Search results for: linear low-density polyethylene

Authors: Mehmet Akköse

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Concern about seismic safety of concrete dams have been growing around the world, partly because the population at risk in locations downstream of major dams continues to expand and also because it is increasingly evident that the seismic design concepts in use at the time most existing dams were built were inadequate. Most of the investigations in the past have been conducted on large dams, typically above 100m high. A large number of concrete dams in our country and in other parts of the world are less than 50m high. Most of these dams were usually designed using pseudo-static methods, ignoring the dynamic characteristics of the structure as well as the characteristics of the ground motion. Therefore, it is important to carry out investigations on seismic behavior this category of dam in order to assess and evaluate the safety of existing dams and improve the knowledge for different high dams to be constructed in the future. In this study, size effects on structural performance of concrete gravity dams subjected to near and far-fault ground motions are investigated including dam-water-foundation interaction. For this purpose, a benchmark problem proposed by ICOLD (International Committee on Large Dams) is chosen as a numerical application. Structural performance of the dam having five different heights is evaluated according to damage criterions in USACE (U.S. Army Corps of Engineers). It is decided according to their structural performance if non-linear analysis of the dams requires or not. The linear elastic dynamic analyses of the dams to near and far-fault ground motions are performed using the step-by-step integration technique. The integration time step is 0.0025 sec. The Rayleigh damping constants are calculated assuming 5% damping ratio. The program NONSAP modified for fluid-structure systems with the Lagrangian fluid finite element is employed in the response calculations.

Keywords: concrete gravity dams, Lagrangian approach, near and far-fault ground motion, USACE damage criterions

Procedia PDF Downloads 269

Authors: Hasan Atakan Sengul, Nergis Canturk, Bahar Erbas

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Drinking water is indispensable for life. With increasing awareness of communities, the content of drinking water and tap water has been a matter of curiosity. The presence of Bisphenol-A is the top one when content curiosity is concerned. The most used chemical worldwide for production of polycarbonate plastics and epoxy resins is Bisphenol-A. People are exposed to Bisphenol-A chemical, which disrupts the endocrine system, almost every day. Each year it is manufactured an average of 5.4 billion kilograms of Bisphenol-A. Linear formula of Bisphenol-A is (CH₃)₂C(C₆H₄OH)₂, its molecular weight is 228.29 and CAS number is 80-05-7. Bisphenol-A is known to be used in the manufacturing of plastics, along with various chemicals. Bisphenol-A, an industrial chemical, is used in the raw materials of packaging mate-rials in the monomers of polycarbonate and epoxy resins. The pass through the nutrients of Bisphenol-A substance happens by packaging. This substance contaminates with nutrition and penetrates into body by consuming. International researches show that BPA is transported through body fluids, leading to hormonal disorders in animals. Experimental studies on animals report that BPA exposure also affects the gender of the newborn and its time to reach adolescence. The extent to what similar endocrine disrupting effects are on humans is a debate topic in many researches. In our country, detailed studies on BPA have not been done. However, it is observed that 'BPA-free' phrases are beginning to appear on plastic packaging such as baby products and water carboys. Accordingly, this situation increases the interest of the society about the subject; yet it causes information pollution. In our country, all national and international studies on exposure to BPA have been examined and Ankara province has been designated as testing region. To assess the effects of plastic use in daily habits of people and the plastic amounts removed out of the body, the results of the survey conducted with volunteers who live in Ankara has been analyzed with Sciex appliance by means of LC-MS/MS in the laboratory and the amount of exposure and BPA removal have been detected by comparing the results elicited before. The results have been compared with similar studies done in international arena and the relation between them has been exhibited. Consequently, there has been found no linear correlation between the amount of BPA in drinking water and the amount of BPA in urine. This has also revealed that environmental exposure and the habits of daily plastic use have also direct effects a human body. When the amount of BPA in drinking water is considered; minimum 0.028 µg/L, maximum 1.136 µg/L, mean 0.29194 µg/L and SD(standard deviation)= 0.199 have been detected. When the amount of BPA in urine is considered; minimum 0.028 µg/L, maximum 0.48 µg/L, mean 0.19181 µg/L and SD= 0.099 have been detected. In conclusion, there has been found no linear correlation between the amount of BPA in drinking water and the amount of BPA in urine (r= -0.151). The p value of the comparison between drinking water’s and urine’s BPA amounts is 0.004 which shows that there is a significant change and the amounts of BPA in urine is dependent on the amounts in drinking waters (p < 0.05). This has revealed that environmental exposure and daily plastic habits have also direct effects on the human body.

Keywords: analyze of bisphenol-A, BPA, BPA in drinking water, BPA in urine

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Authors: Paschal A. Ubi, Salawu Abdul Rahman Asipita

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The use of suitable engineering materials which poses less harm to ,an and the environment is sort for in recent times, thus giving rise to polymer composites filled with natural organic reinforcement which are biodegradable. Treatment of natural fibres is essential in improving matrix to filler adhesion, hence improving its mechanical properties. In this study, investigations were carried out to determine the effect of sodium hydroxide treatment on the tensile, flexural, impact and hardness properties of crushed and uncrushed luffa cylindrica fibre reinforced recycled low density polyethylene composites. The LC (Luffa Cylindrica) fibres were treated with 0%, 2%, 4%, 6%, 8%, and 10% wt. NaOH concentrations for a period of 24 hours under room temperature conditions. The compounding of the waste LDPE was done using a two roll mill at a temperature of 150 oC and cured in a hydraulic press at a temperature of 150oC for 3 minutes at 3 metric tonnes. A formulation of 20/80g (reinforcement to matrix ratio in grams) was maintained for all fabricated samples. Analysis of the results showed that the uncrushed luffa fibre samples gave better mechanical properties compared with the crushed luffa fibre samples. The uncrushed luffa fibre composites had optimum tensile and flexural strengths of 7.65MPa and 17.08Mpa respectively corresponding to a young modulus and flexural modulus of 21.08MPa and 232.22MPa for the 8% and 4%wt. NaOH concentration respectively. Results obtained in the research showed that NaOH treatment with the 8% NaOH concentration improves the mechanical properties of the LC fibre reinforced composites when compared with other NaOH treatment concentration values.

Keywords: LC fibres, NaOH concentration, LC/rLDPE composite, tensile strength, flexural strength

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Authors: Katharigatta N. Venugopala, Fernando Albericio, Bander E. Al-Dhubiab, T. Govender

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Recent years have witnessed a renaissance in the field of peptides that are obtained from various natural sources such as many bacteria, fungi, plants, seaweeds, vertebrates, invertebrates and have been reported for various pharmacological properties such as anti-TB, anticancer, antimalarial, anti-inflammatory, anti-HIV, antibacterial, antifungal, and antidiabetic, activities. In view of the pharmacological significance of natural peptides, serious research efforts of many scientific groups and pharmaceutical companies have consequently focused on them to explore the possibility of developing their potential analogues as therapeutic agents. Solid phase and solution phase peptide synthesis are the two methodologies currently available for the synthesis of natural or synthetic linear or cyclic depsi-peptides. From a synthetic point of view, there is no doubt that the solid-phase methodology gained added advantages over solution phase methodology in terms of simplicity, purity of the compound and the speed with which peptides can be synthesised. In the present study total synthesis, purification and structural elucidation of analogues of natural anti-TB cyclic depsi-peptides such as depsidomycin, massetolides and viscosin has been attempted by solid phase method using standard Fmoc protocols and finally off resin cyclization in solution phase method. In case of depsidomycin, synthesis of linear peptide on solid phase could not be achieved because of two turn inducing amino acids in the peptide sequence, but total synthesis was achieved by convergent solid phase peptide synthesis followed by cyclization in solution phase method. The title compounds obtained were in good yields and characterized by NMR and HRMS. Anti-TB results revealed that the potential title compound exhibited promising activity at 4 µg/mL against H37Rv and 16 µg/mL against MDR strains of tuberculosis.

Keywords: total synthesis, cyclic depsi-peptides, anti-TB activity, tuberculosis

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Authors: Muhammad Cheema, Tahir Shah, Subhash Anand

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The cost of making apparel fabrics for garment manufacturing is very high because of their conventional manufacturing processes and new methods/processes are being constantly developed for making fabrics by unconventional methods. With the advancements in technology and the availability of the innovative fibres, durable nonwoven fabrics by using the hydroentanglement process that can compete with the woven fabrics in terms of their aesthetic and tensile properties are being developed. In the work reported here, the hydroentangled nonwoven fabrics were developed through a hybrid nonwoven manufacturing processes by using fibrillated Tencel® and bi-component (sheath/core) polyethylene/polyester (PE/PET) fibres, in which the initial nonwoven fabrics were prepared by the needle-punching method followed by hydroentanglement process carried out at optimal pressures of 50 to 250bars. The prepared fabrics were characterized according to the British Standards (BS 3356:1990, BS 9237:1995, BS 13934-1:1999) and the attained results were compared with those for a standard plain-weave cotton, polyester woven fabric and commercially available nonwoven fabric (Evolon®). The developed hydroentangled fabrics showed better drape properties owing to their flexural rigidity of 252 mg.cm in the machine direction, while the corresponding commercial hydroentangled fabric displayed a value of 1340 mg.cm in the machine direction. The tensile strength of the developed hydroentangled fabrics showed an approximately 200% increase than the commercial hydroentangled fabrics. Similarly, the developed hydroentangled fabrics showed higher properties in term of air permeability, such as the developed hydroentangled fabric exhibited 448 mm/sec and Evolon fabric exhibited 69 mm/sec at 100 Pa pressure. Thus for apparel fabrics, the work combining the existing methods of nonwoven production, provides additional benefits in terms of cost, time and also helps in reducing the carbon footprint for the apparel fabric manufacture.

Keywords: hydroentanglement, nonwoven apparel, durable nonwoven, wearable nonwoven

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Authors: Abdulaziz Alsadhan, Naveed Khan

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In recent years intrusions on computer network are the major security threat. Hence, it is important to impede such intrusions. The hindrance of such intrusions entirely relies on its detection, which is primary concern of any security tool like Intrusion Detection System (IDS). Therefore, it is imperative to accurately detect network attack. Numerous intrusion detection techniques are available but the main issue is their performance. The performance of IDS can be improved by increasing the accurate detection rate and reducing false positive. The existing intrusion detection techniques have the limitation of usage of raw data set for classification. The classifier may get jumble due to redundancy, which results incorrect classification. To minimize this problem, Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), and Local Binary Pattern (LBP) can be applied to transform raw features into principle features space and select the features based on their sensitivity. Eigen values can be used to determine the sensitivity. To further classify, the selected features greedy search, back elimination, and Particle Swarm Optimization (PSO) can be used to obtain a subset of features with optimal sensitivity and highest discriminatory power. These optimal feature subset used to perform classification. For classification purpose, Support Vector Machine (SVM) and Multilayer Perceptron (MLP) used due to its proven ability in classification. The Knowledge Discovery and Data mining (KDD’99) cup dataset was considered as a benchmark for evaluating security detection mechanisms. The proposed approach can provide an optimal intrusion detection mechanism that outperforms the existing approaches and has the capability to minimize the number of features and maximize the detection rates.

Keywords: Particle Swarm Optimization (PSO), Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA), Local Binary Pattern (LBP), Support Vector Machine (SVM), Multilayer Perceptron (MLP)

Procedia PDF Downloads 376

Authors: Snezana Lazic, Zarko Gacevic, Mark Holmes, Ekaterina Chernysheva, Marcus Müller, Peter Veit, Frank Bertram, Juergen Christen, Yasuhiko Arakawa, Enrique Calleja

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The study reports how the pencil-like morphology of a homoepitaxially grown GaN nanowire can be exploited for the fabrication of a thin conformal InGaN nanoshell, hosting nonpolar, semipolar and polar single photon sources (SPSs). All three SPS types exhibit narrow emission lines (FWHM~0.35 - 2 meV) and high degrees of linear optical polarization (P > 70%) in the low-temperature micro-photoluminescence (µ-PL) experiments and are characterized by a pronounced antibunching in the photon correlation measurements (gcorrected(2)(0) < 0.3). The quantum-dot-like exciton localization centers induced by compositional fluctuations within the InGaN nanoshell are identified as the driving mechanism for the single photon emission. As confirmed by the low-temperature transmission electron microscopy combined with cathodoluminescence (TEM-CL) study, the crystal region (i.e. non-polar m-, semi-polar r- and polar c-facets) hosting the single photon emitters strongly affects their emission wavelength, which ranges from ultra-violet for the non-polar to visible for the polar SPSs. The photon emission lifetime is also found to be facet-dependent and varies from sub-nanosecond time scales for the non- and semi-polar SPSs to a few nanoseconds for the polar ones. These differences are mainly attributed to facet-dependent indium content and electric field distribution across the hosting InGaN nanoshell. The hereby reported pencil-like InGaN nanoshell is the first single nanostructure able to host all three types of single photon emitters and is thus a promising building block for tunable quantum light devices integrated into future photonic and optoelectronic circuits.

Keywords: GaN nanowire, InGaN nanoshell, linear polarization, nonpolar, semipolar, polar quantum dots, single-photon sources

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Authors: Alakija Temitope Olufunmilayo, Akinyemi, Yagba Joy

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Hepatitis is the inflammation of the liver tissue that can cause whiteness of the eyes (Jaundice), lack of appetite, vomiting, tiredness, abdominal pain, diarrhea. Hepatitis is acute if it resolves within 6 months and chronic if it last longer than 6 months. Acute hepatitis can resolve on its own, lead to chronic hepatitis or rarely result in acute liver failure. Chronic hepatitis may lead to scarring of the liver (Cirrhosis), liver failure and liver cancer. Modelling Hepatitis B may become necessary in order to reduce its spread. So, dynamic SIR model can be used. This model consists of a system of three coupled non-linear ordinary differential equation which does not have an explicit formula solution. It is an epidemiological model used to predict the dynamics of infectious disease by categorizing the population into three possible compartments. In this study, a five-compartment dynamic model of Hepatitis B disease was proposed and developed by adding control measure of sensitizing the public called awareness. All the mathematical and statistical formulation of the model, especially the general equilibrium of the model, was derived, including the nonlinear least square estimators. The initial parameters of the model were derived using nonlinear least square embedded in R code. The result study shows that the proportion of Hepatitis B patient in the study population is 1.4 per 1,000,000 populations. The estimated Hepatitis B induced death rate is 0.0108, meaning that 1.08% of the infected individuals die of the disease. The reproduction number of Hepatitis B diseases in Nigeria is 6.0, meaning that one individual can infect more than 6.0 people. The effect of sensitizing the public on the basic reproduction number is significant as the reproduction number is reduced. The study therefore recommends that programme should be designed by government and non-governmental organization to sensitize the entire Nigeria population in order to reduce cases of Hepatitis B disease among the citizens.

Keywords: hepatitis B, modelling, non-linear ordinary differential equation, sihar model, sensitization

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Authors: Lalita, Niladri Sarkar, Subhasis Ghosh

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Since the discovery of high temperature superconductivity (HTSC) in cuprates, several aspects of this phenomena have fascinated physics community. The most debated one is the linear temperature dependence of normal state resistivity over wide range of temperature in violation of with Fermi liquid theory. The linear-in-T resistivity (LITR) is the indication of strongly correlated metallic, known as “strange metal”, attributed to non Fermi liquid theory (NFL). The proximity of superconductivity to LITR suggests that there may be underlying common origin. The LITR has been shown to be due to unknown dissipative phenomena, restricted by quantum mechanics and commonly known as ‘‘Planckian dissipation” , the term first coined by Zaanen and the associated inelastic scattering time τ and given by 1/τ=αkBT/ℏ, where ℏ, kB and α are reduced Planck’s constant, Boltzmann constant and a dimensionless constant of order of unity, respectively. Since the first report, experimental support for α ~ 1 is appearing in literature. There are several striking issues which remain to be resolved if we desire to find out or at least get a clue towards microscopic origin of maximal dissipation in cuprates. (i) Universality of α ~ 1, recently some doubts have been raised in some cases. (ii) So far, Planckian dissipation has been demonstrated in overdoped Cuprates, but if the proximity to quantum criticality is important, then Planckian dissipation should be observed in optimally doped and marginally underdoped cuprates. The link between Planckian dissipation and quantum criticality still remains an open problem. (iii) Validity of Planckian dissipation in all cuprates is an important issue. Here, we report reversible change in the superconducting behavior of high temperature superconductor Bi2Sr2Ca2Cu3O10+δ (Bi-2223) under dynamic doping induced by photo-excitation. Two doped Bi-223 samples, which are x = 0.16 (optimal-doped), x = 0.145 (marginal-doped) have been used for this investigation. It is realized that steady state photo-excitation converts magnetic Cu2+ ions to nonmagnetic Cu1+ ions which reduces superconducting transition temperature (Tc) by killing superfluid density. In Bi-2223, one would expect the maximum of suppression of Tc should be at charge transfer gap. We have observed suppression of Tc starts at 2eV, which is the charge transfer gap in Bi-2223. We attribute this transition due to Cu-3d9(Cu2+) to Cu-3d10(Cu+), known as d9 − d10 L transition, photoexcitation makes some Cu ions in CuO2 planes as spinless non-magnetic potential perturbation as Zn2+ does in CuO2 plane in case Zn-doped cuprates. The resistivity varies linearly with temperature with or without photo-excitation. Tc can be varied by almost by 40K be photoexcitation. Superconductivity can be destroyed completely by introducing ≈ 2% of Cu1+ ions for this range of doping. With this controlled variation of Tc and resistivity, detailed investigation has been carried out to reveal Planckian dissipation underdoped to optimally doped Bi-2223. The most important aspect of this investigation is that we could vary Tc dynamically and reversibly, so that LITR and associated Planckian dissipation can be studied over wide ranges of Tc without changing the doping chemically.

Keywords: linear resistivity, HTSC, Planckian dissipation, strange metal

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Authors: Mounir Zili

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We will introduce a new extension of the Brownian motion, that could serve to get a good model of many natural phenomena. It is a linear combination of a finite number of sub-fractional Brownian motions; that is why we will call it the mixed sub-fractional Brownian motion. We will present some basic properties of this process. Among others, we will check that our process is non-markovian and that it has non-stationary increments. We will also give the conditions under which it is a semi-martingale. Finally, the main features of its sample paths will be specified.

Keywords: fractal dimensions, mixed gaussian processes, sample paths, sub-fractional brownian motion

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Authors: Atakan Aral Ormancı, Tuğçe Arslantaş, Murat Özcü

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This study presents the design and implementation of an experimental chassis-level system for various control applications. Specifically, the height level of the chassis is controlled using proportional integrated derivative, fuzzy logic, and deep learning control methods. Real-time data obtained from height and pressure sensors installed in a 6x2 truck chassis, in combination with pulse-width modulation signal values, are utilized during the tests. A prototype pneumatic system of a 6x2 truck is added to the setup, which enables the Smart Pneumatic Actuators to function as if they were in a real-world setting. To obtain real-time signal data from height sensors, an Arduino Nano is utilized, while a Raspberry Pi processes the data using Matlab/Simulink and provides the correct output signals to control the Smart Pneumatic Actuator in the truck chassis. The objective of this research is to optimize the time it takes for the chassis to level down and up under various loads. To achieve this, proportional integrated derivative control, fuzzy logic control, and deep learning techniques are applied to the system. The results show that the deep learning method is superior in optimizing time for a non-linear system. Fuzzy logic control with a triangular membership function as the rule base achieves better outcomes than proportional integrated derivative control. Traditional proportional integrated derivative control improves the time it takes to level the chassis down and up compared to an uncontrolled system. The findings highlight the superiority of deep learning techniques in optimizing the time for a non-linear system, and the potential of fuzzy logic control. The proposed approach and the experimental results provide a valuable contribution to the field of control, automation, and systems engineering.

Keywords: automotive, chassis level control, control systems, pneumatic system control

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Authors: Xi Quan Cheng, Yan Chao Xu, Xu Jiang, Lu Shao, Cher Hon Lau

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A hydrophilic thin-film-composite (TFC) nanofiltration (NF) membrane has been developed through the interfacial polymerization (IP) of amino-functional polyethylene glycol (PEG) and trimesoyl chloride. The selective layer is formed on a polyethersulfone (PES) support that is characterized using FTIR, XPS and SEM, and is dependent on monomer immersion duration, and the concentration of monomers and additives. The higher hydrophilicity alongside the larger pore size of the PEG-based selective layer is the key to a high water flux of 66.0 L m-2 h-1 at 5.0 bar. With mean pore radius of 0.42 nm and narrow pore size distribution, the MgSO4 rejections of the PEG based PA TFC NF membranes can reach up to 80.2 %. The hydrophilic PEG based membranes shows positive charged since the isoelectric points range from pH=8.9 to pH=9.1 and the rejection rates for different salts of the novel membranes are in the order of R(MgCl2)>R(MgSO4)>R(NaCl)>R(Na2SO4). The pore sizes and water permeability of these membranes are tailored by varying the molecular weight and molecular architecture of amino-functional PEG. Due to the unique structure of the selective layer of the PEG based membranes consisting of saturated aliphatic construction unit (CH2-CH2-O), the membranes demonstrate dual resistance to fouling and chlorine. The membranes maintain good salt rejections and high water flux of PEG based membranes after treatment by 2000 ppm NaClO for 24 hours. Interestingly, the PEG based membranes exhibit excellent fouling resistance with a water flux recovery of 90.2 % using BSA as a model molecule. More importantly, the hydrophilic PEG based NF membranes have been exploited to separate several water soluble antibiotics (such as tobramycin, an aminoglycoside antibiotic applied in the treatment of various types of bacterial infections), showing excellent performance in concentration or removal of antibioics.

Keywords: nanofiltration, antibiotic separation, hydrophilic membrane, high flux

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Authors: A. Torokhti

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A new method of mathematical modeling of the distributed nonlinear system is developed. The system is represented by a combination of the set of spatially distributed sensors and the fusion center. Its mathematical model is obtained from the iterative procedure that converges to the model which is optimal in the sense of minimizing an associated cost function.

Keywords: mathematical modeling, non-linear system, spatially distributed sensors, fusion center

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Authors: Xiaoqian Cheng, Jon Kleppe, Ole Torsaeter

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One objective of this work is to analyze the effects of surfactant properties (viscosity, concentration, and adsorption) on surfactant enhanced oil recovery at laboratory scale. The other objective is to obtain the functional relationships between surfactant properties and the ultimate oil recovery and oil recovery rate. A core is cut into two parts from the middle to imitate the matrix with a horizontal fracture. An injector and a producer are at the left and right sides of the fracture separately. The middle slice of the core is used as the model in this paper, whose size is 4cm x 0.1cm x 4.1cm, and the space of the fracture in the middle is 0.1 cm. The original properties of matrix, brine, oil in the base case are from Ekofisk Field. The properties of surfactant are from literature. Eclipse is used as the simulator. The results are followings: 1) The viscosity of surfactant solution has a positive linear relationship with surfactant oil recovery time. And the relationship between viscosity and oil production rate is an inverse function. The viscosity of surfactant solution has no obvious effect on ultimate oil recovery. Since most of the surfactant has no big effect on viscosity of brine, the viscosity of surfactant solution is not a key parameter of surfactant screening for surfactant flooding in fractured reservoirs. 2) The increase of surfactant concentration results a decrease of oil recovery rate and an increase of ultimate oil recovery. However, there are no functions could describe the relationships. Study on economy should be conducted because of the price of surfactant and oil. 3) In the study of surfactant adsorption, assume that the matrix wettability is changed to water-wet when the surfactant adsorption is to the maximum at all cases. And the ratio of surfactant adsorption and surfactant concentration (Cads/Csurf) is used to estimate the functional relationship. The results show that the relationship between ultimate oil recovery and Cads/Csurf is a logarithmic function. The oil production rate has a positive linear relationship with exp(Cads/Csurf). The work here could be used as a reference for the surfactant screening of surfactant enhanced oil recovery from fractured reservoirs. And the functional relationships between surfactant properties and the oil recovery rate and ultimate oil recovery help to improve upscaling methods.

Keywords: fractured reservoirs, surfactant adsorption, surfactant concentration, surfactant EOR, surfactant viscosity

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Authors: Faramarz Khoshnoudian

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A seismic stability assessment of the concrete gravity dam was performed. Initially (Phase 1), a linear response spectrum analysis was performed to verify the potential for crack formation. The result shows the possibility of developing cracks in the upstream face of the dam close to the lowest gallery, which were sufficiently long that the dam would not be stable following the earthquake. The results show the dam has potentially inadequate seismic and post-earthquake resistance and recommended an update of the stability analysis.

Keywords: crack propgation, concrete gravity dam, seismic, assesment

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Authors: Shoukat Ali, Abdul Qadir Jandga, Amjad Hussain

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Objective: The main purpose of this study is to compare the Percent Depth dose (PDD) and In-plane and cross-plane profiles of Varian Golden beam data to the measured data of 6 and 18 MV photons for the commissioning of Eclipse treatment planning system. Introduction: Commissioning of treatment planning system requires an extensive acquisition of beam data for the clinical use of linear accelerators. Accurate dose delivery require to enter the PDDs, Profiles and dose rate tables for open and wedges fields into treatment planning system, enabling to calculate the MUs and dose distribution. Varian offers a generic set of beam data as a reference data, however not recommend for clinical use. In this study, we compared the generic beam data with the measured beam data to evaluate the reliability of generic beam data to be used for the clinical purpose. Methods and Material: PDDs and Profiles of Open and Wedge fields for different field sizes and at different depths measured as per Varian’s algorithm commissioning guideline. The measurement performed with PTW 3D-scanning water phantom with semi-flex ion chamber and MEPHYSTO software. The online available Varian Golden Beam Data compared with the measured data to evaluate the accuracy of the golden beam data to be used for the commissioning of Eclipse treatment planning system. Results: The deviation between measured vs. golden beam data was in the range of 2% max. In PDDs, the deviation increases more in the deeper depths than the shallower depths. Similarly, profiles have the same trend of increasing deviation at large field sizes and increasing depths. Conclusion: Study shows that the percentage deviation between measured and golden beam data is within the acceptable tolerance and therefore can be used for the commissioning process; however, verification of small subset of acquired data with the golden beam data should be mandatory before clinical use.

Keywords: percent depth dose, flatness, symmetry, golden beam data

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Authors: Ella Bowles, Alexandra Hughes, Clara Karton, T. Blaine Hoshizaki

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As a fast-paced and physical game, body contact is an inevitable component in professional men's ice hockey. Despite efforts and advancements in material engineering to create safer equipment, brain trauma continues to persist and burden hockey players. Head and body contact occur in many ways and vary in terms of impact characteristics including the inbound velocity, force, direction, location, and compliance of the surfaces, which in turn influence head dynamics and brain injury outcomes including concussions. It has been reported that glass and board impacts account for approximately 40% of diagnosed concussions. This type of impact often involves the body (i.e., shoulder) contacting the surface prior to head contact, which may influence the head’s dynamic response by interrupting the head’s initial trajectory.  However, the effect of body-first contact during head impacts is not well understood. The purpose of this research is to compare the head’s kinematic response during direct and non-direct (body-first) head-to-glass impacts representative of ice hockey events. Analysis was performed under varying impact conditions of neck stiffness and impact velocity as they have been shown to influence the resulting head dynamics. Data was collected by video analysis of the 2016-17 NHL season and event reconstructions were performed using a Hybrid III headform, an unbiased neck with tension springs (uONSA), and a high-speed impactor. Direct and non-direct impacts were analyzed at three common velocities (3.0, 5.0, 7.0 m/s), and three neck stiffnesses representing low (25%), medium (75%), and high (100%) contraction. Reconstructions representing non-direct head-to-glass impacts used a shoulder bumper as the first point of contact followed by the head’s contact with the glass. The same method and equipment were used to replicate the direct head impacts, where the head made initial contact with the glass. The dynamic response of the head, specifically the peak resultant linear and rotational acceleration, was collected for each impact and compared between direct and non-direct contact under each condition. The results show that non-direct impacts created an initial head acceleration resulting from shoulder contact, preceding a secondary acceleration response from head contact with the glass. Compared to direct head impacts, non-direct impacts consistently resulted in lower linear and rotational acceleration of the head under all neck stiffness and velocity conditions with an average decrease of 32.56 g and 689.33 rad/s2. However, the linear acceleration produced from shoulder contact in non-direct impacts resulted in a higher response compared to direct impacts with low neck stiffness at 5 m/s (55.2g and 41.2g, respectively) and 7 m/s (76.1g and 73.4g, respectively), and medium neck stiffness at 5 m/s (55.4g and 43.9g, respectively ) and 7 m/s (94.4g and 69.5g, respectively. These findings show that non-direct impacts produce complex scenarios that are further influenced by interaction with neck stiffness and velocity. This research provides an understanding of the fundamentals of body-first impacts. With this basis, an understanding of the implications of body-first head-impacts to better distinguish trauma based on events, and adapt protocols, evaluations, technologies, and equipment accordingly.

Keywords: body-first, concussion, direct, hockey, kinematics

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Authors: Muhammad Naveed Tahir, Wang Yingkuan, Huang Wenjiang, Raheel Osman

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Numerous models used in prediction and decision-making process but most of them are linear in natural environment, and linear models reach their limitations with non-linearity in data. Therefore accurate estimation is difficult. Artificial Neural Networks (ANN) found extensive acceptance to address the modeling of the complex real world for the non-linear environment. ANN’s have more general and flexible functional forms than traditional statistical methods can effectively deal with. The link between information technology and agriculture will become more firm in the near future. Monitoring crop biophysical properties non-destructively can provide a rapid and accurate understanding of its response to various environmental influences. Crop chlorophyll content is an important indicator of crop health and therefore the estimation of crop yield. In recent years, remote sensing has been accepted as a robust tool for site-specific management by detecting crop parameters at both local and large scales. The present research combined the ANN model with satellite-derived chlorophyll indices from LANDSAT 8 imagery for predicting real-time wheat chlorophyll estimation. The cloud-free scenes of LANDSAT 8 were acquired (Feb-March 2016-17) at the same time when ground-truthing campaign was performed for chlorophyll estimation by using SPAD-502. Different vegetation indices were derived from LANDSAT 8 imagery using ERADAS Imagine (v.2014) software for chlorophyll determination. The vegetation indices were including Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Chlorophyll Absorbed Ratio Index (CARI), Modified Chlorophyll Absorbed Ratio Index (MCARI) and Transformed Chlorophyll Absorbed Ratio index (TCARI). For ANN modeling, MATLAB and SPSS (ANN) tools were used. Multilayer Perceptron (MLP) in MATLAB provided very satisfactory results. For training purpose of MLP 61.7% of the data, for validation purpose 28.3% of data and rest 10% of data were used to evaluate and validate the ANN model results. For error evaluation, sum of squares error and relative error were used. ANN model summery showed that sum of squares error of 10.786, the average overall relative error was .099. The MCARI and NDVI were revealed to be more sensitive indices for assessing wheat chlorophyll content with the highest coefficient of determination R²=0.93 and 0.90 respectively. The results suggested that use of high spatial resolution satellite imagery for the retrieval of crop chlorophyll content by using ANN model provides accurate, reliable assessment of crop health status at a larger scale which can help in managing crop nutrition requirement in real time.

Keywords: ANN, chlorophyll content, chlorophyll indices, satellite images, wheat

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Authors: Ivan Poza Martínez

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The international energy landscape has been significantly affected by the Covid-19 pandemic and te conflict in Ukraine. The Vaca Muerta sedimentary formation in Argentina´s Neuquén province has become a crucial area for energy production, specifically in the shale gas ad shale oil sectors. The massive investment required for theexploitation of this reserve make it essential to understand te determinants of the investment in the upstream sector at both local ad international levels. The aim of this study is to identify the qualitative and quantitative determinants of investment in Vaca Muerta. The research methodolody employs both quantiative ( econometrics ) and qualitative approaches. A linear regression model is used to analyze the impact in non-conventional hydrocarbons. The study highlights that, in addition to quantitative factors, qualitative variables, particularly the design of a regulatory framework, significantly influence the level of the investment in Vaca Muerta. The analysis reveals the importance of attracting both domestic and foreign capital investment. This research contributes to understanding the factors influencing investment inthe Vaca Muerta regioncomapred to other published studies. It emphasizes to role of qualitative varibles, such as regulatory frameworks, in the development of the shale gas and oil sectors. The study uses a combination ofquantitative data , such a investment figures, and qualitative data, such a regulatory frameworks. The data is collected from various rpeorts and industry publications. The linear regression model is used to analyze the relationship between the variables and the investment in Vaca Muerta. The research addresses the question of what factors drive investment in the Vaca Muerta region, both from a quantitative and qualitative perspective. The study concludes that a combination of quantitative and qualitative factors, including the design of a regulatory framework, plays a significant role in attracting investment in Vaca Muerta. It highlights the importance of these determinants in the developmentof the local energy sector and the potential economic benefits for Argentina and the Southern Cone region.

Keywords: vaca muerta, FDI, shale gas, shale oil, YPF

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Authors: Debasis Sarkar, Jatan Talati

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This paper is an attempt to develop an Integrated Mass Rapid Transit System (MRTS) for a smart city project in Western India. Integrated transportation is one of the enablers of smart transportation for providing a seamless intercity as well as regional level transportation experience. The success of a smart city project at the city level for transportation is providing proper integration to different mass rapid transit modes by way of integrating information, physical, network of routes fares, etc. The methodology adopted for this study was primary data research through questionnaire survey. The respondents of the questionnaire survey have responded on the issues about their perceptions on the ways and means to improve public transport services in urban cities. The respondents were also required to identify the factors and attributes which might motivate more people to shift towards the public mode. Also, the respondents were questioned about the factors which they feel might restrain the integration of various modes of MRTS. Furthermore, this study also focuses on developing a utility equation for respondents with the help of multiple linear regression analysis and its probability to shift to public transport for certain factors listed in the questionnaire. It has been observed that for shifting to public transport, the most important factors that need to be considered were travel time saving and comfort rating. Also, an Integrated MRTS can be obtained by combining metro rail with BRTS, metro rail with monorail, monorail with BRTS and metro rail with Indian railways. Providing a common smart card to transport users for accessing all the different available modes would be a pragmatic solution towards integration of the available modes of MRTS.

Keywords: mass rapid transit systems, smart city, metro rail, bus rapid transit system, multiple linear regression, smart card, automated fare collection system

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Authors: Iftikhar Ahmad, A. Benallegue, A. El Hadri

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In this paper, we have proposed an observer for the reconstruction and a control law for the rejection application of unknown bounded external disturbance in a dynamical system. The strategy of both the observer and the controller is designed like a second order sliding mode with a proportional-integral (PI) term. Lyapunov theory is used to prove the exponential convergence and stability. Simulations results are given to show the performance of this method.

Keywords: non-linear systems, sliding mode observer, disturbance rejection, nonlinear control

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Authors: Shimayali Kaushal, Nitesh Priyadarshi, Nitin Kumar Singhal

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Food borne bacterial species have been identified as major pathogens in most of the severe pathogen-related diseases among humans which result in great loss to human health and food industry. Conventional methods like plating and enzyme-linked immune sorbent assay (ELISA) are time-consuming, laborious and require specialized instruments. Nanotechnology has emerged as a great field in case of rapid detection of pathogens in recent years. The AuNRs material has good electro-optical properties due to its larger light absorption band and scattering in surface plasmon resonance wavelength regions. By exploiting the sugar-based adhesion properties of microorganism, we can use the glycoconjugates capped gold nanorods as a potential nanobiosensor to detect the foodborne pathogen. In the present study, polyethylene glycol (PEG) coated gold nanorods (AuNRs) were prepared and functionalized with different types of carbohydrates and further characterized by UV-Visible spectrophotometry, dynamic light scattering (DLS), transmission electron microscopy (TEM). The reactivity of above said nano-biosensor was probed by lectin binding assay and also by different strains of foodborne bacteria by using spectrophotometric and microscopic techniques. Due to the specific interaction of probe with foodborne bacteria (Escherichia coli, Pseudomonas aeruginosa), our nanoprobe has shown significant and selective ablation of targeted bacteria. Our findings suggest that our nanoprobe can be an ideal candidate for selective optical detection of food pathogens and can reduce loss to the food industry.

Keywords: glyco-conjugates, gold nanorods, nanobiosensor, nanoprobe

Procedia PDF Downloads 141

Authors: Jill Villarreal, Kristalyn Cooksey, Kai Lloyd, Daniel Ha

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Little research has been conducted to examine college students' reading attitudes, including students' perceptions of reading behaviors and reading abilities. This is problematic, as reading assigned course material is a critical component to an undergraduate student's academic success. For this study, flyers were electronically disseminated to instructors at 24 public and 10 private U.S. institutions in “Reading-Intensive Departments” including Psychology, Sociology, Education, Business, and Communications. We requested the online survey be completed as an in-class activity during the fall 2019 and spring 2020 semesters. All participants voluntarily completed the questionnaire anonymously. Of the participants, 280 self-identified their race as Black and 280 self-identified their race as White. Of the participants, 177 self-identified their gender as Male and 383 self-identified their Gender as Female. Participants ranged in age from 18-24. Factor analysis found four dimensions resulting from the questions regarding reading. The first we interpret as “Reading Proficiency”, accounted for 19% of the variability. The second dimension was “Reading Anxiety” (15%), the third was “Textbook Reading Ability” (9%), and the fourth was “Reading Enjoyment” (8%). Linear models on each of these dimensions revealed no effect of Age, Gender, Race, or Income on “Reading proficiency”. The linear model of “Reading Anxiety” showed a significant effect of race (p = 0.02), with higher anxiety in white students, as well as higher reading anxiety in female students (p < 0.001). The model of “Textbook Reading Ability” found a significant effect of race (p < 0.001), with higher textbook problems in white students. The model of “Reading Enjoyment” showed significant effects of race (p = 0.013) with more enjoyment for white students, gender (p = 0.001) with higher enjoyment for female students, and age (p = 0.033) with older students showing higher enjoyment. These findings suggest that gender, age, and race are important factors in many aspects of college students' reading attitudes. Further research will investigate possible causes for these differences. In addition, the effectiveness of college-level programs to reduce reading anxiety, promote the reading of textbooks, and foster a love of reading will be assessed.

Keywords: age, college, gender, race, reading

Procedia PDF Downloads 156

Authors: A. Soni, D. R. Mishra, D. K. Koul

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α-Al2O3:C has been reported to have deeper traps at 600°C and 900°C respectively. These traps have been reported to accessed at relatively earlier temperatures (122 and 322 °C respectively) using thermally assisted OSL (TA-OSL). In this work, the dose response α-Al2O3:C was studied in the dose range of 10Gy to 10kGy for its application in food irradiation in low ( upto 1kGy) and medium(1 to 10kGy) dose range. The TOL (Thermo-optically stimulated luminescence) measurements were carried out on RisØ TL/OSL, TL-DA-15 system having a blue light-emitting diodes (λ=470 ±30nm) stimulation source with power level set at the 90% of the maximum stimulation intensity for the blue LEDs (40 mW/cm2). The observations were carried on commercial α-Al2O3:C phosphor. The TOL experiments were carried out with number of active channel (300) and inactive channel (1). Using these settings, the sample is subjected to linear thermal heating and constant optical stimulation. The detection filter used in all observations was a Hoya U-340 (Ip ~ 340 nm, FWHM ~ 80 nm). Irradiation of the samples was carried out using a 90Sr/90Y β-source housed in the system. A heating rate of 2 °C/s was preferred in TL measurements so as to reduce the temperature lag between the heater plate and the samples. To study the dose response of deep traps of α-Al2O3:C, samples were irradiated with various dose ranging from 10 Gy to 10 kGy. For each set of dose, three samples were irradiated. In order to record the TA-OSL, initially TL was recorded up to a temperature of 400°C, to deplete the signal due to 185°C main dosimetry TL peak in α-Al2O3:C, which is also associated with the basic OSL traps. After taking TL readout, the sample was subsequently subjected to TOL measurement. As a result, two well-defined TA-OSL peaks at 121°C and at 232°C occur in time as well as temperature domain which are different from the main dosimetric TL peak which occurs at ~ 185°C. The linearity of the integrated TOL signal has been measured as a function of absorbed dose and found to be linear upto 10kGy. Thus, it can be used for low and intermediate dose range of for its application in food irradiation. The deep energy level defects of α-Al2O3:C phosphor can be accessed using TOL section of RisØ reader system.

Keywords: α-Al2O3:C, deep traps, food irradiation, TA-OSL

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Authors: Sadegh Marzban, Mohamad Sobhan Sheikh Andalibi, Farnaz Ghassemi, Farzad Towhidkhah

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Parkinson's disease (PD), which is characterized by the tremor at rest, rigidity, akinesia or bradykinesia and postural instability, affects the quality of life of involved individuals. The concept of a fractal is most often associated with irregular geometric objects that display self-similarity. Fractal dimension (FD) can be used to quantify the complexity and the self-similarity of an object such as tremor. In this work, we are aimed to propose a new method for evaluating hyperkinetic movements such as tremor, by using the FD and other correlated parameters in patients who are suffered from PD. In this study, we used 'the tremor data of Physionet'. The database consists of fourteen participants, diagnosed with PD including six patients with high amplitude tremor and eight patients with low amplitude. We tried to extract features from data, which can distinguish between patients before and after medication. We have selected fractal dimensions, including correlation dimension, box dimension, and information dimension. Lilliefors test has been used for normality test. Paired t-test or Wilcoxon signed rank test were also done to find differences between patients before and after medication, depending on whether the normality is detected or not. In addition, two-way ANOVA was used to investigate the possible association between the therapeutic effects and features extracted from the tremor. Just one of the extracted features showed significant differences between patients before and after medication. According to the results, correlation dimension was significantly different before and after the patient's medication (p=0.009). Also, two-way ANOVA demonstrates significant differences just in medication effect (p=0.033), and no significant differences were found between subject's differences (p=0.34) and interaction (p=0.97). The most striking result emerged from the data is that correlation dimension could quantify medication treatment based on tremor. This study has provided a technique to evaluate a non-linear measure for quantifying medication, nominally the correlation dimension. Furthermore, this study supports the idea that fractal dimension analysis yields additional information compared with conventional spectral measures in the detection of poor prognosis patients.

Keywords: correlation dimension, non-linear measure, Parkinson’s disease, tremor

Procedia PDF Downloads 245

Authors: Strahinja Kovacevic, Milica Karadzic Banjac, Jasmina Vitas, Stefan Vukmanovic, Radomir Malbasa, Lidija Jevric, Sanja Podunavac-Kuzmanovic

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The present study deals with chemometric regression analysis of quality parameters and the radical scavenging ability of kombucha fermented kefir-like products obtained with winter savory (WS), peppermint (P), stinging nettle (SN) and wild thyme tea (WT) kombucha inoculums. Each analyzed sample was described by milk fat content (MF, %), total unsaturated fatty acids content (TUFA, %), monounsaturated fatty acids content (MUFA, %), polyunsaturated fatty acids content (PUFA, %), the ability of free radicals scavenging (RSA Dₚₚₕ, % and RSA.ₒₕ, %) and pH values measured after each hour from the start until the end of fermentation. The aim of the conducted regression analysis was to establish chemometric models which can predict the radical scavenging ability (RSA Dₚₚₕ, % and RSA.ₒₕ, %) of the samples by correlating it with the MF, TUFA, MUFA, PUFA and the pH value at the beginning, in the middle and at the end of fermentation process which lasted between 11 and 17 hours, until pH value of 4.5 was reached. The analysis was carried out applying univariate linear (ULR) and multiple linear regression (MLR) methods on the raw data and the data standardized by the min-max normalization method. The obtained models were characterized by very limited prediction power (poor cross-validation parameters) and weak statistical characteristics. Based on the conducted analysis it can be concluded that the resulting radical scavenging ability cannot be precisely predicted only on the basis of MF, TUFA, MUFA, PUFA content, and pH values, however, other quality parameters should be considered and included in the further modeling. This study is based upon work from project: Kombucha beverages production using alternative substrates from the territory of the Autonomous Province of Vojvodina, 142-451-2400/2019-03, supported by Provincial Secretariat for Higher Education and Scientific Research of AP Vojvodina.

Keywords: chemometrics, regression analysis, kombucha, quality control

Procedia PDF Downloads 147

Authors: Marwa A. A. Ragab, Hadir M. Maher, Eman I. El-Kimary

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Co-administration of methotrexate (MTX) and aspirin (ASP) can cause a pharmacokinetic interaction and a subsequent increase in blood MTX concentrations which may increase the risk of MTX toxicity. Therefore, it is important to develop a sensitive, selective, accurate and precise method for their simultaneous determination in urine. A new hybrid chemometric method has been applied to the emission response data of the two drugs. Spectrofluorimetric method for determination of MTX through measurement of its acid-degradation product, 4-amino-4-deoxy-10-methylpteroic acid (4-AMP), was developed. Moreover, the acid-catalyzed degradation reaction enables the spectrofluorimetric determination of ASP through the formation of its active metabolite salicylic acid (SA). The proposed chemometric method deals with convolution of emission data using 8-points sin xi polynomials (discrete Fourier functions) after the derivative treatment of these emission data. The first and second derivative curves (D1 & D2) were obtained first then convolution of these curves was done to obtain first and second derivative under Fourier functions curves (D1/FF) and (D2/FF). This new application was used for the resolution of the overlapped emission bands of the degradation products of both drugs to allow their simultaneous indirect determination in human urine. Not only this chemometric approach was applied to the emission data but also the obtained data were subjected to non-parametric linear regression analysis (Theil’s method). The proposed method was fully validated according to the ICH guidelines and it yielded linearity ranges as follows: 0.05-0.75 and 0.5-2.5 µg mL-1 for MTX and ASP respectively. It was found that the non-parametric method was superior over the parametric one in the simultaneous determination of MTX and ASP after the chemometric treatment of the emission spectra of their degradation products. The work combines the advantages of derivative and convolution using discrete Fourier function together with the reliability and efficacy of the non-parametric analysis of data. The achieved sensitivity along with the low values of LOD (0.01 and 0.06 µg mL-1) and LOQ (0.04 and 0.2 µg mL-1) for MTX and ASP respectively, by the second derivative under Fourier functions (D2/FF) were promising and guarantee its application for monitoring the two drugs in patients’ urine samples.

Keywords: chemometrics, emission curves, derivative, convolution, Fourier transform, human urine, non-parametric regression, Theil’s method

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Authors: Inese Trusina, Elita Jermolajeva

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Global challenges require a transition from the existing linear economic model to a model that will consider nature as a life support system for the developmenton the way to social well-being in the frame of the ecological economics paradigm. The article presentsbasic definitions for the development of formalized description of sustainabledevelopment monitoring. It provides examples of calculating the parameters of monitoring for the Baltic Sea region countries and their primary interpretation.

Keywords: sustainability, development, power, ecological economics, regional economic, monitoring

Procedia PDF Downloads 126

Authors: Rohini Hariharan, Yazhini R, Bhamidipati Naga Shrikarti

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In the realm of cricket, particularly within the context of the Indian Premier League (IPL), the ability to predict team scores accurately holds significant importance for both cricket enthusiasts and stakeholders alike. This paper presents a comprehensive study on IPL score prediction utilizing various machine learning algorithms, including Support Vector Machines (SVM), XGBoost, Multiple Regression, Linear Regression, K-nearest neighbors (KNN), and Random Forest. Through meticulous data preprocessing, feature engineering, and model selection, we aimed to develop a robust predictive framework capable of forecasting team scores with high precision. Our experimentation involved the analysis of historical IPL match data encompassing diverse match and player statistics. Leveraging this data, we employed state-of-the-art machine learning techniques to train and evaluate the performance of each model. Notably, Multiple Regression emerged as the top-performing algorithm, achieving an impressive accuracy of 77.19% and a precision of 54.05% (within a threshold of +/- 10 runs). This research contributes to the advancement of sports analytics by demonstrating the efficacy of machine learning in predicting IPL team scores. The findings underscore the potential of advanced predictive modeling techniques to provide valuable insights for cricket enthusiasts, team management, and betting agencies. Additionally, this study serves as a benchmark for future research endeavors aimed at enhancing the accuracy and interpretability of IPL score prediction models.

Keywords: indian premier league (IPL), cricket, score prediction, machine learning, support vector machines (SVM), xgboost, multiple regression, linear regression, k-nearest neighbors (KNN), random forest, sports analytics

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Authors: Edison E. Haro, Akindele G. Odeshi, Jerzy A. Szpunar

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Hybrid bio-composites are developed for use in protective armor through positive hybridization offered by reinforcement of high-density polyethylene (HDPE) with Kevlar short fibers and palm wood micro-fillers. The manufacturing process involved a combination of extrusion and compression molding techniques. The mechanical behavior of Kevlar fiber reinforced HDPE with and without palm wood filler additions are compared. The effect of the weight fraction of the added palm wood micro-fillers is also determined. The Young modulus was found to increase as the weight fraction of organic micro-particles increased. However, the flexural strength decreased with increasing weight fraction of added micro-fillers. The interfacial interactions between the components were investigated using scanning electron microscopy. The influence of the size, random alignment and distribution of the natural micro-particles was evaluated. Ballistic impact and dynamic shock loading tests were performed to determine the optimum proportion of Kevlar short fibers and organic micro-fillers needed to improve impact strength of the HDPE. These results indicate a positive hybridization by deposition of organic micro-fillers on the surface of short Kevlar fibers used in reinforcing the thermoplastic matrix leading to enhancement of the mechanical strength and dynamic impact behavior of these materials. Therefore, these hybrid bio-composites can be promising materials for different applications against high velocity impacts.

Keywords: hybrid bio-composites, organic nano-fillers, dynamic shocking loading, ballistic impacts, energy absorption

Procedia PDF Downloads 121