) Methods: Retrospective single center screening study. The study population consisted of women from the Tbilisi maternity hospital “Pineo medical ecosystem” who met the following criteria: they spoke Georgian, English, or Russian and agreed to participate in the study after discussing informed consent and answering questions. Prior to the study, the informed consent forms approved by the Institutional Review Board were obtained from the study subjects. Early assessment of preeclampsia was performed between 11-13 weeks of pregnancy. The following were evaluated: anamnesis, dopplerography of the uterine artery, mean arterial blood pressure, and biochemical parameter: Pregnancy-associated plasma protein A (PAPP-A). Individual risk assessment was performed with performed by Fast Screen 3.0 software ThermoFisher scientific. Results: A total of 513 women were recruited and through the study, 51 women were diagnosed with preeclampsia (34.5% in the pregnant women with high risk, 6.5% in the pregnant women with low risk; P<0.000 1). Conclusions: First-trimester screening combining maternal factors with uterine artery Doppler, blood pressure, and pregnancy-associated plasma protein-A is useful to predict PE in a routine care setting. More patient studies are needed for final conclusions. The research is still ongoing.

Keywords: first-trimester, preeclampsia, screening, pregnancy-associated plasma protein

Procedia PDF Downloads 77

Authors: Lenon M. Pereira, Helen J. Khoury, Marcos E. A. Andrade, Dean L. Cutajar, Vinicius S. M. Barros, Anatoly B. Rozenfeld

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With the increase of beam widths and the advent of multiple-slice and helical scanners, concerns related to the current dose measurement protocols and instrumentation in computed tomography (CT) have arisen. The current methodology of dose evaluation, which is based on the measurement of the integral of a single slice dose profile using a 100 mm long cylinder ionization chamber (Ca,100 and CPPMA, 100), has been shown to be inadequate for wide beams as it does not collect enough of the scatter-tails to make an accurate measurement. In addition, a long ionization chamber does not offer a good representation of the dose profile when tube current modulation is used. An alternative approach has been suggested by translating smaller detectors through the beam plane and assessing the accumulated dose trough the integral of the dose profile, which can be done for any arbitrary length in phantoms or in the air. For this purpose, a MOSFET dosimeter of small dosimetric volume was used. One of its recently designed versions is known as the MOSkin, which is developed by the Centre for Medical Radiation Physics at the University of Wollongong, and measures the radiation dose at a water equivalent depth of 0.07 mm, allowing the evaluation of skin dose when placed at the surface, or internal point doses when placed within a phantom. Thus, the aim of this research was to characterize the response of the MOSkin dosimeter for X-ray CT beams and to evaluate its application for the accumulated dose assessment. Initially, tests using an industrial x-ray unit were carried out at the Laboratory of Ionization Radiation Metrology (LMRI) of Federal University of Pernambuco, in order to investigate the sensitivity, energy dependence, angular dependence, and reproducibility of the dose response for the device for the standard radiation qualities RQT 8, RQT 9 and RQT 10. Finally, the MOSkin was used for the accumulated dose evaluation of scans using a Philips Brilliance 6 CT unit, with comparisons made between the CPPMA,100 value assessed with a pencil ionization chamber (PTW Freiburg TW 30009). Both dosimeters were placed in the center of a PMMA head phantom (diameter of 16 cm) and exposed in the axial mode with collimation of 9 mm, 250 mAs and 120 kV. The results have shown that the MOSkin response was linear with doses in the CT range and reproducible (98.52%). The sensitivity for a single MOSkin in mV/cGy was as follows: 9.208, 7.691 and 6.723 for the RQT 8, RQT 9 and RQT 10 beams qualities respectively. The energy dependence varied up to a factor of ±1.19 among those energies and angular dependence was not greater than 7.78% within the angle range from 0 to 90 degrees. The accumulated dose and the CPMMA, 100 value were 3,97 and 3,79 cGy respectively, which were statistically equivalent within the 95% confidence level. The MOSkin was shown to be a good alternative for CT dose profile measurements and more than adequate to provide accumulated dose assessments for CT procedures.

Keywords: computed tomography dosimetry, MOSFET, MOSkin, semiconductor dosimetry

Procedia PDF Downloads 311

Authors: Praskovya Britskaya, Fatima Shaizadina, Alua Omarova, Nessipkul Alysheva

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Planned preventive vaccination, which is carried out in the Republic of Kazakhstan, promoted permanent decrease in the incidence of measles and viral hepatitis B. In the structure of VHB patients prevail people of young, working age. Monitoring of infectious incidence, monitoring of coverage of immunization of the population, random serological control over the immunity enable well-timed identification of distribution of the activator, effectiveness of the taken measures and forecasting. The serological blood analysis was conducted in indicator groups of the population of Central Kazakhstan for the purpose of identification of antibody titre for vaccine preventable infections (measles, viral hepatitis B). Measles antibodies were defined by method of enzyme-linked assay (ELA) with test-systems "VektoKor" – Ig G ('Vektor-Best' JSC). Antibodies for HBs-antigen of hepatitis B virus in blood serum was identified by method of enzyme-linked assay (ELA) with VektoHBsAg test systems – antibodies ('Vektor-Best' JSC). The result of the analysis is positive, the concentration of IgG to measles virus in the studied sample is equal to 0.18 IU/ml or more. Protective level of concentration of anti-HBsAg makes 10 mIU/ml. The results of the study of postvaccinal measles immunity showed that the share of seropositive people made 87.7% of total number of surveyed. The level of postvaccinal immunity to measles in age groups differs. So, among people older than 56 the percentage of seropositive made 95.2%. Among people aged 15-25 were registered 87.0% seropositive, at the age of 36-45 – 86.6%. In age groups of 25-35 and 36-45 the share of seropositive people was approximately at the same level – 88.5% and 88.8% respectively. The share of people seronegative to a measles virus made 12.3%. The biggest share of seronegative people was found among people aged 36-45 – 13.4% and 15-25 – 13.0%. The analysis of results of the examined people for the existence of postvaccinal immunity to viral hepatitis B showed that from all surveyed only 33.5% have the protective level of concentration of anti-HBsAg of 10 mIU/ml and more. The biggest share of people protected from VHB virus is observed in the age group of 36-45 and makes 60%. In the indicator group – above 56 – seropositive people made 4.8%. The high percentage of seronegative people has been observed in all studied age groups from 40.0% to 95.2%. The group of people which is least protected from getting VHB is people above 56 (95.2%). The probability to get VHB is also high among young people aged 25-35, the percentage of seronegative people made 80%. Thus, the results of the conducted research testify to the need for carrying out serological monitoring of postvaccinal immunity for the purpose of operational assessment of the epidemiological situation, early identification of its changes and prediction of the approaching danger.

Keywords: antibodies, blood serum, immunity, immunoglobulin

Procedia PDF Downloads 255

Authors: A. Ramachandra Reddy, V. Murugan, Prema Kumari

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Residual solvents in Pharmaceutical samples are monitored using gas chromatography with headspace (GC-HS). Based on current regulatory and compendial requirements, measuring the residual solvents are mandatory for all release testing of active pharmaceutical ingredients (API). Generally, isopropyl alcohol is used as the residual solvent in proline and tryptophan; methanol in cysteine monohydrate hydrochloride, glycine, methionine and serine; ethanol in glycine and lysine monohydrate; acetic acid in methionine. In order to have a single method for determining these residual solvents (isopropyl alcohol, ethanol, methanol and acetic acid) in all these 7 amino acids a sensitive and simple method was developed by using gas chromatography headspace technique with flame ionization detection. During development, no reproducibility, retention time variation and bad peak shape of acetic acid peaks were identified due to the reaction of acetic acid with the stationary phase (cyanopropyl dimethyl polysiloxane phase) of column and dissociation of acetic acid with water (if diluent) while applying temperature gradient. Therefore, dimethyl sulfoxide was used as diluent to avoid these issues. But most the methods published for acetic acid quantification by GC-HS uses derivatisation technique to protect acetic acid. As per compendia, risk-based approach was selected as appropriate to determine the degree and extent of the validation process to assure the fitness of the procedure. Therefore, Total error concept was selected to validate the analytical procedure. An accuracy profile of ±40% was selected for lower level (quantitation limit level) and for other levels ±30% with 95% confidence interval (risk profile 5%). The method was developed using DB-Waxetr column manufactured by Agilent contains 530 µm internal diameter, thickness: 2.0 µm, and length: 30 m. A constant flow of 6.0 mL/min. with constant make up mode of Helium gas was selected as a carrier gas. The present method is simple, rapid, and accurate, which is suitable for rapid analysis of isopropyl alcohol, ethanol, methanol and acetic acid in amino acids. The range of the method for isopropyl alcohol is 50ppm to 200ppm, ethanol is 50ppm to 3000ppm, methanol is 50ppm to 400ppm and acetic acid 100ppm to 400ppm, which covers the specification limits provided in European pharmacopeia. The accuracy profile and risk profile generated as part of validation were found to be satisfactory. Therefore, this method can be used for testing of residual solvents in amino acids drug substances.

Keywords: amino acid, head space, gas chromatography, total error

Procedia PDF Downloads 148

Authors: M. Bahari Mehrabani, Hua-Peng Chen

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Management and maintenance of coastal defence structures during the expected life cycle have become a real challenge for decision makers and engineers. Accurate evaluation of the current condition and future performance of flood defence structures is essential for effective practical maintenance strategies on the basis of available field inspection data. Moreover, as coastal defence structures age, it becomes more challenging to implement maintenance and management plans to avoid structural failure. Therefore, condition inspection data are essential for assessing damage and forecasting deterioration of ageing flood defence structures in order to keep the structures in an acceptable condition. The inspection data for flood defence structures are often collected using discrete visual condition rating schemes. In order to evaluate future condition of the structure, a probabilistic deterioration model needs to be utilised. However, existing deterioration models may not provide a reliable prediction of performance deterioration for a long period due to uncertainties. To tackle the limitation, a time-dependent condition-based model associated with a transition probability needs to be developed on the basis of condition grade scheme for flood defences. This paper presents a probabilistic method for predicting future performance deterioration of coastal flood defence structures based on condition grading inspection data and deterioration curves estimated by expert judgement. In condition-based deterioration modelling, the main task is to estimate transition probability matrices. The deterioration process of the structure related to the transition states is modelled according to Markov chain process, and a reliability-based approach is used to estimate the probability of structural failure. Visual inspection data according to the United Kingdom Condition Assessment Manual are used to obtain the initial condition grade curve of the coastal flood defences. The initial curves then modified in order to develop transition probabilities through non-linear regression based optimisation algorithms. The Monte Carlo simulations are then used to evaluate the future performance of the structure on the basis of the estimated transition probabilities. Finally, a case study is given to demonstrate the applicability of the proposed method under no-maintenance and medium-maintenance scenarios. Results show that the proposed method can provide an effective predictive model for various situations in terms of available condition grading data. The proposed model also provides useful information on time-dependent probability of failure in coastal flood defences.

Keywords: condition grading, flood defense, performance assessment, stochastic deterioration modelling

Procedia PDF Downloads 233

Authors: Weikang Gong, Chunhua Li

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Dynamics plays an essential role in function exertion of proteins. Elastic network model (ENM), a harmonic potential-based and cost-effective computational method, is a valuable and efficient tool for characterizing the intrinsic dynamical properties encoded in biomacromolecule structures and has been widely used to detect the large-amplitude collective motions of proteins. Gaussian network model (GNM) and anisotropic network model (ANM) are the two often-used ENM models. In recent years, many ENM variants have been proposed. Here, we propose a small but effective modification (denoted as modified mENM) to the multiscale ENM (mENM) where fitting weights of Kirchhoff/Hessian matrixes with the least square method (LSM) is modified since it neglects the details of pairwise interactions. Then we perform its comparisons with the original mENM, traditional ENM, and parameter-free ENM (pfENM) on reproducing dynamical properties for the six representative proteins whose molecular dynamics (MD) trajectories are available in http://mmb.pcb.ub.es/MoDEL/. In the results, for B-factor prediction, mENM achieves the best performance among the four ENM models. Additionally, it is noted that with the weights of the multiscale Kirchhoff/Hessian matrixes modified, interestingly, the modified mGNM/mANM still has a much better performance than the corresponding traditional ENM and pfENM models. As to dynamical cross-correlation map (DCCM) calculation, taking the data obtained from MD trajectories as the standard, mENM performs the worst while the results produced by the modified mENM and pfENM models are close to those from MD trajectories with the latter a little better than the former. Generally, ANMs perform better than the corresponding GNMs except for the mENM. Thus, pfANM and the modified mANM, especially the former, have an excellent performance in dynamical cross-correlation calculation. Compared with GNMs (except for mGNM), the corresponding ANMs can capture quite a number of positive correlations for the residue pairs nearly largest distances apart, which is maybe due to the anisotropy consideration in ANMs. Furtherly, encouragingly the modified mANM displays the best performance in capturing the functional motional modes, followed by pfANM and traditional ANM models, while mANM fails in all the cases. This suggests that the consideration of long-range interactions is critical for ANM models to produce protein functional motions. Based on the analyses, the modified mENM is a promising method in capturing multiple dynamical characteristics encoded in protein structures. This work is helpful for strengthening the understanding of the elastic network model and provides a valuable guide for researchers to utilize the model to explore protein dynamics.

Keywords: elastic network model, ENM, multiscale ENM, molecular dynamics, parameter-free ENM, protein structure

Procedia PDF Downloads 121

Authors: Raju Chhetri

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Agroforestry is one of the main sources of livelihood among the people of Nepal. In particular, this is the only one mode of livelihood among the Chepangs. The monster earthquake (7.3 MW) that hit the country on the 25th of April in 2015 and many of its aftershocks had devastating effects. As a result, not only the big structures collapsed, it incurred great losses on fabrication, collection centers, schools, markets and other necessary service centers. Although there were a large number of aftershocks after the monster earthquake, the most devastating aftershock took place on 12th May, 2015, which measured 6.3 richter scale. Consequently, it caused more destruction of houses, further calamity to the lives of people, and public life got further perdition. This study was mainly carried out to find out the food security and market situation of Agroforestry product of the Chepang community in Raksirang VDC (one of the severely affected VDCs of Makwanpur district) due to the earthquake. A total of 40 households (12 percent) were randomly selected as a sample in ward number 7 only. Questionnaires and focus groups were used to gather primary data. Additional, two Focus Group Discussions (FGD) were convened in the study area to get some descriptive information on this study. Estimated 370 hectares of land, which was full of Agroforestry plantation, ruptured by the earthquake. It caused severe damages to the households, and a serious loss of food-stock, up to 60-80 percent (maize, millet, and rice). Instead of regular cereal intake, banana (Muas Paradisca) consumption was found ‘high scale’ in the emergency period. The market price of rice (37-44 NRS/Kg) increased by 18.9 percent. Some difference in the income range before and after the earthquake was observed. Before earthquake, sale of Agroforestry, and livestock products were continuing, but after the earthquake, Agroforestry product sale is the only one means of livelihood among Chepangs. Nearly 50-60 percent Agroforestry production of banana (Mass Paradisca), citrus (Citrus Lemon), pineapple (Ananus comosus) and broom grass (Thysanolaena maxima) declined, excepting for cash income from the residual. Heavy demands of Agroforestry product mentioned above lay high farm gate prices (50-100 percent) helps surveyed the community to continue livelihood from its sale. Out of the survey samples, 30 households (75 percent) respondents migrated to safe location due to land rupture, ongoing aftershocks, and landslides. Overall food security situation in this community is acute and challenging for the days to come. Immediate and long term both response from a relief agency concerning food, shelter and safe stocking of Agroforestry product is required to keep secured livelihood in Chepang community.

Keywords: earthquake, rupture, agroforestry, livelihood, indigenous, food security

Procedia PDF Downloads 322

Authors: Mary Jane B. Suarez

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Public speaking anxiety (PSA), also known as speech anxiety, is innumerably persistent in any traditional communication classes, especially for students who learn English as a second language. The speech anxiety intensifies when communication skills assessments have taken their toll in an online or a remote mode of learning due to the perils of the COVID-19 virus. Both teachers and students have experienced vast ambiguity on how to realize a still effective way to teach and learn speaking skills amidst the pandemic. Communication skills assessments like public speaking, oral presentations, and student reporting have defined their new meaning using Google Meet, Zoom, and other online platforms. Though using such technologies has paved for more creative ways for students to acquire and develop communication skills, the effectiveness of using such assessment tools stands in question. This mixed method study aimed to determine the factors that affected the public speaking skills of students in a communication class, to probe on the assessment gaps in assessing speaking skills of students attending online classes vis-à-vis the implementation of remote and blended modalities of learning, and to recommend ways on how to address the public speaking anxieties of students in performing a speaking task online and to bridge the assessment gaps based on the outcome of the study in order to achieve a smooth segue from online to on-ground instructions maneuvering towards a much better post-pandemic academic milieu. Using a convergent parallel design, both quantitative and qualitative data were reconciled by probing on the public speaking anxiety of students and the potential assessment gaps encountered in an online English communication class under remote and blended learning. There were four phases in applying the convergent parallel design. The first phase was the data collection, where both quantitative and qualitative data were collected using document reviews and focus group discussions. The second phase was data analysis, where quantitative data was treated using statistical testing, particularly frequency, percentage, and mean by using Microsoft Excel application and IBM Statistical Package for Social Sciences (SPSS) version 19, and qualitative data was examined using thematic analysis. The third phase was the merging of data analysis results to amalgamate varying comparisons between desired learning competencies versus the actual learning competencies of students. Finally, the fourth phase was the interpretation of merged data that led to the findings that there was a significantly high percentage of students' public speaking anxiety whenever students would deliver speaking tasks online. There were also assessment gaps identified by comparing the desired learning competencies of the formative and alternative assessments implemented and the actual speaking performances of students that showed evidence that public speaking anxiety of students was not properly identified and processed.

Keywords: blended learning, communication skills assessment, public speaking anxiety, speech anxiety

Procedia PDF Downloads 102

Authors: Benjamin Castillo, Luis Pastenes, Fernando Cerdova

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The contamination of food by microbial agents is a common problem in the industry, especially regarding the elaboration of animal source products. Incorrect manipulation of the machinery or on the raw materials can cause a decrease in production or an epidemiological outbreak due to intoxication. In order to improve food product quality, different methods have been used to reduce or, at least, to slow down the growth of the pathogens, especially deteriorated, infectious or toxigenic bacteria. These methods are usually carried out under low temperatures and short processing time (abiotic agents), along with the application of antibacterial substances, such as bacteriocins (biotic agents). This, in a controlled and efficient way that fulfills the purpose of bacterial control without damaging the final product. Therefore, the objective of the present study is to design a secondary mathematical model that allows the prediction of both the biotic and abiotic factor impact associated with animal source food processing. In order to accomplish this objective, the authors propose a three-dimensional differential equation model, whose components are: bacterial growth, release, production and artificial incorporation of bacteriocins and changes in pH levels of the medium. These three dimensions are constantly being influenced by the temperature of the medium. Secondly, this model adapts to an idealized situation of cross-contamination animal source food processing, with the study agents being both the animal product and the contact surface. Thirdly, the stochastic simulations and the parametric sensibility analysis are compared with referential data. The main results obtained from the analysis and simulations of the mathematical model were to discover that, although bacterial growth can be stopped in lower temperatures, even lower ones are needed to eradicate it. However, this can be not only expensive, but counterproductive as well in terms of the quality of the raw materials and, on the other hand, higher temperatures accelerate bacterial growth. In other aspects, the use and efficiency of bacteriocins are an effective alternative in the short and medium terms. Moreover, an indicator of bacterial growth is a low-level pH, since lots of deteriorating bacteria are lactic acids. Lastly, the processing times are a secondary agent of concern when the rest of the aforementioned agents are under control. Our main conclusion is that when acclimating a mathematical model within the context of the industrial process, it can generate new tools that predict bacterial contamination, the impact of bacterial inhibition, and processing method times. In addition, the mathematical modeling proposed logistic input of broad application, which can be replicated on non-meat food products, other pathogens or even on contamination by crossed contact of allergen foods.

Keywords: bacteriocins, cross-contamination, mathematical model, temperature

Procedia PDF Downloads 144

Authors: Linlong Mu, Maosong Huang

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Considering excavations in urban areas, the soil deformation induced by the excavations usually causes damage to the surrounding structures. Displacement control becomes a critical indicator of foundation design in order to protect the surrounding structures. Evaluation, the damage potential of the surrounding structures induced by the excavations, usually depends on the finite element method (FEM) because of the complexity of the excavation and the variety of the surrounding structures. Besides, evaluation the influence of the excavation on surrounding structures is a three-dimensional problem. And it is now well recognized that small strain behaviour of the soil influences the responses of the excavation significantly. Three-dimensional FEM considering small strain behaviour of the soil is a very complex method, which is hard for engineers to use. Thus, it is important to obtain a simplified method for engineers to predict the influence of the excavations on the surrounding structures. Based on large-scale finite element calculation with small-strain based soil model coupling with inverse analysis, an empirical method is proposed to calculate the three-dimensional soil movement induced by braced excavation. The empirical method is able to capture the small-strain behaviour of the soil. And it is suitable to be used in layered soil. Then the free-field soil movement is applied to the pile to calculate the responses of the pile in both vertical and horizontal directions. The asymmetric solutions for problems in layered elastic half-space are employed to solve the interactions between soil points. Both vertical and horizontal pile responses are solved through finite difference method based on elastic theory. Interactions among the nodes along a single pile, pile-pile interactions, pile-soil-pile interaction action and soil-soil interactions are counted to improve the calculation accuracy of the method. For passive piles, the shadow effects are also calculated in the method. Finally, the restrictions of the raft on the piles and the soils are summarized as: (1) the summations of the internal forces between the elements of the raft and the elements of the foundation, including piles and soil surface elements, is equal to 0; (2) the deformations of pile heads or of the soil surface elements are the same as the deformations of the corresponding elements of the raft. Validations are carried out by comparing the results from the proposed method with the results from the model tests, FEM and other existing literatures. From the comparisons, it can be seen that the results from the proposed method fit with the results from other methods very well. The method proposed herein is suitable to predict the responses of the pile-raft foundation induced by braced excavation in layered soil in both vertical and horizontal directions when the deformation is small. However, more data is needed to verify the method before it can be used in practice.

Keywords: excavation, pile-raft foundation, passive piles, deformation control, soil movement

Procedia PDF Downloads 231

Authors: Eva L. Suarez, Daniel E. Meeroff, Yan Yong

Abstract:

The U.S. Federal Emergency Management Agency (FEMA) developed flood maps based on experts’ experience and estimates of the probability of flooding. Current flood-risk models evaluate flood risk with regional and subjective measures without impact from torrential rain and nuisance flooding at the neighborhood level. Nuisance flooding occurs in small areas in the community, where a few streets or blocks are routinely impacted. This type of flooding event occurs when torrential rainstorm combined with high tide and sea level rise temporarily exceeds a given threshold. In South Florida, this threshold is 1.7 ft above Mean Higher High Water (MHHW). The National Weather Service defines torrential rain as rain deposition at a rate greater than 0.3-inches per hour or three inches in a single day. Data from the Florida Climate Center, 1970 to 2020, shows 371 events with more than 3-inches of rain in a day in 612 months. The purpose of this research is to develop a data-driven method to determine comprehensive analytical damage-avoidance criteria that account for nuisance flood events at the single-family home level. The method developed uses the Failure Mode and Effect Analysis (FMEA) method from the American Society of Quality (ASQ) to estimate the Damage Avoidance (DA) preparation for a 1-day 100-year storm. The Consequence of Nuisance Flooding (CoNF) is estimated from community mitigation efforts to prevent nuisance flooding damage. The Probability of Nuisance Flooding (PoNF) is derived from the frequency and duration of torrential rainfall causing delays and community disruptions to daily transportation, human illnesses, and property damage. Urbanization and population changes are related to the U.S. Census Bureau's annual population estimates. Data collected by the United States Department of Agriculture (USDA) Natural Resources Conservation Service’s National Resources Inventory (NRI) and locally by the South Florida Water Management District (SFWMD) track the development and land use/land cover changes with time. The intent is to include temporal trends in population density growth and the impact on land development. Results from this investigation provide the risk of nuisance flooding as a function of CoNF and PoNF for coastal areas of South Florida. The data-based criterion provides awareness to local municipalities on their flood-risk assessment and gives insight into flood management actions and watershed development.

Keywords: flood risk, nuisance flooding, urban flooding, FMEA

Procedia PDF Downloads 99

Authors: Debabrata Adhikari, Mikhail Matveev, Louise Brown, Andy Long, Jan Kočí

Abstract:

A good understanding of mesoscale permeability of complex architectures in fibrous porous preforms is of particular interest in order to achieve efficient and cost-effective resin impregnation of liquid composite molding (LCM). Fabrics used in structural reinforcements are typically woven or stitched. However, 3D fabric reinforcement is of particular interest because of the versatility in the weaving pattern with the binder yarn and in-plain yarn arrangements to manufacture thick composite parts, overcome the limitation in delamination, improve toughness etc. To predict the permeability based on the available pore spaces between the inter yarn spaces, unit cell-based computational fluid dynamics models have been using the Stokes Darcy model. Typically, the preform consists of an arrangement of yarns with spacing in the order of mm, wherein each yarn consists of thousands of filaments with spacing in the order of μm. The fluid flow during infusion exchanges the mass between the intra and inter yarn channels, meaning there is no dead-end of flow between the mesopore in the inter yarn space and the micropore in the yarn. Several studies have employed the Brinkman equation to take into account the flow through dual-scale porosity reinforcement to estimate their permeability. Furthermore, to reduce the computational effort of dual scale flow, scale separation criteria based on the ratio between yarn permeability to the yarn spacing was also proposed to quantify the dual scale and negligible micro-scale flow regime for the prediction of mesoscale permeability. In the present work, the key parameter to identify the influence of intra yarn permeability on the mesoscale permeability has been investigated with the systematic study of weft and warp yarn spacing on the plane weave as well as the position of binder yarn and number of in-plane yarn layers on 3D weave fabric. The permeability tensor has been estimated using an OpenFOAM-based model for the various weave pattern with idealized geometry of yarn implemented using open-source software TexGen. Additionally, scale separation criterion has been established based on the various configuration of yarn permeability for the 3D fabric with both the isotropic and anisotropic yarn from Gebart’s model. It was observed that the variation of mesoscale permeability Kxx within 30% when the isotropic porous yarn is considered for a 3D fabric with binder yarn. Furthermore, the permeability model developed in this study will be used for multi-objective optimizations of the preform mesoscale geometry in terms of yarn spacing, binder pattern, and a number of layers with an aim to obtain improved permeability and reduced void content during the LCM process.

Keywords: permeability, 3D fabric, dual-scale flow, liquid composite molding

Procedia PDF Downloads 96

Authors: Shaukat Ali Shahee, Usha Ananthakumar

Abstract:

A data set exhibits class imbalance problem when one class has very few examples compared to the other class, and this is also referred to as between class imbalance. The traditional classifiers fail to classify the minority class examples correctly due to its bias towards the majority class. Apart from between-class imbalance, imbalance within classes where classes are composed of a different number of sub-clusters with these sub-clusters containing different number of examples also deteriorates the performance of the classifier. Previously, many methods have been proposed for handling imbalanced dataset problem. These methods can be classified into four categories: data preprocessing, algorithmic based, cost-based methods and ensemble of classifier. Data preprocessing techniques have shown great potential as they attempt to improve data distribution rather than the classifier. Data preprocessing technique handles class imbalance either by increasing the minority class examples or by decreasing the majority class examples. Decreasing the majority class examples lead to loss of information and also when minority class has an absolute rarity, removing the majority class examples is generally not recommended. Existing methods available for handling class imbalance do not address both between-class imbalance and within-class imbalance simultaneously. In this paper, we propose a method that handles between class imbalance and within class imbalance simultaneously for binary classification problem. Removing between class imbalance and within class imbalance simultaneously eliminates the biases of the classifier towards bigger sub-clusters by minimizing the error domination of bigger sub-clusters in total error. The proposed method uses model-based clustering to find the presence of sub-clusters or sub-concepts in the dataset. The number of examples oversampled among the sub-clusters is determined based on the complexity of sub-clusters. The method also takes into consideration the scatter of the data in the feature space and also adaptively copes up with unseen test data using Lowner-John ellipsoid for increasing the accuracy of the classifier. In this study, neural network is being used as this is one such classifier where the total error is minimized and removing the between-class imbalance and within class imbalance simultaneously help the classifier in giving equal weight to all the sub-clusters irrespective of the classes. The proposed method is validated on 9 publicly available data sets and compared with three existing oversampling techniques that rely on the spatial location of minority class examples in the euclidean feature space. The experimental results show the proposed method to be statistically significantly superior to other methods in terms of various accuracy measures. Thus the proposed method can serve as a good alternative to handle various problem domains like credit scoring, customer churn prediction, financial distress, etc., that typically involve imbalanced data sets.

Keywords: classification, imbalanced dataset, Lowner-John ellipsoid, model based clustering, oversampling

Procedia PDF Downloads 418

Authors: Michela Quadrini

Abstract:

Chord diagrams occur in mathematics, from the study of RNA to knot theory. They are widely used in theory of knots and links for studying the finite type invariants, whereas in molecular biology one important motivation to study chord diagrams is to deal with the problem of RNA structure prediction. An RNA molecule is a linear polymer, referred to as the backbone, that consists of four types of nucleotides. Each nucleotide is represented by a point, whereas each chord of the diagram stands for one interaction for Watson-Crick base pairs between two nonconsecutive nucleotides. A chord diagram is an oriented circle with a set of n pairs of distinct points, considered up to orientation preserving diffeomorphisms of the circle. A linear chord diagram (LCD) is a special kind of graph obtained cutting the oriented circle of a chord diagram. It consists of a line segment, called its backbone, to which are attached a number of chords with distinct endpoints. There is a natural fattening on any linear chord diagram; the backbone lies on the real axis, while all the chords are in the upper half-plane. Each linear chord diagram has a natural genus of its associated surface. To each chord diagram and linear chord diagram, it is possible to associate the intersection graph. It consists of a graph whose vertices correspond to the chords of the diagram, whereas the chord intersections are represented by a connection between the vertices. Such intersection graph carries a lot of information about the diagram. Our goal is to define an LCD equivalence class in terms of identity of intersection graphs, from which many chord diagram invariants depend. For studying these invariants, we introduce a new representation of Linear Chord Diagrams based on a set of appropriate topological operators that permits to model LCD in terms of the relations among chords. Such set is composed of: crossing, nesting, and concatenations. The crossing operator is able to generate the whole space of linear chord diagrams, and a multiple context free grammar able to uniquely generate each LDC starting from a linear chord diagram adding a chord for each production of the grammar is defined. In other words, it allows to associate a unique algebraic term to each linear chord diagram, while the remaining operators allow to rewrite the term throughout a set of appropriate rewriting rules. Such rules define an LCD equivalence class in terms of the identity of intersection graphs. Starting from a modelled RNA molecule and the linear chord, some authors proposed a topological classification and folding. Our LCD equivalence class could contribute to the RNA folding problem leading to the definition of an algorithm that calculates the free energy of the molecule more accurately respect to the existing ones. Such LCD equivalence class could be useful to obtain a more accurate estimate of link between the crossing number and the topological genus and to study the relation among other invariants.

Keywords: chord diagrams, linear chord diagram, equivalence class, topological language

Procedia PDF Downloads 201